From 25d17f5f57ff27a8c10427f56c12bb3e6d8bf184 Mon Sep 17 00:00:00 2001
From: Inki Dae <inki.dae@samsung.com>
Date: Thu, 11 Aug 2022 10:31:43 +0900
Subject: [PATCH 01/16] mv_machine_learning: code refactoring to
 GetClassficationResults

[Issue type] code cleanup

Did code refactoring to GetClassficationResults functions by doing,
		- drop logs from computing relevant funtions due to performance
		  eating issue.
		- use FillOutputResult function instead of
		  mOutputTensorBuffers.getValue() which is performance eating function
		  because it tries to find tensor buffer with a given layer name
		  for every iteration.
		- and also drop the code smell, code duplication.

This patch is just a step for next code refactoring. Which in turn,
FillOuputResult function will be refactored soon in generic way
including dropping the performance eating functions.

Change-Id: I4d8779001143a569f2f76664511005e7fcd8b389
Signed-off-by: Inki Dae <inki.dae@samsung.com>
---
 mv_machine_learning/inference/src/Inference.cpp   | 92 ++++++++---------------
 mv_machine_learning/inference/src/PostProcess.cpp | 15 ----
 2 files changed, 31 insertions(+), 76 deletions(-)

diff --git a/mv_machine_learning/inference/src/Inference.cpp b/mv_machine_learning/inference/src/Inference.cpp
index 1616ace..478cd17 100755
--- a/mv_machine_learning/inference/src/Inference.cpp
+++ b/mv_machine_learning/inference/src/Inference.cpp
@@ -1098,6 +1098,19 @@ namespace inference
 		// Will contain top N results in ascending order.
 		std::vector<std::pair<float, int>> topScore;
 		auto threadHold = mConfig.mConfidenceThresHold;
+		constexpr unsigned int default_top_number = 5;
+		tensor_t outputData;
+
+		// Get inference result and contain it to outputData.
+		int ret = FillOutputResult(outputData);
+		if (ret != MEDIA_VISION_ERROR_NONE) {
+			LOGE("Fail to get output result.");
+			return ret;
+		}
+
+		PostProcess postProc;
+		unsigned int classes = outputData.dimInfo[0][1];
+		unsigned int top_number = default_top_number;
 
 		if (mMetadata.GetOutputMeta().IsParsed()) {
 			OutputMetadata outputMetadata = mMetadata.GetOutputMeta();
@@ -1108,27 +1121,28 @@ namespace inference
 				return MEDIA_VISION_ERROR_INVALID_OPERATION;
 			}
 
-			int classes = mOutputLayerProperty.layers[outputMetadata.GetScoreName()].shape[indexes[0]];
-
 			if (!mOutputTensorBuffers.exist(outputMetadata.GetScoreName())) {
 				LOGE("output buffe is NULL");
 				return MEDIA_VISION_ERROR_INVALID_OPERATION;
 			}
 
-			PostProcess postProc;
-
-			postProc.ScoreClear(outputMetadata.GetScoreTopNumber());
+			top_number = outputMetadata.GetScoreTopNumber();
 			threadHold = outputMetadata.GetScoreThreshold();
 
-			for (int cId = 0; cId < classes; ++cId) {
-				float value = 0.0f;
+			classes = mOutputLayerProperty.layers[outputMetadata.GetScoreName()].shape[indexes[0]];
+		}
 
-				try {
-					value = mOutputTensorBuffers.getValue<float>(outputMetadata.GetScoreName(), cId);
-				} catch (const std::exception& e) {
-					LOGE(" Fail to get getValue with %s", e.what());
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
+		postProc.ScoreClear(top_number);
+
+		auto *prediction = reinterpret_cast<float *>(outputData.data[0]);
+
+		LOGI("class count: %d", classes);
+
+		for (unsigned int idx = 0; idx < classes; ++idx) {
+			float value = prediction[idx];
+
+			if (mMetadata.GetOutputMeta().IsParsed()) {
+				OutputMetadata outputMetadata = mMetadata.GetOutputMeta();
 
 				if (outputMetadata.GetScoreDeQuant()) {
 					value = PostProcess::dequant(value,
@@ -1138,59 +1152,15 @@ namespace inference
 
 				if (outputMetadata.GetScoreType() == INFERENCE_SCORE_TYPE_SIGMOID)
 					value = PostProcess::sigmoid(value);
-
-				if (value < threadHold)
-					continue;
-
-				LOGI("id[%d]: %.3f", cId, value);
-				postProc.ScorePush(value, cId);
 			}
 
-			postProc.ScorePop(topScore);
-		} else {
-			tensor_t outputData;
-
-			// Get inference result and contain it to outputData.
-			int ret = FillOutputResult(outputData);
-			if (ret != MEDIA_VISION_ERROR_NONE) {
-				LOGE("Fail to get output result.");
-				return ret;
-			}
-
-			auto classes = outputData.dimInfo[0][1];
-			auto *prediction = reinterpret_cast<float *>(outputData.data[0]);
-
-			LOGI("class count: %d", classes);
-
-			std::priority_queue<std::pair<float, int>,
-								std::vector<std::pair<float, int>>,
-								std::greater<std::pair<float, int>>>
-					top_result_pq;
-
-			for (int cId = 0; cId < classes; ++cId) {
-				auto value = prediction[cId];
-
-				if (value < threadHold)
-					continue;
-
-				// Only add it if it beats the threshold and has a chance at being in
-				// the top N.
-				top_result_pq.push(std::pair<float, int>(value, cId));
-
-				// If at capacity, kick the smallest value out.
-				if (top_result_pq.size() > static_cast<size_t>(mConfig.mMaxOutputNumbers))
-					top_result_pq.pop();
-			}
-
-			// Copy to output vector and reverse into descending order.
-			while (!top_result_pq.empty()) {
-				topScore.push_back(top_result_pq.top());
-				top_result_pq.pop();
-			}
+			if (value < threadHold)
+				continue;
 
-			std::reverse(topScore.begin(), topScore.end());
+			postProc.ScorePush(value, idx);
 		}
 
+		postProc.ScorePop(topScore);
 		results->number_of_classes = 0;
 
 		for (auto& score : topScore) {
diff --git a/mv_machine_learning/inference/src/PostProcess.cpp b/mv_machine_learning/inference/src/PostProcess.cpp
index b3a4a96..c7335b3 100755
--- a/mv_machine_learning/inference/src/PostProcess.cpp
+++ b/mv_machine_learning/inference/src/PostProcess.cpp
@@ -33,44 +33,31 @@ namespace inference
 
 	float PostProcess::dequant(float value, float scale, float zeropoint)
 	{
-		LOGI("ENTER");
-
-		LOGI("LEAVE");
 		return value/scale + zeropoint;
 	}
 
 	int PostProcess::ScoreClear(int size)
 	{
-		LOGI("ENTER");
-
 		std::priority_queue<std::pair<float, int>,
 							std::vector<std::pair<float, int>>,
 							std::greater<std::pair<float, int>>>().swap(mScore);
 		mMaxScoreSize = size;
 
-		LOGI("LEAVE");
-
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
 	int PostProcess::ScorePush(float value, int index)
 	{
-		LOGI("ENTER");
-
 		mScore.push(std::pair<float, int>(value, index));
 		if (mScore.size() > (size_t)mMaxScoreSize) {
 			mScore.pop();
 		}
 
-		LOGI("LEAVE");
-
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
 	int PostProcess::ScorePop(std::vector<std::pair<float, int>>& top)
 	{
-		LOGI("ENTER");
-
 		top.clear();
 		while (!mScore.empty()) {
 			top.push_back(mScore.top());
@@ -80,8 +67,6 @@ namespace inference
 
 		std::reverse(top.begin(), top.end());
 
-		LOGI("LEAVE");
-
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
-- 
2.7.4


From 1b01e0440e55b5baf5daecbb27f28e1b15386642 Mon Sep 17 00:00:00 2001
From: Inki Dae <inki.dae@samsung.com>
Date: Fri, 12 Aug 2022 08:04:14 +0900
Subject: [PATCH 02/16] mv_machine_learning: code refactoring to Inference
 class

[Issue type] : code refactoring

Did code refactoring to Inference class by doing,
	- extracted a function - ConvertOutputDataTypeToFloat - from
	  FillOutputResult function, which converts tensor data to float type.
	  In fact, float data of output tensor is needed commonly so
	  converted output tensor data to float type just after inference is
	  completed. And finally, it changed FillOuputResult function name to
	  GetTensorInfo and moved it to TensorBuffer class.
	- renamed several variables and function with meaningful name properly.

This patch is just a step for next code refactoring.

Change-Id: I4fd808ef05dd69203eb815a8230595aa1f1b7e54
Signed-off-by: Inki Dae <inki.dae@samsung.com>
---
 .../face_recognition/src/face_recognition.cpp      |  10 +-
 mv_machine_learning/inference/include/Inference.h  |   6 +-
 .../inference/include/TensorBuffer.h               |  10 +-
 mv_machine_learning/inference/src/Inference.cpp    | 142 ++++++++++-----------
 mv_machine_learning/inference/src/TensorBuffer.cpp |  55 +++++---
 5 files changed, 121 insertions(+), 102 deletions(-)

diff --git a/mv_machine_learning/face_recognition/src/face_recognition.cpp b/mv_machine_learning/face_recognition/src/face_recognition.cpp
index 5f21116..41a71ed 100644
--- a/mv_machine_learning/face_recognition/src/face_recognition.cpp
+++ b/mv_machine_learning/face_recognition/src/face_recognition.cpp
@@ -28,6 +28,7 @@
 #include <mv_private.h>
 
 #include "machine_learning_exception.h"
+#include "TensorBuffer.h"
 #include "face_recognition.h"
 #include "nntrainer_fvm.h"
 #include "nntrainer_dsm.h"
@@ -342,7 +343,8 @@ int FaceRecognition::RegisterNewFace(mv_source_h img_src, string label_name)
 
 		// 2. Get feature vector from a given vec through inference engine.
 		// Ps. output layer size should be 1.
-		inference_engine_tensor_buffer *backbone_output_buffer = _backbone->GetOutputTensorBuffer(output_layer_info[0].layer_name);
+		TensorBuffer tensorBuffer = _backbone->GetOutputTensorBuffer();
+		inference_engine_tensor_buffer *backbone_output_buffer = tensorBuffer.getTensorBuffer(output_layer_info[0].layer_name);
 		if (!backbone_output_buffer) {
 			LOGE("fail to get output tensor buffer.");
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -469,7 +471,8 @@ int FaceRecognition::RecognizeFace(mv_source_h img_src)
 		// Get output layer info for facenet model.
 		vector<model_layer_info>& output_layer_info = _backbone_model_info->GetOutputLayerInfo();
 		// Get output tensor buffer to the output layer.
-		inference_engine_tensor_buffer *backbone_output_buffer = _backbone->GetOutputTensorBuffer(output_layer_info[0].layer_name);
+		TensorBuffer tensorBuffer = _backbone->GetOutputTensorBuffer();
+		inference_engine_tensor_buffer *backbone_output_buffer = tensorBuffer.getTensorBuffer(output_layer_info[0].layer_name);
 		if (!backbone_output_buffer) {
 			LOGE("fail to get backbone output tensor buffer.");
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -504,7 +507,8 @@ int FaceRecognition::RecognizeFace(mv_source_h img_src)
 		}
 
 		// output layer size should be 1.
-		inference_engine_tensor_buffer *internal_output_buffer = _internal->GetOutputTensorBuffer(output_layers[0]);
+		tensorBuffer = _internal->GetOutputTensorBuffer();
+		inference_engine_tensor_buffer *internal_output_buffer = tensorBuffer.getTensorBuffer(output_layers[0]);
 		if (!internal_output_buffer) {
 			LOGE("fail to get internal output tensor buffer.");
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
diff --git a/mv_machine_learning/inference/include/Inference.h b/mv_machine_learning/inference/include/Inference.h
index 5db2092..7096094 100644
--- a/mv_machine_learning/inference/include/Inference.h
+++ b/mv_machine_learning/inference/include/Inference.h
@@ -317,9 +317,9 @@ namespace inference
 			return mConfig.mTargetTypes;
 		}
 
-		inference_engine_tensor_buffer* GetOutputTensorBuffer(std::string name)
+		TensorBuffer& GetOutputTensorBuffer()
 		{
-			return mOutputTensorBuffers.getTensorBuffer(name);
+			return mOutputTensorBuffers;
 		}
 
 	private:
@@ -350,12 +350,12 @@ namespace inference
 		int ConvertEngineErrorToVisionError(int error);
 		int ConvertTargetTypes(int given_types);
 		int ConvertToCv(int given_type);
+		int ConvertOutputDataTypeToFloat();
 		inference_tensor_data_type_e ConvertToIE(int given_type);
 		int Preprocess(cv::Mat cvImg, cv::Mat cvDst, int data_type);
 		int PrepareTenosrBuffers(void);
 		void CleanupTensorBuffers(void);
 		int SetUserFile(std::string filename);
-		int FillOutputResult(tensor_t &outputData);
 
 	};
 
diff --git a/mv_machine_learning/inference/include/TensorBuffer.h b/mv_machine_learning/inference/include/TensorBuffer.h
index c7d4ba3..2f48d4c 100644
--- a/mv_machine_learning/inference/include/TensorBuffer.h
+++ b/mv_machine_learning/inference/include/TensorBuffer.h
@@ -40,7 +40,7 @@ namespace inference
 	class TensorBuffer
 	{
 	private:
-		IETensorBuffer mTensorBuffer;
+		IETensorBuffer _tensorBuffer;
 
 	public:
 		TensorBuffer() = default;
@@ -53,12 +53,12 @@ namespace inference
 		void release();
 		size_t size();
 
-		IETensorBuffer& getAllTensorBuffer();
-		inference_engine_tensor_buffer* getTensorBuffer(std::string name);
+		IETensorBuffer& getIETensorBuffer();
 		bool addTensorBuffer(std::string name, inference_engine_tensor_buffer& buffer);
-
+		int GetTensorInfo(inference_engine_layer_property& layerProperty, tensor_t& tensorInfo);
+		inference_engine_tensor_buffer* getTensorBuffer(std::string name);
 		template <typename T>
-		int convertToFloat(inference_engine_tensor_buffer *tensorBuffer, const inference_engine_tensor_info& tensor_info);
+		int convertToFloat(inference_engine_tensor_buffer *tensorBuffer);
 
 		template <typename T>
 		T getValue(std::string name, int idx);
diff --git a/mv_machine_learning/inference/src/Inference.cpp b/mv_machine_learning/inference/src/Inference.cpp
index 478cd17..b655f22 100755
--- a/mv_machine_learning/inference/src/Inference.cpp
+++ b/mv_machine_learning/inference/src/Inference.cpp
@@ -665,7 +665,7 @@ namespace inference
 		}
 
 		// Get input tensor buffers from a backend engine if the backend engine allocated.
-		auto& inputTensorBuffers = mInputTensorBuffers.getAllTensorBuffer();
+		auto& inputTensorBuffers = mInputTensorBuffers.getIETensorBuffer();
 		int ret = mBackend->GetInputTensorBuffers(inputTensorBuffers);
 		if (ret != INFERENCE_ENGINE_ERROR_NONE) {
 			LOGE("Fail to get input tensor buffers from backend engine.");
@@ -698,7 +698,7 @@ namespace inference
 		LOGI("Input tensor buffer count is %zu", mInputTensorBuffers.size());
 
 		// Get output tensor buffers from a backend engine if the backend engine allocated.
-		auto& outputTensorBuffers = mOutputTensorBuffers.getAllTensorBuffer();
+		auto& outputTensorBuffers = mOutputTensorBuffers.getIETensorBuffer();
 		ret = mBackend->GetOutputTensorBuffers(outputTensorBuffers);
 		if (ret != INFERENCE_ENGINE_ERROR_NONE) {
 			LOGE("Fail to get output tensor buffers from backend engine.");
@@ -733,43 +733,29 @@ namespace inference
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	int Inference::FillOutputResult(tensor_t &outputData)
+	int Inference::ConvertOutputDataTypeToFloat()
 	{
-		for (auto& layer : mOutputLayerProperty.layers) {
-			const inference_engine_tensor_info& tensor_info = layer.second;
+		IETensorBuffer& ieTensorBuffers = mOutputTensorBuffers.getIETensorBuffer();
 
-			std::vector<int> tmpDimInfo;
-			for (auto& dim : tensor_info.shape) {
-				tmpDimInfo.push_back(dim);
-			}
-
-			outputData.dimInfo.push_back(tmpDimInfo);
-
-			inference_engine_tensor_buffer* tensorBuffer =
-								mOutputTensorBuffers.getTensorBuffer(layer.first);
-			if (tensorBuffer == NULL) {
-				LOGE("Fail to getTensorBuffer with name %s", layer.first.c_str());
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
+		for (auto& ieTensorBuffer : ieTensorBuffers) {
+			auto& tensorBuffer = ieTensorBuffer.second;
 
 			// Normalize output tensor data converting it to float type in case of quantized model.
-			if (tensor_info.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT8) {
-				int ret = mOutputTensorBuffers.convertToFloat<unsigned char>(tensorBuffer, tensor_info);
+			if (tensorBuffer.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT8) {
+				int ret = mOutputTensorBuffers.convertToFloat<unsigned char>(&tensorBuffer);
 				if (ret != MEDIA_VISION_ERROR_NONE) {
 					LOGE("Fail to convert tensor data to float type.");
 					return ret;
 				}
 			}
 
-			if (tensor_info.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT16) {
-				int ret = mOutputTensorBuffers.convertToFloat<unsigned short>(tensorBuffer, tensor_info);
+			if (tensorBuffer.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT16) {
+				int ret = mOutputTensorBuffers.convertToFloat<unsigned short>(&tensorBuffer);
 				if (ret != MEDIA_VISION_ERROR_NONE) {
 					LOGE("Fail to convert tensor data to float type.");
 					return ret;
 				}
 			}
-
-			outputData.data.push_back(static_cast<void *>(tensorBuffer->buffer));
 		}
 
 		return MEDIA_VISION_ERROR_NONE;
@@ -998,7 +984,7 @@ namespace inference
 		}
 
 		if (mMetadata.GetInputMeta().IsParsed()) {
-			for (auto& buffer : mInputTensorBuffers.getAllTensorBuffer()) {
+			for (auto& buffer : mInputTensorBuffers.getIETensorBuffer()) {
 				inference_engine_tensor_buffer& tensor_buffer = buffer.second;
 				const LayerInfo& layerInfo = mMetadata.GetInputMeta().GetLayer().at(buffer.first);
 				const Options& opt = mMetadata.GetInputMeta().GetOption().empty() ? Options() : mMetadata.GetInputMeta().GetOption().at(buffer.first);
@@ -1015,7 +1001,7 @@ namespace inference
 				}
 			}
 		} else {
-			for (auto& buffer : mInputTensorBuffers.getAllTensorBuffer()) {
+			for (auto& buffer : mInputTensorBuffers.getIETensorBuffer()) {
 				inference_engine_tensor_buffer& tensor_buffer = buffer.second;
 
 				int data_type = ConvertToCv(tensor_buffer.data_type);
@@ -1033,10 +1019,12 @@ namespace inference
 			}
 		}
 
-		ret = mBackend->Run(mInputTensorBuffers.getAllTensorBuffer(),
-							mOutputTensorBuffers.getAllTensorBuffer());
+		ret = mBackend->Run(mInputTensorBuffers.getIETensorBuffer(),
+							mOutputTensorBuffers.getIETensorBuffer());
+		if (ret != INFERENCE_ENGINE_ERROR_NONE)
+			return ret;
 
-		return ConvertEngineErrorToVisionError(ret);
+		return ConvertOutputDataTypeToFloat();
 	}
 
 	int Inference::Run(std::vector<void *>& buffer_objs)
@@ -1059,14 +1047,14 @@ namespace inference
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 		}
 
-		if (mInputTensorBuffers.getAllTensorBuffer().size() != buffer_objs.size()) {
+		if (mInputTensorBuffers.getIETensorBuffer().size() != buffer_objs.size()) {
 			LOGE("Raw source count is not invalid.");
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 		}
 
 		unsigned int buffer_idx = 0;
 
-		for (auto& buffer : mInputTensorBuffers.getAllTensorBuffer()) {
+		for (auto& buffer : mInputTensorBuffers.getIETensorBuffer()) {
 			inference_engine_tensor_buffer& tensor_buffer = buffer.second;
 			inference_engine_tensor_buffer *buffer_obj = static_cast<inference_engine_tensor_buffer *>(buffer_objs[buffer_idx]);
 
@@ -1081,10 +1069,12 @@ namespace inference
 			buffer_idx++;
 		}
 
-		ret = mBackend->Run(mInputTensorBuffers.getAllTensorBuffer(),
-							mOutputTensorBuffers.getAllTensorBuffer());
+		ret = mBackend->Run(mInputTensorBuffers.getIETensorBuffer(),
+							mOutputTensorBuffers.getIETensorBuffer());
+		if (ret != INFERENCE_ENGINE_ERROR_NONE)
+			return ret;
 
-		return ConvertEngineErrorToVisionError(ret);
+		return ConvertOutputDataTypeToFloat();
 	}
 
 	std::pair<std::string, bool>
@@ -1099,17 +1089,17 @@ namespace inference
 		std::vector<std::pair<float, int>> topScore;
 		auto threadHold = mConfig.mConfidenceThresHold;
 		constexpr unsigned int default_top_number = 5;
-		tensor_t outputData;
+		tensor_t outputTensorInfo;
 
-		// Get inference result and contain it to outputData.
-		int ret = FillOutputResult(outputData);
+		// Get inference result and contain it to outputTensorInfo.
+		int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
 		if (ret != MEDIA_VISION_ERROR_NONE) {
 			LOGE("Fail to get output result.");
 			return ret;
 		}
 
 		PostProcess postProc;
-		unsigned int classes = outputData.dimInfo[0][1];
+		unsigned int classes = outputTensorInfo.dimInfo[0][1];
 		unsigned int top_number = default_top_number;
 
 		if (mMetadata.GetOutputMeta().IsParsed()) {
@@ -1134,7 +1124,7 @@ namespace inference
 
 		postProc.ScoreClear(top_number);
 
-		auto *prediction = reinterpret_cast<float *>(outputData.data[0]);
+		auto *prediction = reinterpret_cast<float *>(outputTensorInfo.data[0]);
 
 		LOGI("class count: %d", classes);
 
@@ -1249,10 +1239,10 @@ namespace inference
 
 			LOGI("Inference: GetObjectDetectionResults: %d\n", results->number_of_objects);
 		} else {
-			tensor_t outputData;
+			tensor_t outputTensorInfo;
 
-			// Get inference result and contain it to outputData.
-			int ret = FillOutputResult(outputData);
+			// Get inference result and contain it to outputTensorInfo.
+			int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
 			if (ret != MEDIA_VISION_ERROR_NONE) {
 				LOGE("Fail to get output result.");
 				return ret;
@@ -1267,18 +1257,18 @@ namespace inference
 			float *scores = nullptr;
 			int number_of_detections = 0;
 
-			if (outputData.dimInfo.size() == 1) {
+			if (outputTensorInfo.dimInfo.size() == 1) {
 				// there is no way to know how many objects are detect unless the number of objects aren't
 				// provided. In the case, each backend should provide the number of results manually.
 				// For example, in OpenCV, MobilenetV1-SSD doesn't provide it so the number of objects are
-				// written to the 1st element i.e., outputData.data[0] (the shape is 1x1xNx7 and the 1st of 7
+				// written to the 1st element i.e., outputTensorInfo.data[0] (the shape is 1x1xNx7 and the 1st of 7
 				// indicates the image id. But it is useless if a batch mode isn't supported.
 				// So, use the 1st of 7.
 
 				number_of_detections = static_cast<int>(
-						*reinterpret_cast<float *>(outputData.data[0]));
-				cv::Mat cvOutputData(number_of_detections, outputData.dimInfo[0][3],
-									CV_32F, outputData.data[0]);
+						*reinterpret_cast<float *>(outputTensorInfo.data[0]));
+				cv::Mat cvOutputData(number_of_detections, outputTensorInfo.dimInfo[0][3],
+									CV_32F, outputTensorInfo.data[0]);
 
 				// boxes
 				cv::Mat cvLeft = cvOutputData.col(3).clone();
@@ -1300,10 +1290,10 @@ namespace inference
 				classes = cvClasses.ptr<float>(0);
 				scores = cvScores.ptr<float>(0);
 			} else {
-				boxes = reinterpret_cast<float *>(outputData.data[0]);
-				classes = reinterpret_cast<float *>(outputData.data[1]);
-				scores = reinterpret_cast<float *>(outputData.data[2]);
-				number_of_detections = (int) (*reinterpret_cast<float *>(outputData.data[3]));
+				boxes = reinterpret_cast<float *>(outputTensorInfo.data[0]);
+				classes = reinterpret_cast<float *>(outputTensorInfo.data[1]);
+				scores = reinterpret_cast<float *>(outputTensorInfo.data[2]);
+				number_of_detections = (int) (*reinterpret_cast<float *>(outputTensorInfo.data[3]));
 			}
 
 			LOGI("number_of_detections = %d", number_of_detections);
@@ -1404,10 +1394,10 @@ namespace inference
 
 			LOGE("Inference: GetFaceDetectionResults: %d\n", results->number_of_faces);
 		} else {
-			tensor_t outputData;
+			tensor_t outputTensorInfo;
 
-			// Get inference result and contain it to outputData.
-			int ret = FillOutputResult(outputData);
+			// Get inference result and contain it to outputTensorInfo.
+			int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
 			if (ret != MEDIA_VISION_ERROR_NONE) {
 				LOGE("Fail to get output result.");
 				return ret;
@@ -1423,16 +1413,16 @@ namespace inference
 			int number_of_detections = 0;
 			cv::Mat cvScores, cvClasses, cvBoxes;
 
-			if (outputData.dimInfo.size() == 1) {
+			if (outputTensorInfo.dimInfo.size() == 1) {
 				// there is no way to know how many objects are detect unless the number of objects aren't
 				// provided. In the case, each backend should provide the number of results manually.
 				// For example, in OpenCV, MobilenetV1-SSD doesn't provide it so the number of objects are
-				// written to the 1st element i.e., outputData.data[0] (the shape is 1x1xNx7 and the 1st of 7
+				// written to the 1st element i.e., outputTensorInfo.data[0] (the shape is 1x1xNx7 and the 1st of 7
 				// indicates the image id. But it is useless if a batch mode isn't supported.
 				// So, use the 1st of 7.
 
-				number_of_detections = static_cast<int>(*reinterpret_cast<float *>(outputData.data[0]));
-				cv::Mat cvOutputData(number_of_detections, outputData.dimInfo[0][3], CV_32F, outputData.data[0]);
+				number_of_detections = static_cast<int>(*reinterpret_cast<float *>(outputTensorInfo.data[0]));
+				cv::Mat cvOutputData(number_of_detections, outputTensorInfo.dimInfo[0][3], CV_32F, outputTensorInfo.data[0]);
 
 				// boxes
 				cv::Mat cvLeft = cvOutputData.col(3).clone();
@@ -1452,10 +1442,10 @@ namespace inference
 				classes = cvClasses.ptr<float>(0);
 				scores = cvScores.ptr<float>(0);
 			} else {
-				boxes = reinterpret_cast<float *>(outputData.data[0]);
-				classes = reinterpret_cast<float *>(outputData.data[1]);
-				scores = reinterpret_cast<float *>(outputData.data[2]);
-				number_of_detections = static_cast<int>(*reinterpret_cast<float *>(outputData.data[3]));
+				boxes = reinterpret_cast<float *>(outputTensorInfo.data[0]);
+				classes = reinterpret_cast<float *>(outputTensorInfo.data[1]);
+				scores = reinterpret_cast<float *>(outputTensorInfo.data[2]);
+				number_of_detections = static_cast<int>(*reinterpret_cast<float *>(outputTensorInfo.data[3]));
 			}
 
 			results->number_of_faces = 0;
@@ -1558,23 +1548,23 @@ namespace inference
 
 			results->number_of_landmarks = results->locations.size();
 		} else {
-			tensor_t outputData;
+			tensor_t outputTensorInfo;
 
-			// Get inference result and contain it to outputData.
-			int ret = FillOutputResult(outputData);
+			// Get inference result and contain it to outputTensorInfo.
+			int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
 			if (ret != MEDIA_VISION_ERROR_NONE) {
 				LOGE("Fail to get output result.");
 				return ret;
 			}
 
-			int number_of_detections = outputData.dimInfo[0][1] >> 1;
+			int number_of_detections = outputTensorInfo.dimInfo[0][1] >> 1;
 
 			results->number_of_landmarks = number_of_detections;
 			results->locations.resize(number_of_detections);
 
 			LOGI("imgW:%d, imgH:%d", mSourceSize.width, mSourceSize.height);
 
-			float *loc = reinterpret_cast<float *>(outputData.data[0]);
+			float *loc = reinterpret_cast<float *>(outputTensorInfo.data[0]);
 
 			for (auto& point : results->locations) {
 				point.x = static_cast<int>(*loc++ * mSourceSize.width);
@@ -1689,26 +1679,26 @@ namespace inference
 
 			detectionResults = std::move(poseResult);
 		} else {
-			tensor_t outputData;
+			tensor_t outputTensorInfo;
 
-			// Get inference result and contain it to outputData.
-			int ret = FillOutputResult(outputData);
+			// Get inference result and contain it to outputTensorInfo.
+			int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
 			if (ret != MEDIA_VISION_ERROR_NONE) {
 					LOGE("Fail to get output result.");
 					return ret;
 			}
 
-			cv::Mat reShapeTest(cv::Size(outputData.dimInfo[0][2], outputData.dimInfo[0][1]),
-										 CV_32FC(outputData.dimInfo[0][3]), outputData.data[0]);
-			cv::Mat multiChannels[outputData.dimInfo[0][3]];
+			cv::Mat reShapeTest(cv::Size(outputTensorInfo.dimInfo[0][2], outputTensorInfo.dimInfo[0][1]),
+										 CV_32FC(outputTensorInfo.dimInfo[0][3]), outputTensorInfo.data[0]);
+			cv::Mat multiChannels[outputTensorInfo.dimInfo[0][3]];
 
 			split(reShapeTest, multiChannels);
 
-			float ratioX = static_cast<float>(outputData.dimInfo[0][2]);
-			float ratioY = static_cast<float>(outputData.dimInfo[0][1]);
+			float ratioX = static_cast<float>(outputTensorInfo.dimInfo[0][2]);
+			float ratioY = static_cast<float>(outputTensorInfo.dimInfo[0][1]);
 
 			poseResult->number_of_poses = 1;
-			poseResult->number_of_landmarks_per_pose = outputData.dimInfo[0][3];
+			poseResult->number_of_landmarks_per_pose = outputTensorInfo.dimInfo[0][3];
 
 			if (poseResult->number_of_landmarks_per_pose >= MAX_NUMBER_OF_LANDMARKS_PER_POSE) {
 				LOGE("Exeeded maxinum number of landmarks per pose(%d >= %d).",
diff --git a/mv_machine_learning/inference/src/TensorBuffer.cpp b/mv_machine_learning/inference/src/TensorBuffer.cpp
index e08e5d8..161f72f 100644
--- a/mv_machine_learning/inference/src/TensorBuffer.cpp
+++ b/mv_machine_learning/inference/src/TensorBuffer.cpp
@@ -31,7 +31,7 @@ namespace inference
 
 	bool TensorBuffer::empty()
 	{
-		return mTensorBuffer.empty();
+		return _tensorBuffer.empty();
 	}
 
 	bool TensorBuffer::exist(std::string name)
@@ -78,7 +78,7 @@ namespace inference
 
 	void TensorBuffer::release()
 	{
-		for (auto& tensorBuffer : mTensorBuffer) {
+		for (auto& tensorBuffer : _tensorBuffer) {
 			auto& tBuffer = tensorBuffer.second;
 			if (tBuffer.owner_is_backend) {
 				continue;
@@ -97,27 +97,27 @@ namespace inference
 			}
 		}
 
-		LOGI("Tensor(%zu) have been released.", mTensorBuffer.size());
-		IETensorBuffer().swap(mTensorBuffer);
+		LOGI("Tensor(%zu) have been released.", _tensorBuffer.size());
+		IETensorBuffer().swap(_tensorBuffer);
 	}
 
 	size_t TensorBuffer::size()
 	{
-		return mTensorBuffer.size();
+		return _tensorBuffer.size();
 	}
 
-	IETensorBuffer& TensorBuffer::getAllTensorBuffer()
+	IETensorBuffer& TensorBuffer::getIETensorBuffer()
 	{
-		return mTensorBuffer;
+		return _tensorBuffer;
 	}
 
 	inference_engine_tensor_buffer* TensorBuffer::getTensorBuffer(std::string name)
 	{
-		if (mTensorBuffer.find(name) == mTensorBuffer.end()){
+		if (_tensorBuffer.find(name) == _tensorBuffer.end()){
 			return nullptr;
 		}
 
-		return &mTensorBuffer[name];
+		return &_tensorBuffer[name];
 	}
 
 	bool TensorBuffer::addTensorBuffer(std::string name, inference_engine_tensor_buffer& buffer)
@@ -127,7 +127,7 @@ namespace inference
 			return false;
 		}
 
-		auto ret = mTensorBuffer.insert(std::make_pair(name, buffer));
+		auto ret = _tensorBuffer.insert(std::make_pair(name, buffer));
 		if (ret.second == false) {
 			LOGE("Fail to insert %s with buffer %p", name.c_str(), buffer.buffer);
 			return false;
@@ -136,10 +136,35 @@ namespace inference
 		return true;
 	}
 
+	int TensorBuffer::GetTensorInfo(inference_engine_layer_property& layerProperty, tensor_t& outputTensorInfo)
+	{
+		for (auto& layer : layerProperty.layers) {
+			const inference_engine_tensor_info& tensor_info = layer.second;
+
+			std::vector<int> dimInfo;
+
+			for (auto& dim : tensor_info.shape) {
+				dimInfo.push_back(dim);
+			}
+
+			outputTensorInfo.dimInfo.push_back(dimInfo);
+
+			inference_engine_tensor_buffer* tensorBuffer = getTensorBuffer(layer.first);
+			if (tensorBuffer == NULL) {
+				LOGE("Fail to getTensorBuffer with name %s", layer.first.c_str());
+				return MEDIA_VISION_ERROR_INVALID_OPERATION;
+			}
+
+			outputTensorInfo.data.push_back(static_cast<void *>(tensorBuffer->buffer));
+		}
+
+		return MEDIA_VISION_ERROR_NONE;
+	}
+
 	template <typename T>
-	int TensorBuffer::convertToFloat(inference_engine_tensor_buffer *tensorBuffer, const inference_engine_tensor_info& tensor_info)
+	int TensorBuffer::convertToFloat(inference_engine_tensor_buffer *tensorBuffer)
 	{
-		float *new_buf = new(std::nothrow) float[tensor_info.size];
+		float *new_buf = new(std::nothrow) float[tensorBuffer->size];
 		if (new_buf == NULL) {
 			LOGE("Fail to allocate a new output tensor buffer.");
 			return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
@@ -147,7 +172,7 @@ namespace inference
 
 		auto ori_buf = static_cast<T *>(tensorBuffer->buffer);
 
-		for (size_t idx = 0; idx < tensor_info.size; idx++)
+		for (size_t idx = 0; idx < tensorBuffer->size; idx++)
 			new_buf[idx] = static_cast<float>(ori_buf[idx]) / 255.0f;
 
 		// replace original buffer with new one, and release origin one.
@@ -195,8 +220,8 @@ namespace inference
 
 	template float TensorBuffer::getValue<float>(std::string, int);
 	template int TensorBuffer::getValue<int>(std::string, int);
-	template int TensorBuffer::convertToFloat<unsigned char>(_inference_engine_tensor_buffer*, _inference_engine_tensor_info const&);
-	template int TensorBuffer::convertToFloat<unsigned short>(_inference_engine_tensor_buffer*, _inference_engine_tensor_info const&);
+	template int TensorBuffer::convertToFloat<unsigned char>(_inference_engine_tensor_buffer*);
+	template int TensorBuffer::convertToFloat<unsigned short>(_inference_engine_tensor_buffer*);
 
 } /* Inference */
 } /* MediaVision */
-- 
2.7.4


From fa6bfdb69365fb4285322eccc86aec19516e24d0 Mon Sep 17 00:00:00 2001
From: Kwanghoon Son <k.son@samsung.com>
Date: Thu, 25 Aug 2022 22:00:57 -0400
Subject: [PATCH 03/16] Apply code lint and update copyright year

Change-Id: I53fd18c3c5b3961b8c7e8fb903199e4150bf03e3
Signed-off-by: Kwanghoon Son <k.son@samsung.com>
---
 mv_machine_learning/inference/include/ScoreInfo.h | 205 ++++++++++++----------
 1 file changed, 116 insertions(+), 89 deletions(-)

diff --git a/mv_machine_learning/inference/include/ScoreInfo.h b/mv_machine_learning/inference/include/ScoreInfo.h
index 2004002..096a120 100644
--- a/mv_machine_learning/inference/include/ScoreInfo.h
+++ b/mv_machine_learning/inference/include/ScoreInfo.h
@@ -1,5 +1,5 @@
 /**
- * Copyright (c) 2021 Samsung Electronics Co., Ltd All Rights Reserved
+ * Copyright (c) 2021 - 2022 Samsung Electronics Co., Ltd All Rights Reserved
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -30,103 +30,130 @@ namespace mediavision
 {
 namespace inference
 {
-	struct DeQuantization
+struct DeQuantization
+{
+	double scale;
+	double zeropoint;
+
+	DeQuantization(double s, double z) : scale(s), zeropoint(z)
+	{}
+};
+
+class ScoreInfo
+{
+private:
+	std::string name;
+	DimInfo dimInfo;
+	double threshold;
+	int topNumber;
+	inference_score_type_e type;
+	std::shared_ptr<DeQuantization> deQuantization;
+	std::map<std::string, inference_score_type_e> supportedScoreTypes;
+
+public:
+	ScoreInfo()
+			: name()
+			, dimInfo()
+			, threshold(0.0)
+			, topNumber(1)
+			, type(INFERENCE_SCORE_TYPE_NORMAL)
+			, deQuantization(nullptr)
 	{
-		double scale;
-		double zeropoint;
+		// Score type
+		supportedScoreTypes.insert({ "NORMAL", INFERENCE_SCORE_TYPE_NORMAL });
+		supportedScoreTypes.insert({ "SIGMOID", INFERENCE_SCORE_TYPE_SIGMOID });
+	}
 
-		DeQuantization(double s, double z) : scale(s), zeropoint(z) { }
-	};
+	~ScoreInfo() = default;
 
-	class ScoreInfo
+	std::string GetName()
 	{
-	private:
-		std::string name;
-		DimInfo dimInfo;
-		double threshold;
-		int topNumber;
-		inference_score_type_e type;
-		std::shared_ptr<DeQuantization> deQuantization;
-		std::map<std::string, inference_score_type_e> supportedScoreTypes;
-
-	public:
-		ScoreInfo() :
-			name(),
-			dimInfo(),
-			threshold(0.0),
-			topNumber(1),
-			type(INFERENCE_SCORE_TYPE_NORMAL),
-			deQuantization(nullptr)
-		{
-			// Score type
-			supportedScoreTypes.insert({"NORMAL", INFERENCE_SCORE_TYPE_NORMAL});
-			supportedScoreTypes.insert({"SIGMOID", INFERENCE_SCORE_TYPE_SIGMOID});
-		}
+		return name;
+	}
+	DimInfo GetDimInfo()
+	{
+		return dimInfo;
+	}
+	double GetThresHold()
+	{
+		return threshold;
+	}
+	inference_score_type_e GetType()
+	{
+		return type;
+	}
+	int GetTopNumber()
+	{
+		return topNumber;
+	}
+	std::shared_ptr<DeQuantization> GetDeQuant()
+	{
+		return deQuantization;
+	}
+	double GetDeQuantScale()
+	{
+		return deQuantization->scale;
+	}
+	double GetDeQuantZeroPoint()
+	{
+		return deQuantization->zeropoint;
+	}
 
-		~ScoreInfo() = default;
-
-		std::string GetName() { return name; }
-		DimInfo GetDimInfo() { return dimInfo; }
-		double GetThresHold() { return threshold; }
-		inference_score_type_e GetType() { return type; }
-		int GetTopNumber() { return topNumber; }
-		std::shared_ptr<DeQuantization> GetDeQuant() { return deQuantization; }
-		double GetDeQuantScale() { return deQuantization->scale; }
-		double GetDeQuantZeroPoint() { return deQuantization->zeropoint; }
-
-		int ParseScore(JsonObject *root)
-		{
-			LOGI("ENTER");
-
-			JsonArray * rootArray = json_object_get_array_member(root, "score");
-			unsigned int elements = json_array_get_length(rootArray);
-
-			for (unsigned int elem = 0; elem < elements; ++elem) {
-				JsonNode *pNode = json_array_get_element(rootArray, elem);
-				JsonObject *pObject = json_node_get_object(pNode);
-
-				name = json_object_get_string_member(pObject,"name");
-				LOGI("layer: %s", name.c_str());
-
-				JsonArray * array = json_object_get_array_member(pObject, "index");
-				unsigned int elements2 = json_array_get_length(array);
-				LOGI("range dim: size[%u]", elements2);
-				for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
-					if (static_cast<int>(json_array_get_int_element(array, elem2)) == 1)
-						dimInfo.SetValidIndex(elem2);
-				}
-				if (json_object_has_member(pObject, "top_number"))
-					topNumber = static_cast<int>(
-							json_object_get_int_member(pObject, "top_number"));
-				LOGI("top number: %d", topNumber);
-
-				if (json_object_has_member(pObject, "threshold"))
-					threshold = static_cast<double>(
-							json_object_get_double_member(pObject, "threshold"));
-				LOGI("threshold: %1.3f", threshold);
-
-				try {
-					type = GetSupportedType(pObject, "score_type", supportedScoreTypes);
-				} catch (const std::exception& e) {
-					LOGE("Invalid %s", e.what());
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-
-				if (json_object_has_member(pObject, "dequantization")) {
-					array = json_object_get_array_member(pObject, "dequantization");
-					JsonNode *node = json_array_get_element(array, 0);
-					JsonObject *object = json_node_get_object(node);
-
-					deQuantization = std::make_shared<DeQuantization>(
+	int ParseScore(JsonObject *root)
+	{
+		LOGI("ENTER");
+
+		JsonArray *rootArray = json_object_get_array_member(root, "score");
+		unsigned int elements = json_array_get_length(rootArray);
+
+		for (unsigned int elem = 0; elem < elements; ++elem) {
+			JsonNode *pNode = json_array_get_element(rootArray, elem);
+			JsonObject *pObject = json_node_get_object(pNode);
+
+			name = json_object_get_string_member(pObject, "name");
+			LOGI("layer: %s", name.c_str());
+
+			JsonArray *array = json_object_get_array_member(pObject, "index");
+			unsigned int elements2 = json_array_get_length(array);
+			LOGI("range dim: size[%u]", elements2);
+			for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
+				if (static_cast<int>(
+							json_array_get_int_element(array, elem2)) == 1)
+					dimInfo.SetValidIndex(elem2);
+			}
+			if (json_object_has_member(pObject, "top_number"))
+				topNumber = static_cast<int>(
+						json_object_get_int_member(pObject, "top_number"));
+			LOGI("top number: %d", topNumber);
+
+			if (json_object_has_member(pObject, "threshold"))
+				threshold = static_cast<double>(
+						json_object_get_double_member(pObject, "threshold"));
+			LOGI("threshold: %1.3f", threshold);
+
+			try {
+				type = GetSupportedType(pObject, "score_type",
+										supportedScoreTypes);
+			} catch (const std::exception &e) {
+				LOGE("Invalid %s", e.what());
+				return MEDIA_VISION_ERROR_INVALID_OPERATION;
+			}
+
+			if (json_object_has_member(pObject, "dequantization")) {
+				array = json_object_get_array_member(pObject, "dequantization");
+				JsonNode *node = json_array_get_element(array, 0);
+				JsonObject *object = json_node_get_object(node);
+
+				deQuantization = std::make_shared<DeQuantization>(
 						json_object_get_double_member(object, "scale"),
 						json_object_get_double_member(object, "zeropoint"));
-				}
 			}
-
-			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
 		}
-	};
+
+		LOGI("LEAVE");
+		return MEDIA_VISION_ERROR_NONE;
+	}
+};
 } /* Inference */
 } /* MediaVision */
 
-- 
2.7.4


From a179cb54eefe437e96a296fc7299e6d61e7f498b Mon Sep 17 00:00:00 2001
From: Kwanghoon Son <k.son@samsung.com>
Date: Fri, 26 Aug 2022 00:14:31 -0400
Subject: [PATCH 04/16] Fix score array to object in meta json

outputmetadata score object has array, but usage only accept 1 array
element. This change handle object instead array.
`before`
"score" : [
    {
        "name" : "some name",
	...
    }
],
`after`
"score" :
    {
        "name" : "some name",
	...
    }

Change-Id: I5a3ddb4c4d29ffd7f2024a40e5065222d7197fc9
Signed-off-by: Kwanghoon Son <k.son@samsung.com>
---
 mv_machine_learning/inference/include/ScoreInfo.h | 85 +++++++++++------------
 1 file changed, 40 insertions(+), 45 deletions(-)

diff --git a/mv_machine_learning/inference/include/ScoreInfo.h b/mv_machine_learning/inference/include/ScoreInfo.h
index 096a120..97e0c52 100644
--- a/mv_machine_learning/inference/include/ScoreInfo.h
+++ b/mv_machine_learning/inference/include/ScoreInfo.h
@@ -102,52 +102,47 @@ public:
 	int ParseScore(JsonObject *root)
 	{
 		LOGI("ENTER");
+		if (!json_object_has_member(root, "score")) {
+			LOGE("member score not exists");
+			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+		}
+		JsonObject *pObject = json_object_get_object_member(root, "score");
+
+		name = json_object_get_string_member(pObject, "name");
+		LOGI("layer: %s", name.c_str());
+
+		JsonArray *array = json_object_get_array_member(pObject, "index");
+		unsigned int elements2 = json_array_get_length(array);
+		LOGI("range dim: size[%u]", elements2);
+		for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
+			if (static_cast<int>(json_array_get_int_element(array, elem2)) == 1)
+				dimInfo.SetValidIndex(elem2);
+		}
+		if (json_object_has_member(pObject, "top_number"))
+			topNumber = static_cast<int>(
+					json_object_get_int_member(pObject, "top_number"));
+		LOGI("top number: %d", topNumber);
+
+		if (json_object_has_member(pObject, "threshold"))
+			threshold = static_cast<double>(
+					json_object_get_double_member(pObject, "threshold"));
+		LOGI("threshold: %1.3f", threshold);
+
+		try {
+			type = GetSupportedType(pObject, "score_type", supportedScoreTypes);
+		} catch (const std::exception &e) {
+			LOGE("Invalid %s", e.what());
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
+		}
+
+		if (json_object_has_member(pObject, "dequantization")) {
+			array = json_object_get_array_member(pObject, "dequantization");
+			JsonNode *node = json_array_get_element(array, 0);
+			JsonObject *object = json_node_get_object(node);
 
-		JsonArray *rootArray = json_object_get_array_member(root, "score");
-		unsigned int elements = json_array_get_length(rootArray);
-
-		for (unsigned int elem = 0; elem < elements; ++elem) {
-			JsonNode *pNode = json_array_get_element(rootArray, elem);
-			JsonObject *pObject = json_node_get_object(pNode);
-
-			name = json_object_get_string_member(pObject, "name");
-			LOGI("layer: %s", name.c_str());
-
-			JsonArray *array = json_object_get_array_member(pObject, "index");
-			unsigned int elements2 = json_array_get_length(array);
-			LOGI("range dim: size[%u]", elements2);
-			for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
-				if (static_cast<int>(
-							json_array_get_int_element(array, elem2)) == 1)
-					dimInfo.SetValidIndex(elem2);
-			}
-			if (json_object_has_member(pObject, "top_number"))
-				topNumber = static_cast<int>(
-						json_object_get_int_member(pObject, "top_number"));
-			LOGI("top number: %d", topNumber);
-
-			if (json_object_has_member(pObject, "threshold"))
-				threshold = static_cast<double>(
-						json_object_get_double_member(pObject, "threshold"));
-			LOGI("threshold: %1.3f", threshold);
-
-			try {
-				type = GetSupportedType(pObject, "score_type",
-										supportedScoreTypes);
-			} catch (const std::exception &e) {
-				LOGE("Invalid %s", e.what());
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
-
-			if (json_object_has_member(pObject, "dequantization")) {
-				array = json_object_get_array_member(pObject, "dequantization");
-				JsonNode *node = json_array_get_element(array, 0);
-				JsonObject *object = json_node_get_object(node);
-
-				deQuantization = std::make_shared<DeQuantization>(
-						json_object_get_double_member(object, "scale"),
-						json_object_get_double_member(object, "zeropoint"));
-			}
+			deQuantization = std::make_shared<DeQuantization>(
+					json_object_get_double_member(object, "scale"),
+					json_object_get_double_member(object, "zeropoint"));
 		}
 
 		LOGI("LEAVE");
-- 
2.7.4


From d0a2d5d5c2af91a7218ab0689175561a9e6c1bd3 Mon Sep 17 00:00:00 2001
From: Kwanghoon Son <k.son@samsung.com>
Date: Sun, 28 Aug 2022 22:33:19 -0400
Subject: [PATCH 05/16] Change score name to array in meta json

outputmetadata score name was single string, but needs to change to
handle yolo models.(multiple names)
`before`
"score" :
    {
        "name" : "some name",
        ...
    }
`after`
"score" :
    {
        "name" : ["some name"],
        ...
    }

Change-Id: Ie76b38ad6eb7665300b556c2d9ce0be576a537f3
Signed-off-by: Kwanghoon Son <k.son@samsung.com>
---
 mv_machine_learning/inference/include/ScoreInfo.h | 22 ++++++++++++++++------
 1 file changed, 16 insertions(+), 6 deletions(-)

diff --git a/mv_machine_learning/inference/include/ScoreInfo.h b/mv_machine_learning/inference/include/ScoreInfo.h
index 97e0c52..5810324 100644
--- a/mv_machine_learning/inference/include/ScoreInfo.h
+++ b/mv_machine_learning/inference/include/ScoreInfo.h
@@ -23,6 +23,7 @@
 #include <memory>
 
 #include <mv_inference_type.h>
+#include <mv_private.h>
 #include "DimInfo.h"
 #include "Utils.h"
 
@@ -42,7 +43,7 @@ struct DeQuantization
 class ScoreInfo
 {
 private:
-	std::string name;
+	std::vector<std::string> names;
 	DimInfo dimInfo;
 	double threshold;
 	int topNumber;
@@ -52,7 +53,7 @@ private:
 
 public:
 	ScoreInfo()
-			: name()
+			: names()
 			, dimInfo()
 			, threshold(0.0)
 			, topNumber(1)
@@ -68,7 +69,7 @@ public:
 
 	std::string GetName()
 	{
-		return name;
+		return names[0];
 	}
 	DimInfo GetDimInfo()
 	{
@@ -108,10 +109,19 @@ public:
 		}
 		JsonObject *pObject = json_object_get_object_member(root, "score");
 
-		name = json_object_get_string_member(pObject, "name");
-		LOGI("layer: %s", name.c_str());
+		JsonArray *array = json_object_get_array_member(pObject, "name");
+		MEDIA_VISION_NULL_ARG_CHECK(array);
 
-		JsonArray *array = json_object_get_array_member(pObject, "index");
+		unsigned int elements1 = json_array_get_length(array);
+		MEDIA_VISION_CHECK_CONDITION(elements1 > 0,
+									 MEDIA_VISION_ERROR_INVALID_PARAMETER,
+									 "No name on meta file");
+
+		for (unsigned int elem1 = 0; elem1 < elements1; ++elem1) {
+			names.push_back(json_array_get_string_element(array, elem1));
+		}
+
+		array = json_object_get_array_member(pObject, "index");
 		unsigned int elements2 = json_array_get_length(array);
 		LOGI("range dim: size[%u]", elements2);
 		for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
-- 
2.7.4


From 38af500c31778fcacbff4890289931a2b2b4d2c9 Mon Sep 17 00:00:00 2001
From: Kwanghoon Son <k.son@samsung.com>
Date: Sun, 28 Aug 2022 22:43:48 -0400
Subject: [PATCH 06/16] Split BoxInfo implementation and add missing header

Change-Id: Idcf2a0d06986cb8b7b23ec94af582a6fa4f37991
Signed-off-by: Kwanghoon Son <k.son@samsung.com>
---
 mv_machine_learning/inference/include/BoxInfo.h    | 346 +++++++--------------
 mv_machine_learning/inference/include/DecodeInfo.h |   1 +
 mv_machine_learning/inference/include/DimInfo.h    |   1 +
 mv_machine_learning/inference/include/Utils.h      |   1 +
 mv_machine_learning/inference/src/BoxInfo.cpp      | 207 ++++++++++++
 5 files changed, 315 insertions(+), 241 deletions(-)
 create mode 100644 mv_machine_learning/inference/src/BoxInfo.cpp

diff --git a/mv_machine_learning/inference/include/BoxInfo.h b/mv_machine_learning/inference/include/BoxInfo.h
index d384ecd..783342a 100644
--- a/mv_machine_learning/inference/include/BoxInfo.h
+++ b/mv_machine_learning/inference/include/BoxInfo.h
@@ -1,5 +1,5 @@
 /**
- * Copyright (c) 2021 Samsung Electronics Co., Ltd All Rights Reserved
+ * Copyright (c) 2021 - 2022 Samsung Electronics Co., Ltd All Rights Reserved
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -36,253 +36,117 @@ namespace inference
 {
 namespace box
 {
-	struct Label
-	{
-		std::string name;
-		DimInfo dimInfo;
-	};
-
-	struct Number
-	{
-		std::string name;
-		DimInfo dimInfo;
-	};
-
-	class BoxInfo
-	{
-	private:
-		std::string name;
-		DimInfo dimInfo;
-		inference_box_type_e type; // 0:L-T-R-B, 1: Cx-Cy-W-H
-		std::vector<int> order; // Order based on box type
-		inference_box_coordinate_type_e coordinate; // 0: ratio, 1: pixel
-		inference_box_decoding_type_e decodingType; // 0: bypass , 1:ssd with anchor
-		DecodeInfo decodingInfo;
-		Label label;
-		Number number;
-
-		std::map<std::string, inference_box_type_e> supportedBoxTypes;
-		std::map<std::string, inference_box_coordinate_type_e> supportedBoxCoordinateTypes;
-		std::map<std::string, inference_box_decoding_type_e> supportedBoxDecodingTypes;
-
-	public:
-		BoxInfo() :
-				name(),
-				dimInfo(),
-				type(INFERENCE_BOX_TYPE_ORIGIN_LEFTTOP),
-				order(),
-				coordinate(INFERENCE_BOX_COORDINATE_TYPE_RATIO),
-				decodingType(INFERENCE_BOX_DECODING_TYPE_BYPASS),
-				decodingInfo()
-
-		{
-			supportedBoxTypes.insert({"ORIGIN_LEFTTOP", INFERENCE_BOX_TYPE_ORIGIN_LEFTTOP});
-			supportedBoxTypes.insert({"ORIGIN_CENTER", INFERENCE_BOX_TYPE_ORIGIN_CENTER});
-
-			supportedBoxCoordinateTypes.insert({"RATIO", INFERENCE_BOX_COORDINATE_TYPE_RATIO});
-			supportedBoxCoordinateTypes.insert({"PIXEL", INFERENCE_BOX_COORDINATE_TYPE_PIXEL});
-
-			supportedBoxDecodingTypes.insert({"BYPASS", INFERENCE_BOX_DECODING_TYPE_BYPASS});
-			supportedBoxDecodingTypes.insert({"SSD_ANCHOR", INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR});
-			supportedBoxDecodingTypes.insert({"YOLO_ANCHOR", INFERENCE_BOX_DECODING_TYPE_YOLO_ANCHOR});
-		}
-
-		~BoxInfo() = default;
-
-		std::string GetName() { return name; }
-		DimInfo GetDimInfo() { return dimInfo; }
-		inference_box_type_e GetType() { return type; }
-		inference_box_decoding_type_e GetDecodingType() { return decodingType; }
-		std::vector<int> GetOrder() { return order; }
-		int GetCoordinate() { return coordinate; }
-		DecodeInfo& GetDecodeInfo() {return decodingInfo; }
-		std::string GetLabelName() { return label.name; }
-		std::string GetNumberName() { return number.name; }
-		DimInfo GetNumberDimInfo() { return number.dimInfo; }
-
-		int ParseBox(JsonObject *root)
-		{
-			LOGI("ENTER");
-
-			JsonArray * rootArray = json_object_get_array_member(root, "box");
-			unsigned int elements = json_array_get_length(rootArray);
-
-			for (unsigned int elem_idx = 0; elem_idx < elements; ++elem_idx) {
-				JsonNode *pNode = json_array_get_element(rootArray, elem_idx);
-				JsonObject *pObject = json_node_get_object(pNode);
-
-				name = json_object_get_string_member(pObject,"name");
-				LOGI("layer: %s", name.c_str());
-
-				JsonArray * array = json_object_get_array_member(pObject, "index");
-				unsigned int elements2 = json_array_get_length(array);
-
-				LOGI("range dim: size[%u]", elements2);
-
-				for (unsigned int elem2_idx = 0; elem2_idx < elements2; ++elem2_idx)
-					if (static_cast<int>(json_array_get_int_element(array, elem2_idx)) == 1)
-						dimInfo.SetValidIndex(elem2_idx);
-
-				try {
-					type = GetSupportedType(pObject, "box_type", supportedBoxTypes);
-					coordinate = GetSupportedType(pObject, "box_coordinate", supportedBoxCoordinateTypes);
-					decodingType = GetSupportedType(pObject, "decoding_type", supportedBoxDecodingTypes);
-				} catch (const std::exception& e) {
-					LOGE("Invalid %s", e.what());
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-
-				array = json_object_get_array_member(pObject, "box_order");
-				elements2 = json_array_get_length(array);
-				LOGI("box order should have 4 elements and it has [%u]", elements2);
-
-				for (unsigned int elem2_idx = 0; elem2_idx < elements2; ++elem2_idx) {
-					auto val = static_cast<int>(json_array_get_int_element(array, elem2_idx));
-					order.push_back(val);
-					LOGI("%d", val);
-				}
-			}
-
-			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
-		}
-
-		int ParseLabel(JsonObject *root)
-		{
-			LOGI("ENTER");
-
-			if (!json_object_has_member(root, "label")) {
-				LOGE("No box outputmetadata");
-				LOGI("LEAVE");
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
-
-			JsonArray * rootArray = json_object_get_array_member(root, "label");
-			unsigned int elements = json_array_get_length(rootArray);
-
-			// TODO: handling error
-			for (unsigned int elem = 0; elem < elements; ++elem) {
-				JsonNode *pNode = json_array_get_element(rootArray, elem);
-				JsonObject *pObject = json_node_get_object(pNode);
-
-				label.name = json_object_get_string_member(pObject,"name");
-				LOGI("layer: %s", label.name.c_str());
-
-				JsonArray * array = json_object_get_array_member(pObject, "index");
-				unsigned int elements2 = json_array_get_length(array);
-				LOGI("range dim: size[%u]", elements2);
-				for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
-					if (static_cast<int>(json_array_get_int_element(array, elem2)) == 1)
-						label.dimInfo.SetValidIndex(elem2);
-				}
-			}
-
-			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
-		}
-
-		int ParseNumber(JsonObject *root)
-		{
-			LOGI("ENTER");
-
-			if (!json_object_has_member(root, "number")) {
-				LOGE("No number outputmetadata");
-				LOGI("LEAVE");
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
-
-			// box
-			JsonArray * rootArray = json_object_get_array_member(root, "number");
-			unsigned int elements = json_array_get_length(rootArray);
-
-			// TODO: handling error
-			for (unsigned int elem = 0; elem < elements; ++elem) {
-				JsonNode *pNode = json_array_get_element(rootArray, elem);
-				JsonObject *pObject = json_node_get_object(pNode);
-
-				number.name = json_object_get_string_member(pObject,"name");
-
-				LOGI("layer: %s", number.name.c_str());
-
-				JsonArray * array = json_object_get_array_member(pObject, "index");
-				unsigned int elements2 = json_array_get_length(array);
-
-				LOGI("range dim: size[%u]", elements2);
-
-				for (unsigned int elem2 = 0; elem2 < elements2; ++elem2)
-					if (static_cast<int>(json_array_get_int_element(array, elem2)) == 1)
-						number.dimInfo.SetValidIndex(elem2);
-			}
-
-			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
-		}
-
-		int ParseDecodeInfo(JsonObject *root)
-		{
-			LOGI("ENTER");
-
-			// box
-			JsonArray * rootArray = json_object_get_array_member(root, "box");
-			unsigned int elements = json_array_get_length(rootArray);
-
-			// TODO: handling error
-			for (unsigned int elem = 0; elem < elements; ++elem) {
-				JsonNode *pNode = json_array_get_element(rootArray, elem);
-				JsonObject *pObject = json_node_get_object(pNode);
-
-				if (!json_object_has_member(pObject, "decoding_info")) {
-					LOGE("decoding_info is mandatory. Invalid metadata");
-					LOGI("LEAVE");
-
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
+struct Label
+{
+	std::string name;
+	DimInfo dimInfo;
+};
 
-				int ret = MEDIA_VISION_ERROR_NONE;
-				JsonObject *cObject = json_object_get_object_member(pObject, "decoding_info");
-				if (json_object_has_member(cObject, "anchor")) {
-					ret = GetDecodeInfo().ParseAnchorParam(cObject);
-					if (ret != MEDIA_VISION_ERROR_NONE) {
-						LOGE("Fail to ParseAnchorParam[%d]", ret);
-						return ret;
-					}
-				} else if (json_object_has_member(cObject, "cell")) {
-					ret = GetDecodeInfo().ParseCellParam(cObject);
-					if (ret != MEDIA_VISION_ERROR_NONE) {
-						LOGE("Fail to ParseCellParam[%d]", ret);
-						return ret;
-					}
-				} else {
+struct Number
+{
+	std::string name;
+	DimInfo dimInfo;
+};
 
-					LOGE("anchor is mandatory. Invalid metadata");
-					LOGI("LEAVE");
+class BoxInfo
+{
+private:
+	std::string name;
+	DimInfo dimInfo;
+	inference_box_type_e type; // 0:L-T-R-B, 1: Cx-Cy-W-H
+	std::vector<int> order; // Order based on box type
+	inference_box_coordinate_type_e coordinate; // 0: ratio, 1: pixel
+	inference_box_decoding_type_e decodingType; // 0: bypass , 1:ssd with anchor
+	DecodeInfo decodingInfo;
+	Label label;
+	Number number;
+
+	std::map<std::string, inference_box_type_e> supportedBoxTypes;
+	std::map<std::string, inference_box_coordinate_type_e>
+			supportedBoxCoordinateTypes;
+	std::map<std::string, inference_box_decoding_type_e>
+			supportedBoxDecodingTypes;
+
+public:
+	BoxInfo()
+			: name()
+			, dimInfo()
+			, type(INFERENCE_BOX_TYPE_ORIGIN_LEFTTOP)
+			, order()
+			, coordinate(INFERENCE_BOX_COORDINATE_TYPE_RATIO)
+			, decodingType(INFERENCE_BOX_DECODING_TYPE_BYPASS)
+			, decodingInfo()
 
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
+	{
+		supportedBoxTypes.insert(
+				{ "ORIGIN_LEFTTOP", INFERENCE_BOX_TYPE_ORIGIN_LEFTTOP });
+		supportedBoxTypes.insert(
+				{ "ORIGIN_CENTER", INFERENCE_BOX_TYPE_ORIGIN_CENTER });
+
+		supportedBoxCoordinateTypes.insert(
+				{ "RATIO", INFERENCE_BOX_COORDINATE_TYPE_RATIO });
+		supportedBoxCoordinateTypes.insert(
+				{ "PIXEL", INFERENCE_BOX_COORDINATE_TYPE_PIXEL });
+
+		supportedBoxDecodingTypes.insert(
+				{ "BYPASS", INFERENCE_BOX_DECODING_TYPE_BYPASS });
+		supportedBoxDecodingTypes.insert(
+				{ "SSD_ANCHOR", INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR });
+		supportedBoxDecodingTypes.insert(
+				{ "YOLO_ANCHOR", INFERENCE_BOX_DECODING_TYPE_YOLO_ANCHOR });
+	}
+
+	~BoxInfo() = default;
+
+	std::string GetName()
+	{
+		return name;
+	}
+	DimInfo GetDimInfo()
+	{
+		return dimInfo;
+	}
+	inference_box_type_e GetType()
+	{
+		return type;
+	}
+	inference_box_decoding_type_e GetDecodingType()
+	{
+		return decodingType;
+	}
+	std::vector<int> GetOrder()
+	{
+		return order;
+	}
+	int GetCoordinate()
+	{
+		return coordinate;
+	}
+	DecodeInfo &GetDecodeInfo()
+	{
+		return decodingInfo;
+	}
+	std::string GetLabelName()
+	{
+		return label.name;
+	}
+	std::string GetNumberName()
+	{
+		return number.name;
+	}
+	DimInfo GetNumberDimInfo()
+	{
+		return number.dimInfo;
+	}
 
-				ret = GetDecodeInfo().ParseNms(cObject);
-				if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to ParseNms[%d]", ret);
-					return ret;
-				}
+	int ParseBox(JsonObject *root);
 
-				ret = GetDecodeInfo().ParseRotate(cObject);
-				if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to ParseRotate[%d]", ret);
-					return ret;
-				}
+	int ParseLabel(JsonObject *root);
 
-				ret = GetDecodeInfo().ParseRoiOption(cObject);
-				if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to ParseRoiOption[%d]", ret);
-					return ret;
-				}
-			}
+	int ParseNumber(JsonObject *root);
 
-			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
-		}
-	};
+	int ParseDecodeInfo(JsonObject *root);
+};
 } /* box */
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/include/DecodeInfo.h b/mv_machine_learning/inference/include/DecodeInfo.h
index d28444a..dba3647 100644
--- a/mv_machine_learning/inference/include/DecodeInfo.h
+++ b/mv_machine_learning/inference/include/DecodeInfo.h
@@ -22,6 +22,7 @@
 #include <map>
 #include <memory>
 
+#include <OutputMetadataTypes.h>
 #include <mv_inference_type.h>
 #include <opencv2/core.hpp>
 #include "Utils.h"
diff --git a/mv_machine_learning/inference/include/DimInfo.h b/mv_machine_learning/inference/include/DimInfo.h
index d061122..64e0f05 100644
--- a/mv_machine_learning/inference/include/DimInfo.h
+++ b/mv_machine_learning/inference/include/DimInfo.h
@@ -18,6 +18,7 @@
 #define __DIM_INFO_H__
 
 #include <vector>
+#include <dlog.h>
 
 namespace mediavision
 {
diff --git a/mv_machine_learning/inference/include/Utils.h b/mv_machine_learning/inference/include/Utils.h
index c8a37cd..d5db2b5 100644
--- a/mv_machine_learning/inference/include/Utils.h
+++ b/mv_machine_learning/inference/include/Utils.h
@@ -23,6 +23,7 @@
 #include <memory>
 
 #include <json-glib/json-glib.h>
+#include <dlog.h>
 
 namespace mediavision
 {
diff --git a/mv_machine_learning/inference/src/BoxInfo.cpp b/mv_machine_learning/inference/src/BoxInfo.cpp
new file mode 100644
index 0000000..1585691
--- /dev/null
+++ b/mv_machine_learning/inference/src/BoxInfo.cpp
@@ -0,0 +1,207 @@
+
+/**
+ * Copyright (c) 2022 Samsung Electronics Co., Ltd All Rights Reserved
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <BoxInfo.h>
+
+using namespace mediavision::inference::box;
+
+int BoxInfo::ParseBox(JsonObject *root)
+{
+	LOGI("ENTER");
+
+	JsonArray *rootArray = json_object_get_array_member(root, "box");
+	unsigned int elements = json_array_get_length(rootArray);
+
+	for (unsigned int elem_idx = 0; elem_idx < elements; ++elem_idx) {
+		JsonNode *pNode = json_array_get_element(rootArray, elem_idx);
+		JsonObject *pObject = json_node_get_object(pNode);
+
+		name = json_object_get_string_member(pObject, "name");
+		LOGI("layer: %s", name.c_str());
+
+		JsonArray *array = json_object_get_array_member(pObject, "index");
+		unsigned int elements2 = json_array_get_length(array);
+
+		LOGI("range dim: size[%u]", elements2);
+
+		for (unsigned int elem2_idx = 0; elem2_idx < elements2; ++elem2_idx)
+			if (static_cast<int>(
+						json_array_get_int_element(array, elem2_idx)) == 1)
+				dimInfo.SetValidIndex(elem2_idx);
+
+		try {
+			type = GetSupportedType(pObject, "box_type", supportedBoxTypes);
+			coordinate = GetSupportedType(pObject, "box_coordinate",
+										  supportedBoxCoordinateTypes);
+			decodingType = GetSupportedType(pObject, "decoding_type",
+											supportedBoxDecodingTypes);
+		} catch (const std::exception &e) {
+			LOGE("Invalid %s", e.what());
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
+		}
+
+		array = json_object_get_array_member(pObject, "box_order");
+		elements2 = json_array_get_length(array);
+		LOGI("box order should have 4 elements and it has [%u]", elements2);
+
+		for (unsigned int elem2_idx = 0; elem2_idx < elements2; ++elem2_idx) {
+			auto val = static_cast<int>(
+					json_array_get_int_element(array, elem2_idx));
+			order.push_back(val);
+			LOGI("%d", val);
+		}
+	}
+
+	LOGI("LEAVE");
+	return MEDIA_VISION_ERROR_NONE;
+}
+
+int BoxInfo::ParseLabel(JsonObject *root)
+{
+	LOGI("ENTER");
+
+	if (!json_object_has_member(root, "label")) {
+		LOGE("No box outputmetadata");
+		LOGI("LEAVE");
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
+	}
+
+	JsonArray *rootArray = json_object_get_array_member(root, "label");
+	unsigned int elements = json_array_get_length(rootArray);
+
+	// TODO: handling error
+	for (unsigned int elem = 0; elem < elements; ++elem) {
+		JsonNode *pNode = json_array_get_element(rootArray, elem);
+		JsonObject *pObject = json_node_get_object(pNode);
+
+		label.name = json_object_get_string_member(pObject, "name");
+		LOGI("layer: %s", label.name.c_str());
+
+		JsonArray *array = json_object_get_array_member(pObject, "index");
+		unsigned int elements2 = json_array_get_length(array);
+		LOGI("range dim: size[%u]", elements2);
+		for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
+			if (static_cast<int>(json_array_get_int_element(array, elem2)) == 1)
+				label.dimInfo.SetValidIndex(elem2);
+		}
+	}
+
+	LOGI("LEAVE");
+	return MEDIA_VISION_ERROR_NONE;
+}
+
+int BoxInfo::ParseNumber(JsonObject *root)
+{
+	LOGI("ENTER");
+
+	if (!json_object_has_member(root, "number")) {
+		LOGE("No number outputmetadata");
+		LOGI("LEAVE");
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
+	}
+
+	// box
+	JsonArray *rootArray = json_object_get_array_member(root, "number");
+	unsigned int elements = json_array_get_length(rootArray);
+
+	// TODO: handling error
+	for (unsigned int elem = 0; elem < elements; ++elem) {
+		JsonNode *pNode = json_array_get_element(rootArray, elem);
+		JsonObject *pObject = json_node_get_object(pNode);
+
+		number.name = json_object_get_string_member(pObject, "name");
+
+		LOGI("layer: %s", number.name.c_str());
+
+		JsonArray *array = json_object_get_array_member(pObject, "index");
+		unsigned int elements2 = json_array_get_length(array);
+
+		LOGI("range dim: size[%u]", elements2);
+
+		for (unsigned int elem2 = 0; elem2 < elements2; ++elem2)
+			if (static_cast<int>(json_array_get_int_element(array, elem2)) == 1)
+				number.dimInfo.SetValidIndex(elem2);
+	}
+
+	LOGI("LEAVE");
+	return MEDIA_VISION_ERROR_NONE;
+}
+
+int BoxInfo::ParseDecodeInfo(JsonObject *root)
+{
+	LOGI("ENTER");
+
+	// box
+	JsonArray *rootArray = json_object_get_array_member(root, "box");
+	unsigned int elements = json_array_get_length(rootArray);
+
+	// TODO: handling error
+	for (unsigned int elem = 0; elem < elements; ++elem) {
+		JsonNode *pNode = json_array_get_element(rootArray, elem);
+		JsonObject *pObject = json_node_get_object(pNode);
+
+		if (!json_object_has_member(pObject, "decoding_info")) {
+			LOGE("decoding_info is mandatory. Invalid metadata");
+			LOGI("LEAVE");
+
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
+		}
+
+		int ret = MEDIA_VISION_ERROR_NONE;
+		JsonObject *cObject =
+				json_object_get_object_member(pObject, "decoding_info");
+		if (json_object_has_member(cObject, "anchor")) {
+			ret = GetDecodeInfo().ParseAnchorParam(cObject);
+			if (ret != MEDIA_VISION_ERROR_NONE) {
+				LOGE("Fail to ParseAnchorParam[%d]", ret);
+				return ret;
+			}
+		} else if (json_object_has_member(cObject, "cell")) {
+			ret = GetDecodeInfo().ParseCellParam(cObject);
+			if (ret != MEDIA_VISION_ERROR_NONE) {
+				LOGE("Fail to ParseCellParam[%d]", ret);
+				return ret;
+			}
+		} else {
+			LOGE("anchor is mandatory. Invalid metadata");
+			LOGI("LEAVE");
+
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
+		}
+
+		ret = GetDecodeInfo().ParseNms(cObject);
+		if (ret != MEDIA_VISION_ERROR_NONE) {
+			LOGE("Fail to ParseNms[%d]", ret);
+			return ret;
+		}
+
+		ret = GetDecodeInfo().ParseRotate(cObject);
+		if (ret != MEDIA_VISION_ERROR_NONE) {
+			LOGE("Fail to ParseRotate[%d]", ret);
+			return ret;
+		}
+
+		ret = GetDecodeInfo().ParseRoiOption(cObject);
+		if (ret != MEDIA_VISION_ERROR_NONE) {
+			LOGE("Fail to ParseRoiOption[%d]", ret);
+			return ret;
+		}
+	}
+
+	LOGI("LEAVE");
+	return MEDIA_VISION_ERROR_NONE;
+}
\ No newline at end of file
-- 
2.7.4


From 8a0bcb13b9aa25b0205080cefaac53aba7833aca Mon Sep 17 00:00:00 2001
From: Inki Dae <inki.dae@samsung.com>
Date: Fri, 19 Aug 2022 19:51:00 +0900
Subject: [PATCH 07/16] mv_machine_learning: code refactoring to Inference
 class

[Issue type] : code refactoring

Did code refactoring to Run member function of Inference class by doing,
	- extracted a function which converts mv sources to cv ones. And
	  this converting function is now considered for multiple sources.
	- introduced a new util file which can contain common things
	  to be used by machine learning relevant code.
	- and did code sliding and renaming several variables.

This is just a step for next code refactoring and there are many things to do.

Change-Id: Ic78ef26156481def5ecda537657638c613a304d1
Signed-off-by: Inki Dae <inki.dae@samsung.com>
---
 mv_common/include/util.h                        | 85 +++++++++++++++++++++++
 mv_machine_learning/inference/src/Inference.cpp | 92 ++++++++-----------------
 2 files changed, 114 insertions(+), 63 deletions(-)
 create mode 100644 mv_common/include/util.h

diff --git a/mv_common/include/util.h b/mv_common/include/util.h
new file mode 100644
index 0000000..5cb6b8e
--- /dev/null
+++ b/mv_common/include/util.h
@@ -0,0 +1,85 @@
+/**
+ * Copyright (c) 2022 Samsung Electronics Co., Ltd All Rights Reserved
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef __UTIL_H__
+#define __UTIL_H__
+
+#include <vector>
+
+#include <opencv2/core.hpp>
+#include <opencv2/imgproc.hpp>
+
+namespace mediavision
+{
+namespace common
+{
+namespace util
+{
+
+	static int ConvertToCvSource(std::vector<mv_source_h> &mv_srcs, std::vector<cv::Mat>& cv_srcs, std::vector<mv_rectangle_s>& rects)
+	{
+		unsigned int rect_idx = 0;
+
+		for (auto& mv_src : mv_srcs) {
+			mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
+			mv_rectangle_s *roi = &rects[rect_idx++];
+			unsigned int width = 0, height = 0;
+			unsigned int bufferSize = 0;
+			unsigned char *buffer = NULL;
+
+			if (mv_source_get_width(mv_src, &width) != MEDIA_VISION_ERROR_NONE ||
+				mv_source_get_height(mv_src, &height) !=
+						MEDIA_VISION_ERROR_NONE ||
+				mv_source_get_colorspace(mv_src, &colorspace) !=
+						MEDIA_VISION_ERROR_NONE ||
+				mv_source_get_buffer(mv_src, &buffer, &bufferSize))
+				return MEDIA_VISION_ERROR_INTERNAL;
+
+			// TODO. Let's support various color spaces.
+
+			if (colorspace != MEDIA_VISION_COLORSPACE_RGB888) {
+				LOGE("Not Supported format.");
+				return MEDIA_VISION_ERROR_NOT_SUPPORTED_FORMAT;
+			}
+
+			/* convert mv_source to cv::Mat */
+			cv::Mat cvSource;
+
+			if (roi == NULL) {
+				cvSource = cv::Mat(cv::Size(width, height), CV_MAKETYPE(CV_8U, 3), buffer).clone();
+			} else {
+				cv::Rect cvRoi;
+
+				cvRoi.x = roi->point.x;
+				cvRoi.y = roi->point.y;
+				cvRoi.width = unsigned(roi->point.x + roi->width) >= width ? width - roi->point.x : roi->width;
+				cvRoi.height = unsigned(roi->point.y + roi->height) >= height ? height - roi->point.y : roi->height;
+				cvSource = cv::Mat(cv::Size(width, height), CV_MAKETYPE(CV_8U, 3), buffer)(cvRoi).clone();
+			}
+
+			cv_srcs.push_back(cvSource);
+			LOGI("Size: w:%u, h:%u", cvSource.size().width, cvSource.size().height);
+		}
+
+		return MEDIA_VISION_ERROR_NONE;
+	}
+
+
+} // util
+} // common
+} // mediavision
+
+#endif
\ No newline at end of file
diff --git a/mv_machine_learning/inference/src/Inference.cpp b/mv_machine_learning/inference/src/Inference.cpp
index b655f22..0e3123e 100755
--- a/mv_machine_learning/inference/src/Inference.cpp
+++ b/mv_machine_learning/inference/src/Inference.cpp
@@ -19,6 +19,7 @@
 #include "InferenceIni.h"
 #include "ObjectDecoder.h"
 #include "PoseDecoder.h"
+#include "util.h"
 #include <map>
 #include <list>
 
@@ -43,6 +44,8 @@ typedef enum {
 	InputAttrBool = 6,
 } InputAttrType;
 
+using namespace mediavision::common::util;
+
 namespace mediavision
 {
 namespace inference
@@ -278,7 +281,6 @@ namespace inference
 
 	int Inference::Preprocess(cv::Mat cvImg, cv::Mat cvDst, int data_type)
 	{
-		mSourceSize = cvImg.size();
 		int width = mInputSize.width;
 		int height = mInputSize.height;
 		const int ch = mConfig.mTensorInfo.ch;
@@ -931,87 +933,51 @@ namespace inference
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 		}
 
-		// TODO. Consider multiple sources.
-		mv_source_h mvSource = mvSources.front();
-		mv_rectangle_s *roi = rects.empty() ? NULL : &(rects.front());
-		mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
-		unsigned int width = 0, height = 0;
-		unsigned int bufferSize = 0;
-		unsigned char *buffer = NULL;
-
-		if (mv_source_get_width(mvSource, &width) != MEDIA_VISION_ERROR_NONE ||
-			mv_source_get_height(mvSource, &height) !=
-					MEDIA_VISION_ERROR_NONE ||
-			mv_source_get_colorspace(mvSource, &colorspace) !=
-					MEDIA_VISION_ERROR_NONE ||
-			mv_source_get_buffer(mvSource, &buffer, &bufferSize))
-			return MEDIA_VISION_ERROR_INTERNAL;
-
-		// TODO. Let's support various color spaces.
+		if (!rects.empty() && rects.size() != mvSources.size()) {
+			LOGE("mvSources.size() should be same as rects.size() if rects.empty() is false.");
+			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+		}
 
-		if (colorspace != MEDIA_VISION_COLORSPACE_RGB888) {
-			LOGE("Not Supported format!\n");
-			return MEDIA_VISION_ERROR_NOT_SUPPORTED_FORMAT;
+		if (mConfig.mTensorInfo.ch != 1 && mConfig.mTensorInfo.ch != 3) {
+			LOGE("Channel not supported.");
+			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 		}
 
-		/* convert mv_source to cv::Mat */
-		cv::Mat cvSource;
-		cv::Rect cvRoi;
+		std::vector<cv::Mat> cvSources;
 
-		if (roi == NULL) {
-			cvSource = cv::Mat(cv::Size(width, height), CV_MAKETYPE(CV_8U, 3),
-							   buffer)
-							   .clone();
-		} else {
-			cvRoi.x = roi->point.x;
-			cvRoi.y = roi->point.y;
-			cvRoi.width = unsigned(roi->point.x + roi->width) >= width ?
-								  width - roi->point.x :
-								  roi->width;
-			cvRoi.height = unsigned(roi->point.y + roi->height) >= height ?
-								   height - roi->point.y :
-								   roi->height;
-			cvSource = cv::Mat(cv::Size(width, height), CV_MAKETYPE(CV_8U, 3),
-							   buffer)(cvRoi)
-							   .clone();
+		ret = ConvertToCvSource(mvSources, cvSources, rects);
+		if (ret != MEDIA_VISION_ERROR_NONE) {
+			LOGE("Fail to convert mv source to cv source.");
+			return ret;
 		}
 
-		LOGI("Size: w:%u, h:%u", cvSource.size().width, cvSource.size().height);
+		// mSourceSize is original input image's size
+		// TODO. consider multiple cv sources.
+		mSourceSize = cvSources[0].size();
 
-		if (mConfig.mTensorInfo.ch != 1 && mConfig.mTensorInfo.ch != 3) {
-			LOGE("Channel not supported.");
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-		}
+		unsigned int src_idx = 0;
 
-		if (mMetadata.GetInputMeta().IsParsed()) {
-			for (auto& buffer : mInputTensorBuffers.getIETensorBuffer()) {
-				inference_engine_tensor_buffer& tensor_buffer = buffer.second;
+		for (auto& buffer : mInputTensorBuffers.getIETensorBuffer()) {
+			inference_engine_tensor_buffer& tensor_buffer = buffer.second;
+			int data_type = ConvertToCv(tensor_buffer.data_type);
+
+			if (mMetadata.GetInputMeta().IsParsed()) {
 				const LayerInfo& layerInfo = mMetadata.GetInputMeta().GetLayer().at(buffer.first);
 				const Options& opt = mMetadata.GetInputMeta().GetOption().empty() ? Options() : mMetadata.GetInputMeta().GetOption().at(buffer.first);
+				mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
 
-				int data_type = ConvertToCv(tensor_buffer.data_type);
+				mv_source_get_colorspace(mvSources[src_idx], &colorspace);
 
-				// mSourceSize is original input image's size
-				mSourceSize = cvSource.size();
 				// TODO: try-catch{} error handling
-				ret = mPreProc.Run(cvSource, colorspace, data_type, layerInfo, opt, tensor_buffer.buffer);
+				ret = mPreProc.Run(cvSources[src_idx++], colorspace, data_type, layerInfo, opt, tensor_buffer.buffer);
 				if (ret != MEDIA_VISION_ERROR_NONE) {
 					LOGE("Fail to run pre-process.");
 					return ret;
 				}
-			}
-		} else {
-			for (auto& buffer : mInputTensorBuffers.getIETensorBuffer()) {
-				inference_engine_tensor_buffer& tensor_buffer = buffer.second;
-
-				int data_type = ConvertToCv(tensor_buffer.data_type);
-
+			} else {
 				// Convert color space of input tensor data and then normalize it.
 
-				ret = Preprocess(cvSource,
-								cv::Mat(mInputSize.height, mInputSize.width,
-										data_type, tensor_buffer.buffer),
-								data_type);
+				ret = Preprocess(cvSources[src_idx++], cv::Mat(mInputSize.height, mInputSize.width, data_type, tensor_buffer.buffer), data_type);
 				if (ret != MEDIA_VISION_ERROR_NONE) {
 					LOGE("Fail to preprocess input tensor data.");
 					return ret;
-- 
2.7.4


From 72bf17c96c7c0e0b18596dc9ecc76d80b6da5012 Mon Sep 17 00:00:00 2001
From: Kwanghoon Son <k.son@samsung.com>
Date: Mon, 29 Aug 2022 02:00:14 -0400
Subject: [PATCH 08/16] Fix box array to object in meta json

outputmetadata box object has array, but usage only accept 1 array
element. This change handle object instead array.
`before`
"box" : [
    {
        "name" : "some name",
        ...
    }
],
`after`
"box" :
    {
        "name" : "some name",
        ...
    }

Change-Id: If77d781a5f4bbf6beb7078e34edd5309f29a471e
Signed-off-by: Kwanghoon Son <k.son@samsung.com>
---
 mv_machine_learning/inference/src/BoxInfo.cpp | 151 +++++++++++++-------------
 1 file changed, 73 insertions(+), 78 deletions(-)

diff --git a/mv_machine_learning/inference/src/BoxInfo.cpp b/mv_machine_learning/inference/src/BoxInfo.cpp
index 1585691..2c44757 100644
--- a/mv_machine_learning/inference/src/BoxInfo.cpp
+++ b/mv_machine_learning/inference/src/BoxInfo.cpp
@@ -23,47 +23,45 @@ int BoxInfo::ParseBox(JsonObject *root)
 {
 	LOGI("ENTER");
 
-	JsonArray *rootArray = json_object_get_array_member(root, "box");
-	unsigned int elements = json_array_get_length(rootArray);
+	if (!json_object_has_member(root, "box")) {
+		LOGE("member box not exists");
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+	}
 
-	for (unsigned int elem_idx = 0; elem_idx < elements; ++elem_idx) {
-		JsonNode *pNode = json_array_get_element(rootArray, elem_idx);
-		JsonObject *pObject = json_node_get_object(pNode);
+	JsonObject *pObject = json_object_get_object_member(root, "box");
 
-		name = json_object_get_string_member(pObject, "name");
-		LOGI("layer: %s", name.c_str());
+	name = json_object_get_string_member(pObject, "name");
+	LOGI("layer: %s", name.c_str());
 
-		JsonArray *array = json_object_get_array_member(pObject, "index");
-		unsigned int elements2 = json_array_get_length(array);
+	JsonArray *array = json_object_get_array_member(pObject, "index");
+	unsigned int elements2 = json_array_get_length(array);
 
-		LOGI("range dim: size[%u]", elements2);
+	LOGI("range dim: size[%u]", elements2);
 
-		for (unsigned int elem2_idx = 0; elem2_idx < elements2; ++elem2_idx)
-			if (static_cast<int>(
-						json_array_get_int_element(array, elem2_idx)) == 1)
-				dimInfo.SetValidIndex(elem2_idx);
-
-		try {
-			type = GetSupportedType(pObject, "box_type", supportedBoxTypes);
-			coordinate = GetSupportedType(pObject, "box_coordinate",
-										  supportedBoxCoordinateTypes);
-			decodingType = GetSupportedType(pObject, "decoding_type",
-											supportedBoxDecodingTypes);
-		} catch (const std::exception &e) {
-			LOGE("Invalid %s", e.what());
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
+	for (unsigned int elem2_idx = 0; elem2_idx < elements2; ++elem2_idx)
+		if (static_cast<int>(json_array_get_int_element(array, elem2_idx)) == 1)
+			dimInfo.SetValidIndex(elem2_idx);
+
+	try {
+		type = GetSupportedType(pObject, "box_type", supportedBoxTypes);
+		coordinate = GetSupportedType(pObject, "box_coordinate",
+									  supportedBoxCoordinateTypes);
+		decodingType = GetSupportedType(pObject, "decoding_type",
+										supportedBoxDecodingTypes);
+	} catch (const std::exception &e) {
+		LOGE("Invalid %s", e.what());
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
+	}
 
-		array = json_object_get_array_member(pObject, "box_order");
-		elements2 = json_array_get_length(array);
-		LOGI("box order should have 4 elements and it has [%u]", elements2);
+	array = json_object_get_array_member(pObject, "box_order");
+	elements2 = json_array_get_length(array);
+	LOGI("box order should have 4 elements and it has [%u]", elements2);
 
-		for (unsigned int elem2_idx = 0; elem2_idx < elements2; ++elem2_idx) {
-			auto val = static_cast<int>(
-					json_array_get_int_element(array, elem2_idx));
-			order.push_back(val);
-			LOGI("%d", val);
-		}
+	for (unsigned int elem2_idx = 0; elem2_idx < elements2; ++elem2_idx) {
+		auto val =
+				static_cast<int>(json_array_get_int_element(array, elem2_idx));
+		order.push_back(val);
+		LOGI("%d", val);
 	}
 
 	LOGI("LEAVE");
@@ -145,61 +143,58 @@ int BoxInfo::ParseDecodeInfo(JsonObject *root)
 {
 	LOGI("ENTER");
 
-	// box
-	JsonArray *rootArray = json_object_get_array_member(root, "box");
-	unsigned int elements = json_array_get_length(rootArray);
-
-	// TODO: handling error
-	for (unsigned int elem = 0; elem < elements; ++elem) {
-		JsonNode *pNode = json_array_get_element(rootArray, elem);
-		JsonObject *pObject = json_node_get_object(pNode);
+	if (!json_object_has_member(root, "box")) {
+		LOGE("member box not exists");
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+	}
 
-		if (!json_object_has_member(pObject, "decoding_info")) {
-			LOGE("decoding_info is mandatory. Invalid metadata");
-			LOGI("LEAVE");
+	JsonObject *pObject = json_object_get_object_member(root, "box");
 
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
+	if (!json_object_has_member(pObject, "decoding_info")) {
+		LOGE("decoding_info is mandatory. Invalid metadata");
+		LOGI("LEAVE");
 
-		int ret = MEDIA_VISION_ERROR_NONE;
-		JsonObject *cObject =
-				json_object_get_object_member(pObject, "decoding_info");
-		if (json_object_has_member(cObject, "anchor")) {
-			ret = GetDecodeInfo().ParseAnchorParam(cObject);
-			if (ret != MEDIA_VISION_ERROR_NONE) {
-				LOGE("Fail to ParseAnchorParam[%d]", ret);
-				return ret;
-			}
-		} else if (json_object_has_member(cObject, "cell")) {
-			ret = GetDecodeInfo().ParseCellParam(cObject);
-			if (ret != MEDIA_VISION_ERROR_NONE) {
-				LOGE("Fail to ParseCellParam[%d]", ret);
-				return ret;
-			}
-		} else {
-			LOGE("anchor is mandatory. Invalid metadata");
-			LOGI("LEAVE");
-
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
+	}
 
-		ret = GetDecodeInfo().ParseNms(cObject);
+	int ret = MEDIA_VISION_ERROR_NONE;
+	JsonObject *cObject =
+			json_object_get_object_member(pObject, "decoding_info");
+	if (json_object_has_member(cObject, "anchor")) {
+		ret = GetDecodeInfo().ParseAnchorParam(cObject);
 		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to ParseNms[%d]", ret);
+			LOGE("Fail to ParseAnchorParam[%d]", ret);
 			return ret;
 		}
-
-		ret = GetDecodeInfo().ParseRotate(cObject);
+	} else if (json_object_has_member(cObject, "cell")) {
+		ret = GetDecodeInfo().ParseCellParam(cObject);
 		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to ParseRotate[%d]", ret);
+			LOGE("Fail to ParseCellParam[%d]", ret);
 			return ret;
 		}
+	} else {
+		LOGE("anchor is mandatory. Invalid metadata");
+		LOGI("LEAVE");
 
-		ret = GetDecodeInfo().ParseRoiOption(cObject);
-		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to ParseRoiOption[%d]", ret);
-			return ret;
-		}
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
+	}
+
+	ret = GetDecodeInfo().ParseNms(cObject);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to ParseNms[%d]", ret);
+		return ret;
+	}
+
+	ret = GetDecodeInfo().ParseRotate(cObject);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to ParseRotate[%d]", ret);
+		return ret;
+	}
+
+	ret = GetDecodeInfo().ParseRoiOption(cObject);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to ParseRoiOption[%d]", ret);
+		return ret;
 	}
 
 	LOGI("LEAVE");
-- 
2.7.4


From b693ad22d1587459d8494eb092662c8ddca99599 Mon Sep 17 00:00:00 2001
From: Kwanghoon Son <k.son@samsung.com>
Date: Mon, 29 Aug 2022 02:44:00 -0400
Subject: [PATCH 09/16] Change box name to vector in meta json

outputmetadata box name was single string, but needs to change to
handle yolo models.(multiple names)
`before`
"box" :
    {
        "name" : "some name",
        ...
    }
`after`
"box" :
    {
        "name" : ["some name"],
        ...
    }

Change-Id: Ia76001c2670c0a1fae272c31ba56dfc0cbc591de
Signed-off-by: Kwanghoon Son <k.son@samsung.com>
---
 mv_machine_learning/inference/include/BoxInfo.h | 10 ++++------
 mv_machine_learning/inference/src/BoxInfo.cpp   | 25 ++++++++++++++++++++++---
 2 files changed, 26 insertions(+), 9 deletions(-)

diff --git a/mv_machine_learning/inference/include/BoxInfo.h b/mv_machine_learning/inference/include/BoxInfo.h
index 783342a..d4d6c6a 100644
--- a/mv_machine_learning/inference/include/BoxInfo.h
+++ b/mv_machine_learning/inference/include/BoxInfo.h
@@ -51,7 +51,7 @@ struct Number
 class BoxInfo
 {
 private:
-	std::string name;
+	std::vector<std::string> names;
 	DimInfo dimInfo;
 	inference_box_type_e type; // 0:L-T-R-B, 1: Cx-Cy-W-H
 	std::vector<int> order; // Order based on box type
@@ -69,7 +69,7 @@ private:
 
 public:
 	BoxInfo()
-			: name()
+			: names()
 			, dimInfo()
 			, type(INFERENCE_BOX_TYPE_ORIGIN_LEFTTOP)
 			, order()
@@ -98,10 +98,8 @@ public:
 
 	~BoxInfo() = default;
 
-	std::string GetName()
-	{
-		return name;
-	}
+	std::string GetName();
+
 	DimInfo GetDimInfo()
 	{
 		return dimInfo;
diff --git a/mv_machine_learning/inference/src/BoxInfo.cpp b/mv_machine_learning/inference/src/BoxInfo.cpp
index 2c44757..1e57a19 100644
--- a/mv_machine_learning/inference/src/BoxInfo.cpp
+++ b/mv_machine_learning/inference/src/BoxInfo.cpp
@@ -16,9 +16,19 @@
  */
 
 #include <BoxInfo.h>
+#include <mv_private.h>
 
 using namespace mediavision::inference::box;
 
+std::string BoxInfo::GetName()
+{
+	// OutputMetadata needs empty sting
+	if (names.empty())
+		return "";
+
+	return names[0];
+}
+
 int BoxInfo::ParseBox(JsonObject *root)
 {
 	LOGI("ENTER");
@@ -30,10 +40,19 @@ int BoxInfo::ParseBox(JsonObject *root)
 
 	JsonObject *pObject = json_object_get_object_member(root, "box");
 
-	name = json_object_get_string_member(pObject, "name");
-	LOGI("layer: %s", name.c_str());
+	JsonArray *array = json_object_get_array_member(pObject, "name");
+	MEDIA_VISION_NULL_ARG_CHECK(array);
+
+	unsigned int elements1 = json_array_get_length(array);
+	MEDIA_VISION_CHECK_CONDITION(elements1 > 0,
+								 MEDIA_VISION_ERROR_INVALID_PARAMETER,
+								 "No name on meta file");
+
+	for (unsigned int elem1 = 0; elem1 < elements1; ++elem1) {
+		names.push_back(json_array_get_string_element(array, elem1));
+	}
 
-	JsonArray *array = json_object_get_array_member(pObject, "index");
+	array = json_object_get_array_member(pObject, "index");
 	unsigned int elements2 = json_array_get_length(array);
 
 	LOGI("range dim: size[%u]", elements2);
-- 
2.7.4


From 5d9b738d4fae348fe23dec785dd937e1113f0e95 Mon Sep 17 00:00:00 2001
From: Inki Dae <inki.dae@samsung.com>
Date: Tue, 30 Aug 2022 13:54:46 +0900
Subject: [PATCH 10/16] mv_machine_learning: code cleanup to Options and
 LayerInfo classes

[Issue type] : code cleanup

Cleaned up Options and LayerInfo classes by doing,
		- Change Options and LayerInfo classes to structure type.
		  No reason for they are class type. It's enough with structure type.

Change-Id: Ie50877881b6acb211b9d7ae5a0800f1e7185d78a
Signed-off-by: Inki Dae <inki.dae@samsung.com>
---
 .../inference/include/InputMetadata.h              | 81 +++++++++++-----------
 mv_machine_learning/inference/src/Inference.cpp    | 22 +++---
 .../inference/src/InputMetadata.cpp                | 25 +------
 mv_machine_learning/inference/src/PreProcess.cpp   |  2 +-
 4 files changed, 56 insertions(+), 74 deletions(-)

diff --git a/mv_machine_learning/inference/include/InputMetadata.h b/mv_machine_learning/inference/include/InputMetadata.h
index c2bf94d..77a5c71 100644
--- a/mv_machine_learning/inference/include/InputMetadata.h
+++ b/mv_machine_learning/inference/include/InputMetadata.h
@@ -35,54 +35,55 @@ namespace mediavision
 {
 namespace inference
 {
-	class Options
-	{
-	public:
-		class Normalization
-		{
-		public:
-			bool use;
-			std::vector<double> mean;
-			std::vector<double> std;
-
-			Normalization() : use(false) {}
-			~Normalization() = default;
-		};
-
-		class Quantization
-		{
-		public:
-			bool use;
-			std::vector<double> scale;
-			std::vector<double> zeropoint;
-
-			Quantization() : use(false) {};
-			~Quantization() = default;
-		};
 
+	struct Normalization {
+		bool use { false };
+		std::vector<double> mean;
+		std::vector<double> std;
+	};
+
+	struct Quantization {
+		bool use { false };
+		std::vector<double> scale;
+		std::vector<double> zeropoint;
+	};
+
+	struct Options {
 		Normalization normalization;
 		Quantization  quantization;
-
-		Options() = default;
-		~Options() = default;
 	};
 
-	class LayerInfo
+	struct LayerInfo
 	{
-	public:
-
 		std::string name;
 		std::vector<int> dims;
-		mv_colorspace_e colorSpace;
-		mv_inference_data_type_e dataType;
-		inference_tensor_shape_type_e shapeType; // TODO: define mv_inference_shape_type_e
-
-		LayerInfo() = default;
-		~LayerInfo() = default;
-
-		int GetWidth() const;
-		int GetHeight() const;
-		int GetChannel() const;
+		mv_colorspace_e colorSpace {};
+		mv_inference_data_type_e dataType {};
+		inference_tensor_shape_type_e shapeType {}; // TODO: define mv_inference_shape_type_e
+
+		int getWidth() const {
+			if (shapeType == INFERENCE_TENSOR_SHAPE_NCHW) {
+				return dims[3];
+			} else { // INFERENCE_TENSOR_SHAPE_NHWC
+				return dims[2];
+			}
+		}
+
+		int getHeight() const {
+			if (shapeType == INFERENCE_TENSOR_SHAPE_NCHW) {
+				return dims[2];
+			} else { // INFERENCE_TENSOR_SHAPE_NHWC
+				return dims[1];
+			}
+		}
+
+		int getChannel() const {
+			if (shapeType == INFERENCE_TENSOR_SHAPE_NCHW) {
+				return dims[1];
+			} else { // INFERENCE_TENSOR_SHAPE_NHWC
+				return dims[3];
+			}
+		}
 	};
 
 	class InputMetadata
diff --git a/mv_machine_learning/inference/src/Inference.cpp b/mv_machine_learning/inference/src/Inference.cpp
index 0e3123e..4f426c7 100755
--- a/mv_machine_learning/inference/src/Inference.cpp
+++ b/mv_machine_learning/inference/src/Inference.cpp
@@ -963,7 +963,11 @@ namespace inference
 
 			if (mMetadata.GetInputMeta().IsParsed()) {
 				const LayerInfo& layerInfo = mMetadata.GetInputMeta().GetLayer().at(buffer.first);
-				const Options& opt = mMetadata.GetInputMeta().GetOption().empty() ? Options() : mMetadata.GetInputMeta().GetOption().at(buffer.first);
+				Options opt;
+
+				if (!mMetadata.GetInputMeta().GetOption().empty())
+					opt = mMetadata.GetInputMeta().GetOption().at(buffer.first);
+
 				mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
 
 				mv_source_get_colorspace(mvSources[src_idx], &colorspace);
@@ -1183,8 +1187,8 @@ namespace inference
 			}
 
 			ObjectDecoder objDecoder(mOutputTensorBuffers, outputMeta, boxOffset,
-						static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.GetWidth()),
-						static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.GetHeight()),
+						static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getWidth()),
+						static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getHeight()),
 						numberOfObjects);
 
 			objDecoder.init();
@@ -1340,8 +1344,8 @@ namespace inference
 			}
 
 			ObjectDecoder objDecoder(mOutputTensorBuffers, outputMeta, boxOffset,
-						static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.GetWidth()),
-						static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.GetHeight()),
+						static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getWidth()),
+						static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getHeight()),
 						numberOfFaces);
 
 			objDecoder.init();
@@ -1497,8 +1501,8 @@ namespace inference
 			float inputH = 1.f;
 
 			if (outputMeta.GetLandmarkCoordinate() == INFERENCE_LANDMARK_COORDINATE_TYPE_PIXEL) {
-				inputW = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.GetWidth());
-				inputH = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.GetHeight());
+				inputW = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getWidth());
+				inputH = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getHeight());
 			}
 
 			float thresRadius = outputMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE ? 0.0 :
@@ -1615,8 +1619,8 @@ namespace inference
 			float thresRadius = outputMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE ? 0.0 :
 														outputMeta.GetLandmarkHeatMapInfo().nmsRadius;
 			if (outputMeta.GetLandmarkCoordinate() == INFERENCE_LANDMARK_COORDINATE_TYPE_PIXEL) {
-				inputW = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.GetWidth());
-				inputH = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.GetHeight());
+				inputW = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getWidth());
+				inputH = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getHeight());
 			}
 
 			poseDecoder.decode(inputW, inputH, thresRadius);
diff --git a/mv_machine_learning/inference/src/InputMetadata.cpp b/mv_machine_learning/inference/src/InputMetadata.cpp
index 2ca878d..22b8383 100644
--- a/mv_machine_learning/inference/src/InputMetadata.cpp
+++ b/mv_machine_learning/inference/src/InputMetadata.cpp
@@ -119,6 +119,7 @@ namespace inference
 		// TODO: handling error
 		for (unsigned int elem = 0; elem < elements; ++elem, ++iterLayer) {
 			Options opt;
+
 			JsonNode *pNode = json_array_get_element(rootArray, elem);
 			JsonObject *pObject = json_node_get_object(pNode);
 
@@ -204,29 +205,5 @@ namespace inference
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	int LayerInfo::GetWidth() const {
-		if (shapeType == INFERENCE_TENSOR_SHAPE_NCHW) {
-			return dims[3];
-		} else { // INFERENCE_TENSOR_SHAPE_NHWC
-			return dims[2];
-		}
-	}
-
-	int LayerInfo::GetHeight() const {
-		if (shapeType == INFERENCE_TENSOR_SHAPE_NCHW) {
-			return dims[2];
-		} else { // INFERENCE_TENSOR_SHAPE_NHWC
-			return dims[1];
-		}
-	}
-
-	int LayerInfo::GetChannel() const {
-		if (shapeType == INFERENCE_TENSOR_SHAPE_NCHW) {
-			return dims[1];
-		} else { // INFERENCE_TENSOR_SHAPE_NHWC
-			return dims[3];
-		}
-	}
-
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/src/PreProcess.cpp b/mv_machine_learning/inference/src/PreProcess.cpp
index 6d79586..0529124 100644
--- a/mv_machine_learning/inference/src/PreProcess.cpp
+++ b/mv_machine_learning/inference/src/PreProcess.cpp
@@ -124,7 +124,7 @@ namespace inference
 		LOGI("ENTER");
 
 		// dest is a wrapper of the buffer
-		cv::Mat dest(cv::Size(layerInfo.GetWidth(), layerInfo.GetHeight()),
+		cv::Mat dest(cv::Size(layerInfo.getWidth(), layerInfo.getHeight()),
 					dataType, buffer);
 
 		cv::Mat cvSource, cvDest;
-- 
2.7.4


From c2a68d4e2ce9d02f76f49335ebaa7ad2c82bc592 Mon Sep 17 00:00:00 2001
From: Kwanghoon Son <k.son@samsung.com>
Date: Tue, 30 Aug 2022 22:28:53 -0400
Subject: [PATCH 11/16] Disable SNPE gtest

[Issue type] : Change

Snpe test needs special hardware which is not related with public tizen
test. To enable snpe test, run mv_test with --gtest_also_run_disabled_tests

Change-Id: I36fdc978b0298ab435ff1e5a91f63703c685c86e
Signed-off-by: Kwanghoon Son <k.son@samsung.com>
---
 .../testsuites/machine_learning/inference/test_image_classification.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/testsuites/machine_learning/inference/test_image_classification.cpp b/test/testsuites/machine_learning/inference/test_image_classification.cpp
index f0ebba3..fbece70 100644
--- a/test/testsuites/machine_learning/inference/test_image_classification.cpp
+++ b/test/testsuites/machine_learning/inference/test_image_classification.cpp
@@ -303,7 +303,7 @@ TEST_P(TestImageClassificationTflite, QUANT_MobilenetV1)
 	inferenceBanana();
 }
 
-TEST_P(TestImageClassificationSnpe, InceptionV3_Quantized)
+TEST_P(TestImageClassificationSnpe, DISABLED_InceptionV3_Quantized)
 {
 	engine_config_hosted_snpe_model(engine_cfg, IC_SNPE_WEIGHT_QUANT_INCEPTION_V3_299_PATH,
 									IC_LABEL_INCEPTION_V3_299_PATH, _use_json_parser,
-- 
2.7.4


From 6a062af3e62703064891676c9734dc00ad16e822 Mon Sep 17 00:00:00 2001
From: Inki Dae <inki.dae@samsung.com>
Date: Thu, 1 Sep 2022 09:41:17 +0900
Subject: [PATCH 12/16] mv_machine_learning: Use Preprocess class instead of
 legacy one

[Issue type] code refactoring

Did code refactoring to Run function of Inference class by replacing
existing internal Preprocess function with the one of Proprocess class.
We can use Preprocess class instead of Inference class internal one.
With this change, we can use Preprocess class commonly.

Change-Id: Id22de1532ce352abb013ad6bb26075c74a835949
Signed-off-by: Inki Dae <inki.dae@samsung.com>
---
 mv_machine_learning/inference/include/Inference.h |   2 +-
 mv_machine_learning/inference/src/Inference.cpp   | 133 +++++++++-------------
 2 files changed, 57 insertions(+), 78 deletions(-)

diff --git a/mv_machine_learning/inference/include/Inference.h b/mv_machine_learning/inference/include/Inference.h
index 7096094..84a63d2 100644
--- a/mv_machine_learning/inference/include/Inference.h
+++ b/mv_machine_learning/inference/include/Inference.h
@@ -351,8 +351,8 @@ namespace inference
 		int ConvertTargetTypes(int given_types);
 		int ConvertToCv(int given_type);
 		int ConvertOutputDataTypeToFloat();
+		int Preprocess(std::vector<mv_source_h>& mv_sources, std::vector<cv::Mat>& cv_sources);
 		inference_tensor_data_type_e ConvertToIE(int given_type);
-		int Preprocess(cv::Mat cvImg, cv::Mat cvDst, int data_type);
 		int PrepareTenosrBuffers(void);
 		void CleanupTensorBuffers(void);
 		int SetUserFile(std::string filename);
diff --git a/mv_machine_learning/inference/src/Inference.cpp b/mv_machine_learning/inference/src/Inference.cpp
index 4f426c7..6a5a6ca 100755
--- a/mv_machine_learning/inference/src/Inference.cpp
+++ b/mv_machine_learning/inference/src/Inference.cpp
@@ -279,51 +279,6 @@ namespace inference
 		return type;
 	}
 
-	int Inference::Preprocess(cv::Mat cvImg, cv::Mat cvDst, int data_type)
-	{
-		int width = mInputSize.width;
-		int height = mInputSize.height;
-		const int ch = mConfig.mTensorInfo.ch;
-
-		cv::Mat sample;
-		if (cvImg.channels() == 3 && ch == 1)
-			cv::cvtColor(cvImg, sample, cv::COLOR_BGR2GRAY);
-		else
-			sample = cvImg;
-
-		// size
-		cv::Mat sampleResized;
-		if (sample.size() != cv::Size(width, height))
-			cv::resize(sample, sampleResized, cv::Size(width, height));
-		else
-			sampleResized = sample;
-
-		// type
-		cv::Mat sampleFloat;
-		if (ch == 3)
-			sampleResized.convertTo(sampleFloat, CV_32FC3);
-		else
-			sampleResized.convertTo(sampleFloat, CV_32FC1);
-
-		// normalize
-		cv::Mat sampleNormalized;
-		cv::Mat meanMat;
-		auto mean = static_cast<float>(mConfig.mMeanValue);
-
-		if (ch == 3)
-			meanMat = cv::Mat(sampleFloat.size(), CV_32FC3, cv::Scalar(mean, mean, mean));
-		else
-			meanMat = cv::Mat(sampleFloat.size(), CV_32FC1, cv::Scalar(mean));
-
-		cv::subtract(sampleFloat, meanMat, sampleNormalized);
-
-		sampleNormalized /= static_cast<float>(mConfig.mStdValue);
-
-		sampleNormalized.convertTo(cvDst, data_type);
-
-		return MEDIA_VISION_ERROR_NONE;
-	}
-
 	int Inference::SetUserFile(std::string filename)
 	{
 		std::ifstream fp(filename.c_str());
@@ -912,6 +867,58 @@ namespace inference
 		return ConvertEngineErrorToVisionError(ret);
 	}
 
+	int Inference::Preprocess(std::vector<mv_source_h>& mv_sources, std::vector<cv::Mat>& cv_sources)
+	{
+		unsigned int src_idx = 0;
+
+		for (auto& buffer : mInputTensorBuffers.getIETensorBuffer()) {
+			inference_engine_tensor_buffer& tensor_buffer = buffer.second;
+			int data_type = ConvertToCv(tensor_buffer.data_type);
+			LayerInfo layerInfo;
+			Options opt;
+			mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
+
+			mv_source_get_colorspace(mv_sources[src_idx], &colorspace);
+
+			if (mMetadata.GetInputMeta().IsParsed()) {
+				layerInfo = mMetadata.GetInputMeta().GetLayer().at(buffer.first);
+
+				if (!mMetadata.GetInputMeta().GetOption().empty())
+					opt = mMetadata.GetInputMeta().GetOption().at(buffer.first);
+			} else {
+				// Ps. in case of legacy way, there is no way to set model specific dequantization parameters - zero point and scale.
+				// TODO. find a proper way for it.
+				opt.normalization.use = true;
+				opt.normalization.mean.assign(3, mConfig.mMeanValue);
+				opt.normalization.std.assign(3, mConfig.mStdValue);
+
+				layerInfo.name = buffer.first;
+				layerInfo.dims.push_back(mConfig.mTensorInfo.dim);
+				layerInfo.dims.push_back(mConfig.mTensorInfo.height);
+				layerInfo.dims.push_back(mConfig.mTensorInfo.width);
+				layerInfo.dims.push_back(mConfig.mTensorInfo.ch);
+
+				// Ps. in case of legacy way, there is no way to use model specific color space but only fixed one.
+				// TODO. find a proper way for it.
+				layerInfo.colorSpace = MEDIA_VISION_COLORSPACE_RGB888;
+				layerInfo.dataType = mConfig.mDataType;
+				// TODO. find a proper way for setting the shape type. In case of legacy way, there is no way to change the shape type properly.
+				//       According to a given inference engine, different shape type can be needed.
+				layerInfo.shapeType = INFERENCE_TENSOR_SHAPE_NHWC;
+			}
+
+			// TODO: try-catch{} error handling
+			int ret = mPreProc.Run(cv_sources[src_idx++], colorspace, data_type, layerInfo, opt, tensor_buffer.buffer);
+			if (ret != MEDIA_VISION_ERROR_NONE) {
+				LOGE("Fail to run pre-process.");
+				return ret;
+			}
+		}
+
+		return MEDIA_VISION_ERROR_NONE;
+
+	}
+
 	int Inference::Run(std::vector<mv_source_h> &mvSources,
 					   std::vector<mv_rectangle_s> &rects)
 	{
@@ -955,38 +962,10 @@ namespace inference
 		// TODO. consider multiple cv sources.
 		mSourceSize = cvSources[0].size();
 
-		unsigned int src_idx = 0;
-
-		for (auto& buffer : mInputTensorBuffers.getIETensorBuffer()) {
-			inference_engine_tensor_buffer& tensor_buffer = buffer.second;
-			int data_type = ConvertToCv(tensor_buffer.data_type);
-
-			if (mMetadata.GetInputMeta().IsParsed()) {
-				const LayerInfo& layerInfo = mMetadata.GetInputMeta().GetLayer().at(buffer.first);
-				Options opt;
-
-				if (!mMetadata.GetInputMeta().GetOption().empty())
-					opt = mMetadata.GetInputMeta().GetOption().at(buffer.first);
-
-				mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
-
-				mv_source_get_colorspace(mvSources[src_idx], &colorspace);
-
-				// TODO: try-catch{} error handling
-				ret = mPreProc.Run(cvSources[src_idx++], colorspace, data_type, layerInfo, opt, tensor_buffer.buffer);
-				if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to run pre-process.");
-					return ret;
-				}
-			} else {
-				// Convert color space of input tensor data and then normalize it.
-
-				ret = Preprocess(cvSources[src_idx++], cv::Mat(mInputSize.height, mInputSize.width, data_type, tensor_buffer.buffer), data_type);
-				if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to preprocess input tensor data.");
-					return ret;
-				}
-			}
+		ret = Preprocess(mvSources, cvSources);
+		if (ret != MEDIA_VISION_ERROR_NONE) {
+			LOGE("Fail to preprocess given input sources.");
+			return ret;
 		}
 
 		ret = mBackend->Run(mInputTensorBuffers.getIETensorBuffer(),
-- 
2.7.4


From cd69a17b23173da1ad3a139fad11183d1f8dd360 Mon Sep 17 00:00:00 2001
From: Kwanghoon Son <k.son@samsung.com>
Date: Thu, 1 Sep 2022 03:07:38 -0400
Subject: [PATCH 13/16] Apply clang-format rule

[Issue type] refactoring

Change-Id: Ib947e0660c3b1057859dbc1c96650a8de4370a0a
Signed-off-by: Kwanghoon Son <k.son@samsung.com>
---
 .../inference/test_object_detection.cpp            | 65 ++++++++++++----------
 1 file changed, 37 insertions(+), 28 deletions(-)

diff --git a/test/testsuites/machine_learning/inference/test_object_detection.cpp b/test/testsuites/machine_learning/inference/test_object_detection.cpp
index 75b54b0..7e685d6 100644
--- a/test/testsuites/machine_learning/inference/test_object_detection.cpp
+++ b/test/testsuites/machine_learning/inference/test_object_detection.cpp
@@ -47,42 +47,51 @@ public:
 
 TEST_P(TestObjectDetectionTflite, MobilenetV1_SSD)
 {
-	engine_config_hosted_tflite_model(engine_cfg, OD_TFLITE_WEIGHT_MOBILENET_V1_SSD_300_PATH,
-									  OD_LABEL_MOBILENET_V1_SSD_300_PATH, _use_json_parser,
-									  _target_device_type);
+	engine_config_hosted_tflite_model(
+			engine_cfg, OD_TFLITE_WEIGHT_MOBILENET_V1_SSD_300_PATH,
+			OD_LABEL_MOBILENET_V1_SSD_300_PATH, _use_json_parser,
+			_target_device_type);
 
 	if (!_use_json_parser) {
 		const char *inputNodeName = "normalized_input_image_tensor";
 		const char *outputNodeName[] = { "TFLite_Detection_PostProcess",
-											"TFLite_Detection_PostProcess:1",
-											"TFLite_Detection_PostProcess:2",
-											"TFLite_Detection_PostProcess:3" };
+										 "TFLite_Detection_PostProcess:1",
+										 "TFLite_Detection_PostProcess:2",
+										 "TFLite_Detection_PostProcess:3" };
 
-		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3),
-					MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_double_attribute(
+						  engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_double_attribute(
+						  engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 127.5),
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_double_attribute(
+						  engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3),
+				  MEDIA_VISION_ERROR_NONE);
 
-		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME,
-														inputNodeName), MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_array_string_attribute(engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
-																outputNodeName, 4), MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_int_attribute(
+						  engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300),
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_int_attribute(
+						  engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300),
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_int_attribute(
+						  engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_string_attribute(
+						  engine_cfg, MV_INFERENCE_INPUT_NODE_NAME,
+						  inputNodeName),
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_array_string_attribute(
+						  engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
+						  outputNodeName, 4),
+				  MEDIA_VISION_ERROR_NONE);
 	}
 
 	inferenceDog();
 }
 
-INSTANTIATE_TEST_CASE_P(Prefix, TestObjectDetectionTflite,
-						::testing::Values(
-							ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
-							ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU)
-						)
-);
+INSTANTIATE_TEST_CASE_P(
+		Prefix, TestObjectDetectionTflite,
+		::testing::Values(ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
+						  ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU)));
-- 
2.7.4


From fe02f05b54290d93405eda7403675a335d162d05 Mon Sep 17 00:00:00 2001
From: Kwanghoon Son <k.son@samsung.com>
Date: Fri, 2 Sep 2022 01:29:40 -0400
Subject: [PATCH 14/16] Add SNPE efficient net test

[Issue type] new test

Change-Id: Ia141001c1957709075da62416e6d4c0c6dc89916
Signed-off-by: Kwanghoon Son <k.son@samsung.com>
---
 .../inference/test_object_detection.cpp            | 45 ++++++++++++++++++++--
 1 file changed, 42 insertions(+), 3 deletions(-)

diff --git a/test/testsuites/machine_learning/inference/test_object_detection.cpp b/test/testsuites/machine_learning/inference/test_object_detection.cpp
index 7e685d6..42c0c48 100644
--- a/test/testsuites/machine_learning/inference/test_object_detection.cpp
+++ b/test/testsuites/machine_learning/inference/test_object_detection.cpp
@@ -12,16 +12,22 @@
 #define IMG_DOG    \
 	MV_CONFIG_PATH \
 	"/res/inference/images/dog2.jpg"
+#define OD_LABEL_EFFICIENTDET_LITE2_448_PATH \
+	MV_CONFIG_PATH                           \
+	"models/OD/snpe/label_coco_90.txt"
+#define OD_SNPE_WEIGHT_QC_EFFCIENTDET_LITE2_448_PATH \
+	MV_CONFIG_PATH                                   \
+	"/models/OD/snpe/lite2_fp32.dlc"
 
 void _object_detected_cb(mv_source_h source, const int number_of_objects,
 						 const int *indices, const char **names,
 						 const float *confidences,
 						 const mv_rectangle_s *locations, void *user_data)
 {
-	const std::string answer = "Dog";
+	auto answer = static_cast<std::string *>(user_data);
 	auto answer_found = false;
 	for (int i = 0; i < number_of_objects; i++) {
-		if (answer == names[i]) {
+		if (*answer == names[i]) {
 			answer_found = true;
 			break;
 		}
@@ -34,13 +40,14 @@ class TestObjectDetectionTflite : public TestInference
 public:
 	void inferenceDog()
 	{
+		std::string result("Dog");
 		TestInference::ConfigureInference();
 
 		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(
 						  IMG_DOG, mv_source),
 				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_inference_object_detect(mv_source, infer,
-											 _object_detected_cb, NULL),
+											 _object_detected_cb, &result),
 				  MEDIA_VISION_ERROR_NONE);
 	}
 };
@@ -95,3 +102,35 @@ INSTANTIATE_TEST_CASE_P(
 		Prefix, TestObjectDetectionTflite,
 		::testing::Values(ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
 						  ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU)));
+
+class TestObjectDetectionSnpe : public TestInference
+{
+public:
+	void inferenceDog()
+	{
+		std::string result("dog");
+		TestInference::ConfigureInference();
+
+		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(
+						  IMG_DOG, mv_source),
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_inference_object_detect(mv_source, infer,
+											 _object_detected_cb, &result),
+				  MEDIA_VISION_ERROR_NONE);
+	}
+};
+
+TEST_P(TestObjectDetectionSnpe, DISABLED_EFDLite2QC)
+{
+	ASSERT_TRUE(_use_json_parser);
+	engine_config_hosted_snpe_model(
+			engine_cfg, OD_SNPE_WEIGHT_QC_EFFCIENTDET_LITE2_448_PATH,
+			OD_LABEL_EFFICIENTDET_LITE2_448_PATH, _use_json_parser,
+			_target_device_type);
+
+	inferenceDog();
+}
+
+INSTANTIATE_TEST_CASE_P(
+		Prefix, TestObjectDetectionSnpe,
+		::testing::Values(ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CUSTOM)));
\ No newline at end of file
-- 
2.7.4


From ee852016683c6fed53fdddcc54ebea2c9212e4ff Mon Sep 17 00:00:00 2001
From: Kwanghoon Son <k.son@samsung.com>
Date: Fri, 2 Sep 2022 05:25:40 -0400
Subject: [PATCH 15/16] Apply clang-format

[Issue type] Clean code
[Version] 0.23.23

This patch only change code convention.

Change-Id: I5f1d3dd56ecd5d962c8a9a52087ed8315db156a6
Signed-off-by: Kwanghoon Son <k.son@samsung.com>
---
 .clang-format                                      |    7 +-
 doc/mediavision_doc.h                              |    2 +-
 include/mv_barcode_detect.h                        |   40 +-
 include/mv_barcode_generate.h                      |   36 +-
 include/mv_barcode_type.h                          |   72 +-
 include/mv_common.h                                |  207 +-
 include/mv_face.h                                  |  156 +-
 include/mv_face_type.h                             |   28 +-
 include/mv_image.h                                 |   94 +-
 include/mv_inference.h                             |  108 +-
 include/mv_inference_private.h                     |   40 +-
 include/mv_inference_type.h                        |  104 +-
 include/mv_private.h                               |   49 +-
 include/mv_roi_tracker.h                           |   16 +-
 include/mv_roi_tracker_type.h                      |   29 +-
 include/mv_surveillance.h                          |  120 +-
 include/mv_surveillance_private.h                  |   11 +-
 mv_barcode/barcode_detector/include/Barcode.h      |   13 +-
 mv_barcode/barcode_detector/include/BarcodeUtils.h |   14 +-
 .../include/mv_barcode_detect_open.h               |    8 +-
 mv_barcode/barcode_detector/src/Barcode.cpp        |   30 +-
 mv_barcode/barcode_detector/src/BarcodeUtils.cpp   |   13 +-
 .../barcode_detector/src/mv_barcode_detect.c       |   16 +-
 .../src/mv_barcode_detect_open.cpp                 |   62 +-
 .../barcode_generator/include/BarcodeGenerator.h   |   48 +-
 .../barcode_generator/include/BarcodeOptions.h     |   25 +-
 .../include/mv_barcode_generate_open.h             |   25 +-
 .../barcode_generator/src/BarcodeGenerator.cpp     |  150 +-
 .../barcode_generator/src/mv_barcode_generate.c    |   56 +-
 .../src/mv_barcode_generate_open.cpp               |  131 +-
 mv_common/include/CommonUtils.h                    |    9 +-
 mv_common/include/EngineConfig.h                   |   49 +-
 mv_common/include/MediaSource.h                    |   30 +-
 mv_common/include/mv_common_c.h                    |  103 +-
 mv_common/include/util.h                           |   81 +-
 mv_common/src/CommonUtils.cpp                      |   37 +-
 mv_common/src/EngineConfig.cpp                     |  118 +-
 mv_common/src/MediaSource.cpp                      |   69 +-
 mv_common/src/mv_common.c                          |  140 +-
 mv_common/src/mv_common_c.cpp                      |  323 +--
 mv_common/src/mv_private.c                         |  161 +-
 mv_face/face/include/FaceDetector.h                |   20 +-
 mv_face/face/include/FaceExpressionRecognizer.h    |   20 +-
 mv_face/face/include/FaceEyeCondition.h            |   25 +-
 mv_face/face/include/FaceRecognitionModel.h        |   63 +-
 mv_face/face/include/FaceTracker.h                 |   70 +-
 mv_face/face/include/FaceTrackingModel.h           |   35 +-
 mv_face/face/include/FaceUtil.h                    |   20 +-
 mv_face/face/include/mv_face_open.h                |  114 +-
 mv_face/face/src/FaceDetector.cpp                  |   37 +-
 mv_face/face/src/FaceExpressionRecognizer.cpp      |   50 +-
 mv_face/face/src/FaceEyeCondition.cpp              |  107 +-
 mv_face/face/src/FaceRecognitionModel.cpp          |  189 +-
 mv_face/face/src/FaceTracker.cpp                   |  157 +-
 mv_face/face/src/FaceTrackingModel.cpp             |   43 +-
 mv_face/face/src/FaceUtil.cpp                      |   12 +-
 mv_face/face/src/mv_face.c                         |  176 +-
 mv_face/face/src/mv_face_open.cpp                  |  366 +--
 .../image/include/Features/BasicExtractorFactory.h |   10 +-
 mv_image/image/include/Features/FeatureExtractor.h |   32 +-
 .../include/Features/FeatureExtractorFactory.h     |   10 +-
 mv_image/image/include/Features/FeatureMatcher.h   |   25 +-
 mv_image/image/include/Features/FeaturePack.h      |   13 +-
 .../image/include/Features/ORBExtractorFactory.h   |   18 +-
 mv_image/image/include/ImageConfig.h               |   77 +-
 mv_image/image/include/ImageMathUtil.h             |   29 +-
 mv_image/image/include/Recognition/ImageObject.h   |   35 +-
 .../image/include/Recognition/ImageRecognizer.h    |   38 +-
 mv_image/image/include/Tracking/AsyncTracker.h     |   23 +-
 mv_image/image/include/Tracking/CascadeTracker.h   |   28 +-
 .../include/Tracking/FeatureSubstitutionTracker.h  |   22 +-
 .../include/Tracking/ImageContourStabilizator.h    |   26 +-
 .../image/include/Tracking/ImageTrackingModel.h    |   25 +-
 mv_image/image/include/Tracking/MFTracker.h        |   60 +-
 mv_image/image/include/Tracking/ObjectTracker.h    |   15 +-
 .../include/Tracking/RecognitionBasedTracker.h     |   19 +-
 mv_image/image/include/mv_image_open.h             |   81 +-
 .../image/src/Features/BasicExtractorFactory.cpp   |   17 +-
 mv_image/image/src/Features/FeatureExtractor.cpp   |   51 +-
 .../image/src/Features/FeatureExtractorFactory.cpp |    7 +-
 mv_image/image/src/Features/FeatureMatcher.cpp     |   77 +-
 mv_image/image/src/Features/FeaturePack.cpp        |   33 +-
 .../image/src/Features/ORBExtractorFactory.cpp     |   37 +-
 mv_image/image/src/ImageConfig.cpp                 |   85 +-
 mv_image/image/src/ImageMathUtil.cpp               |   43 +-
 mv_image/image/src/Recognition/ImageObject.cpp     |   87 +-
 mv_image/image/src/Recognition/ImageRecognizer.cpp |  119 +-
 mv_image/image/src/Tracking/AsyncTracker.cpp       |   57 +-
 mv_image/image/src/Tracking/CascadeTracker.cpp     |   47 +-
 .../src/Tracking/FeatureSubstitutionTracker.cpp    |   60 +-
 .../src/Tracking/ImageContourStabilizator.cpp      |   75 +-
 mv_image/image/src/Tracking/ImageTrackingModel.cpp |   88 +-
 mv_image/image/src/Tracking/MFTracker.cpp          |  149 +-
 mv_image/image/src/Tracking/ObjectTracker.cpp      |    6 +-
 .../image/src/Tracking/RecognitionBasedTracker.cpp |   32 +-
 mv_image/image/src/mv_image.c                      |   83 +-
 mv_image/image/src/mv_image_open.cpp               |  363 +--
 mv_machine_learning/common/include/context.h       |    9 +-
 mv_machine_learning/common/include/itask.h         |   10 +-
 .../common/include/machine_learning_exception.h    |   60 +-
 .../face_recognition/include/backbone_model_info.h |   13 +-
 .../face_recognition/include/face_net_info.h       |    7 +-
 .../face_recognition/include/face_recognition.h    |   44 +-
 .../include/face_recognition_adapter.h             |   11 +-
 .../include/mv_face_recognition_open.h             |   31 +-
 .../face_recognition/include/nntrainer_dsm.h       |    6 +-
 .../face_recognition/include/nntrainer_fvm.h       |    9 +-
 .../face_recognition/include/simple_shot.h         |    7 +-
 .../face_recognition/src/face_net_info.cpp         |   16 +-
 .../face_recognition/src/face_recognition.cpp      |  104 +-
 .../src/face_recognition_adapter.cpp               |   46 +-
 .../face_recognition/src/mv_face_recognition.c     |   21 +-
 .../src/mv_face_recognition_open.cpp               |   16 +-
 .../face_recognition/src/nntrainer_dsm.cpp         |   18 +-
 .../face_recognition/src/nntrainer_fvm.cpp         |   42 +-
 .../face_recognition/src/simple_shot.cpp           |   23 +-
 mv_machine_learning/inference/include/BoxInfo.h    |   31 +-
 mv_machine_learning/inference/include/Bvh.h        |  123 +-
 mv_machine_learning/inference/include/BvhParser.h  |   61 +-
 mv_machine_learning/inference/include/BvhUtils.h   |   10 +-
 mv_machine_learning/inference/include/DecodeInfo.h |  283 ++-
 mv_machine_learning/inference/include/DimInfo.h    |   36 +-
 mv_machine_learning/inference/include/DispVec.h    |  100 +-
 mv_machine_learning/inference/include/Edge.h       |   57 +-
 mv_machine_learning/inference/include/Inference.h  |  269 +-
 .../inference/include/InferenceIni.h               |   36 +-
 .../inference/include/InputMetadata.h              |  143 +-
 mv_machine_learning/inference/include/Joint.h      |  305 ++-
 mv_machine_learning/inference/include/Landmark.h   |  432 ++--
 mv_machine_learning/inference/include/Metadata.h   |   42 +-
 .../inference/include/ObjectDecoder.h              |   53 +-
 mv_machine_learning/inference/include/OffsetVec.h  |   90 +-
 .../inference/include/OutputMetadata.h             |  187 +-
 .../inference/include/OutputMetadataTypes.h        |   95 +-
 .../inference/include/PoseDecoder.h                |   96 +-
 .../inference/include/PostProcess.h                |   47 +-
 mv_machine_learning/inference/include/Posture.h    |   54 +-
 mv_machine_learning/inference/include/PreProcess.h |   37 +-
 mv_machine_learning/inference/include/ScoreInfo.h  |   15 +-
 .../inference/include/TensorBuffer.h               |   42 +-
 mv_machine_learning/inference/include/Utils.h      |   20 +-
 .../inference/include/mv_inference_open.h          |  127 +-
 mv_machine_learning/inference/src/BoxInfo.cpp      |   16 +-
 mv_machine_learning/inference/src/Bvh.cpp          |  137 +-
 mv_machine_learning/inference/src/BvhParser.cpp    |  641 +++--
 mv_machine_learning/inference/src/BvhUtils.cpp     |   73 +-
 mv_machine_learning/inference/src/Inference.cpp    | 2627 ++++++++++----------
 mv_machine_learning/inference/src/InferenceIni.cpp |  122 +-
 .../inference/src/InputMetadata.cpp                |  296 ++-
 mv_machine_learning/inference/src/Metadata.cpp     |  153 +-
 .../inference/src/ObjectDecoder.cpp                |  362 ++-
 .../inference/src/OutputMetadata.cpp               |  811 +++---
 mv_machine_learning/inference/src/PoseDecoder.cpp  |  711 +++---
 mv_machine_learning/inference/src/PostProcess.cpp  |  217 +-
 mv_machine_learning/inference/src/Posture.cpp      |  541 ++--
 mv_machine_learning/inference/src/PreProcess.cpp   |  187 +-
 mv_machine_learning/inference/src/TensorBuffer.cpp |  297 ++-
 mv_machine_learning/inference/src/mv_inference.c   |  106 +-
 .../inference/src/mv_inference_open.cpp            |  199 +-
 .../training/include/data_augment.h                |    5 +-
 .../training/include/data_augment_default.h        |    5 +-
 .../training/include/data_augment_flip.h           |    5 +-
 .../training/include/data_augment_rotate.h         |    5 +-
 .../training/include/data_set_manager.h            |   15 +-
 .../training/include/feature_vector_manager.h      |   26 +-
 mv_machine_learning/training/include/file_util.h   |    4 +-
 .../training/include/label_manager.h               |    7 +-
 .../training/include/training_model.h              |   14 +-
 mv_machine_learning/training/src/data_augment.cpp  |    8 +-
 .../training/src/data_augment_default.cpp          |   12 +-
 .../training/src/data_augment_flip.cpp             |   12 +-
 .../training/src/data_augment_rotate.cpp           |   12 +-
 .../training/src/data_set_manager.cpp              |   21 +-
 .../training/src/feature_vector_manager.cpp        |   32 +-
 mv_machine_learning/training/src/file_util.cpp     |   41 +-
 mv_machine_learning/training/src/label_manager.cpp |   18 +-
 .../training/src/training_model.cpp                |   13 +-
 mv_roi_tracker/roi_tracker/include/ROITracker.h    |   16 +-
 .../roi_tracker/include/ROITrackerUtil.h           |    8 +-
 .../roi_tracker/include/mv_roi_tracker_open.h      |    9 +-
 mv_roi_tracker/roi_tracker/src/ROITracker.cpp      |   25 +-
 mv_roi_tracker/roi_tracker/src/ROITrackerUtil.cpp  |   32 +-
 mv_roi_tracker/roi_tracker/src/mv_roi_tracker.c    |   21 +-
 .../roi_tracker/src/mv_roi_tracker_open.cpp        |   29 +-
 mv_surveillance/surveillance/include/EventDefs.h   |    7 +-
 .../surveillance/include/EventManager.h            |   55 +-
 mv_surveillance/surveillance/include/EventResult.h |   14 +-
 .../surveillance/include/EventTrigger.h            |   56 +-
 .../include/EventTriggerMovementDetection.h        |   30 +-
 .../include/EventTriggerPersonAppearance.h         |   45 +-
 .../include/EventTriggerPersonRecognition.h        |   56 +-
 mv_surveillance/surveillance/include/MFTracker.h   |   59 +-
 .../surveillance/include/SurveillanceHelper.h      |   14 +-
 mv_surveillance/surveillance/include/mv_absdiff.h  |   10 +-
 .../surveillance/include/mv_apply_mask.h           |   10 +-
 .../surveillance/include/mv_mask_buffer.h          |    9 +-
 .../surveillance/include/mv_surveillance_open.h    |   33 +-
 mv_surveillance/surveillance/src/EventManager.cpp  |  195 +-
 mv_surveillance/surveillance/src/EventTrigger.cpp  |   72 +-
 .../src/EventTriggerMovementDetection.cpp          |   96 +-
 .../src/EventTriggerPersonAppearance.cpp           |  228 +-
 .../src/EventTriggerPersonRecognition.cpp          |  147 +-
 mv_surveillance/surveillance/src/MFTracker.cpp     |  148 +-
 .../surveillance/src/SurveillanceHelper.cpp        |  109 +-
 mv_surveillance/surveillance/src/mv_absdiff.c      |   18 +-
 mv_surveillance/surveillance/src/mv_apply_mask.c   |   11 +-
 mv_surveillance/surveillance/src/mv_mask_buffer.c  |   21 +-
 mv_surveillance/surveillance/src/mv_surveillance.c |  101 +-
 .../surveillance/src/mv_surveillance_open.cpp      |   73 +-
 packaging/capi-media-vision.spec                   |    2 +-
 test/assessment/barcode/assessment_barcode.cpp     |   44 +-
 test/assessment/face/assessment_face.cpp           |   50 +-
 .../surveillance/assessment_surveillance.cpp       |   96 +-
 test/testsuites/barcode/barcode_test_suite.c       |  409 ++-
 test/testsuites/barcode/test_barcode.cpp           |   26 +-
 .../common/image_helper/include/ImageHelper.h      |   79 +-
 .../common/image_helper/include/image_helper.h     |   52 +-
 .../common/image_helper/src/ImageHelper.cpp        |  115 +-
 .../common/image_helper/src/image_helper.cpp       |   58 +-
 .../common/testsuite_common/mv_testsuite_common.c  |   61 +-
 .../common/testsuite_common/mv_testsuite_common.h  |   27 +-
 test/testsuites/common/video_helper/mv_log_cfg.h   |   68 +-
 .../common/video_helper/mv_video_helper.c          |  242 +-
 .../common/video_helper/mv_video_helper.h          |   55 +-
 test/testsuites/face/face_test_suite.c             | 1064 +++-----
 test/testsuites/image/image_test_suite.c           |  914 +++----
 .../face_recognition/measure_face_recognition.cpp  |   26 +-
 .../face_recognition/test_face_recognition.cpp     |   94 +-
 .../inference/inference_test_suite.c               | 1122 +++------
 .../inference/test_face_detection.cpp              |   47 +-
 .../inference/test_face_landmark_detection.cpp     |   64 +-
 .../inference/test_image_classification.cpp        |  228 +-
 .../inference/test_inference_helper.cpp            |   47 +-
 .../inference/test_object_detection.cpp            |   79 +-
 .../inference/test_pose_landmark_detection.cpp     |   52 +-
 .../surveillance/surveillance_test_suite.c         |  499 ++--
 test/testsuites/tracker/test_tracker.cpp           |    7 +-
 237 files changed, 10707 insertions(+), 14148 deletions(-)
 mode change 100755 => 100644 mv_machine_learning/inference/include/ObjectDecoder.h
 mode change 100755 => 100644 mv_machine_learning/inference/src/Inference.cpp
 mode change 100755 => 100644 mv_machine_learning/inference/src/ObjectDecoder.cpp
 mode change 100755 => 100644 mv_machine_learning/inference/src/OutputMetadata.cpp
 mode change 100755 => 100644 mv_machine_learning/inference/src/PostProcess.cpp

diff --git a/.clang-format b/.clang-format
index 3409848..aa20f06 100644
--- a/.clang-format
+++ b/.clang-format
@@ -46,14 +46,14 @@ BraceWrapping:
   AfterClass:      true
   AfterNamespace:  true
   AfterObjCDeclaration: true
-  AfterExternBlock: true
+  AfterExternBlock: false # mediavision want false
   IndentBraces:    false
   SplitEmptyFunction: false
   SplitEmptyRecord: false
   SplitEmptyNamespace: false
 
 # from pptx
-ColumnLimit:     80
+ColumnLimit:     120 # mediavision want 120
 
 # M11
 SpaceAfterCStyleCast: true
@@ -87,7 +87,7 @@ ConstructorInitializerIndentWidth: 8
 ContinuationIndentWidth: 8
 Cpp11BracedListStyle: false
 KeepEmptyLinesAtTheStartOfBlocks: false
-NamespaceIndentation: Inner
+NamespaceIndentation: None # mediavision want None
 PenaltyBreakAssignment: 10
 PenaltyBreakBeforeFirstCallParameter: 30
 PenaltyBreakComment: 10
@@ -96,7 +96,6 @@ PenaltyBreakString: 10
 PenaltyExcessCharacter: 100
 SpacesInAngles:  false
 SpacesInContainerLiterals: false
-NamespaceIndentation: None
 
 ForEachMacros:
   - 'apei_estatus_for_each_section'
diff --git a/doc/mediavision_doc.h b/doc/mediavision_doc.h
index 2fa14a9..bf43202 100644
--- a/doc/mediavision_doc.h
+++ b/doc/mediavision_doc.h
@@ -500,4 +500,4 @@
  * and it sets newly generated coordinates to result parameter.
  */
 
-#endif  /* __TIZEN_MEDIAVISION_DOC_H__ */
+#endif /* __TIZEN_MEDIAVISION_DOC_H__ */
diff --git a/include/mv_barcode_detect.h b/include/mv_barcode_detect.h
index c0e7ca7..caed05d 100644
--- a/include/mv_barcode_detect.h
+++ b/include/mv_barcode_detect.h
@@ -41,7 +41,7 @@ extern "C" {
  *
  * @see mv_barcode_detect_attr_target_e
  */
-#define MV_BARCODE_DETECT_ATTR_TARGET "MV_BARCODE_DETECT_ATTR_TARGET"  /**< Target: 0-all, 1-1D, 2-2D*/
+#define MV_BARCODE_DETECT_ATTR_TARGET "MV_BARCODE_DETECT_ATTR_TARGET" /**< Target: 0-all, 1-1D, 2-2D*/
 
 /**
  * @brief Use #MV_BARCODE_DETECT_ATTR_ROTATION_DEGREES
@@ -94,10 +94,11 @@ extern "C" {
  *
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  */
-typedef enum {
-	MV_BARCODE_DETECT_ATTR_TARGET_ALL,          /**< 1D and 2D */
-	MV_BARCODE_DETECT_ATTR_TARGET_1D_BARCODE,   /**< 1D barcode only */
-	MV_BARCODE_DETECT_ATTR_TARGET_2D_BARCODE,   /**< 2D barcode only */
+typedef enum
+{
+	MV_BARCODE_DETECT_ATTR_TARGET_ALL, /**< 1D and 2D */
+	MV_BARCODE_DETECT_ATTR_TARGET_1D_BARCODE, /**< 1D barcode only */
+	MV_BARCODE_DETECT_ATTR_TARGET_2D_BARCODE, /**< 2D barcode only */
 } mv_barcode_detect_attr_target_e;
 
 /**
@@ -111,13 +112,13 @@ typedef enum {
  * @see #MV_BARCODE_DETECT_ATTR_ROTATION_DIRECTION
  * @see #MV_BARCODE_DETECT_ATTR_ROTATION_COUNT
  */
-typedef enum {
-	MV_BARCODE_DETECT_ATTR_ROTATION_CLOCKWISE,           /**< Clockwise */
-	MV_BARCODE_DETECT_ATTR_ROTATION_COUNTER_CLOCKWISE,   /**< Counter clockwise */
-	MV_BARCODE_DETECT_ATTR_ROTATION_ALL,   /**< Clockwise and counter clockwise */
+typedef enum
+{
+	MV_BARCODE_DETECT_ATTR_ROTATION_CLOCKWISE, /**< Clockwise */
+	MV_BARCODE_DETECT_ATTR_ROTATION_COUNTER_CLOCKWISE, /**< Counter clockwise */
+	MV_BARCODE_DETECT_ATTR_ROTATION_ALL, /**< Clockwise and counter clockwise */
 } mv_barcode_detect_attr_rotation_direction_e;
 
-
 /**
  * @brief Called when barcode detection is completed.
  * @details If no barcode is detected then the method will be called, barcodes
@@ -137,14 +138,9 @@ typedef enum {
  *
  * @see mv_barcode_detect()
  */
-typedef void (*mv_barcode_detected_cb)(
-	mv_source_h source,
-	mv_engine_config_h engine_cfg,
-	const mv_quadrangle_s *barcode_locations,
-	const char* messages[],
-	const mv_barcode_type_e *types,
-	int number_of_barcodes,
-	void *user_data);
+typedef void (*mv_barcode_detected_cb)(mv_source_h source, mv_engine_config_h engine_cfg,
+									   const mv_quadrangle_s *barcode_locations, const char *messages[],
+									   const mv_barcode_type_e *types, int number_of_barcodes, void *user_data);
 
 /**
  * @brief Detects barcode(s) on source and reads message from it.
@@ -171,12 +167,8 @@ typedef void (*mv_barcode_detected_cb)(
  *
  * @see mv_barcode_detected_cb()
  */
-int mv_barcode_detect(
-	mv_source_h source,
-	mv_engine_config_h engine_cfg,
-	mv_rectangle_s roi,
-	mv_barcode_detected_cb detect_cb,
-	void *user_data);
+int mv_barcode_detect(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s roi,
+					  mv_barcode_detected_cb detect_cb, void *user_data);
 
 /**
  * @}
diff --git a/include/mv_barcode_generate.h b/include/mv_barcode_generate.h
index aaaa2b4..0654fdc 100644
--- a/include/mv_barcode_generate.h
+++ b/include/mv_barcode_generate.h
@@ -43,7 +43,8 @@ extern "C" {
  *
  * @see mv_barcode_generate_attr_text_e
  */
-#define MV_BARCODE_GENERATE_ATTR_TEXT "MV_BARCODE_GENERATE_ATTR_TEXT" /**< Text:
+#define MV_BARCODE_GENERATE_ATTR_TEXT \
+	"MV_BARCODE_GENERATE_ATTR_TEXT" /**< Text:
 								0-invisible,
 								1-visible */
 
@@ -70,12 +71,12 @@ extern "C" {
  *
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  */
-typedef enum {
-	MV_BARCODE_GENERATE_ATTR_TEXT_INVISIBLE,   /**< Invisible */
-	MV_BARCODE_GENERATE_ATTR_TEXT_VISIBLE,     /**< Visible */
+typedef enum
+{
+	MV_BARCODE_GENERATE_ATTR_TEXT_INVISIBLE, /**< Invisible */
+	MV_BARCODE_GENERATE_ATTR_TEXT_VISIBLE, /**< Visible */
 } mv_barcode_generate_attr_text_e;
 
-
 /**
  * @brief Generates #mv_source_h with barcode image.
  * @details Pay attention that for EAN-8 and EAN-13 barcode types the barcode
@@ -116,14 +117,9 @@ typedef enum {
  *
  * @see mv_barcode_generate_image()
  */
-int mv_barcode_generate_source(
-	mv_engine_config_h engine_cfg,
-	const char *message,
-	mv_barcode_type_e type,
-	mv_barcode_qr_mode_e qr_enc_mode,
-	mv_barcode_qr_ecc_e qr_ecc,
-	int qr_version,
-	mv_source_h image);
+int mv_barcode_generate_source(mv_engine_config_h engine_cfg, const char *message, mv_barcode_type_e type,
+							   mv_barcode_qr_mode_e qr_enc_mode, mv_barcode_qr_ecc_e qr_ecc, int qr_version,
+							   mv_source_h image);
 
 /**
  * @brief Generates image file with barcode.
@@ -173,17 +169,9 @@ int mv_barcode_generate_source(
  *
  * @see mv_barcode_generate_source()
  */
-int mv_barcode_generate_image(
-	mv_engine_config_h engine_cfg,
-	const char *message,
-	int image_width,
-	int image_height,
-	mv_barcode_type_e type,
-	mv_barcode_qr_mode_e qr_enc_mode,
-	mv_barcode_qr_ecc_e qr_ecc,
-	int qr_version,
-	const char *image_path,
-	mv_barcode_image_format_e image_format);
+int mv_barcode_generate_image(mv_engine_config_h engine_cfg, const char *message, int image_width, int image_height,
+							  mv_barcode_type_e type, mv_barcode_qr_mode_e qr_enc_mode, mv_barcode_qr_ecc_e qr_ecc,
+							  int qr_version, const char *image_path, mv_barcode_image_format_e image_format);
 
 /**
  * @}
diff --git a/include/mv_barcode_type.h b/include/mv_barcode_type.h
index 89080b2..1f033a2 100644
--- a/include/mv_barcode_type.h
+++ b/include/mv_barcode_type.h
@@ -38,23 +38,24 @@ extern "C" {
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  * @remarks #MV_BARCODE_UNDEFINED is deprecated. Use #MV_BARCODE_UNKNOWN instead
  */
-typedef enum {
-	MV_BARCODE_QR,          /**< 2D barcode - Quick Response code */
-	MV_BARCODE_UPC_A,       /**< 1D barcode - Universal Product Code with 12-digit */
-	MV_BARCODE_UPC_E,       /**< 1D barcode - Universal Product Code with 6-digit */
-	MV_BARCODE_EAN_8,       /**< 1D barcode - International Article Number with 8-digit */
-	MV_BARCODE_EAN_13,      /**< 1D barcode - International Article Number with 13-digit */
-	MV_BARCODE_CODE128,     /**< 1D barcode - Code 128 */
-	MV_BARCODE_CODE39,      /**< 1D barcode - Code 39 */
-	MV_BARCODE_I2_5,        /**< 1D barcode - Interleaved Two of Five */
-	MV_BARCODE_UNDEFINED,   /**< @deprecated Undefined (Deprecated since 6.0) */
-	MV_BARCODE_EAN_2,       /**< 1D barcode - International Article Number with 2-digit(add-on) (since 6.0) */
-	MV_BARCODE_EAN_5,       /**< 1D barcode - International Article Number with 5-digit(add-on) (since 6.0) */
-	MV_BARCODE_CODE93,      /**< 1D barcode - Code 93 (since 6.0)  */
-	MV_BARCODE_CODABAR,     /**< 1D barcode - CODABAR (since 6.0)  */
-	MV_BARCODE_DATABAR,     /**< 1D barcode - GS1 DATABAR (since 6.0)  */
-	MV_BARCODE_DATABAR_EXPAND,     /**< 1D barcode - GS1 DATABAR EXPAND(since 6.0)  */
-	MV_BARCODE_UNKNOWN  = 100   /**< Unknown (since 6.0) */
+typedef enum
+{
+	MV_BARCODE_QR, /**< 2D barcode - Quick Response code */
+	MV_BARCODE_UPC_A, /**< 1D barcode - Universal Product Code with 12-digit */
+	MV_BARCODE_UPC_E, /**< 1D barcode - Universal Product Code with 6-digit */
+	MV_BARCODE_EAN_8, /**< 1D barcode - International Article Number with 8-digit */
+	MV_BARCODE_EAN_13, /**< 1D barcode - International Article Number with 13-digit */
+	MV_BARCODE_CODE128, /**< 1D barcode - Code 128 */
+	MV_BARCODE_CODE39, /**< 1D barcode - Code 39 */
+	MV_BARCODE_I2_5, /**< 1D barcode - Interleaved Two of Five */
+	MV_BARCODE_UNDEFINED, /**< @deprecated Undefined (Deprecated since 6.0) */
+	MV_BARCODE_EAN_2, /**< 1D barcode - International Article Number with 2-digit(add-on) (since 6.0) */
+	MV_BARCODE_EAN_5, /**< 1D barcode - International Article Number with 5-digit(add-on) (since 6.0) */
+	MV_BARCODE_CODE93, /**< 1D barcode - Code 93 (since 6.0)  */
+	MV_BARCODE_CODABAR, /**< 1D barcode - CODABAR (since 6.0)  */
+	MV_BARCODE_DATABAR, /**< 1D barcode - GS1 DATABAR (since 6.0)  */
+	MV_BARCODE_DATABAR_EXPAND, /**< 1D barcode - GS1 DATABAR EXPAND(since 6.0)  */
+	MV_BARCODE_UNKNOWN = 100 /**< Unknown (since 6.0) */
 } mv_barcode_type_e;
 
 /**
@@ -63,12 +64,13 @@ typedef enum {
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  * @remarks This is unavailable for 1D barcodes
  */
-typedef enum {
-	MV_BARCODE_QR_ECC_LOW,           /**< Recovery up to  7% losses */
-	MV_BARCODE_QR_ECC_MEDIUM,        /**< Recovery up to 15% losses */
-	MV_BARCODE_QR_ECC_QUARTILE,      /**< Recovery up to 25% losses */
-	MV_BARCODE_QR_ECC_HIGH,          /**< Recovery up to 30% losses */
-	MV_BARCODE_QR_ECC_UNAVAILABLE    /**< Unavailable  */
+typedef enum
+{
+	MV_BARCODE_QR_ECC_LOW, /**< Recovery up to  7% losses */
+	MV_BARCODE_QR_ECC_MEDIUM, /**< Recovery up to 15% losses */
+	MV_BARCODE_QR_ECC_QUARTILE, /**< Recovery up to 25% losses */
+	MV_BARCODE_QR_ECC_HIGH, /**< Recovery up to 30% losses */
+	MV_BARCODE_QR_ECC_UNAVAILABLE /**< Unavailable  */
 } mv_barcode_qr_ecc_e;
 
 /**
@@ -77,12 +79,13 @@ typedef enum {
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  * @remarks This is unavailable for 1D barcodes
  */
-typedef enum {
-	MV_BARCODE_QR_MODE_NUMERIC,         /**< Numeric digits */
-	MV_BARCODE_QR_MODE_ALPHANUMERIC,    /**< Alphanumeric characters */
-	MV_BARCODE_QR_MODE_BYTE,            /**< Raw 8-bit bytes */
-	MV_BARCODE_QR_MODE_UTF8,            /**< UTF-8 character encoding */
-	MV_BARCODE_QR_MODE_UNAVAILABLE      /**< Unavailable */
+typedef enum
+{
+	MV_BARCODE_QR_MODE_NUMERIC, /**< Numeric digits */
+	MV_BARCODE_QR_MODE_ALPHANUMERIC, /**< Alphanumeric characters */
+	MV_BARCODE_QR_MODE_BYTE, /**< Raw 8-bit bytes */
+	MV_BARCODE_QR_MODE_UTF8, /**< UTF-8 character encoding */
+	MV_BARCODE_QR_MODE_UNAVAILABLE /**< Unavailable */
 } mv_barcode_qr_mode_e;
 
 /**
@@ -90,12 +93,13 @@ typedef enum {
  *
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  */
-typedef enum {
+typedef enum
+{
 	MV_BARCODE_IMAGE_FORMAT_UNAVAILABLE = -1, /**< Unavailable image format */
-	MV_BARCODE_IMAGE_FORMAT_BMP,    /**< BMP image format */
-	MV_BARCODE_IMAGE_FORMAT_JPG,    /**< JPEG image format */
-	MV_BARCODE_IMAGE_FORMAT_PNG,    /**< PNG image format */
-	MV_BARCODE_IMAGE_FORMAT_NUM,    /**< The number of supported image format */
+	MV_BARCODE_IMAGE_FORMAT_BMP, /**< BMP image format */
+	MV_BARCODE_IMAGE_FORMAT_JPG, /**< JPEG image format */
+	MV_BARCODE_IMAGE_FORMAT_PNG, /**< PNG image format */
+	MV_BARCODE_IMAGE_FORMAT_NUM, /**< The number of supported image format */
 } mv_barcode_image_format_e;
 
 /**
diff --git a/include/mv_common.h b/include/mv_common.h
index b678894..fe06802 100644
--- a/include/mv_common.h
+++ b/include/mv_common.h
@@ -38,7 +38,8 @@ extern "C" {
  *
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  */
-typedef struct {
+typedef struct
+{
 	int x; /**< X-axis coordinate of the point in 2D space */
 	int y; /**< Y-axis coordinate of the point in 2D space */
 } mv_point_s;
@@ -48,8 +49,9 @@ typedef struct {
  *
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  */
-typedef struct {
-	mv_point_s points[4];    /**< Four points that define object bounding
+typedef struct
+{
+	mv_point_s points[4]; /**< Four points that define object bounding
 								quadrangle */
 } mv_quadrangle_s;
 
@@ -59,10 +61,11 @@ typedef struct {
  *
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  */
-typedef struct {
-	mv_point_s point;     /**< Top left corner of rectangle coordinates */
-	int width;            /**< Width of the bounding rectangle */
-	int height;           /**< Height of the bounding rectangle */
+typedef struct
+{
+	mv_point_s point; /**< Top left corner of rectangle coordinates */
+	int width; /**< Width of the bounding rectangle */
+	int height; /**< Height of the bounding rectangle */
 } mv_rectangle_s;
 
 /**
@@ -70,35 +73,22 @@ typedef struct {
  *
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  */
-typedef enum {
-	MEDIA_VISION_ERROR_NONE
-			= TIZEN_ERROR_NONE,                /**< Successful */
-	MEDIA_VISION_ERROR_NOT_SUPPORTED
-			= TIZEN_ERROR_NOT_SUPPORTED,       /**< Not supported */
-	MEDIA_VISION_ERROR_MSG_TOO_LONG
-			= TIZEN_ERROR_MSG_TOO_LONG,        /**< Message too long */
-	MEDIA_VISION_ERROR_NO_DATA
-			= TIZEN_ERROR_NO_DATA,             /**< No data */
-	MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE
-			= TIZEN_ERROR_KEY_NOT_AVAILABLE,   /**< Key not available */
-	MEDIA_VISION_ERROR_OUT_OF_MEMORY
-			= TIZEN_ERROR_OUT_OF_MEMORY,       /**< Out of memory */
-	MEDIA_VISION_ERROR_INVALID_PARAMETER
-			= TIZEN_ERROR_INVALID_PARAMETER,   /**< Invalid parameter */
-	MEDIA_VISION_ERROR_INVALID_OPERATION
-			= TIZEN_ERROR_INVALID_OPERATION,   /**< Invalid operation */
-	MEDIA_VISION_ERROR_PERMISSION_DENIED
-			= TIZEN_ERROR_NOT_PERMITTED,       /**< Not permitted */
-	MEDIA_VISION_ERROR_NOT_SUPPORTED_FORMAT
-			= TIZEN_ERROR_MEDIA_VISION | 0x01, /**< Not supported format */
-	MEDIA_VISION_ERROR_INTERNAL
-			= TIZEN_ERROR_MEDIA_VISION | 0x02, /**< Internal error */
-	MEDIA_VISION_ERROR_INVALID_DATA
-			= TIZEN_ERROR_MEDIA_VISION | 0x03, /**< Invalid data */
-	MEDIA_VISION_ERROR_INVALID_PATH
-			= TIZEN_ERROR_MEDIA_VISION | 0x04, /**< Invalid path (Since 3.0) */
-	MEDIA_VISION_ERROR_NOT_SUPPORTED_ENGINE
-			= TIZEN_ERROR_MEDIA_VISION | 0x05  /**< Not supported engine (Since 5.5.) */
+typedef enum
+{
+	MEDIA_VISION_ERROR_NONE = TIZEN_ERROR_NONE, /**< Successful */
+	MEDIA_VISION_ERROR_NOT_SUPPORTED = TIZEN_ERROR_NOT_SUPPORTED, /**< Not supported */
+	MEDIA_VISION_ERROR_MSG_TOO_LONG = TIZEN_ERROR_MSG_TOO_LONG, /**< Message too long */
+	MEDIA_VISION_ERROR_NO_DATA = TIZEN_ERROR_NO_DATA, /**< No data */
+	MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE = TIZEN_ERROR_KEY_NOT_AVAILABLE, /**< Key not available */
+	MEDIA_VISION_ERROR_OUT_OF_MEMORY = TIZEN_ERROR_OUT_OF_MEMORY, /**< Out of memory */
+	MEDIA_VISION_ERROR_INVALID_PARAMETER = TIZEN_ERROR_INVALID_PARAMETER, /**< Invalid parameter */
+	MEDIA_VISION_ERROR_INVALID_OPERATION = TIZEN_ERROR_INVALID_OPERATION, /**< Invalid operation */
+	MEDIA_VISION_ERROR_PERMISSION_DENIED = TIZEN_ERROR_NOT_PERMITTED, /**< Not permitted */
+	MEDIA_VISION_ERROR_NOT_SUPPORTED_FORMAT = TIZEN_ERROR_MEDIA_VISION | 0x01, /**< Not supported format */
+	MEDIA_VISION_ERROR_INTERNAL = TIZEN_ERROR_MEDIA_VISION | 0x02, /**< Internal error */
+	MEDIA_VISION_ERROR_INVALID_DATA = TIZEN_ERROR_MEDIA_VISION | 0x03, /**< Invalid data */
+	MEDIA_VISION_ERROR_INVALID_PATH = TIZEN_ERROR_MEDIA_VISION | 0x04, /**< Invalid path (Since 3.0) */
+	MEDIA_VISION_ERROR_NOT_SUPPORTED_ENGINE = TIZEN_ERROR_MEDIA_VISION | 0x05 /**< Not supported engine (Since 5.5.) */
 } mv_error_e;
 
 /**
@@ -107,11 +97,12 @@ typedef enum {
  *
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  */
-typedef enum {
-	MV_ENGINE_CONFIG_ATTR_TYPE_DOUBLE,     /**< Double attribute type */
-	MV_ENGINE_CONFIG_ATTR_TYPE_INTEGER,    /**< Integer attribute type */
-	MV_ENGINE_CONFIG_ATTR_TYPE_BOOLEAN,    /**< Boolean attribute type */
-	MV_ENGINE_CONFIG_ATTR_TYPE_STRING,      /**< String attribute type */
+typedef enum
+{
+	MV_ENGINE_CONFIG_ATTR_TYPE_DOUBLE, /**< Double attribute type */
+	MV_ENGINE_CONFIG_ATTR_TYPE_INTEGER, /**< Integer attribute type */
+	MV_ENGINE_CONFIG_ATTR_TYPE_BOOLEAN, /**< Boolean attribute type */
+	MV_ENGINE_CONFIG_ATTR_TYPE_STRING, /**< String attribute type */
 	MV_ENGINE_CONFIG_ATTR_TYPE_ARRAY_STRING /**< Array of string attribute type (Since 5.5) */
 } mv_config_attribute_type_e;
 
@@ -120,19 +111,20 @@ typedef enum {
  *
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  */
-typedef enum {
+typedef enum
+{
 	MEDIA_VISION_COLORSPACE_INVALID, /**< The colorspace type is invalid */
-	MEDIA_VISION_COLORSPACE_Y800,    /**< The colorspace type is Y800 */
-	MEDIA_VISION_COLORSPACE_I420,    /**< The colorspace type is I420 */
-	MEDIA_VISION_COLORSPACE_NV12,    /**< The colorspace type is NV12 */
-	MEDIA_VISION_COLORSPACE_YV12,    /**< The colorspace type is YV12 */
-	MEDIA_VISION_COLORSPACE_NV21,    /**< The colorspace type is NV21 */
-	MEDIA_VISION_COLORSPACE_YUYV,    /**< The colorspace type is YUYV */
-	MEDIA_VISION_COLORSPACE_UYVY,    /**< The colorspace type is UYVY */
-	MEDIA_VISION_COLORSPACE_422P,    /**< The colorspace type is 422P */
-	MEDIA_VISION_COLORSPACE_RGB565,  /**< The colorspace type is RGB565 */
-	MEDIA_VISION_COLORSPACE_RGB888,  /**< The colorspace type is RGB888 */
-	MEDIA_VISION_COLORSPACE_RGBA,    /**< The colorspace type is RGBA */
+	MEDIA_VISION_COLORSPACE_Y800, /**< The colorspace type is Y800 */
+	MEDIA_VISION_COLORSPACE_I420, /**< The colorspace type is I420 */
+	MEDIA_VISION_COLORSPACE_NV12, /**< The colorspace type is NV12 */
+	MEDIA_VISION_COLORSPACE_YV12, /**< The colorspace type is YV12 */
+	MEDIA_VISION_COLORSPACE_NV21, /**< The colorspace type is NV21 */
+	MEDIA_VISION_COLORSPACE_YUYV, /**< The colorspace type is YUYV */
+	MEDIA_VISION_COLORSPACE_UYVY, /**< The colorspace type is UYVY */
+	MEDIA_VISION_COLORSPACE_422P, /**< The colorspace type is 422P */
+	MEDIA_VISION_COLORSPACE_RGB565, /**< The colorspace type is RGB565 */
+	MEDIA_VISION_COLORSPACE_RGB888, /**< The colorspace type is RGB888 */
+	MEDIA_VISION_COLORSPACE_RGBA, /**< The colorspace type is RGBA */
 } mv_colorspace_e;
 
 /**
@@ -175,8 +167,7 @@ typedef void *mv_source_h;
  *
  * @see mv_destroy_source()
  */
-int mv_create_source(
-		mv_source_h *source);
+int mv_create_source(mv_source_h *source);
 
 /**
  * @brief Destroys the source handle and releases all its resources.
@@ -190,8 +181,7 @@ int mv_create_source(
  *
  * @see mv_create_source()
  */
-int mv_destroy_source(
-		mv_source_h source);
+int mv_destroy_source(mv_source_h source);
 
 /**
  * @brief Fills the media source based on the media packet.
@@ -213,9 +203,7 @@ int mv_destroy_source(
  * @see mv_create_source()
  * @see mv_destroy_source()
  */
-int mv_source_fill_by_media_packet(
-		mv_source_h source,
-		media_packet_h media_packet);
+int mv_source_fill_by_media_packet(mv_source_h source, media_packet_h media_packet);
 
 /**
  * @brief Fills the media source based on the buffer and metadata.
@@ -237,13 +225,8 @@ int mv_source_fill_by_media_packet(
  *
  * @see mv_source_clear()
  */
-int mv_source_fill_by_buffer(
-		mv_source_h source,
-		unsigned char *data_buffer,
-		unsigned int buffer_size,
-		unsigned int image_width,
-		unsigned int image_height,
-		mv_colorspace_e image_colorspace);
+int mv_source_fill_by_buffer(mv_source_h source, unsigned char *data_buffer, unsigned int buffer_size,
+							 unsigned int image_width, unsigned int image_height, mv_colorspace_e image_colorspace);
 
 /**
  * @brief Clears the buffer of the media source.
@@ -257,8 +240,7 @@ int mv_source_fill_by_buffer(
  *
  * @see mv_source_fill_by_buffer()
  */
-int mv_source_clear(
-		mv_source_h source);
+int mv_source_clear(mv_source_h source);
 
 /**
  * @brief Gets buffer of the media source.
@@ -280,10 +262,7 @@ int mv_source_clear(
  * @see mv_source_get_height()
  * @see mv_source_get_colorspace()
  */
-int mv_source_get_buffer(
-		mv_source_h source,
-		unsigned char **data_buffer,
-		unsigned int *buffer_size);
+int mv_source_get_buffer(mv_source_h source, unsigned char **data_buffer, unsigned int *buffer_size);
 
 /**
  * @brief Gets height of the media source.
@@ -300,9 +279,7 @@ int mv_source_get_buffer(
  * @see mv_source_get_colorspace()
  * @see mv_source_get_buffer()
  */
-int mv_source_get_height(
-		mv_source_h source,
-		unsigned int *image_height);
+int mv_source_get_height(mv_source_h source, unsigned int *image_height);
 
 /**
  * @brief Gets width of the media source.
@@ -319,9 +296,7 @@ int mv_source_get_height(
  * @see mv_source_get_colorspace()
  * @see mv_source_get_buffer()
  */
-int mv_source_get_width(
-		mv_source_h source,
-		unsigned int *image_width);
+int mv_source_get_width(mv_source_h source, unsigned int *image_width);
 
 /**
  * @brief Gets colorspace of the media source.
@@ -338,9 +313,7 @@ int mv_source_get_width(
  * @see mv_source_get_height()
  * @see mv_source_get_buffer()
  */
-int mv_source_get_colorspace(
-		mv_source_h source,
-		mv_colorspace_e *image_colorspace);
+int mv_source_get_colorspace(mv_source_h source, mv_colorspace_e *image_colorspace);
 
 /**
  * @brief Creates the handle to the configuration of engine.
@@ -369,8 +342,7 @@ int mv_source_get_colorspace(
  * @see mv_engine_config_get_bool_attribute()
  * @see mv_engine_config_get_string_attribute()
  */
-int mv_create_engine_config(
-		mv_engine_config_h *engine_cfg);
+int mv_create_engine_config(mv_engine_config_h *engine_cfg);
 
 /**
  * @brief Destroys the engine configuration handle and releases all its
@@ -387,8 +359,7 @@ int mv_create_engine_config(
  * @see #mv_engine_config_h
  * @see mv_create_engine_config()
  */
-int mv_destroy_engine_config(
-		mv_engine_config_h engine_cfg);
+int mv_destroy_engine_config(mv_engine_config_h engine_cfg);
 
 /**
  * @brief Sets the double attribute to the configuration.
@@ -411,10 +382,7 @@ int mv_destroy_engine_config(
  * @see mv_engine_config_set_bool_attribute()
  * @see mv_engine_config_set_string_attribute()
  */
-int mv_engine_config_set_double_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		double value);
+int mv_engine_config_set_double_attribute(mv_engine_config_h engine_cfg, const char *name, double value);
 
 /**
  * @brief Sets the integer attribute to the configuration.
@@ -439,10 +407,7 @@ int mv_engine_config_set_double_attribute(
  * @see mv_barcode_detect_attr_target_e
  * @see mv_barcode_generate_attr_text_e
  */
-int mv_engine_config_set_int_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		int value);
+int mv_engine_config_set_int_attribute(mv_engine_config_h engine_cfg, const char *name, int value);
 
 /**
  * @brief Sets the boolean attribute to the configuration.
@@ -465,10 +430,7 @@ int mv_engine_config_set_int_attribute(
  * @see mv_engine_config_set_int_attribute()
  * @see mv_engine_config_set_string_attribute()
  */
-int mv_engine_config_set_bool_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		bool value);
+int mv_engine_config_set_bool_attribute(mv_engine_config_h engine_cfg, const char *name, bool value);
 
 /**
  * @brief Sets the string attribute to the configuration.
@@ -491,10 +453,7 @@ int mv_engine_config_set_bool_attribute(
  * @see mv_engine_config_set_int_attribute()
  * @see mv_engine_config_set_bool_attribute()
  */
-int mv_engine_config_set_string_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		const char *value);
+int mv_engine_config_set_string_attribute(mv_engine_config_h engine_cfg, const char *name, const char *value);
 
 /**
  * @brief Sets the array of string attribute to the configuration.
@@ -515,11 +474,8 @@ int mv_engine_config_set_string_attribute(
  *
  * @see mv_engine_config_get_array_string_attribute()
  */
-int mv_engine_config_set_array_string_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		const char **values,
-		unsigned int size);
+int mv_engine_config_set_array_string_attribute(mv_engine_config_h engine_cfg, const char *name, const char **values,
+												unsigned int size);
 
 /**
  * @brief Gets the double attribute from the configuration dictionary.
@@ -543,10 +499,7 @@ int mv_engine_config_set_array_string_attribute(
  * @see mv_engine_config_get_bool_attribute()
  * @see mv_engine_config_get_string_attribute()
  */
-int mv_engine_config_get_double_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		double *value);
+int mv_engine_config_get_double_attribute(mv_engine_config_h engine_cfg, const char *name, double *value);
 
 /**
  * @brief Gets the integer attribute from the configuration dictionary.
@@ -572,10 +525,7 @@ int mv_engine_config_get_double_attribute(
  * @see mv_barcode_detect_attr_target_e
  * @see mv_barcode_generate_attr_text_e
  */
-int mv_engine_config_get_int_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		int *value);
+int mv_engine_config_get_int_attribute(mv_engine_config_h engine_cfg, const char *name, int *value);
 
 /**
  * @brief Gets the boolean attribute from the configuration dictionary.
@@ -599,10 +549,7 @@ int mv_engine_config_get_int_attribute(
  * @see mv_engine_config_get_int_attribute()
  * @see mv_engine_config_get_string_attribute()
  */
-int mv_engine_config_get_bool_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		bool *value);
+int mv_engine_config_get_bool_attribute(mv_engine_config_h engine_cfg, const char *name, bool *value);
 
 /**
  * @brief Gets the string attribute from the configuration dictionary.
@@ -628,10 +575,7 @@ int mv_engine_config_get_bool_attribute(
  * @see mv_engine_config_get_int_attribute()
  * @see mv_engine_config_get_bool_attribute()
  */
-int mv_engine_config_get_string_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		char **value);
+int mv_engine_config_get_string_attribute(mv_engine_config_h engine_cfg, const char *name, char **value);
 
 /**
  * @brief Gets the array of string attribute from the configuration dictionary.
@@ -655,11 +599,8 @@ int mv_engine_config_get_string_attribute(
  *
  * @see mv_engine_config_set_array_string_attribute()
  */
-int mv_engine_config_get_array_string_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		char ***values,
-		int *size);
+int mv_engine_config_get_array_string_attribute(mv_engine_config_h engine_cfg, const char *name, char ***values,
+												int *size);
 
 /**
  * @brief Called to get information (type and name) once for each supported
@@ -677,10 +618,8 @@ int mv_engine_config_get_array_string_attribute(
  * @pre mv_engine_config_foreach_supported_attribute() will invoke this callback
  * @see mv_engine_config_foreach_supported_attribute()
  */
-typedef bool (*mv_supported_attribute_cb)(
-		mv_config_attribute_type_e attribute_type,
-		const char *attribute_name,
-		void *user_data);
+typedef bool (*mv_supported_attribute_cb)(mv_config_attribute_type_e attribute_type, const char *attribute_name,
+										  void *user_data);
 
 /**
  * @brief Traverses the list of supported attribute names and types.
@@ -719,9 +658,7 @@ typedef bool (*mv_supported_attribute_cb)(
  * @see mv_engine_config_get_bool_attribute()
  * @see mv_engine_config_get_string_attribute()
  */
-int mv_engine_config_foreach_supported_attribute(
-		mv_supported_attribute_cb callback,
-		void *user_data);
+int mv_engine_config_foreach_supported_attribute(mv_supported_attribute_cb callback, void *user_data);
 
 /**
  * @}
diff --git a/include/mv_face.h b/include/mv_face.h
index e3c90f6..bcb58fe 100644
--- a/include/mv_face.h
+++ b/include/mv_face.h
@@ -163,12 +163,8 @@ extern "C" {
  *
  * @see mv_face_detect()
  */
-typedef void (*mv_face_detected_cb)(
-	mv_source_h source,
-	mv_engine_config_h engine_cfg,
-	mv_rectangle_s *faces_locations,
-	int number_of_faces,
-	void *user_data);
+typedef void (*mv_face_detected_cb)(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s *faces_locations,
+									int number_of_faces, void *user_data);
 
 /**
  * @brief Performs face detection on the @a source for the @a engine_cfg.
@@ -202,12 +198,7 @@ typedef void (*mv_face_detected_cb)(
  *
  * @see mv_face_detected_cb()
  */
-int mv_face_detect(
-	mv_source_h source,
-	mv_engine_config_h engine_cfg,
-	mv_face_detected_cb detected_cb,
-	void *user_data);
-
+int mv_face_detect(mv_source_h source, mv_engine_config_h engine_cfg, mv_face_detected_cb detected_cb, void *user_data);
 
 /********************/
 /* Face recognition */
@@ -249,14 +240,9 @@ int mv_face_detect(
  *
  * @see mv_face_recognize()
  */
-typedef void (*mv_face_recognized_cb)(
-	mv_source_h source,
-	mv_face_recognition_model_h recognition_model,
-	mv_engine_config_h engine_cfg,
-	mv_rectangle_s *face_location,
-	const int *face_label,
-	double confidence,
-	void *user_data);
+typedef void (*mv_face_recognized_cb)(mv_source_h source, mv_face_recognition_model_h recognition_model,
+									  mv_engine_config_h engine_cfg, mv_rectangle_s *face_location,
+									  const int *face_label, double confidence, void *user_data);
 
 /**
  * @brief Performs face recognition on the @a source image.
@@ -308,14 +294,8 @@ typedef void (*mv_face_recognized_cb)(
  *
  * @see mv_face_recognized_cb()
  */
-int mv_face_recognize(
-	mv_source_h source,
-	mv_face_recognition_model_h recognition_model,
-	mv_engine_config_h engine_cfg,
-	mv_rectangle_s *face_location,
-	mv_face_recognized_cb recognized_cb,
-	void *user_data);
-
+int mv_face_recognize(mv_source_h source, mv_face_recognition_model_h recognition_model, mv_engine_config_h engine_cfg,
+					  mv_rectangle_s *face_location, mv_face_recognized_cb recognized_cb, void *user_data);
 
 /*****************/
 /* Face tracking */
@@ -352,13 +332,9 @@ int mv_face_recognize(
  *
  * @see mv_face_track()
  */
-typedef void (*mv_face_tracked_cb)(
-	mv_source_h source,
-	mv_face_tracking_model_h tracking_model,
-	mv_engine_config_h engine_cfg,
-	mv_quadrangle_s *location,
-	double confidence,
-	void *user_data);
+typedef void (*mv_face_tracked_cb)(mv_source_h source, mv_face_tracking_model_h tracking_model,
+								   mv_engine_config_h engine_cfg, mv_quadrangle_s *location, double confidence,
+								   void *user_data);
 
 /**
  * @brief Performs face tracking on the @a source for the @a tracking_model.
@@ -411,14 +387,8 @@ typedef void (*mv_face_tracked_cb)(
  *
  * @see mv_face_tracked_cb()
  */
-int mv_face_track(
-	mv_source_h source,
-	mv_face_tracking_model_h tracking_model,
-	mv_engine_config_h engine_cfg,
-	mv_face_tracked_cb tracked_cb,
-	bool do_learn,
-	void *user_data);
-
+int mv_face_track(mv_source_h source, mv_face_tracking_model_h tracking_model, mv_engine_config_h engine_cfg,
+				  mv_face_tracked_cb tracked_cb, bool do_learn, void *user_data);
 
 /********************************/
 /* Recognition of eye condition */
@@ -449,12 +419,9 @@ int mv_face_track(
  *
  * @see mv_face_eye_condition_recognize()
  */
-typedef void (*mv_face_eye_condition_recognized_cb)(
-	mv_source_h source,
-	mv_engine_config_h engine_cfg,
-	mv_rectangle_s face_location,
-	mv_face_eye_condition_e eye_condition,
-	void *user_data);
+typedef void (*mv_face_eye_condition_recognized_cb)(mv_source_h source, mv_engine_config_h engine_cfg,
+													mv_rectangle_s face_location, mv_face_eye_condition_e eye_condition,
+													void *user_data);
 
 /**
  * @brief Determines eye-blink condition for @a face_location on media @a source.
@@ -486,13 +453,8 @@ typedef void (*mv_face_eye_condition_recognized_cb)(
  *
  * @see mv_face_eye_condition_recognized_cb()
  */
-int mv_face_eye_condition_recognize(
-	mv_source_h source,
-	mv_engine_config_h engine_cfg,
-	mv_rectangle_s face_location,
-	mv_face_eye_condition_recognized_cb eye_condition_recognized_cb,
-	void *user_data);
-
+int mv_face_eye_condition_recognize(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s face_location,
+									mv_face_eye_condition_recognized_cb eye_condition_recognized_cb, void *user_data);
 
 /************************************/
 /* Recognition of facial expression */
@@ -521,12 +483,9 @@ int mv_face_eye_condition_recognize(
  *
  * @see mv_face_facial_expression_recognize()
  */
-typedef void (*mv_face_facial_expression_recognized_cb)(
-	mv_source_h source,
-	mv_engine_config_h engine_cfg,
-	mv_rectangle_s face_location,
-	mv_face_facial_expression_e facial_expression,
-	void *user_data);
+typedef void (*mv_face_facial_expression_recognized_cb)(mv_source_h source, mv_engine_config_h engine_cfg,
+														mv_rectangle_s face_location,
+														mv_face_facial_expression_e facial_expression, void *user_data);
 
 /**
  * @brief Determines facial expression for @a face_location on media @a source.
@@ -557,12 +516,9 @@ typedef void (*mv_face_facial_expression_recognized_cb)(
  *
  * @see mv_face_facial_expression_recognized_cb()
  */
-int mv_face_facial_expression_recognize(
-	mv_source_h source,
-	mv_engine_config_h engine_cfg,
-	mv_rectangle_s face_location,
-	mv_face_facial_expression_recognized_cb expression_recognized_cb,
-	void *user_data);
+int mv_face_facial_expression_recognize(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s face_location,
+										mv_face_facial_expression_recognized_cb expression_recognized_cb,
+										void *user_data);
 
 /*******************************/
 /* Recognition model behavior */
@@ -604,8 +560,7 @@ int mv_face_facial_expression_recognize(
  *
  * @see mv_face_recognition_model_destroy()
  */
-int mv_face_recognition_model_create(
-	mv_face_recognition_model_h *recognition_model);
+int mv_face_recognition_model_create(mv_face_recognition_model_h *recognition_model);
 
 /**
  * @brief Destroys the face recognition model handle and releases all its
@@ -623,8 +578,7 @@ int mv_face_recognition_model_create(
  *
  * @see mv_face_recognition_model_create()
  */
-int mv_face_recognition_model_destroy(
-	mv_face_recognition_model_h recognition_model);
+int mv_face_recognition_model_destroy(mv_face_recognition_model_h recognition_model);
 
 /**
  * @brief Creates a copy of existed recognition model handle and clones all its
@@ -648,9 +602,7 @@ int mv_face_recognition_model_destroy(
  *
  * @see mv_face_recognition_model_create()
  */
-int mv_face_recognition_model_clone(
-	mv_face_recognition_model_h src,
-	mv_face_recognition_model_h *dst);
+int mv_face_recognition_model_clone(mv_face_recognition_model_h src, mv_face_recognition_model_h *dst);
 
 /**
  * @brief Saves recognition model to the file.
@@ -686,9 +638,7 @@ int mv_face_recognition_model_clone(
  * @see mv_face_recognition_model_create()
  * @see app_get_data_path()
  */
-int mv_face_recognition_model_save(
-	const char *file_name,
-	mv_face_recognition_model_h recognition_model);
+int mv_face_recognition_model_save(const char *file_name, mv_face_recognition_model_h recognition_model);
 
 /**
  * @brief Loads recognition model from file.
@@ -724,9 +674,7 @@ int mv_face_recognition_model_save(
  * @see mv_face_recognition_model_destroy()
  * @see app_get_data_path()
  */
-int mv_face_recognition_model_load(
-	const char *file_name,
-	mv_face_recognition_model_h *recognition_model);
+int mv_face_recognition_model_load(const char *file_name, mv_face_recognition_model_h *recognition_model);
 
 /**
  * @brief Adds face image example to be used for face recognition model learning
@@ -768,11 +716,8 @@ int mv_face_recognition_model_load(
  * @see mv_face_recognition_model_reset()
  * @see mv_face_recognition_model_learn()
  */
-int mv_face_recognition_model_add(
-	const mv_source_h source,
-	mv_face_recognition_model_h recognition_model,
-	const mv_rectangle_s *example_location,
-	int face_label);
+int mv_face_recognition_model_add(const mv_source_h source, mv_face_recognition_model_h recognition_model,
+								  const mv_rectangle_s *example_location, int face_label);
 
 /**
  * @brief Removes from @a recognition_model all collected with
@@ -805,9 +750,7 @@ int mv_face_recognition_model_add(
  * @see mv_face_recognition_model_add()
  * @see mv_face_recognition_model_learn()
  */
-int mv_face_recognition_model_reset(
-	mv_face_recognition_model_h recognition_model,
-	int *face_label);
+int mv_face_recognition_model_reset(mv_face_recognition_model_h recognition_model, int *face_label);
 
 /**
  * @brief Learns face recognition model.
@@ -865,9 +808,7 @@ int mv_face_recognition_model_reset(
  * @see mv_face_recognition_model_reset()
  * @see mv_face_recognize()
  */
-int mv_face_recognition_model_learn(
-	mv_engine_config_h engine_cfg,
-	mv_face_recognition_model_h recognition_model);
+int mv_face_recognition_model_learn(mv_engine_config_h engine_cfg, mv_face_recognition_model_h recognition_model);
 
 /**
  * @brief Queries labels list and number of labels had been learned by the model.
@@ -895,10 +836,8 @@ int mv_face_recognition_model_learn(
  * @see mv_face_recognition_model_reset()
  * @see mv_face_recognition_model_learn()
  */
-int mv_face_recognition_model_query_labels(
-	mv_face_recognition_model_h recognition_model,
-	int **labels,
-	unsigned int *number_of_labels);
+int mv_face_recognition_model_query_labels(mv_face_recognition_model_h recognition_model, int **labels,
+										   unsigned int *number_of_labels);
 
 /***************************/
 /* Tracking model behavior */
@@ -937,8 +876,7 @@ int mv_face_recognition_model_query_labels(
  * @see mv_face_tracking_model_prepare()
  * @see mv_face_tracking_model_load()
  */
-int mv_face_tracking_model_create(
-	mv_face_tracking_model_h *tracking_model);
+int mv_face_tracking_model_create(mv_face_tracking_model_h *tracking_model);
 
 /**
  * @brief Calls this function to destroy the face tracking model handle and
@@ -956,8 +894,7 @@ int mv_face_tracking_model_create(
  *
  * @see mv_face_tracking_model_create()
  */
-int mv_face_tracking_model_destroy(
-	mv_face_tracking_model_h tracking_model);
+int mv_face_tracking_model_destroy(mv_face_tracking_model_h tracking_model);
 
 /**
  * @brief Calls this function to initialize tracking model by the location of the
@@ -1001,11 +938,8 @@ int mv_face_tracking_model_destroy(
  * @see mv_face_tracking_model_create()
  * @see mv_face_track()
  */
-int mv_face_tracking_model_prepare(
-	mv_face_tracking_model_h tracking_model,
-	mv_engine_config_h engine_cfg,
-	mv_source_h source,
-	mv_quadrangle_s *location);
+int mv_face_tracking_model_prepare(mv_face_tracking_model_h tracking_model, mv_engine_config_h engine_cfg,
+								   mv_source_h source, mv_quadrangle_s *location);
 
 /**
  * @brief Calls this function to make a copy of existed tracking model handle and
@@ -1029,9 +963,7 @@ int mv_face_tracking_model_prepare(
  *
  * @see mv_face_tracking_model_create()
  */
-int mv_face_tracking_model_clone(
-	mv_face_tracking_model_h src,
-	mv_face_tracking_model_h *dst);
+int mv_face_tracking_model_clone(mv_face_tracking_model_h src, mv_face_tracking_model_h *dst);
 
 /**
  * @brief Calls this method to save tracking model to the file.
@@ -1062,9 +994,7 @@ int mv_face_tracking_model_clone(
  * @see mv_face_tracking_model_create()
  * @see app_get_data_path()
  */
-int mv_face_tracking_model_save(
-	const char *file_name,
-	mv_face_tracking_model_h tracking_model);
+int mv_face_tracking_model_save(const char *file_name, mv_face_tracking_model_h tracking_model);
 
 /**
  * @brief Calls this method to load a tracking model from file.
@@ -1098,9 +1028,7 @@ int mv_face_tracking_model_save(
  * @see mv_face_tracking_model_destroy()
  * @see app_get_data_path()
  */
-int mv_face_tracking_model_load(
-	const char *file_name,
-	mv_face_tracking_model_h *tracking_model);
+int mv_face_tracking_model_load(const char *file_name, mv_face_tracking_model_h *tracking_model);
 
 /**
  * @}
diff --git a/include/mv_face_type.h b/include/mv_face_type.h
index f26b5f7..170bd4d 100644
--- a/include/mv_face_type.h
+++ b/include/mv_face_type.h
@@ -39,10 +39,11 @@ extern "C" {
  *
  * @see mv_face_eye_condition_recognize()
  */
-typedef enum {
-	MV_FACE_EYES_OPEN,      /**< Eyes are open */
-	MV_FACE_EYES_CLOSED,    /**< Eyes are closed */
-	MV_FACE_EYES_NOT_FOUND  /**< The eyes condition wasn't determined */
+typedef enum
+{
+	MV_FACE_EYES_OPEN, /**< Eyes are open */
+	MV_FACE_EYES_CLOSED, /**< Eyes are closed */
+	MV_FACE_EYES_NOT_FOUND /**< The eyes condition wasn't determined */
 } mv_face_eye_condition_e;
 
 /**
@@ -52,15 +53,16 @@ typedef enum {
  *
  * @see mv_face_facial_expression_recognize()
  */
-typedef enum {
-	MV_FACE_UNKNOWN,    /**< Unknown face expression */
-	MV_FACE_NEUTRAL,    /**< Face expression is neutral */
-	MV_FACE_SMILE,      /**< Face expression is smiling */
-	MV_FACE_SADNESS,    /**< Face expression is sadness */
-	MV_FACE_SURPRISE,   /**< Face expression is surprise */
-	MV_FACE_ANGER,      /**< Face expression is anger */
-	MV_FACE_FEAR,       /**< Face expression is fear */
-	MV_FACE_DISGUST,    /**< Face expression is disgust */
+typedef enum
+{
+	MV_FACE_UNKNOWN, /**< Unknown face expression */
+	MV_FACE_NEUTRAL, /**< Face expression is neutral */
+	MV_FACE_SMILE, /**< Face expression is smiling */
+	MV_FACE_SADNESS, /**< Face expression is sadness */
+	MV_FACE_SURPRISE, /**< Face expression is surprise */
+	MV_FACE_ANGER, /**< Face expression is anger */
+	MV_FACE_FEAR, /**< Face expression is fear */
+	MV_FACE_DISGUST, /**< Face expression is disgust */
 } mv_face_facial_expression_e;
 
 /**
diff --git a/include/mv_image.h b/include/mv_image.h
index 1ad1a99..0145398 100644
--- a/include/mv_image.h
+++ b/include/mv_image.h
@@ -253,13 +253,9 @@ extern "C" {
  * @see mv_engine_config_h
  * @see mv_quadrangle_s
  */
-typedef void (*mv_image_recognized_cb)(
-	mv_source_h source,
-	mv_engine_config_h engine_cfg,
-	const mv_image_object_h *image_objects,
-	mv_quadrangle_s **locations,
-	unsigned int number_of_objects,
-	void *user_data);
+typedef void (*mv_image_recognized_cb)(mv_source_h source, mv_engine_config_h engine_cfg,
+									   const mv_image_object_h *image_objects, mv_quadrangle_s **locations,
+									   unsigned int number_of_objects, void *user_data);
 
 /**
  * @brief Recognizes the given image objects on the source image.
@@ -305,13 +301,8 @@ typedef void (*mv_image_recognized_cb)(
  * @see mv_image_object_destroy()
  * @see mv_engine_config_h
  */
-int mv_image_recognize(
-	mv_source_h source,
-	const mv_image_object_h *image_objects,
-	int number_of_objects,
-	mv_engine_config_h engine_cfg,
-	mv_image_recognized_cb recognized_cb,
-	void *user_data);
+int mv_image_recognize(mv_source_h source, const mv_image_object_h *image_objects, int number_of_objects,
+					   mv_engine_config_h engine_cfg, mv_image_recognized_cb recognized_cb, void *user_data);
 
 /*************************/
 /* Image object tracking */
@@ -352,12 +343,8 @@ int mv_image_recognize(
  * @see mv_engine_config_h
  * @see mv_quadrangle_s
  */
-typedef void (*mv_image_tracked_cb)(
-	mv_source_h source,
-	mv_image_tracking_model_h image_tracking_model,
-	mv_engine_config_h engine_cfg,
-	mv_quadrangle_s *location,
-	void *user_data);
+typedef void (*mv_image_tracked_cb)(mv_source_h source, mv_image_tracking_model_h image_tracking_model,
+									mv_engine_config_h engine_cfg, mv_quadrangle_s *location, void *user_data);
 
 /**
  * @brief Tracks the given image tracking model on the current frame
@@ -411,12 +398,8 @@ typedef void (*mv_image_tracked_cb)(
  * @see mv_image_tracking_model_set_target()
  * @see mv_image_tracking_model_destroy()
  */
-int mv_image_track(
-	mv_source_h source,
-	mv_image_tracking_model_h image_tracking_model,
-	mv_engine_config_h engine_cfg,
-	mv_image_tracked_cb tracked_cb,
-	void *user_data);
+int mv_image_track(mv_source_h source, mv_image_tracking_model_h image_tracking_model, mv_engine_config_h engine_cfg,
+				   mv_image_tracked_cb tracked_cb, void *user_data);
 
 /**************************/
 /* Image object behaviour */
@@ -438,8 +421,7 @@ int mv_image_track(
  * @see mv_image_object_destroy()
  * @see mv_image_object_h
  */
-int mv_image_object_create(
-	mv_image_object_h *image_object);
+int mv_image_object_create(mv_image_object_h *image_object);
 
 /**
  * @brief Destroys the image object.
@@ -456,8 +438,7 @@ int mv_image_object_create(
  * @see mv_image_object_create()
  * @see mv_image_object_h
  */
-int mv_image_object_destroy(
-	mv_image_object_h image_object);
+int mv_image_object_destroy(mv_image_object_h image_object);
 
 /**
  * @brief Fills the image object.
@@ -497,11 +478,8 @@ int mv_image_object_destroy(
  * @see mv_image_object_destroy()
  * @see mv_engine_config_h
  */
-int mv_image_object_fill(
-	mv_image_object_h image_object,
-	mv_engine_config_h engine_cfg,
-	mv_source_h source,
-	mv_rectangle_s *location);
+int mv_image_object_fill(mv_image_object_h image_object, mv_engine_config_h engine_cfg, mv_source_h source,
+						 mv_rectangle_s *location);
 
 /**
  * @brief Gets a value that determines how well an image object can be recognized.
@@ -533,9 +511,7 @@ int mv_image_object_fill(
  * @see mv_image_object_destroy()
  * @see mv_engine_config_h
  */
-int mv_image_object_get_recognition_rate(
-	mv_image_object_h image_object,
-	double *recognition_rate);
+int mv_image_object_get_recognition_rate(mv_image_object_h image_object, double *recognition_rate);
 
 /**
  * @brief Sets a label for the image object.
@@ -559,9 +535,7 @@ int mv_image_object_get_recognition_rate(
  * @see mv_image_object_create()
  * @see mv_image_object_destroy()
  */
-int mv_image_object_set_label(
-	mv_image_object_h image_object,
-	int label);
+int mv_image_object_set_label(mv_image_object_h image_object, int label);
 
 /**
  * @brief Gets a label of image object.
@@ -587,9 +561,7 @@ int mv_image_object_set_label(
  * @see mv_image_object_create()
  * @see mv_image_object_destroy()
  */
-int mv_image_object_get_label(
-	mv_image_object_h image_object,
-	int *label);
+int mv_image_object_get_label(mv_image_object_h image_object, int *label);
 
 /**
  * @brief Clones the image object.
@@ -609,9 +581,7 @@ int mv_image_object_get_label(
  * @see mv_image_object_create()
  * @see mv_image_object_destroy()
  */
-int mv_image_object_clone(
-	mv_image_object_h src,
-	mv_image_object_h *dst);
+int mv_image_object_clone(mv_image_object_h src, mv_image_object_h *dst);
 
 /**
  * @brief Saves the image object.
@@ -636,8 +606,7 @@ int mv_image_object_clone(
  * @see mv_image_object_load()
  * @see mv_image_object_destroy()
  */
-int mv_image_object_save(
-	const char *file_name, mv_image_object_h image_object);
+int mv_image_object_save(const char *file_name, mv_image_object_h image_object);
 
 /**
  * @brief Loads an image object from the file.
@@ -664,8 +633,7 @@ int mv_image_object_save(
  * @see mv_image_object_save()
  * @see mv_image_object_destroy()
  */
-int mv_image_object_load(
-	const char *file_name, mv_image_object_h *image_object);
+int mv_image_object_load(const char *file_name, mv_image_object_h *image_object);
 
 /**********************************/
 /* Image tracking model behaviour */
@@ -685,8 +653,7 @@ int mv_image_object_load(
  *
  * @see mv_image_tracking_model_destroy()
  */
-int mv_image_tracking_model_create(
-	mv_image_tracking_model_h *image_tracking_model);
+int mv_image_tracking_model_create(mv_image_tracking_model_h *image_tracking_model);
 
 /**
  * @brief Sets target of image tracking model.
@@ -720,9 +687,7 @@ int mv_image_tracking_model_create(
  * @see mv_image_track()
  * @see mv_image_tracking_model_destroy()
  */
-int mv_image_tracking_model_set_target(
-	mv_image_object_h image_object,
-	mv_image_tracking_model_h image_tracking_model);
+int mv_image_tracking_model_set_target(mv_image_object_h image_object, mv_image_tracking_model_h image_tracking_model);
 
 /**
  * @brief Destroys the image tracking model.
@@ -739,8 +704,7 @@ int mv_image_tracking_model_set_target(
  *
  * @see mv_image_tracking_model_create()
  */
-int mv_image_tracking_model_destroy(
-	mv_image_tracking_model_h image_tracking_model);
+int mv_image_tracking_model_destroy(mv_image_tracking_model_h image_tracking_model);
 
 /**
  * @brief Refreshes the state of image tracking model.
@@ -771,9 +735,7 @@ int mv_image_tracking_model_destroy(
  * @see mv_image_track()
  * @see mv_image_tracking_model_destroy()
  */
-int mv_image_tracking_model_refresh(
-	mv_image_tracking_model_h image_tracking_model,
-	mv_engine_config_h engine_cfg);
+int mv_image_tracking_model_refresh(mv_image_tracking_model_h image_tracking_model, mv_engine_config_h engine_cfg);
 
 /**
  * @brief Clones the image tracking model.
@@ -794,9 +756,7 @@ int mv_image_tracking_model_refresh(
  * @see mv_image_tracking_model_create()
  * @see mv_image_tracking_model_destroy()
  */
-int mv_image_tracking_model_clone(
-	mv_image_tracking_model_h src,
-	mv_image_tracking_model_h *dst);
+int mv_image_tracking_model_clone(mv_image_tracking_model_h src, mv_image_tracking_model_h *dst);
 
 /**
  * @brief Saves the image tracking model.
@@ -823,8 +783,7 @@ int mv_image_tracking_model_clone(
  * @see mv_image_tracking_model_load()
  * @see mv_image_tracking_model_destroy()
  */
-int mv_image_tracking_model_save(
-	const char *file_name, mv_image_tracking_model_h image_tracking_model);
+int mv_image_tracking_model_save(const char *file_name, mv_image_tracking_model_h image_tracking_model);
 
 /**
  * @brief Loads an image tracking model from the file.
@@ -851,8 +810,7 @@ int mv_image_tracking_model_save(
  * @see mv_image_tracking_model_save()
  * @see mv_image_tracking_model_destroy()
  */
-int mv_image_tracking_model_load(
-	const char *file_name, mv_image_tracking_model_h *image_tracking_model);
+int mv_image_tracking_model_load(const char *file_name, mv_image_tracking_model_h *image_tracking_model);
 
 /**
  * @}
diff --git a/include/mv_inference.h b/include/mv_inference.h
index 2b8e054..0032481 100644
--- a/include/mv_inference.h
+++ b/include/mv_inference.h
@@ -247,7 +247,6 @@ extern "C" {
  */
 #define MV_INFERENCE_CONFIDENCE_THRESHOLD "MV_INFERENCE_CONFIDENCE_THRESHOLD"
 
-
 /*************/
 /* Inference */
 /*************/
@@ -321,8 +320,7 @@ int mv_inference_destroy(mv_inference_h infer);
  * @retval #MEDIA_VISION_ERROR_INVALID_PATH Invalid path of model data
  *                                          in @a engine_config
  */
-int mv_inference_configure(mv_inference_h infer,
-            mv_engine_config_h engine_config);
+int mv_inference_configure(mv_inference_h infer, mv_engine_config_h engine_config);
 
 /**
  * @brief Prepares inference.
@@ -362,10 +360,7 @@ int mv_inference_prepare(mv_inference_h infer);
 *
 * @pre mv_inference_foreach_supported_engine()
 */
-typedef bool(*mv_inference_supported_engine_cb) (
-	const char *engine,
-	bool supported,
-	void *user_data);
+typedef bool (*mv_inference_supported_engine_cb)(const char *engine, bool supported, void *user_data);
 
 /**
 * @brief Traverses the list of supported engines for inference.
@@ -385,10 +380,8 @@ typedef bool(*mv_inference_supported_engine_cb) (
 *
 * @see mv_inference_supported_engine_cb()
 */
-int mv_inference_foreach_supported_engine(
-	mv_inference_h infer,
-	mv_inference_supported_engine_cb callback,
-	void *user_data);
+int mv_inference_foreach_supported_engine(mv_inference_h infer, mv_inference_supported_engine_cb callback,
+										  void *user_data);
 
 /************************/
 /* Image classification */
@@ -420,13 +413,8 @@ int mv_inference_foreach_supported_engine(
  *
  * @see mv_inference_image_classify()
  */
-typedef void (*mv_inference_image_classified_cb)(
-	mv_source_h source,
-	int number_of_classes,
-	const int *indices,
-	const char **names,
-	const float *confidences,
-	void *user_data);
+typedef void (*mv_inference_image_classified_cb)(mv_source_h source, int number_of_classes, const int *indices,
+												 const char **names, const float *confidences, void *user_data);
 
 /**
  * @brief Performs image classification on the @a source.
@@ -465,13 +453,8 @@ typedef void (*mv_inference_image_classified_cb)(
  *
  * @see mv_inference_image_classified_cb()
  */
-int mv_inference_image_classify(
-	mv_source_h source,
-	mv_inference_h infer,
-	mv_rectangle_s *roi,
-	mv_inference_image_classified_cb classified_cb,
-	void *user_data);
-
+int mv_inference_image_classify(mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
+								mv_inference_image_classified_cb classified_cb, void *user_data);
 
 /************************/
 /* Object Detection     */
@@ -504,14 +487,9 @@ int mv_inference_image_classify(
  *
  * @see mv_inference_object_detect()
  */
-typedef void (*mv_inference_object_detected_cb)(
-	mv_source_h source,
-	int number_of_objects,
-	const int *indices,
-	const char **names,
-	const float *confidences,
-	const mv_rectangle_s *locations,
-	void *user_data);
+typedef void (*mv_inference_object_detected_cb)(mv_source_h source, int number_of_objects, const int *indices,
+												const char **names, const float *confidences,
+												const mv_rectangle_s *locations, void *user_data);
 
 /**
  * @brief Performs object detection on the @a source.
@@ -547,11 +525,8 @@ typedef void (*mv_inference_object_detected_cb)(
  *
  * @see mv_inference_object_detected_cb()
  */
-int mv_inference_object_detect(
-	mv_source_h source,
-	mv_inference_h infer,
-	mv_inference_object_detected_cb detected_cb,
-	void *user_data);
+int mv_inference_object_detect(mv_source_h source, mv_inference_h infer, mv_inference_object_detected_cb detected_cb,
+							   void *user_data);
 
 /*************************************/
 /* Face and its landmark detection   */
@@ -582,12 +557,8 @@ int mv_inference_object_detect(
  *
  * @see mv_inference_face_detect()
  */
-typedef void (*mv_inference_face_detected_cb)(
-	mv_source_h source,
-	int number_of_faces,
-	const float *confidences,
-	const mv_rectangle_s *locations,
-	void *user_data);
+typedef void (*mv_inference_face_detected_cb)(mv_source_h source, int number_of_faces, const float *confidences,
+											  const mv_rectangle_s *locations, void *user_data);
 
 /**
  * @brief Performs face detection on the @a source.
@@ -623,11 +594,8 @@ typedef void (*mv_inference_face_detected_cb)(
  *
  * @see mv_inference_face_detected_cb()
  */
-int mv_inference_face_detect(
-	mv_source_h source,
-	mv_inference_h infer,
-	mv_inference_face_detected_cb detected_cb,
-	void *user_data);
+int mv_inference_face_detect(mv_source_h source, mv_inference_h infer, mv_inference_face_detected_cb detected_cb,
+							 void *user_data);
 
 /**
  * @brief Called when facial landmarks in @a source are detected.
@@ -653,11 +621,8 @@ int mv_inference_face_detect(
  *
  * @see mv_inference_face_detect()
  */
-typedef void (*mv_inference_facial_landmark_detected_cb)(
-	mv_source_h source,
-	int number_of_landmarks,
-	const mv_point_s *locations,
-	void *user_data);
+typedef void (*mv_inference_facial_landmark_detected_cb)(mv_source_h source, int number_of_landmarks,
+														 const mv_point_s *locations, void *user_data);
 
 /**
  * @brief Performs facial landmarks detection on the @a source.
@@ -694,12 +659,8 @@ typedef void (*mv_inference_facial_landmark_detected_cb)(
  *
  * @see mv_inference_facial_landmark_detected_cb()
  */
-int mv_inference_facial_landmark_detect(
-	mv_source_h source,
-	mv_inference_h infer,
-	mv_rectangle_s *roi,
-	mv_inference_facial_landmark_detected_cb detected_cb,
-	void *user_data);
+int mv_inference_facial_landmark_detect(mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
+										mv_inference_facial_landmark_detected_cb detected_cb, void *user_data);
 
 /**
  * @brief Called when poses in @a source are detected.
@@ -720,10 +681,8 @@ int mv_inference_facial_landmark_detect(
  *
  * @see mv_inference_pose_landmark_detect()
  */
-typedef void (*mv_inference_pose_landmark_detected_cb)(
-	mv_source_h source,
-	mv_inference_pose_result_h locations,
-	void *user_data);
+typedef void (*mv_inference_pose_landmark_detected_cb)(mv_source_h source, mv_inference_pose_result_h locations,
+													   void *user_data);
 
 /**
  * @brief Performs pose landmarks detection on the @a source.
@@ -759,12 +718,8 @@ typedef void (*mv_inference_pose_landmark_detected_cb)(
  *
  * @see mv_inference_pose_landmark_detected_cb()
  */
-int mv_inference_pose_landmark_detect(
-	mv_source_h source,
-	mv_inference_h infer,
-	mv_rectangle_s *roi,
-	mv_inference_pose_landmark_detected_cb detected_cb,
-	void *user_data);
+int mv_inference_pose_landmark_detect(mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
+									  mv_inference_pose_landmark_detected_cb detected_cb, void *user_data);
 
 /**
  * @brief Gets the number of poses.
@@ -782,8 +737,7 @@ int mv_inference_pose_landmark_detect(
  * @see mv_inference_pose_landmark_detected_cb()
  * @see mv_inference_pose_result_h
  */
-int mv_inference_pose_get_number_of_poses(
-	mv_inference_pose_result_h result, int *number_of_poses);
+int mv_inference_pose_get_number_of_poses(mv_inference_pose_result_h result, int *number_of_poses);
 
 /**
  * @brief Gets the number of landmarks per a pose.
@@ -801,8 +755,7 @@ int mv_inference_pose_get_number_of_poses(
  * @see mv_inference_pose_landmark_detected_cb()
  * @see mv_inference_pose_result_h
  */
-int mv_inference_pose_get_number_of_landmarks(
-	mv_inference_pose_result_h result, int *number_of_landmarks);
+int mv_inference_pose_get_number_of_landmarks(mv_inference_pose_result_h result, int *number_of_landmarks);
 
 /**
  * @brief Gets landmark location of a part of a pose.
@@ -829,8 +782,8 @@ int mv_inference_pose_get_number_of_landmarks(
  * @see mv_inference_pose_landmark_detected_cb()
  * @see mv_inference_pose_result_h
  */
-int mv_inference_pose_get_landmark(
-	mv_inference_pose_result_h result, int pose_index, int pose_part, mv_point_s *location, float *score);
+int mv_inference_pose_get_landmark(mv_inference_pose_result_h result, int pose_index, int pose_part,
+								   mv_point_s *location, float *score);
 
 /**
  * @brief Gets a label of a pose.
@@ -853,8 +806,7 @@ int mv_inference_pose_get_landmark(
  * @see mv_inference_pose_landmark_detected_cb()
  * @see mv_inference_pose_result_h
  */
-int mv_inference_pose_get_label(
-	mv_inference_pose_result_h result, int pose_index, int *label);
+int mv_inference_pose_get_label(mv_inference_pose_result_h result, int pose_index, int *label);
 
 /**
  * @brief Creates pose handle.
diff --git a/include/mv_inference_private.h b/include/mv_inference_private.h
index 7bcd315..604810d 100644
--- a/include/mv_inference_private.h
+++ b/include/mv_inference_private.h
@@ -19,8 +19,8 @@
 
 #include <mv_common.h>
 
-#define MAX_NUMBER_OF_POSE	5
-#define MAX_NUMBER_OF_LANDMARKS_PER_POSE	500
+#define MAX_NUMBER_OF_POSE 5
+#define MAX_NUMBER_OF_LANDMARKS_PER_POSE 500
 
 #ifdef __cplusplus
 extern "C" {
@@ -37,19 +37,21 @@ extern "C" {
   * @since_tizen 6.0
   *
   */
-typedef struct mv_inference_landmark_s{
-    bool isAvailable;   /**< Availability of landmark */
-    mv_point_s point;   /**< 2D position of landmark */
-    int label;    /**< Label of landmark */
-    float score;        /**< Score of landmark */
+typedef struct mv_inference_landmark_s
+{
+	bool isAvailable; /**< Availability of landmark */
+	mv_point_s point; /**< 2D position of landmark */
+	int label; /**< Label of landmark */
+	float score; /**< Score of landmark */
 
-    mv_inference_landmark_s() {
-      isAvailable = false;
-      point.x = -1;
-      point.y = -1;
-      label = -1;
-      score = -1.0f;
-    }
+	mv_inference_landmark_s()
+	{
+		isAvailable = false;
+		point.x = -1;
+		point.y = -1;
+		label = -1;
+		score = -1.0f;
+	}
 } mv_inference_landmark_s;
 
 /**
@@ -58,10 +60,12 @@ typedef struct mv_inference_landmark_s{
   * @since_tizen 6.0
   *
   */
-typedef struct {
-    int number_of_poses;
-    int number_of_landmarks_per_pose;            /**< The number of landmarks*/
-    mv_inference_landmark_s landmarks[MAX_NUMBER_OF_POSE][MAX_NUMBER_OF_LANDMARKS_PER_POSE]; /**< A set of landmarks describing pose */
+typedef struct
+{
+	int number_of_poses;
+	int number_of_landmarks_per_pose; /**< The number of landmarks*/
+	mv_inference_landmark_s landmarks[MAX_NUMBER_OF_POSE]
+									 [MAX_NUMBER_OF_LANDMARKS_PER_POSE]; /**< A set of landmarks describing pose */
 } mv_inference_pose_s;
 
 /**
diff --git a/include/mv_inference_type.h b/include/mv_inference_type.h
index 1794b83..1aaff69 100644
--- a/include/mv_inference_type.h
+++ b/include/mv_inference_type.h
@@ -58,16 +58,17 @@ extern "C" {
  *
  * @see mv_inference_prepare()
  */
-typedef enum {
-    MV_INFERENCE_BACKEND_NONE = -1, /**< None */
-    MV_INFERENCE_BACKEND_OPENCV,    /**< OpenCV */
-    MV_INFERENCE_BACKEND_TFLITE,    /**< TensorFlow-Lite */
-    MV_INFERENCE_BACKEND_ARMNN,     /**< ARMNN (Since 6.0) */
-    MV_INFERENCE_BACKEND_MLAPI,     /**< @deprecated ML Single API of NNStreamer (Deprecated since 7.0) */
-    MV_INFERENCE_BACKEND_ONE,       /**< On-device Neural Engine (Since 6.0) */
-    MV_INFERENCE_BACKEND_NNTRAINER, /**< NNTrainer (Since 7.0) */
-    MV_INFERENCE_BACKEND_SNPE,      /**< SNPE Engine (Since 7.0) */
-    MV_INFERENCE_BACKEND_MAX        /**< @deprecated Backend MAX (Deprecated since 7.0) */
+typedef enum
+{
+	MV_INFERENCE_BACKEND_NONE = -1, /**< None */
+	MV_INFERENCE_BACKEND_OPENCV, /**< OpenCV */
+	MV_INFERENCE_BACKEND_TFLITE, /**< TensorFlow-Lite */
+	MV_INFERENCE_BACKEND_ARMNN, /**< ARMNN (Since 6.0) */
+	MV_INFERENCE_BACKEND_MLAPI, /**< @deprecated ML Single API of NNStreamer (Deprecated since 7.0) */
+	MV_INFERENCE_BACKEND_ONE, /**< On-device Neural Engine (Since 6.0) */
+	MV_INFERENCE_BACKEND_NNTRAINER, /**< NNTrainer (Since 7.0) */
+	MV_INFERENCE_BACKEND_SNPE, /**< SNPE Engine (Since 7.0) */
+	MV_INFERENCE_BACKEND_MAX /**< @deprecated Backend MAX (Deprecated since 7.0) */
 } mv_inference_backend_type_e;
 
 /**
@@ -77,12 +78,13 @@ typedef enum {
  * @since_tizen 5.5
  *
  */
-typedef enum {
-    MV_INFERENCE_TARGET_NONE = -1,	/**< None */
-    MV_INFERENCE_TARGET_CPU,		/**< CPU */
-    MV_INFERENCE_TARGET_GPU,		/**< GPU*/
-    MV_INFERENCE_TARGET_CUSTOM,		/**< CUSTOM*/
-    MV_INFERENCE_TARGET_MAX			/**< Target MAX */
+typedef enum
+{
+	MV_INFERENCE_TARGET_NONE = -1, /**< None */
+	MV_INFERENCE_TARGET_CPU, /**< CPU */
+	MV_INFERENCE_TARGET_GPU, /**< GPU*/
+	MV_INFERENCE_TARGET_CUSTOM, /**< CUSTOM*/
+	MV_INFERENCE_TARGET_MAX /**< Target MAX */
 } mv_inference_target_type_e;
 
 /**
@@ -91,12 +93,13 @@ typedef enum {
  * @since_tizen 6.0
  *
  */
-typedef enum {
-    MV_INFERENCE_TARGET_DEVICE_NONE = 0,		/**< None */
-    MV_INFERENCE_TARGET_DEVICE_CPU = 1 << 0,	/**< CPU */
-    MV_INFERENCE_TARGET_DEVICE_GPU = 1 << 1,	/**< GPU*/
-    MV_INFERENCE_TARGET_DEVICE_CUSTOM = 1 << 2,	/**< CUSTOM*/
-    MV_INFERENCE_TARGET_DEVICE_MAX = 1 << 3		/**< Target MAX */
+typedef enum
+{
+	MV_INFERENCE_TARGET_DEVICE_NONE = 0, /**< None */
+	MV_INFERENCE_TARGET_DEVICE_CPU = 1 << 0, /**< CPU */
+	MV_INFERENCE_TARGET_DEVICE_GPU = 1 << 1, /**< GPU*/
+	MV_INFERENCE_TARGET_DEVICE_CUSTOM = 1 << 2, /**< CUSTOM*/
+	MV_INFERENCE_TARGET_DEVICE_MAX = 1 << 3 /**< Target MAX */
 } mv_inference_target_device_e;
 
 /**
@@ -105,9 +108,10 @@ typedef enum {
  * @since_tizen 6.0
  *
  */
-typedef enum {
-	MV_INFERENCE_DATA_FLOAT32 = 0,	/**< Data type of a given pre-trained model is float. */
-	MV_INFERENCE_DATA_UINT8			/**< Data type of a given pre-trained model is unsigned char. */
+typedef enum
+{
+	MV_INFERENCE_DATA_FLOAT32 = 0, /**< Data type of a given pre-trained model is float. */
+	MV_INFERENCE_DATA_UINT8 /**< Data type of a given pre-trained model is unsigned char. */
 } mv_inference_data_type_e;
 
 /**
@@ -116,23 +120,24 @@ typedef enum {
   * @since_tizen 6.0
   *
   */
-typedef enum {
-    MV_INFERENCE_HUMAN_POSE_HEAD = 1,       /**< Head of human pose */
-    MV_INFERENCE_HUMAN_POSE_NECK,           /**< Neck of human pose */
-    MV_INFERENCE_HUMAN_POSE_THORAX,         /**< Thorax of human pose */
-    MV_INFERENCE_HUMAN_POSE_RIGHT_SHOULDER, /**< Right shoulder of human pose */
-    MV_INFERENCE_HUMAN_POSE_RIGHT_ELBOW,    /**< Right elbow of human pose */
-    MV_INFERENCE_HUMAN_POSE_RIGHT_WRIST,    /**< Right wrist of human pose */
-    MV_INFERENCE_HUMAN_POSE_LEFT_SHOULDER,  /**< Left shoulder of human pose */
-    MV_INFERENCE_HUMAN_POSE_LEFT_ELBOW,     /**< Left elbow of human pose */
-    MV_INFERENCE_HUMAN_POSE_LEFT_WRIST,     /**< Left wrist of human pose */
-    MV_INFERENCE_HUMAN_POSE_PELVIS,         /**< Pelvis of human pose */
-    MV_INFERENCE_HUMAN_POSE_RIGHT_HIP,      /**< Right hip of human pose */
-    MV_INFERENCE_HUMAN_POSE_RIGHT_KNEE,     /**< Right knee of human pose */
-    MV_INFERENCE_HUMAN_POSE_RIGHT_ANKLE,    /**< Right ankle of human pose */
-    MV_INFERENCE_HUMAN_POSE_LEFT_HIP,       /**< Left hip of human pose */
-    MV_INFERENCE_HUMAN_POSE_LEFT_KNEE,      /**< Left knee of human pose */
-    MV_INFERENCE_HUMAN_POSE_LEFT_ANKLE      /**< Left ankle of human pose */
+typedef enum
+{
+	MV_INFERENCE_HUMAN_POSE_HEAD = 1, /**< Head of human pose */
+	MV_INFERENCE_HUMAN_POSE_NECK, /**< Neck of human pose */
+	MV_INFERENCE_HUMAN_POSE_THORAX, /**< Thorax of human pose */
+	MV_INFERENCE_HUMAN_POSE_RIGHT_SHOULDER, /**< Right shoulder of human pose */
+	MV_INFERENCE_HUMAN_POSE_RIGHT_ELBOW, /**< Right elbow of human pose */
+	MV_INFERENCE_HUMAN_POSE_RIGHT_WRIST, /**< Right wrist of human pose */
+	MV_INFERENCE_HUMAN_POSE_LEFT_SHOULDER, /**< Left shoulder of human pose */
+	MV_INFERENCE_HUMAN_POSE_LEFT_ELBOW, /**< Left elbow of human pose */
+	MV_INFERENCE_HUMAN_POSE_LEFT_WRIST, /**< Left wrist of human pose */
+	MV_INFERENCE_HUMAN_POSE_PELVIS, /**< Pelvis of human pose */
+	MV_INFERENCE_HUMAN_POSE_RIGHT_HIP, /**< Right hip of human pose */
+	MV_INFERENCE_HUMAN_POSE_RIGHT_KNEE, /**< Right knee of human pose */
+	MV_INFERENCE_HUMAN_POSE_RIGHT_ANKLE, /**< Right ankle of human pose */
+	MV_INFERENCE_HUMAN_POSE_LEFT_HIP, /**< Left hip of human pose */
+	MV_INFERENCE_HUMAN_POSE_LEFT_KNEE, /**< Left knee of human pose */
+	MV_INFERENCE_HUMAN_POSE_LEFT_ANKLE /**< Left ankle of human pose */
 } mv_inference_human_pose_landmark_e;
 
 /**
@@ -141,13 +146,14 @@ typedef enum {
   * @since_tizen 6.0
   *
   */
-typedef enum {
-    MV_INFERENCE_HUMAN_BODY_PART_HEAD = 1 << 0,         /**< HEAD, NECK, and THORAX */
-    MV_INFERENCE_HUMAN_BODY_PART_ARM_RIGHT = 1 << 1,    /**< RIGHT SHOULDER, ELBOW, and WRIST */
-    MV_INFERENCE_HUMAN_BODY_PART_ARM_LEFT = 1 << 2,     /**< LEFT SHOULDER, ELBOW, and WRIST */
-    MV_INFERENCE_HUMAN_BODY_PART_BODY = 1 << 3,         /**< THORAX, PELVIS, RIGHT HIP, and LEFT HIP */
-    MV_INFERENCE_HUMAN_BODY_PART_LEG_RIGHT = 1 << 4,    /**< RIGHT HIP, KNEE, and ANKLE */
-    MV_INFERENCE_HUMAN_BODY_PART_LEG_LEFT = 1 << 5      /**< LEFT HIP, KNEE, and ANKLE */
+typedef enum
+{
+	MV_INFERENCE_HUMAN_BODY_PART_HEAD = 1 << 0, /**< HEAD, NECK, and THORAX */
+	MV_INFERENCE_HUMAN_BODY_PART_ARM_RIGHT = 1 << 1, /**< RIGHT SHOULDER, ELBOW, and WRIST */
+	MV_INFERENCE_HUMAN_BODY_PART_ARM_LEFT = 1 << 2, /**< LEFT SHOULDER, ELBOW, and WRIST */
+	MV_INFERENCE_HUMAN_BODY_PART_BODY = 1 << 3, /**< THORAX, PELVIS, RIGHT HIP, and LEFT HIP */
+	MV_INFERENCE_HUMAN_BODY_PART_LEG_RIGHT = 1 << 4, /**< RIGHT HIP, KNEE, and ANKLE */
+	MV_INFERENCE_HUMAN_BODY_PART_LEG_LEFT = 1 << 5 /**< LEFT HIP, KNEE, and ANKLE */
 } mv_inference_human_body_part_e;
 
 /**
diff --git a/include/mv_private.h b/include/mv_private.h
index 94aa31c..49eb3aa 100644
--- a/include/mv_private.h
+++ b/include/mv_private.h
@@ -30,44 +30,35 @@ extern "C" {
 
 #define LOG_TAG "TIZEN_MEDIA_VISION"
 
-#define MEDIA_VISION_FUNCTION_ENTER() \
-		LOGI("[%s] <ENTER>", __FUNCTION__)
+#define MEDIA_VISION_FUNCTION_ENTER() LOGI("[%s] <ENTER>", __FUNCTION__)
 
-#define MEDIA_VISION_FUNCTION_LEAVE() \
-		LOGI("[%s] <LEAVE>", __FUNCTION__)
+#define MEDIA_VISION_FUNCTION_LEAVE() LOGI("[%s] <LEAVE>", __FUNCTION__)
 
-#define MEDIA_VISION_ASSERT(function, msg) \
-		do { \
-			int error_code = function; \
-			if (error_code != MEDIA_VISION_ERROR_NONE) { \
-				LOGE("%s(0x%08x)", msg, error_code); \
-				return error_code; \
-			} \
-		} \
-		while (0)
+#define MEDIA_VISION_ASSERT(function, msg)           \
+	do {                                             \
+		int error_code = function;                   \
+		if (error_code != MEDIA_VISION_ERROR_NONE) { \
+			LOGE("%s(0x%08x)", msg, error_code);     \
+			return error_code;                       \
+		}                                            \
+	} while (0)
 
-#define MEDIA_VISION_CHECK_CONDITION(condition, error, msg) \
-		do { \
-			if (!(condition)) { \
-				LOGE("[%s] %s(0x%08x)", __FUNCTION__, msg, error); \
-				return error; \
-			} \
-		} \
-		while (0)
+#define MEDIA_VISION_CHECK_CONDITION(condition, error, msg)    \
+	do {                                                       \
+		if (!(condition)) {                                    \
+			LOGE("[%s] %s(0x%08x)", __FUNCTION__, msg, error); \
+			return error;                                      \
+		}                                                      \
+	} while (0)
 
 #define MEDIA_VISION_INSTANCE_CHECK(arg) \
-		MEDIA_VISION_CHECK_CONDITION((arg), \
-									MEDIA_VISION_ERROR_INVALID_PARAMETER, \
-									"MEDIA_VISION_ERROR_INVALID_PARAMETER")
+	MEDIA_VISION_CHECK_CONDITION((arg), MEDIA_VISION_ERROR_INVALID_PARAMETER, "MEDIA_VISION_ERROR_INVALID_PARAMETER")
 
 #define MEDIA_VISION_NULL_ARG_CHECK(arg) \
-		MEDIA_VISION_CHECK_CONDITION((arg), \
-									MEDIA_VISION_ERROR_INVALID_PARAMETER, \
-									"MEDIA_VISION_ERROR_INVALID_PARAMETER")
+	MEDIA_VISION_CHECK_CONDITION((arg), MEDIA_VISION_ERROR_INVALID_PARAMETER, "MEDIA_VISION_ERROR_INVALID_PARAMETER")
 
 #define MEDIA_VISION_SUPPORT_CHECK(arg) \
-		MEDIA_VISION_CHECK_CONDITION((arg), MEDIA_VISION_ERROR_NOT_SUPPORTED, \
-									"MEDIA_VISION_ERROR_NOT_SUPPORTED")
+	MEDIA_VISION_CHECK_CONDITION((arg), MEDIA_VISION_ERROR_NOT_SUPPORTED, "MEDIA_VISION_ERROR_NOT_SUPPORTED")
 
 bool _mv_check_system_info_feature_supported(void);
 bool _mv_barcode_detect_check_system_info_feature_supported(void);
diff --git a/include/mv_roi_tracker.h b/include/mv_roi_tracker.h
index 180f848..b13d31c 100644
--- a/include/mv_roi_tracker.h
+++ b/include/mv_roi_tracker.h
@@ -102,8 +102,7 @@ int mv_roi_tracker_destroy(mv_roi_tracker_h handle);
  * @retval #MEDIA_VISION_ERROR_INVALID_PARAMETER Invalid parameter
  *                                               in @a engine_config
  */
-int mv_roi_tracker_configure(mv_roi_tracker_h handle,
-            mv_engine_config_h engine_config);
+int mv_roi_tracker_configure(mv_roi_tracker_h handle, mv_engine_config_h engine_config);
 
 /**
  * @brief Prepares roi tracker.
@@ -143,11 +142,7 @@ int mv_roi_tracker_prepare(mv_roi_tracker_h handle, int x, int y, int width, int
  *
  * @see mv_roi_tracker_perform()
  */
-typedef void (*mv_roi_tracker_tracked_cb)(
-	mv_source_h source,
-	mv_rectangle_s roi,
-	void *user_data);
-
+typedef void (*mv_roi_tracker_tracked_cb)(mv_source_h source, mv_rectangle_s roi, void *user_data);
 
 /**
  * @brief Tracks with a given tracker on the @a source.
@@ -173,11 +168,8 @@ typedef void (*mv_roi_tracker_tracked_cb)(
  *
  * @pre Create a new tracker handle by calling @ref mv_roi_tracker_create()
  */
-int mv_roi_tracker_perform(
-	mv_roi_tracker_h handle,
-	mv_source_h source,
-	mv_roi_tracker_tracked_cb tracked_cb,
-	void *user_data);
+int mv_roi_tracker_perform(mv_roi_tracker_h handle, mv_source_h source, mv_roi_tracker_tracked_cb tracked_cb,
+						   void *user_data);
 
 /**
  * @}
diff --git a/include/mv_roi_tracker_type.h b/include/mv_roi_tracker_type.h
index f5d8c54..11c09e2 100644
--- a/include/mv_roi_tracker_type.h
+++ b/include/mv_roi_tracker_type.h
@@ -20,8 +20,8 @@
 
 #include <mv_common.h>
 
-#define MAX_LABEL_LEN	128
-#define MAX_LABEL_CNT	100
+#define MAX_LABEL_LEN 128
+#define MAX_LABEL_CNT 100
 
 #ifdef __cplusplus
 extern "C" {
@@ -43,12 +43,13 @@ extern "C" {
  * @details Contains roi tracker result such as coordinates.
  * @since_tizen 7.0
  */
-typedef struct {
-	int x;				/**< Left-top x coordinate of tracked region */
-	int y;				/**< Left-top y coordinate of tracked region */
-	int width;			/**< Width of tracked region */
-	int height;			/**< Height of tracked region */
-	bool initialized;	/**< flag that struct is initialized or not */
+typedef struct
+{
+	int x; /**< Left-top x coordinate of tracked region */
+	int y; /**< Left-top y coordinate of tracked region */
+	int width; /**< Width of tracked region */
+	int height; /**< Height of tracked region */
+	bool initialized; /**< flag that struct is initialized or not */
 } mv_roi_tracker_result_s;
 
 /**
@@ -57,16 +58,16 @@ typedef struct {
  */
 typedef void *mv_roi_tracker_h;
 
-
 /**
  * @brief Enumeration for ROI tracker type.
  * @since_tizen 7.0
  */
-typedef enum {
-	MV_ROI_TRACKER_TYPE_NONE = 0,	/**< None */
-	MV_ROI_TRACKER_TYPE_ACCURACY,	/**< Tracker type focused on accuracy */
-	MV_ROI_TRACKER_TYPE_BALANCE,	/**< Tracker type focused on balance */
-	MV_ROI_TRACKER_TYPE_SPEED		/**< Tracker type focused on speed */
+typedef enum
+{
+	MV_ROI_TRACKER_TYPE_NONE = 0, /**< None */
+	MV_ROI_TRACKER_TYPE_ACCURACY, /**< Tracker type focused on accuracy */
+	MV_ROI_TRACKER_TYPE_BALANCE, /**< Tracker type focused on balance */
+	MV_ROI_TRACKER_TYPE_SPEED /**< Tracker type focused on speed */
 } mv_roi_tracker_type_e;
 /**
  * @}
diff --git a/include/mv_surveillance.h b/include/mv_surveillance.h
index 90b4f7d..3deb6e9 100644
--- a/include/mv_surveillance.h
+++ b/include/mv_surveillance.h
@@ -48,8 +48,7 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-#define MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED \
-		"MV_SURVEILLANCE_EVENT_MOVEMENT_DETECTED"
+#define MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED "MV_SURVEILLANCE_EVENT_MOVEMENT_DETECTED"
 
 /**
  * @brief Name of the event result value that contains number of regions where
@@ -90,8 +89,7 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-#define MV_SURVEILLANCE_MOVEMENT_NUMBER_OF_REGIONS \
-		"NUMBER_OF_MOVEMENT_REGIONS"
+#define MV_SURVEILLANCE_MOVEMENT_NUMBER_OF_REGIONS "NUMBER_OF_MOVEMENT_REGIONS"
 
 /**
  * @brief Name of the event result value that contains rectangular regions where
@@ -175,8 +173,7 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-#define MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED \
-		"MV_SURVEILLANCE_EVENT_PERSON_APPEARED_DISAPEARED"
+#define MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED "MV_SURVEILLANCE_EVENT_PERSON_APPEARED_DISAPEARED"
 
 /**
  * @brief Name of the event result value that contains number
@@ -216,8 +213,7 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-#define MV_SURVEILLANCE_PERSONS_APPEARED_NUMBER \
-		"NUMBER_OF_APPEARED_PERSONS"
+#define MV_SURVEILLANCE_PERSONS_APPEARED_NUMBER "NUMBER_OF_APPEARED_PERSONS"
 
 /**
  * @brief Name of the event result value that contains number
@@ -257,8 +253,7 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-#define MV_SURVEILLANCE_PERSONS_DISAPPEARED_NUMBER \
-		"NUMBER_OF_DISAPPEARED_PERSONS"
+#define MV_SURVEILLANCE_PERSONS_DISAPPEARED_NUMBER "NUMBER_OF_DISAPPEARED_PERSONS"
 
 /**
  * @brief Name of the event result value that contains number
@@ -298,8 +293,7 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-#define MV_SURVEILLANCE_PERSONS_TRACKED_NUMBER \
-		"NUMBER_OF_TRACKED_PERSONS"
+#define MV_SURVEILLANCE_PERSONS_TRACKED_NUMBER "NUMBER_OF_TRACKED_PERSONS"
 
 /**
  * @brief Name of the event result value that contains a set of rectangular
@@ -351,8 +345,7 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-#define MV_SURVEILLANCE_PERSONS_APPEARED_LOCATIONS \
-		"APPEARED_PERSONS_LOCATIONS"
+#define MV_SURVEILLANCE_PERSONS_APPEARED_LOCATIONS "APPEARED_PERSONS_LOCATIONS"
 
 /**
  * @brief Name of the event result value that contains a set of rectangular
@@ -404,8 +397,7 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-#define MV_SURVEILLANCE_PERSONS_DISAPPEARED_LOCATIONS \
-		"DISAPPEARED_PERSONS_LOCATIONS"
+#define MV_SURVEILLANCE_PERSONS_DISAPPEARED_LOCATIONS "DISAPPEARED_PERSONS_LOCATIONS"
 
 /**
  * @brief Name of the event result value that contains a set of rectangular
@@ -456,8 +448,7 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-#define MV_SURVEILLANCE_PERSONS_TRACKED_LOCATIONS \
-		"TRACKED_PERSONS_LOCATIONS"
+#define MV_SURVEILLANCE_PERSONS_TRACKED_LOCATIONS "TRACKED_PERSONS_LOCATIONS"
 
 /**
  * @brief Name of the person recognition event type.
@@ -487,8 +478,7 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-#define MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED \
-		"MV_SURVEILLANCE_EVENT_PERSON_RECOGNIZED"
+#define MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED "MV_SURVEILLANCE_EVENT_PERSON_RECOGNIZED"
 
 /**
  * @brief Name of the event result value that contains number of locations where
@@ -528,8 +518,7 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-#define MV_SURVEILLANCE_PERSONS_RECOGNIZED_NUMBER \
-		"NUMBER_OF_PERSONS"
+#define MV_SURVEILLANCE_PERSONS_RECOGNIZED_NUMBER "NUMBER_OF_PERSONS"
 
 /**
  * @brief Name of the event result value that contains a set of rectangular
@@ -579,8 +568,7 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-#define MV_SURVEILLANCE_PERSONS_RECOGNIZED_LOCATIONS \
-		"PERSONS_LOCATIONS"
+#define MV_SURVEILLANCE_PERSONS_RECOGNIZED_LOCATIONS "PERSONS_LOCATIONS"
 
 /**
  * @brief Name of the event result value that contains a set of labels that
@@ -629,8 +617,7 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-#define MV_SURVEILLANCE_PERSONS_RECOGNIZED_LABELS \
-		"PERSONS_LABELS"
+#define MV_SURVEILLANCE_PERSONS_RECOGNIZED_LABELS "PERSONS_LABELS"
 
 /**
  * @brief Name of the event result value that contains a set of confidence
@@ -679,8 +666,7 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-#define MV_SURVEILLANCE_PERSONS_RECOGNIZED_CONFIDENCES \
-		"PERSONS_CONFIDENCES"
+#define MV_SURVEILLANCE_PERSONS_RECOGNIZED_CONFIDENCES "PERSONS_CONFIDENCES"
 
 /**
  * @}
@@ -702,8 +688,7 @@ extern "C" {
  * @see mv_engine_config_set_string_attribute()
  * @see mv_engine_config_get_string_attribute()
  */
-#define MV_SURVEILLANCE_FACE_RECOGNITION_MODEL_FILE_PATH \
-		"MV_SURVEILLANCE_FACE_RECOGNITION_MODEL_FILE_PATH"
+#define MV_SURVEILLANCE_FACE_RECOGNITION_MODEL_FILE_PATH "MV_SURVEILLANCE_FACE_RECOGNITION_MODEL_FILE_PATH"
 
 /**
  * @brief Defines MV_SURVEILLANCE_MOVEMENT_DETECTION_THRESOLD to set movement
@@ -719,8 +704,7 @@ extern "C" {
  * @see mv_engine_config_set_int_attribute()
  * @see mv_engine_config_get_int_attribute()
  */
-#define MV_SURVEILLANCE_MOVEMENT_DETECTION_THRESHOLD \
-		"MV_SURVEILLANCE_MOVEMENT_DETECTION_THRESHOLD"
+#define MV_SURVEILLANCE_MOVEMENT_DETECTION_THRESHOLD "MV_SURVEILLANCE_MOVEMENT_DETECTION_THRESHOLD"
 
 /**
  * @brief Defines MV_SURVEILLANCE_SKIP_FRAMES_COUNT to set how many frames
@@ -789,12 +773,9 @@ typedef void *mv_surveillance_result_h;
  * @see mv_surveillance_subscribe_event_trigger()
  * @see mv_surveillance_unsubscribe_event_trigger()
  */
-typedef void (*mv_surveillance_event_occurred_cb)(
-		mv_surveillance_event_trigger_h trigger,
-		mv_source_h source,
-		int video_stream_id,
-		mv_surveillance_result_h event_result,
-		void *user_data);
+typedef void (*mv_surveillance_event_occurred_cb)(mv_surveillance_event_trigger_h trigger, mv_source_h source,
+												  int video_stream_id, mv_surveillance_result_h event_result,
+												  void *user_data);
 
 /**
  * @brief Called to get the information once for each supported event type.
@@ -811,9 +792,7 @@ typedef void (*mv_surveillance_event_occurred_cb)(
  * @pre mv_surveillance_foreach_supported_event_type() will invoke this callback
  * @see mv_surveillance_foreach_supported_event_type()
  */
-typedef bool (*mv_surveillance_event_type_cb)(
-		const char *event_type,
-		void *user_data);
+typedef bool (*mv_surveillance_event_type_cb)(const char *event_type, void *user_data);
 
 /**
  * @brief Called to get the result name from the triggered event.
@@ -834,9 +813,7 @@ typedef bool (*mv_surveillance_event_type_cb)(
  *      callback
  * @see mv_surveillance_foreach_event_result_name()
  */
-typedef bool (*mv_surveillance_event_result_name_cb)(
-		const char *name,
-		void *user_data);
+typedef bool (*mv_surveillance_event_result_name_cb)(const char *name, void *user_data);
 
 /**
  * @brief Creates surveillance event trigger handle.
@@ -858,9 +835,7 @@ typedef bool (*mv_surveillance_event_result_name_cb)(
  * @see mv_surveillance_event_trigger_destroy()
  * @see mv_surveillance_foreach_supported_event_type()
  */
-int mv_surveillance_event_trigger_create(
-		const char *event_type,
-		mv_surveillance_event_trigger_h *trigger);
+int mv_surveillance_event_trigger_create(const char *event_type, mv_surveillance_event_trigger_h *trigger);
 
 /**
  * @brief Destroys the surveillance event trigger handle and releases all its
@@ -875,8 +850,7 @@ int mv_surveillance_event_trigger_create(
  *
  * @see mv_surveillance_event_trigger_create()
  */
-int mv_surveillance_event_trigger_destroy(
-		mv_surveillance_event_trigger_h trigger);
+int mv_surveillance_event_trigger_destroy(mv_surveillance_event_trigger_h trigger);
 
 /**
  * @brief Gets the surveillance event trigger type as character string.
@@ -894,9 +868,7 @@ int mv_surveillance_event_trigger_destroy(
  * @pre Event trigger has to be created by
  *      mv_surveillance_event_trigger_create() function
  */
-int mv_surveillance_get_event_trigger_type(
-		mv_surveillance_event_trigger_h trigger,
-		char **event_type);
+int mv_surveillance_get_event_trigger_type(mv_surveillance_event_trigger_h trigger, char **event_type);
 
 /**
  * @brief Sets ROI (Region Of Interest) to the event trigger.
@@ -924,10 +896,8 @@ int mv_surveillance_get_event_trigger_type(
  * @see mv_surveillance_event_trigger_h
  * @see mv_surveillance_get_event_trigger_roi()
  */
-int mv_surveillance_set_event_trigger_roi(
-		mv_surveillance_event_trigger_h trigger,
-		int number_of_points,
-		mv_point_s *roi);
+int mv_surveillance_set_event_trigger_roi(mv_surveillance_event_trigger_h trigger, int number_of_points,
+										  mv_point_s *roi);
 
 /**
  * @brief Gets ROI (Region Of Interest) from the event trigger.
@@ -952,10 +922,8 @@ int mv_surveillance_set_event_trigger_roi(
  * @see mv_surveillance_event_trigger_h
  * @see mv_surveillance_set_event_trigger_roi()
  */
-int mv_surveillance_get_event_trigger_roi(
-		mv_surveillance_event_trigger_h trigger,
-		int *number_of_points,
-		mv_point_s **roi);
+int mv_surveillance_get_event_trigger_roi(mv_surveillance_event_trigger_h trigger, int *number_of_points,
+										  mv_point_s **roi);
 
 /**
  * @brief Subscribes @a trigger to process sources pushed from video identified
@@ -991,12 +959,9 @@ int mv_surveillance_get_event_trigger_roi(
  * @see mv_surveillance_unsubscribe_event_trigger()
  * @see mv_surveillance_push_source()
  */
-int mv_surveillance_subscribe_event_trigger(
-		mv_surveillance_event_trigger_h trigger,
-		int video_stream_id,
-		mv_engine_config_h engine_cfg,
-		mv_surveillance_event_occurred_cb callback,
-		void *user_data);
+int mv_surveillance_subscribe_event_trigger(mv_surveillance_event_trigger_h trigger, int video_stream_id,
+											mv_engine_config_h engine_cfg, mv_surveillance_event_occurred_cb callback,
+											void *user_data);
 
 /**
  * @brief Unsubscribes @a trigger from the event and stop calling @a video_stream_id.
@@ -1019,9 +984,7 @@ int mv_surveillance_subscribe_event_trigger(
  * @see mv_surveillance_event_trigger_h
  * @see mv_surveillance_subscribe_event_trigger()
  */
-int mv_surveillance_unsubscribe_event_trigger(
-		mv_surveillance_event_trigger_h trigger,
-		int video_stream_id);
+int mv_surveillance_unsubscribe_event_trigger(mv_surveillance_event_trigger_h trigger, int video_stream_id);
 
 /**
  * @brief Pushes source to the surveillance system to detect events.
@@ -1051,9 +1014,7 @@ int mv_surveillance_unsubscribe_event_trigger(
  * @see mv_surveillance_subscribe_event_trigger()
  * @see mv_surveillance_unsubscribe_event_trigger()
  */
-int mv_surveillance_push_source(
-		mv_source_h source,
-		int video_stream_id);
+int mv_surveillance_push_source(mv_source_h source, int video_stream_id);
 
 /**
  * @brief Starts traversing through list of supported event types.
@@ -1074,9 +1035,7 @@ int mv_surveillance_push_source(
  * @see mv_surveillance_event_type_cb()
  * @see mv_surveillance_foreach_event_result_name()
  */
-int mv_surveillance_foreach_supported_event_type(
-		mv_surveillance_event_type_cb callback,
-		void *user_data);
+int mv_surveillance_foreach_supported_event_type(mv_surveillance_event_type_cb callback, void *user_data);
 
 /**
  * @brief Starts traversing through list of supported event result value names.
@@ -1103,10 +1062,8 @@ int mv_surveillance_foreach_supported_event_type(
  * @see mv_surveillance_foreach_supported_event_type()
  * @see mv_surveillance_get_result_value()
  */
-int mv_surveillance_foreach_event_result_name(
-		const char *event_type,
-		mv_surveillance_event_result_name_cb callback,
-		void *user_data);
+int mv_surveillance_foreach_event_result_name(const char *event_type, mv_surveillance_event_result_name_cb callback,
+											  void *user_data);
 
 /**
  * @brief Gets result value.
@@ -1138,10 +1095,7 @@ int mv_surveillance_foreach_event_result_name(
  * @see mv_surveillance_foreach_supported_event_type()
  * @see mv_surveillance_foreach_event_result_name()
  */
-int mv_surveillance_get_result_value(
-		mv_surveillance_result_h result,
-		const char *name,
-		void *value);
+int mv_surveillance_get_result_value(mv_surveillance_result_h result, const char *name, void *value);
 
 /**
  * @}
diff --git a/include/mv_surveillance_private.h b/include/mv_surveillance_private.h
index 1097370..c64e1b5 100644
--- a/include/mv_surveillance_private.h
+++ b/include/mv_surveillance_private.h
@@ -33,11 +33,12 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-typedef struct {
-	unsigned int trigger_id;     /**< Unique event trigger identifier */
-	char *event_type;            /**< Type of the event */
-	int number_of_roi_points;    /**< Number of ROI (Region of interest) points */
-	mv_point_s *roi;             /**< ROI points array */
+typedef struct
+{
+	unsigned int trigger_id; /**< Unique event trigger identifier */
+	char *event_type; /**< Type of the event */
+	int number_of_roi_points; /**< Number of ROI (Region of interest) points */
+	mv_point_s *roi; /**< ROI points array */
 } mv_surveillance_event_trigger_s;
 
 #ifdef __cplusplus
diff --git a/mv_barcode/barcode_detector/include/Barcode.h b/mv_barcode/barcode_detector/include/Barcode.h
index 79c76c5..46c24a5 100644
--- a/mv_barcode/barcode_detector/include/Barcode.h
+++ b/mv_barcode/barcode_detector/include/Barcode.h
@@ -22,13 +22,16 @@
 #include <stddef.h>
 #include <zbar.h>
 
-namespace MediaVision {
-namespace Barcode {
+namespace MediaVision
+{
+namespace Barcode
+{
 /**
  * @class    Barcode
  * @brief    Handle to barcode object.
  */
-class Barcode {
+class Barcode
+{
 public:
 	/**
 	 * @brief   Barcode constructor.
@@ -38,7 +41,7 @@ public:
 	 * @param   [in] barObj zbar barcode handle
 	 *
 	 */
-	Barcode(const zbar::Symbol& barObj);
+	Barcode(const zbar::Symbol &barObj);
 
 	/**
 	 * @brief  Barcode destructor.
@@ -72,7 +75,7 @@ public:
 	 * @return @c MEDIA_VISION_ERROR_NONE on success,
 	 *         otherwise a negative error value
 	 */
-	int calculateLocation(mv_quadrangle_s& location) const;
+	int calculateLocation(mv_quadrangle_s &location) const;
 
 private:
 	const zbar::Symbol *__pBarcodeObj; ///< Pointer to zbar barcode handle
diff --git a/mv_barcode/barcode_detector/include/BarcodeUtils.h b/mv_barcode/barcode_detector/include/BarcodeUtils.h
index 2d1392b..72fb8d0 100644
--- a/mv_barcode/barcode_detector/include/BarcodeUtils.h
+++ b/mv_barcode/barcode_detector/include/BarcodeUtils.h
@@ -21,13 +21,15 @@
 #include <opencv2/core/core.hpp>
 #include <opencv2/imgproc/imgproc.hpp>
 
-namespace zbar {
-	class Image;
+namespace zbar
+{
+class Image;
 }
 
-namespace MediaVision {
-namespace Barcode {
-
+namespace MediaVision
+{
+namespace Barcode
+{
 /**
  * @brief    This function converts media vision image handle to zbar image handle.
  *
@@ -37,7 +39,7 @@ namespace Barcode {
  * @return @c MEDIA_VISION_ERROR_NONE on success,
            otherwise a negative error value
  */
-int convertSourceMV2Zbar(mv_source_h mvSource, zbar::Image& zbarSource);
+int convertSourceMV2Zbar(mv_source_h mvSource, zbar::Image &zbarSource);
 
 } /* Barcode */
 } /* MediaVision */
diff --git a/mv_barcode/barcode_detector/include/mv_barcode_detect_open.h b/mv_barcode/barcode_detector/include/mv_barcode_detect_open.h
index 8631b36..413a6da 100644
--- a/mv_barcode/barcode_detector/include/mv_barcode_detect_open.h
+++ b/mv_barcode/barcode_detector/include/mv_barcode_detect_open.h
@@ -52,12 +52,8 @@ extern "C" {
  *
  * @see mv_barcode_detected_cb()
  */
-int mv_barcode_detect_open(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s roi,
-		mv_barcode_detected_cb detect_cb,
-		void *user_data);
+int mv_barcode_detect_open(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s roi,
+						   mv_barcode_detected_cb detect_cb, void *user_data);
 
 #ifdef __cplusplus
 }
diff --git a/mv_barcode/barcode_detector/src/Barcode.cpp b/mv_barcode/barcode_detector/src/Barcode.cpp
index b6ef76c..7e61d70 100644
--- a/mv_barcode/barcode_detector/src/Barcode.cpp
+++ b/mv_barcode/barcode_detector/src/Barcode.cpp
@@ -18,11 +18,11 @@
 
 #include <mv_private.h>
 
-namespace MediaVision {
-namespace Barcode {
-
-Barcode::Barcode(const zbar::Symbol& barObj):
-				__pBarcodeObj(new zbar::Symbol(barObj))
+namespace MediaVision
+{
+namespace Barcode
+{
+Barcode::Barcode(const zbar::Symbol &barObj) : __pBarcodeObj(new zbar::Symbol(barObj))
 {
 	; /* NULL */
 }
@@ -92,7 +92,7 @@ mv_barcode_type_e Barcode::getType(void) const
 	}
 }
 
-int Barcode::calculateLocation(mv_quadrangle_s& location) const
+int Barcode::calculateLocation(mv_quadrangle_s &location) const
 {
 	const int numberOfVertexes = 4;
 
@@ -101,13 +101,12 @@ int Barcode::calculateLocation(mv_quadrangle_s& location) const
 	/* polygon location should contain at least 4 points */
 	if (locationPolygonSize < numberOfVertexes) {
 		LOGE("Can't compute location of the barcode by %i"
-				" points (less then %i).", locationPolygonSize,
-				numberOfVertexes);
+			 " points (less then %i).",
+			 locationPolygonSize, numberOfVertexes);
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 	/* bounding quadrangle is computing by 4 marginal points */
-	mv_point_s first = {__pBarcodeObj->get_location_x(0),
-		__pBarcodeObj->get_location_y(0)};
+	mv_point_s first = { __pBarcodeObj->get_location_x(0), __pBarcodeObj->get_location_y(0) };
 
 	int minX = first.x;
 	int maxX = first.x;
@@ -115,8 +114,7 @@ int Barcode::calculateLocation(mv_quadrangle_s& location) const
 	int maxY = first.y;
 
 	for (int i = 0; i < locationPolygonSize; ++i) {
-		mv_point_s current = {__pBarcodeObj->get_location_x(i),
-			__pBarcodeObj->get_location_y(i)};
+		mv_point_s current = { __pBarcodeObj->get_location_x(i), __pBarcodeObj->get_location_y(i) };
 		if (current.x < minX) {
 			minX = current.x;
 		} else if (current.x > maxX) {
@@ -141,10 +139,10 @@ int Barcode::calculateLocation(mv_quadrangle_s& location) const
 	if (abs(minX - maxX) < 5 || abs(minY - maxY) < 5)
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 
-	mv_point_s bottomLeft = {minX, maxY};
-	mv_point_s bottomRight = {maxX, maxY};
-	mv_point_s topRight = {maxX, minY};
-	mv_point_s topLeft = {minX, minY};
+	mv_point_s bottomLeft = { minX, maxY };
+	mv_point_s bottomRight = { maxX, maxY };
+	mv_point_s topRight = { maxX, minY };
+	mv_point_s topLeft = { minX, minY };
 
 	location.points[0] = topLeft;
 	location.points[1] = topRight;
diff --git a/mv_barcode/barcode_detector/src/BarcodeUtils.cpp b/mv_barcode/barcode_detector/src/BarcodeUtils.cpp
index 807a92b..f002dcd 100644
--- a/mv_barcode/barcode_detector/src/BarcodeUtils.cpp
+++ b/mv_barcode/barcode_detector/src/BarcodeUtils.cpp
@@ -21,11 +21,12 @@
 
 #include <zbar.h>
 
-namespace MediaVision {
-namespace Barcode {
-
+namespace MediaVision
+{
+namespace Barcode
+{
 // LCOV_EXCL_START
-int convertSourceMV2Zbar(mv_source_h mvSource, zbar::Image& zbarSource)
+int convertSourceMV2Zbar(mv_source_h mvSource, zbar::Image &zbarSource)
 {
 	int err = MEDIA_VISION_ERROR_NONE;
 	unsigned char *buffer = NULL;
@@ -37,11 +38,11 @@ int convertSourceMV2Zbar(mv_source_h mvSource, zbar::Image& zbarSource)
 	err = mv_source_get_colorspace_c(mvSource, &colorspace);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Can't determine mv_source_h colorspace to convert"
-				" to ZBar colorspace. Conversion failed");
+			 " to ZBar colorspace. Conversion failed");
 		return err;
 	}
 
-	switch(colorspace) {
+	switch (colorspace) {
 	case MEDIA_VISION_COLORSPACE_Y800:
 		zbarSource.set_format("Y800");
 		break;
diff --git a/mv_barcode/barcode_detector/src/mv_barcode_detect.c b/mv_barcode/barcode_detector/src/mv_barcode_detect.c
index c46d12a..aa36a95 100644
--- a/mv_barcode/barcode_detector/src/mv_barcode_detect.c
+++ b/mv_barcode/barcode_detector/src/mv_barcode_detect.c
@@ -27,12 +27,8 @@
  * @brief This file contains the porting layer for Media Vision barcode module.
  */
 
-int mv_barcode_detect(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s roi,
-		mv_barcode_detected_cb detect_cb,
-		void *user_data)
+int mv_barcode_detect(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s roi,
+					  mv_barcode_detected_cb detect_cb, void *user_data)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_barcode_detect_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -56,16 +52,14 @@ int mv_barcode_detect(
 		return ret;
 	}
 
-	if (roi.point.x < 0 || roi.point.y < 0 ||
-		(unsigned int)(roi.point.x + roi.width) > src_w ||
-		(unsigned int)(roi.point.y + roi.height) > src_h) {
+	if (roi.point.x < 0 || roi.point.y < 0 || (unsigned int) (roi.point.x + roi.width) > src_w ||
+		(unsigned int) (roi.point.y + roi.height) > src_h) {
 		LOGE("roi is out of area on source");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
 	/* Use open barcode detect functionality here. */
-	ret = mv_barcode_detect_open(
-					source, engine_cfg, roi, detect_cb, user_data);
+	ret = mv_barcode_detect_open(source, engine_cfg, roi, detect_cb, user_data);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
diff --git a/mv_barcode/barcode_detector/src/mv_barcode_detect_open.cpp b/mv_barcode/barcode_detector/src/mv_barcode_detect_open.cpp
index c2a7e83..d375e53 100644
--- a/mv_barcode/barcode_detector/src/mv_barcode_detect_open.cpp
+++ b/mv_barcode/barcode_detector/src/mv_barcode_detect_open.cpp
@@ -28,12 +28,8 @@
 
 using namespace MediaVision::Barcode;
 
-int mv_barcode_detect_open(
-	mv_source_h source,
-	mv_engine_config_h engine_cfg,
-	mv_rectangle_s roi,
-	mv_barcode_detected_cb detect_cb,
-	void *user_data)
+int mv_barcode_detect_open(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s roi,
+						   mv_barcode_detected_cb detect_cb, void *user_data)
 {
 	if (!source || !detect_cb)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -41,13 +37,10 @@ int mv_barcode_detect_open(
 	zbar::ImageScanner scanner;
 
 	int target_val;
-	int err = mv_engine_config_get_int_attribute(
-			engine_cfg,
-			"MV_BARCODE_DETECT_ATTR_TARGET",
-		&target_val);
+	int err = mv_engine_config_get_int_attribute(engine_cfg, "MV_BARCODE_DETECT_ATTR_TARGET", &target_val);
 	if (err != MEDIA_VISION_ERROR_NONE || engine_cfg == NULL) {
 		LOGW("mv_engine_config_get_int_attribute failed."
-			"MV_BARCODE_DETECT_ATTR_TARGET_ALL is used as default");
+			 "MV_BARCODE_DETECT_ATTR_TARGET_ALL is used as default");
 		/* Default value */
 		target_val = 0;
 	}
@@ -78,7 +71,7 @@ int mv_barcode_detect_open(
 		scanner.set_config(zbar::ZBAR_DATABAR_EXP, zbar::ZBAR_CFG_ENABLE, 1);
 		scanner.set_config(zbar::ZBAR_QRCODE, zbar::ZBAR_CFG_ENABLE, 1);
 		break;
-// LCOV_EXCL_START
+		// LCOV_EXCL_START
 	case 1:
 		scanner.set_config(zbar::ZBAR_UPCA, zbar::ZBAR_CFG_ENABLE, 1);
 		scanner.set_config(zbar::ZBAR_UPCE, zbar::ZBAR_CFG_ENABLE, 1);
@@ -97,7 +90,7 @@ int mv_barcode_detect_open(
 	case 2:
 		scanner.set_config(zbar::ZBAR_QRCODE, zbar::ZBAR_CFG_ENABLE, 1);
 		break;
-// LCOV_EXCL_STOP
+		// LCOV_EXCL_STOP
 	default:
 		LOGW("Unavailable target value %d", target_val);
 	}
@@ -107,37 +100,27 @@ int mv_barcode_detect_open(
 	int rotateDirection = 0;
 	bool isEnhancementMode = false;
 	if (engine_cfg != NULL) {
-		err = mv_engine_config_get_int_attribute(
-				engine_cfg,
-				MV_BARCODE_DETECT_ATTR_ROTATION_DEGREES,
-				&rotateDegree);
+		err = mv_engine_config_get_int_attribute(engine_cfg, MV_BARCODE_DETECT_ATTR_ROTATION_DEGREES, &rotateDegree);
 		if (err != MEDIA_VISION_ERROR_NONE) {
 			LOGE("mv_engine_config_get_int_attribute failed to get MV_BARCODE_DETECT_ATTR_ROTATE_DEGREES");
 			return err;
 		}
 
-		err = mv_engine_config_get_int_attribute(
-				engine_cfg,
-				MV_BARCODE_DETECT_ATTR_ROTATION_COUNT,
-				&rotateNumber);
+		err = mv_engine_config_get_int_attribute(engine_cfg, MV_BARCODE_DETECT_ATTR_ROTATION_COUNT, &rotateNumber);
 		if (err != MEDIA_VISION_ERROR_NONE) {
 			LOGE("mv_engine_config_get_int_attribute failed to get MV_BARCODE_DETECT_ATTR_ROTATE_COUNT");
 			return err;
 		}
 
-		err = mv_engine_config_get_int_attribute(
-				engine_cfg,
-				MV_BARCODE_DETECT_ATTR_ROTATION_DIRECTION,
-				&rotateDirection);
+		err = mv_engine_config_get_int_attribute(engine_cfg, MV_BARCODE_DETECT_ATTR_ROTATION_DIRECTION,
+												 &rotateDirection);
 		if (err != MEDIA_VISION_ERROR_NONE) {
 			LOGE("mv_engine_config_get_int_attribute failed to get MV_BARCODE_DETECT_ATTR_ROTATE_DIRECTION");
 			return err;
 		}
 
-		err = mv_engine_config_get_bool_attribute(
-				engine_cfg,
-				MV_BARCODE_DETECT_ATTR_USE_ENHANCEMENT,
-				&isEnhancementMode);
+		err = mv_engine_config_get_bool_attribute(engine_cfg, MV_BARCODE_DETECT_ATTR_USE_ENHANCEMENT,
+												  &isEnhancementMode);
 		if (err != MEDIA_VISION_ERROR_NONE) {
 			LOGE("mv_engine_config_get_bool_attribute failed to get MV_BARCODE_DETECT_ATTR_USE_ENHANCEMENT");
 			return err;
@@ -182,14 +165,14 @@ int mv_barcode_detect_open(
 		} else if (rotateDirection == MV_BARCODE_DETECT_ATTR_ROTATION_COUNTER_CLOCKWISE) {
 			degree = rotateDegree * i;
 		} else { // MV_BARCODE_DETECT_ATTR_ROTATE_ALL
-			if (i%2) {
-				degree = -1 * rotateDegree * ((i+1)/2);
+			if (i % 2) {
+				degree = -1 * rotateDegree * ((i + 1) / 2);
 			} else {
-				degree =  rotateDegree * (i/2);
+				degree = rotateDegree * (i / 2);
 			}
 		}
 
-		rotMat = cv::getRotationMatrix2D(cv::Point((roi.width/2), (roi.height/2)), degree, 1.0);
+		rotMat = cv::getRotationMatrix2D(cv::Point((roi.width / 2), (roi.height / 2)), degree, 1.0);
 		warpAffine(rawBuffer, rotBuffer, rotMat, rawBuffer.size());
 
 		_image.set_format("Y800");
@@ -211,9 +194,7 @@ int mv_barcode_detect_open(
 		barcodeTypes.clear();
 		barcodeLocations.clear();
 		bool isDetected = true;
-		for (zbar::SymbolIterator symbol = _image.symbol_begin();
-			symbol != _image.symbol_end(); ++symbol) {
-
+		for (zbar::SymbolIterator symbol = _image.symbol_begin(); symbol != _image.symbol_end(); ++symbol) {
 			Barcode curBarcode(*symbol);
 			mv_quadrangle_s location;
 			int err = curBarcode.calculateLocation(location);
@@ -229,12 +210,11 @@ int mv_barcode_detect_open(
 
 		if (isDetected) {
 			LOGI("Call the detect callback for %d detected barcodes", numberOfBarcodes);
-			const char **messagesArray = new const char*[numberOfBarcodes];
+			const char **messagesArray = new const char *[numberOfBarcodes];
 			mv_barcode_type_e *types = new mv_barcode_type_e[numberOfBarcodes];
 			mv_quadrangle_s *locations = new mv_quadrangle_s[numberOfBarcodes];
 
 			for (int i = 0; i < numberOfBarcodes; ++i) {
-
 				size_t messageLength = barcodeMessages[i].size();
 				char *curMessage = new char[messageLength + 1];
 				barcodeMessages[i].copy(curMessage, messageLength);
@@ -245,8 +225,7 @@ int mv_barcode_detect_open(
 				locations[i] = barcodeLocations[i];
 				LOGI("%d: barcode with %s with type %d", i, messagesArray[i], types[i]);
 			}
-			detect_cb(source, engine_cfg, locations, messagesArray, types,
-					numberOfBarcodes, user_data);
+			detect_cb(source, engine_cfg, locations, messagesArray, types, numberOfBarcodes, user_data);
 			LOGI("Clean the memory from barcodes messages and types");
 			for (int j = 0; j < numberOfBarcodes; ++j)
 				delete[] messagesArray[j];
@@ -258,8 +237,7 @@ int mv_barcode_detect_open(
 		}
 	}
 	LOGI("Call the detect callback for 0 detected barcodes");
-	detect_cb(source, engine_cfg, NULL, NULL,
-			NULL, 0, user_data);
+	detect_cb(source, engine_cfg, NULL, NULL, NULL, 0, user_data);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
diff --git a/mv_barcode/barcode_generator/include/BarcodeGenerator.h b/mv_barcode/barcode_generator/include/BarcodeGenerator.h
index 288e169..9f7075d 100644
--- a/mv_barcode/barcode_generator/include/BarcodeGenerator.h
+++ b/mv_barcode/barcode_generator/include/BarcodeGenerator.h
@@ -26,15 +26,18 @@
  * @brief This file contains the BarcodeGenerator class.
  */
 
-namespace MediaVision {
-namespace Barcode {
+namespace MediaVision
+{
+namespace Barcode
+{
 /**
  * @brief This class implements barcode generation.
  * @details 1D Barcodes and 2D QR codes are supported.
  *
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  */
-class BarcodeGenerator {
+class BarcodeGenerator
+{
 public:
 	/**
 	 * @brief This method generates Barcodes image according to options.
@@ -55,19 +58,12 @@ public:
 	 * @return BARCODE_ERROR_NONE from BarcodeError which is 0 if success,
 	 *         BarcodeError value otherwise
 	 */
-	static int generateBarcodeToImage(
-		const std::string& imageFileName,
-		BarcodeImageFormat imageFormat,
-		const int imageWidth,
-		const int imageHeight,
-		const std::string& message,
-		BarcodeType type,
-		BarcodeQREncodingMode encodingMode = BARCODE_QR_MODE_UNAVAILABLE,
-		BarcodeQRErrorCorrectionLevel correctionLevel = BARCODE_QR_ECC_UNAVAILABLE,
-		int qrVersion = 0,
-		int showText = 0,
-		char *fgcolour = NULL,
-		char *bgcolur = NULL);
+	static int generateBarcodeToImage(const std::string &imageFileName, BarcodeImageFormat imageFormat,
+									  const int imageWidth, const int imageHeight, const std::string &message,
+									  BarcodeType type,
+									  BarcodeQREncodingMode encodingMode = BARCODE_QR_MODE_UNAVAILABLE,
+									  BarcodeQRErrorCorrectionLevel correctionLevel = BARCODE_QR_ECC_UNAVAILABLE,
+									  int qrVersion = 0, int showText = 0, char *fgcolour = NULL, char *bgcolur = NULL);
 
 	/**
 	 * @brief This method generates Barcodes image buffer according to options.
@@ -88,23 +84,15 @@ public:
 	 * @return BARCODE_ERROR_NONE from BarcodeError which is 0 if success,
 	 *         BarcodeError value otherwise
 	 */
-	static int generateBarcodeToBuffer(
-		unsigned char **imageBuffer,
-		unsigned int *imageWidth,
-		unsigned int *imageHeight,
-		unsigned int *imageChannels,
-		const std::string& message,
-		BarcodeType type,
-		BarcodeQREncodingMode encodingMode = BARCODE_QR_MODE_UNAVAILABLE,
-		BarcodeQRErrorCorrectionLevel correctionLevel = BARCODE_QR_ECC_UNAVAILABLE,
-		int qrVersion = 0,
-		int showText = 0,
-		char *fgcolour = NULL,
-		char *bgcolur = NULL);
+	static int generateBarcodeToBuffer(unsigned char **imageBuffer, unsigned int *imageWidth, unsigned int *imageHeight,
+									   unsigned int *imageChannels, const std::string &message, BarcodeType type,
+									   BarcodeQREncodingMode encodingMode = BARCODE_QR_MODE_UNAVAILABLE,
+									   BarcodeQRErrorCorrectionLevel correctionLevel = BARCODE_QR_ECC_UNAVAILABLE,
+									   int qrVersion = 0, int showText = 0, char *fgcolour = NULL,
+									   char *bgcolur = NULL);
 };
 
 } /* Barcode */
 } /* MediaVision */
 
 #endif /* __MEDIA_VISION_BARCODE_GENERATOR_H__ */
-
diff --git a/mv_barcode/barcode_generator/include/BarcodeOptions.h b/mv_barcode/barcode_generator/include/BarcodeOptions.h
index 5399b8a..1a2cbfd 100644
--- a/mv_barcode/barcode_generator/include/BarcodeOptions.h
+++ b/mv_barcode/barcode_generator/include/BarcodeOptions.h
@@ -22,14 +22,17 @@
  * @brief This file contains the Barcode options.
  */
 
-namespace MediaVision {
-namespace Barcode {
+namespace MediaVision
+{
+namespace Barcode
+{
 /**
  * @brief The Barcode type enumeration.
  *
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  */
-enum BarcodeType {
+enum BarcodeType
+{
 	BARCODE_QR = 58,
 	BARCODE_UPCA = 34,
 	BARCODE_UPCE = 37,
@@ -52,7 +55,8 @@ enum BarcodeType {
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  * @remarks This is unavailable for 1D barcodes.
  */
-enum BarcodeQRErrorCorrectionLevel {
+enum BarcodeQRErrorCorrectionLevel
+{
 	BARCODE_QR_ECC_UNAVAILABLE = 0,
 	BARCODE_QR_ECC_LOW = 1,
 	BARCODE_QR_ECC_MEDIUM = 2,
@@ -66,7 +70,8 @@ enum BarcodeQRErrorCorrectionLevel {
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  * @remarks This is unavailable for 1D barcodes.
  */
-enum BarcodeQREncodingMode {
+enum BarcodeQREncodingMode
+{
 	BARCODE_QR_MODE_NUMERIC = 1,
 	BARCODE_QR_MODE_ALPHANUMERIC = 1,
 	BARCODE_QR_MODE_BYTE = 0,
@@ -80,7 +85,8 @@ enum BarcodeQREncodingMode {
  *
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  */
-enum BarcodeImageFormat {
+enum BarcodeImageFormat
+{
 	BARCODE_IMAGE_JPG,
 	BARCODE_IMAGE_PNG,
 	BARCODE_IMAGE_BMP
@@ -91,7 +97,8 @@ enum BarcodeImageFormat {
  *
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  */
-enum BarcodeGenTextOpt {
+enum BarcodeGenTextOpt
+{
 	BARCODE_GEN_TEXT_INVISIBLE,
 	BARCODE_GEN_TEXT_VISIBLE
 };
@@ -101,7 +108,8 @@ enum BarcodeGenTextOpt {
  *
  * @since_tizen @if MOBILE 2.4 @else 3.0 @endif
  */
-enum BarcodeError {
+enum BarcodeError
+{
 	BARCODE_ERROR_NONE = 0,
 	BARCODE_WARNING_INVALID_OPTION = 2,
 	BARCODE_ERROR_TOO_LONG = 5,
@@ -118,4 +126,3 @@ enum BarcodeError {
 } /* MediaVision */
 
 #endif /* __MEDIA_VISION_BARCODE_OPTIONS_H__ */
-
diff --git a/mv_barcode/barcode_generator/include/mv_barcode_generate_open.h b/mv_barcode/barcode_generator/include/mv_barcode_generate_open.h
index 612a681..772668d 100644
--- a/mv_barcode/barcode_generator/include/mv_barcode_generate_open.h
+++ b/mv_barcode/barcode_generator/include/mv_barcode_generate_open.h
@@ -54,13 +54,9 @@ extern "C" {
  *
  * @see mv_barcode_generate_image_open()
  */
-int mv_barcode_generate_source_open(mv_engine_config_h engine_cfg,
-		const char *message,
-		mv_barcode_type_e type,
-		mv_barcode_qr_mode_e qr_enc_mode,
-		mv_barcode_qr_ecc_e qr_ecc,
-		int qr_version,
-		mv_source_h image);
+int mv_barcode_generate_source_open(mv_engine_config_h engine_cfg, const char *message, mv_barcode_type_e type,
+									mv_barcode_qr_mode_e qr_enc_mode, mv_barcode_qr_ecc_e qr_ecc, int qr_version,
+									mv_source_h image);
 
 /**
  * @brief Generates image file with barcode.
@@ -90,17 +86,10 @@ int mv_barcode_generate_source_open(mv_engine_config_h engine_cfg,
  *
  * @see mv_barcode_generate_source_open()
  */
-int mv_barcode_generate_image_open(
-		mv_engine_config_h engine_cfg,
-		const char *message,
-		int image_width,
-		int image_height,
-		mv_barcode_type_e type,
-		mv_barcode_qr_mode_e qr_enc_mode,
-		mv_barcode_qr_ecc_e qr_ecc,
-		int qr_version,
-		const char *image_path,
-		mv_barcode_image_format_e image_format);
+int mv_barcode_generate_image_open(mv_engine_config_h engine_cfg, const char *message, int image_width,
+								   int image_height, mv_barcode_type_e type, mv_barcode_qr_mode_e qr_enc_mode,
+								   mv_barcode_qr_ecc_e qr_ecc, int qr_version, const char *image_path,
+								   mv_barcode_image_format_e image_format);
 
 #ifdef __cplusplus
 }
diff --git a/mv_barcode/barcode_generator/src/BarcodeGenerator.cpp b/mv_barcode/barcode_generator/src/BarcodeGenerator.cpp
index c54bfe1..9798da0 100644
--- a/mv_barcode/barcode_generator/src/BarcodeGenerator.cpp
+++ b/mv_barcode/barcode_generator/src/BarcodeGenerator.cpp
@@ -31,15 +31,14 @@
 
 #define ZINT_COLOUR_SIZE 10
 
-namespace MediaVision {
-namespace Barcode {
-
-namespace {
-
-int getFormatEncodingInfo(
-		BarcodeImageFormat imageFormat,
-		std::vector<std::string>& extensions,
-		std::vector<int>& compressionParams)
+namespace MediaVision
+{
+namespace Barcode
+{
+namespace
+{
+int getFormatEncodingInfo(BarcodeImageFormat imageFormat, std::vector<std::string> &extensions,
+						  std::vector<int> &compressionParams)
 {
 	static const int PNG_COMPRESSION_LEVEL = 3;
 
@@ -67,16 +66,9 @@ int getFormatEncodingInfo(
 	return BARCODE_ERROR_NONE;
 }
 
-int createBarcode(
-		const std::string& message,
-		BarcodeType type,
-		BarcodeQREncodingMode encodingMode,
-		BarcodeQRErrorCorrectionLevel correctionLevel,
-		int qrVersion,
-		int showText,
-		char *fgcolour,
-		char *bgcolour,
-		zint_symbol *symbol)
+int createBarcode(const std::string &message, BarcodeType type, BarcodeQREncodingMode encodingMode,
+				  BarcodeQRErrorCorrectionLevel correctionLevel, int qrVersion, int showText, char *fgcolour,
+				  char *bgcolour, zint_symbol *symbol)
 {
 	/* set input values */
 	symbol->symbology = type;
@@ -88,21 +80,21 @@ int createBarcode(
 
 	/* set default values */
 	if (fgcolour) {
-		std::strncpy(symbol->fgcolour, fgcolour, ZINT_COLOUR_SIZE-1);
+		std::strncpy(symbol->fgcolour, fgcolour, ZINT_COLOUR_SIZE - 1);
 		if (strlen(fgcolour) > 9) {
 			symbol->fgcolour[9] = '\0';
 		}
 	} else {
-		std::strncpy(symbol->fgcolour, "000000", ZINT_COLOUR_SIZE-1);
+		std::strncpy(symbol->fgcolour, "000000", ZINT_COLOUR_SIZE - 1);
 	}
 
 	if (bgcolour) {
-		std::strncpy(symbol->bgcolour, bgcolour, ZINT_COLOUR_SIZE-1);
+		std::strncpy(symbol->bgcolour, bgcolour, ZINT_COLOUR_SIZE - 1);
 		if (strlen(bgcolour) > 9) {
 			symbol->bgcolour[9] = '\0';
 		}
 	} else {
-		std::strncpy(symbol->bgcolour, "ffffff", ZINT_COLOUR_SIZE-1);
+		std::strncpy(symbol->bgcolour, "ffffff", ZINT_COLOUR_SIZE - 1);
 	}
 
 	LOGI("Check colors: front %s, back %s", symbol->fgcolour, symbol->bgcolour);
@@ -118,25 +110,19 @@ int createBarcode(
 
 	/* create barcode */
 	const int rotationAngle = 0;
-	int error = ZBarcode_Encode_and_Buffer(
-					symbol,
-					(unsigned char*)(message.c_str()),
-					message.length(),
-					rotationAngle);
+	int error =
+			ZBarcode_Encode_and_Buffer(symbol, (unsigned char *) (message.c_str()), message.length(), rotationAngle);
 
 	return error;
 }
 
-int writeBufferToImageFile(
-		zint_symbol *symbol,
-		const std::string& imageFileName,
-		BarcodeImageFormat imageFormat,
-		const int imageWidth,
-		const int imageHeight)
+int writeBufferToImageFile(zint_symbol *symbol, const std::string &imageFileName, BarcodeImageFormat imageFormat,
+						   const int imageWidth, const int imageHeight)
 {
 	if (imageWidth <= 0 || imageHeight <= 0) {
 		LOGE("Barcode image size is invalid: %i x %i. Terminate write to "
-			"the image operation", imageWidth, imageHeight);
+			 "the image operation",
+			 imageWidth, imageHeight);
 		return BARCODE_ERROR_INVALID_DATA;
 	}
 
@@ -154,8 +140,7 @@ int writeBufferToImageFile(
 	std::vector<std::string> expectedExtensions;
 	std::vector<int> compressionParams;
 
-	int error = getFormatEncodingInfo(imageFormat,
-				expectedExtensions, compressionParams);
+	int error = getFormatEncodingInfo(imageFormat, expectedExtensions, compressionParams);
 
 	if (BARCODE_ERROR_NONE != error || expectedExtensions.empty()) {
 		LOGE("Image format is incorrectly specified or not supported");
@@ -169,12 +154,9 @@ int writeBufferToImageFile(
 	for (size_t extNum = 0; extNum < expectedExtensions.size(); ++extNum) {
 		if (resultFilePath.size() >= expectedExtensions[extNum].size()) {
 			std::string givenExtension = resultFilePath.substr(
-				resultFilePath.length() - expectedExtensions[extNum].size(),
-				expectedExtensions[extNum].size());
+					resultFilePath.length() - expectedExtensions[extNum].size(), expectedExtensions[extNum].size());
 
-			std::transform(
-				givenExtension.begin(), givenExtension.end(),
-				givenExtension.begin(), ::tolower);
+			std::transform(givenExtension.begin(), givenExtension.end(), givenExtension.begin(), ::tolower);
 
 			if (givenExtension == expectedExtensions[extNum]) {
 				rightExtensionFlag = true;
@@ -189,12 +171,10 @@ int writeBufferToImageFile(
 	cv::Mat image(symbol->bitmap_height, symbol->bitmap_width, CV_8UC3, symbol->bitmap);
 	cv::resize(image, image, cv::Size(imageWidth, imageHeight), 0, 0, cv::INTER_AREA);
 
-	error = cv::imwrite(resultFilePath, image, compressionParams) ?
-			BARCODE_ERROR_NONE : BARCODE_ERROR_INVALID_DATA;
+	error = cv::imwrite(resultFilePath, image, compressionParams) ? BARCODE_ERROR_NONE : BARCODE_ERROR_INVALID_DATA;
 
 	if (BARCODE_ERROR_NONE != error) {
-		LOGE("Write barcode image to file %s operation failed.",
-				resultFilePath.c_str());
+		LOGE("Write barcode image to file %s operation failed.", resultFilePath.c_str());
 		return error;
 	}
 
@@ -203,37 +183,21 @@ int writeBufferToImageFile(
 
 } /* anonymous namespace */
 
-int BarcodeGenerator::generateBarcodeToImage(
-		const std::string& imageFileName,
-		BarcodeImageFormat imageFormat,
-		const int imageWidth,
-		const int imageHeight,
-		const std::string& message,
-		BarcodeType type,
-		BarcodeQREncodingMode encodingMode,
-		BarcodeQRErrorCorrectionLevel correctionLevel,
-		int qrVersion,
-		int showText,
-		char *fgcolour,
-		char *bgcolour)
+int BarcodeGenerator::generateBarcodeToImage(const std::string &imageFileName, BarcodeImageFormat imageFormat,
+											 const int imageWidth, const int imageHeight, const std::string &message,
+											 BarcodeType type, BarcodeQREncodingMode encodingMode,
+											 BarcodeQRErrorCorrectionLevel correctionLevel, int qrVersion, int showText,
+											 char *fgcolour, char *bgcolour)
 {
 	zint_symbol *symbol = ZBarcode_Create();
 
-	if(symbol == NULL) {
+	if (symbol == NULL) {
 		LOGE("ZBarcode creation failed");
 		return BARCODE_ERROR_ENCODING_PROBLEM;
 	}
 
-	int error = createBarcode(
-					message,
-					type,
-					encodingMode,
-					correctionLevel,
-					qrVersion,
-					showText,
-					fgcolour,
-					bgcolour,
-					symbol);
+	int error = createBarcode(message, type, encodingMode, correctionLevel, qrVersion, showText, fgcolour, bgcolour,
+							  symbol);
 
 	if (error != BARCODE_ERROR_NONE) {
 		LOGE("Barcode creation failed, clean memory");
@@ -241,55 +205,34 @@ int BarcodeGenerator::generateBarcodeToImage(
 		return error;
 	}
 
-	error = writeBufferToImageFile(
-				symbol,
-				imageFileName,
-				imageFormat,
-				imageWidth,
-				imageHeight);
+	error = writeBufferToImageFile(symbol, imageFileName, imageFormat, imageWidth, imageHeight);
 	if (error != BARCODE_ERROR_NONE)
 		LOGE("Barcode [%s] file write fail, clean memory", imageFileName.c_str());
 	else
-		LOGI("Barcode image [%s] is successfully generated, clean memory",
-				imageFileName.c_str());
+		LOGI("Barcode image [%s] is successfully generated, clean memory", imageFileName.c_str());
 
 	ZBarcode_Delete(symbol);
 
 	return error;
 }
 
-int BarcodeGenerator::generateBarcodeToBuffer(
-		unsigned char **imageBuffer,
-		unsigned int *imageWidth,
-		unsigned int *imageHeight,
-		unsigned int *imageChannels,
-		const std::string& message,
-		BarcodeType type,
-		BarcodeQREncodingMode encodingMode,
-		BarcodeQRErrorCorrectionLevel correctionLevel,
-		int qrVersion,
-		int showText,
-		char *fgcolour,
-		char *bgcolour)
+int BarcodeGenerator::generateBarcodeToBuffer(unsigned char **imageBuffer, unsigned int *imageWidth,
+											  unsigned int *imageHeight, unsigned int *imageChannels,
+											  const std::string &message, BarcodeType type,
+											  BarcodeQREncodingMode encodingMode,
+											  BarcodeQRErrorCorrectionLevel correctionLevel, int qrVersion,
+											  int showText, char *fgcolour, char *bgcolour)
 {
 	zint_symbol *symbol = ZBarcode_Create();
 
-	if(symbol == NULL) {
+	if (symbol == NULL) {
 		LOGE("ZBarcode creation failed");
 
 		return BARCODE_ERROR_ENCODING_PROBLEM;
 	}
 
-	int error = createBarcode(
-					message,
-					type,
-					encodingMode,
-					correctionLevel,
-					qrVersion,
-					showText,
-					fgcolour,
-					bgcolour,
-					symbol);
+	int error = createBarcode(message, type, encodingMode, correctionLevel, qrVersion, showText, fgcolour, bgcolour,
+							  symbol);
 
 	if (error != BARCODE_ERROR_NONE) {
 		LOGE("Barcode creation failed, clean memory");
@@ -301,8 +244,7 @@ int BarcodeGenerator::generateBarcodeToBuffer(
 	*imageWidth = symbol->bitmap_width;
 	*imageHeight = symbol->bitmap_height;
 	*imageChannels = 3;
-	const unsigned int imageBufferSize = (*imageWidth) * (*imageHeight) *
-		(*imageChannels);
+	const unsigned int imageBufferSize = (*imageWidth) * (*imageHeight) * (*imageChannels);
 	*imageBuffer = new unsigned char[imageBufferSize];
 	memmove(*imageBuffer, symbol->bitmap, imageBufferSize);
 
diff --git a/mv_barcode/barcode_generator/src/mv_barcode_generate.c b/mv_barcode/barcode_generator/src/mv_barcode_generate.c
index a1340a1..caa3f03 100644
--- a/mv_barcode/barcode_generator/src/mv_barcode_generate.c
+++ b/mv_barcode/barcode_generator/src/mv_barcode_generate.c
@@ -27,15 +27,9 @@
  * @brief This file contains the porting layer for Media Vision barcode module.
  */
 
-
-int mv_barcode_generate_source(
-		mv_engine_config_h engine_cfg,
-		const char *message,
-		mv_barcode_type_e type,
-		mv_barcode_qr_mode_e qr_enc_mode,
-		mv_barcode_qr_ecc_e qr_ecc,
-		int qr_version,
-		mv_source_h image)
+int mv_barcode_generate_source(mv_engine_config_h engine_cfg, const char *message, mv_barcode_type_e type,
+							   mv_barcode_qr_mode_e qr_enc_mode, mv_barcode_qr_ecc_e qr_ecc, int qr_version,
+							   mv_source_h image)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_barcode_generate_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(message);
@@ -43,21 +37,18 @@ int mv_barcode_generate_source(
 
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	if (type < MV_BARCODE_QR ||
-		type >= MV_BARCODE_UNKNOWN || type == MV_BARCODE_UNDEFINED) {
+	if (type < MV_BARCODE_QR || type >= MV_BARCODE_UNKNOWN || type == MV_BARCODE_UNDEFINED) {
 		LOGE("Not supported barcode type [%d]", type);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
 	if (type == MV_BARCODE_QR) {
-		if (qr_enc_mode < MV_BARCODE_QR_MODE_NUMERIC ||
-			qr_enc_mode >= MV_BARCODE_QR_MODE_UNAVAILABLE) {
+		if (qr_enc_mode < MV_BARCODE_QR_MODE_NUMERIC || qr_enc_mode >= MV_BARCODE_QR_MODE_UNAVAILABLE) {
 			LOGE("Not supported QR encoding mode[%d]", qr_enc_mode);
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 		}
 
-		if (qr_ecc < MV_BARCODE_QR_ECC_LOW ||
-			qr_ecc >= MV_BARCODE_QR_ECC_UNAVAILABLE) {
+		if (qr_ecc < MV_BARCODE_QR_ECC_LOW || qr_ecc >= MV_BARCODE_QR_ECC_UNAVAILABLE) {
 			LOGE("Not supported QR ECC level [%d]", qr_ecc);
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 		}
@@ -69,25 +60,15 @@ int mv_barcode_generate_source(
 	}
 
 	/* Use open barcode generate functionality here. */
-	int ret = mv_barcode_generate_source_open(
-					engine_cfg, message, type, qr_enc_mode, qr_ecc, qr_version,
-					image);
+	int ret = mv_barcode_generate_source_open(engine_cfg, message, type, qr_enc_mode, qr_ecc, qr_version, image);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_barcode_generate_image(
-		mv_engine_config_h engine_cfg,
-		const char *message,
-		int image_width,
-		int image_height,
-		mv_barcode_type_e type,
-		mv_barcode_qr_mode_e qr_enc_mode,
-		mv_barcode_qr_ecc_e qr_ecc,
-		int qr_version,
-		const char *image_path,
-		mv_barcode_image_format_e image_format)
+int mv_barcode_generate_image(mv_engine_config_h engine_cfg, const char *message, int image_width, int image_height,
+							  mv_barcode_type_e type, mv_barcode_qr_mode_e qr_enc_mode, mv_barcode_qr_ecc_e qr_ecc,
+							  int qr_version, const char *image_path, mv_barcode_image_format_e image_format)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_barcode_generate_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(message);
@@ -99,21 +80,18 @@ int mv_barcode_generate_image(
 		return MEDIA_VISION_ERROR_INVALID_PATH;
 	}
 
-	if (type < MV_BARCODE_QR ||
-		type >= MV_BARCODE_UNKNOWN || type == MV_BARCODE_UNDEFINED) {
+	if (type < MV_BARCODE_QR || type >= MV_BARCODE_UNKNOWN || type == MV_BARCODE_UNDEFINED) {
 		LOGE("Not supported barcode type [%d]", type);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
 	if (type == MV_BARCODE_QR) {
-		if (qr_enc_mode < MV_BARCODE_QR_MODE_NUMERIC ||
-			qr_enc_mode >= MV_BARCODE_QR_MODE_UNAVAILABLE) {
+		if (qr_enc_mode < MV_BARCODE_QR_MODE_NUMERIC || qr_enc_mode >= MV_BARCODE_QR_MODE_UNAVAILABLE) {
 			LOGE("Not supported QR encoding mode[%d]", qr_enc_mode);
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 		}
 
-		if (qr_ecc < MV_BARCODE_QR_ECC_LOW ||
-			qr_ecc >= MV_BARCODE_QR_ECC_UNAVAILABLE) {
+		if (qr_ecc < MV_BARCODE_QR_ECC_LOW || qr_ecc >= MV_BARCODE_QR_ECC_UNAVAILABLE) {
 			LOGE("Not supported QR ECC level [%d]", qr_ecc);
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 		}
@@ -124,16 +102,14 @@ int mv_barcode_generate_image(
 		}
 	}
 
-	if (image_format < MV_BARCODE_IMAGE_FORMAT_BMP ||
-		image_format >= MV_BARCODE_IMAGE_FORMAT_NUM) {
+	if (image_format < MV_BARCODE_IMAGE_FORMAT_BMP || image_format >= MV_BARCODE_IMAGE_FORMAT_NUM) {
 		LOGE("Not supported image format [%d]", image_format);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
 	/* Use open barcode generate functionality here. */
-	int ret = mv_barcode_generate_image_open(
-					engine_cfg, message, image_width, image_height, type,
-					qr_enc_mode, qr_ecc, qr_version, image_path, image_format);
+	int ret = mv_barcode_generate_image_open(engine_cfg, message, image_width, image_height, type, qr_enc_mode, qr_ecc,
+											 qr_version, image_path, image_format);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
diff --git a/mv_barcode/barcode_generator/src/mv_barcode_generate_open.cpp b/mv_barcode/barcode_generator/src/mv_barcode_generate_open.cpp
index c689f9f..17da765 100644
--- a/mv_barcode/barcode_generator/src/mv_barcode_generate_open.cpp
+++ b/mv_barcode/barcode_generator/src/mv_barcode_generate_open.cpp
@@ -26,24 +26,24 @@
 
 using namespace MediaVision::Barcode;
 
-namespace {
-
-int alphanumToUpper(std::string& strToTransform)
+namespace
+{
+int alphanumToUpper(std::string &strToTransform)
 {
 	std::string tempString = strToTransform;
-	std::transform(tempString.begin(), tempString.end(),
-			tempString.begin(), ::toupper);
+	std::transform(tempString.begin(), tempString.end(), tempString.begin(), ::toupper);
 
-	if (std::string::npos != tempString.find_first_not_of(
-			"0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ $%*+-./:")) {
+	if (std::string::npos != tempString.find_first_not_of("0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ $%*+-./:")) {
 		LOGE("Barcode message can't be converted according to support "
-				"alphanumeric (0..9, A..Z, space, $, %%, *, +, -, ., /, :) "
-				"mode: %s", strToTransform.c_str());
+			 "alphanumeric (0..9, A..Z, space, $, %%, *, +, -, ., /, :) "
+			 "mode: %s",
+			 strToTransform.c_str());
 		return BARCODE_ERROR_INVALID_DATA;
 	}
 
 	LOGI("Barcode message was converted according to support alphanumeric "
-			"mode: %s -> %s", strToTransform.c_str(), tempString.c_str());
+		 "mode: %s -> %s",
+		 strToTransform.c_str(), tempString.c_str());
 	strToTransform = tempString;
 	return BARCODE_ERROR_NONE;
 }
@@ -96,7 +96,8 @@ BarcodeType convertBarcodeType(mv_barcode_type_e type)
 	}
 
 	LOGI("Media vision barcode type has been converted to ZInt barcode type "
-			"(%i -> %i)", type, barcodeType);
+		 "(%i -> %i)",
+		 type, barcodeType);
 	return barcodeType;
 }
 
@@ -119,7 +120,8 @@ BarcodeQREncodingMode convertEncodingMode(mv_barcode_qr_mode_e mode)
 	}
 
 	LOGI("Media vision QRCode encoding mode has been converted to "
-			"ZInt encoding mode (%i -> %i)", mode, encodingMode);
+		 "ZInt encoding mode (%i -> %i)",
+		 mode, encodingMode);
 	return encodingMode;
 }
 
@@ -142,7 +144,8 @@ BarcodeQRErrorCorrectionLevel convertECC(mv_barcode_qr_ecc_e ecc)
 	}
 
 	LOGI("Media vision ECC level has been converted to "
-			"ZInt ECC level (%i -> %i)", ecc, ecclevel);
+		 "ZInt ECC level (%i -> %i)",
+		 ecc, ecclevel);
 	return ecclevel;
 }
 
@@ -182,7 +185,8 @@ int convertBarcodeError(int barcodeError)
 	}
 
 	LOGI("ZInt error code has been converted to the media vision error code "
-			"(%i -> (0x%08x))", barcodeError, mvError);
+		 "(%i -> (0x%08x))",
+		 barcodeError, mvError);
 	return mvError;
 }
 
@@ -202,33 +206,28 @@ BarcodeImageFormat convertImageFormat(mv_barcode_image_format_e format)
 	}
 
 	LOGI("Media vision image format has been converted to "
-			"internal image format (%i -> %i)", format, imageFormat);
+		 "internal image format (%i -> %i)",
+		 format, imageFormat);
 	return imageFormat;
 }
 
 } /* anonymous namespace */
 
-int mv_barcode_generate_source_open(
-		mv_engine_config_h engine_cfg,
-		const char *message,
-		mv_barcode_type_e type,
-		mv_barcode_qr_mode_e qr_enc_mode,
-		mv_barcode_qr_ecc_e qr_ecc,
-		int qr_version,
-		mv_source_h image)
+int mv_barcode_generate_source_open(mv_engine_config_h engine_cfg, const char *message, mv_barcode_type_e type,
+									mv_barcode_qr_mode_e qr_enc_mode, mv_barcode_qr_ecc_e qr_ecc, int qr_version,
+									mv_source_h image)
 {
 	std::string messageStr = std::string(message);
 
-	if (qr_enc_mode == MV_BARCODE_QR_MODE_NUMERIC &&
-		messageStr.find_first_not_of("0123456789") != std::string::npos) {
+	if (qr_enc_mode == MV_BARCODE_QR_MODE_NUMERIC && messageStr.find_first_not_of("0123456789") != std::string::npos) {
 		LOGE("Barcode message can't be used according to support "
-			"numeric (0..9) mode: %s", messageStr.c_str());
+			 "numeric (0..9) mode: %s",
+			 messageStr.c_str());
 		return MEDIA_VISION_ERROR_INVALID_DATA;
 	}
 
 	int error = BARCODE_ERROR_NONE;
-	if (MV_BARCODE_QR == type &&
-		MV_BARCODE_QR_MODE_ALPHANUMERIC == qr_enc_mode) {
+	if (MV_BARCODE_QR == type && MV_BARCODE_QR_MODE_ALPHANUMERIC == qr_enc_mode) {
 		error = alphanumToUpper(messageStr);
 		if (BARCODE_ERROR_NONE != error)
 			return convertBarcodeError(error);
@@ -305,19 +304,10 @@ int mv_barcode_generate_source_open(
 		bgcolour[5] = value;
 	}
 
-	error = BarcodeGenerator::generateBarcodeToBuffer(
-					&imageBuffer,
-					&imageWidth,
-					&imageHeight,
-					&imageChannels,
-					messageStr,
-					convertBarcodeType(type),
-					convertEncodingMode(qr_enc_mode),
-					convertECC(qr_ecc),
-					qr_version,
-					showText,
-					fgcolour,
-					bgcolour);
+	error = BarcodeGenerator::generateBarcodeToBuffer(&imageBuffer, &imageWidth, &imageHeight, &imageChannels,
+													  messageStr, convertBarcodeType(type),
+													  convertEncodingMode(qr_enc_mode), convertECC(qr_ecc), qr_version,
+													  showText, fgcolour, bgcolour);
 
 	if (fgcolour != NULL) {
 		free(fgcolour);
@@ -341,16 +331,11 @@ int mv_barcode_generate_source_open(
 	const unsigned int imageBufferSize = imageWidth * imageHeight * imageChannels;
 
 	LOGI("Barcode has been generated to the buffer: "
-		"Buffer size = %ui x %ui; Channels = %ui; Message = %s",
-		imageWidth, imageHeight, imageChannels, messageStr.c_str());
+		 "Buffer size = %ui x %ui; Channels = %ui; Message = %s",
+		 imageWidth, imageHeight, imageChannels, messageStr.c_str());
 
-	error = mv_source_fill_by_buffer_c(
-					image,
-					imageBuffer,
-					imageBufferSize,
-					imageWidth,
-					imageHeight,
-					MEDIA_VISION_COLORSPACE_RGB888);
+	error = mv_source_fill_by_buffer_c(image, imageBuffer, imageBufferSize, imageWidth, imageHeight,
+									   MEDIA_VISION_COLORSPACE_RGB888);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Meidiavision source fill by generated buffer failed");
@@ -364,25 +349,17 @@ int mv_barcode_generate_source_open(
 	return error;
 }
 
-
-int mv_barcode_generate_image_open(
-		mv_engine_config_h engine_cfg,
-		const char *message,
-		int image_width,
-		int image_height,
-		mv_barcode_type_e type,
-		mv_barcode_qr_mode_e qr_enc_mode,
-		mv_barcode_qr_ecc_e qr_ecc,
-		int qr_version,
-		const char *image_path,
-		mv_barcode_image_format_e image_format)
+int mv_barcode_generate_image_open(mv_engine_config_h engine_cfg, const char *message, int image_width,
+								   int image_height, mv_barcode_type_e type, mv_barcode_qr_mode_e qr_enc_mode,
+								   mv_barcode_qr_ecc_e qr_ecc, int qr_version, const char *image_path,
+								   mv_barcode_image_format_e image_format)
 {
 	std::string messageStr = std::string(message);
 
-	if (qr_enc_mode == MV_BARCODE_QR_MODE_NUMERIC &&
-		messageStr.find_first_not_of("0123456789") != std::string::npos) {
+	if (qr_enc_mode == MV_BARCODE_QR_MODE_NUMERIC && messageStr.find_first_not_of("0123456789") != std::string::npos) {
 		LOGE("Barcode message can't be used according to support "
-				"numeric (0..9) mode: %s", messageStr.c_str());
+			 "numeric (0..9) mode: %s",
+			 messageStr.c_str());
 		return MEDIA_VISION_ERROR_INVALID_DATA;
 	}
 
@@ -392,8 +369,7 @@ int mv_barcode_generate_image_open(
 	}
 
 	int error = BARCODE_ERROR_NONE;
-	if (MV_BARCODE_QR == type &&
-		MV_BARCODE_QR_MODE_ALPHANUMERIC == qr_enc_mode) {
+	if (MV_BARCODE_QR == type && MV_BARCODE_QR_MODE_ALPHANUMERIC == qr_enc_mode) {
 		error = alphanumToUpper(messageStr);
 		if (BARCODE_ERROR_NONE != error) {
 			return convertBarcodeError(error);
@@ -467,19 +443,10 @@ int mv_barcode_generate_image_open(
 		bgcolour[5] = value;
 	}
 
-	error = BarcodeGenerator::generateBarcodeToImage(
-							std::string(image_path),
-							convertImageFormat(image_format),
-							image_width,
-							image_height,
-							messageStr,
-							convertBarcodeType(type),
-							convertEncodingMode(qr_enc_mode),
-							convertECC(qr_ecc),
-							qr_version,
-							showText,
-							fgcolour,
-							bgcolour);
+	error = BarcodeGenerator::generateBarcodeToImage(std::string(image_path), convertImageFormat(image_format),
+													 image_width, image_height, messageStr, convertBarcodeType(type),
+													 convertEncodingMode(qr_enc_mode), convertECC(qr_ecc), qr_version,
+													 showText, fgcolour, bgcolour);
 
 	if (fgcolour != NULL) {
 		free(fgcolour);
@@ -495,8 +462,8 @@ int mv_barcode_generate_image_open(
 		LOGE("Barcode generation to the image file failed");
 	} else {
 		LOGI("Barcode has been generated to the image: "
-			"Image size = %ui x %ui; Message = %s",
-			image_width, image_height, messageStr.c_str());
+			 "Image size = %ui x %ui; Message = %s",
+			 image_width, image_height, messageStr.c_str());
 	}
 
 	return convertBarcodeError(error);
diff --git a/mv_common/include/CommonUtils.h b/mv_common/include/CommonUtils.h
index 9d81649..5131260 100644
--- a/mv_common/include/CommonUtils.h
+++ b/mv_common/include/CommonUtils.h
@@ -21,9 +21,10 @@
 #include <opencv2/core/mat.hpp>
 #include <opencv2/imgproc.hpp>
 
-namespace MediaVision {
-namespace Common {
-
+namespace MediaVision
+{
+namespace Common
+{
 /**
  * @brief    This function converts media vision image handle to cv::Mat with gray color.
  *
@@ -33,7 +34,7 @@ namespace Common {
  * @return @c MEDIA_VISION_ERROR_NONE on success,
            otherwise a negative error value
  */
-int convertSourceMV2GrayCV(mv_source_h mvSource, cv::Mat& cvSource);
+int convertSourceMV2GrayCV(mv_source_h mvSource, cv::Mat &cvSource);
 
 } /* Common */
 } /* MediaVision */
diff --git a/mv_common/include/EngineConfig.h b/mv_common/include/EngineConfig.h
index 365e5fb..9be5ed6 100644
--- a/mv_common/include/EngineConfig.h
+++ b/mv_common/include/EngineConfig.h
@@ -30,16 +30,18 @@
  * @brief  Engine Configuration class definition.
  */
 
-namespace MediaVision {
-namespace Common {
-
+namespace MediaVision
+{
+namespace Common
+{
 using DictDblConstIter = std::map<std::string, double>::const_iterator;
 using DictIntConstIter = std::map<std::string, int>::const_iterator;
 using DictBoolConstIter = std::map<std::string, bool>::const_iterator;
 using DictStrConstIter = std::map<std::string, std::string>::const_iterator;
-using DictVecStrConstIter = std::map<std::string, std::vector<std::string>>::const_iterator;
+using DictVecStrConstIter = std::map<std::string, std::vector<std::string> >::const_iterator;
 
-class EngineConfig {
+class EngineConfig
+{
 public:
 	/**
 	 * @brief Engine configuration constructor.
@@ -49,7 +51,8 @@ public:
 	 * @since_tizen 7.0
 	 * @param [in] config_file_path      A full path of config file. (Optional)
 	 */
-	explicit EngineConfig(std::string config_file_path = std::string(MV_CONFIG_PATH) + std::string(MV_ENGINE_CONFIG_FILE_NAME));
+	explicit EngineConfig(std::string config_file_path = std::string(MV_CONFIG_PATH) +
+														 std::string(MV_ENGINE_CONFIG_FILE_NAME));
 
 	/**
 	 * @brief Engine configuration destructor.
@@ -65,7 +68,7 @@ public:
 	 * @return @c MEDIA_VISION_ERROR_NONE on success,\n
 	 *         otherwise a negative error value
 	 */
-	int setAttribute(const std::string& key, const double value);
+	int setAttribute(const std::string &key, const double value);
 
 	/**
 	 * @brief Sets attribute with integer value.
@@ -76,7 +79,7 @@ public:
 	 * @return @c MEDIA_VISION_ERROR_NONE on success,\n
 	 *         otherwise a negative error value
 	 */
-	int setAttribute(const std::string& key, const int value);
+	int setAttribute(const std::string &key, const int value);
 
 	/**
 	 * @brief Sets attribute with boolean value.
@@ -87,7 +90,7 @@ public:
 	 * @return @c MEDIA_VISION_ERROR_NONE on success,\n
 	 *         otherwise a negative error value
 	 */
-	int setAttribute(const std::string& key, const bool value);
+	int setAttribute(const std::string &key, const bool value);
 
 	/**
 	 * @brief Sets attribute with string value.
@@ -98,7 +101,7 @@ public:
 	 * @return @c MEDIA_VISION_ERROR_NONE on success,\n
 	 *         otherwise a negative error value
 	 */
-	int setAttribute(const std::string& key, const std::string& value);
+	int setAttribute(const std::string &key, const std::string &value);
 
 	/**
 	 * @brief Sets attribute with the vector of string value.
@@ -109,7 +112,7 @@ public:
 	 * @return @c MEDIA_VISION_ERROR_NONE on success,\n
 	 *         otherwise a negative error value
 	 */
-	int setAttribute(const std::string& key, const std::vector<std::string>& value);
+	int setAttribute(const std::string &key, const std::vector<std::string> &value);
 
 	/**
 	 * @brief Gets double attribute value by attribute name.
@@ -122,7 +125,7 @@ public:
 	 * @retval #MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE If attribute with name @a key
 	 *         doesn't exist in the engine configuration dictionary
 	 */
-	int getDoubleAttribute(const std::string& key, double *value) const;
+	int getDoubleAttribute(const std::string &key, double *value) const;
 
 	/**
 	 * @brief Gets integer attribute value by attribute name.
@@ -135,7 +138,7 @@ public:
 	 * @retval #MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE If attribute with name @a key
 	 *         doesn't exist in the engine configuration dictionary
 	 */
-	int getIntegerAttribute(const std::string& key, int *value) const;
+	int getIntegerAttribute(const std::string &key, int *value) const;
 
 	/**
 	 * @brief Gets boolean attribute value by attribute name.
@@ -148,7 +151,7 @@ public:
 	 * @retval #MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE If attribute with name @a key
 	 *         doesn't exist in the engine configuration dictionary
 	 */
-	int getBooleanAttribute(const std::string& key, bool *value) const;
+	int getBooleanAttribute(const std::string &key, bool *value) const;
 
 	/**
 	 * @brief Gets string attribute value by attribute name.
@@ -161,7 +164,7 @@ public:
 	 * @retval #MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE If attribute with name @a key
 	 *         doesn't exist in the engine configuration dictionary
 	 */
-	int getStringAttribute(const std::string& key, std::string *value) const;
+	int getStringAttribute(const std::string &key, std::string *value) const;
 
 	/**
 	 * @brief Gets vector attribute value of string by attribute name.
@@ -174,22 +177,22 @@ public:
 	 * @retval #MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE If attribute with name @a key
 	 *         doesn't exist in the engine configuration dictionary
 	 */
-	int getStringAttribute(const std::string& key, std::vector<std::string> *value) const;
+	int getStringAttribute(const std::string &key, std::vector<std::string> *value) const;
 
-	const std::map<std::string, double>& getDefaultDblDict();
-	const std::map<std::string, int>& getDefaultIntDict();
-	const std::map<std::string, bool>& getDefaultBoolDict();
-	const std::map<std::string, std::string>& getDefaultStrDict();
-	const std::map<std::string, std::vector<std::string>>& getDefaultVecStrDict();
+	const std::map<std::string, double> &getDefaultDblDict();
+	const std::map<std::string, int> &getDefaultIntDict();
+	const std::map<std::string, bool> &getDefaultBoolDict();
+	const std::map<std::string, std::string> &getDefaultStrDict();
+	const std::map<std::string, std::vector<std::string> > &getDefaultVecStrDict();
 
 private:
 	std::map<std::string, double> __dblDict;
 	std::map<std::string, int> __intDict;
 	std::map<std::string, bool> __boolDict;
 	std::map<std::string, std::string> __strDict;
-	std::map<std::string, std::vector<std::string>> __vecStrDict;
+	std::map<std::string, std::vector<std::string> > __vecStrDict;
 
-	int loadDictionaries(std::string& config_file_path);
+	int loadDictionaries(std::string &config_file_path);
 };
 
 } /* Common */
diff --git a/mv_common/include/MediaSource.h b/mv_common/include/MediaSource.h
index 1cf2965..69c1ca7 100644
--- a/mv_common/include/MediaSource.h
+++ b/mv_common/include/MediaSource.h
@@ -25,15 +25,18 @@
  * @brief This file contains the MediaSource class.
  */
 
-namespace MediaVision {
-namespace Common {
+namespace MediaVision
+{
+namespace Common
+{
 /**
  * @class   MediaSource
  * @brief   The Media Source container
  * @details It is class which contains Media Source information. This class
  *          will be use in the Media Vision as simple image.
  */
-class MediaSource {
+class MediaSource
+{
 public:
 	/**
 	 * @brief   Creates a MediaSource.
@@ -69,8 +72,7 @@ public:
 	 * @see MediaSource::MediaSource()
 	 * @see MediaSource::fill()
 	 */
-	bool alloc(unsigned int bufferSize,
-			unsigned int width, unsigned int height, mv_colorspace_e colorspace);
+	bool alloc(unsigned int bufferSize, unsigned int width, unsigned int height, mv_colorspace_e colorspace);
 
 	/**
 	 * @brief   Clears the MediaSource.
@@ -97,8 +99,8 @@ public:
 	 * @see MediaSource::MediaSource()
 	 * @see MediaSource::clear()
 	 */
-	bool fill(const unsigned char *buffer, unsigned int bufferSize,
-			unsigned int width, unsigned int height, mv_colorspace_e colorspace);
+	bool fill(const unsigned char *buffer, unsigned int bufferSize, unsigned int width, unsigned int height,
+			  mv_colorspace_e colorspace);
 
 	/**
 	 * @brief Fills the MediaSource based on the buffer and metadata.
@@ -116,8 +118,8 @@ public:
 	 * @see MediaSource::MediaSource()
 	 * @see MediaSource::clear()
 	 */
-	bool fill(const unsigned char *buffer, unsigned int bufferSize,
-			unsigned int width, unsigned int height, size_t offset);
+	bool fill(const unsigned char *buffer, unsigned int bufferSize, unsigned int width, unsigned int height,
+			  size_t offset);
 
 	/**
 	 * @brief Gets data buffer of the MediaSource.
@@ -160,15 +162,15 @@ public:
 	mv_colorspace_e getColorspace(void) const;
 
 protected:
-	unsigned char *m_pBuffer;        /**< The data buffer */
+	unsigned char *m_pBuffer; /**< The data buffer */
 
-	unsigned int m_bufferSize;       /**< The buffer size */
+	unsigned int m_bufferSize; /**< The buffer size */
 
-	unsigned int m_width;            /**< The image width */
+	unsigned int m_width; /**< The image width */
 
-	unsigned int m_height;           /**< The image height */
+	unsigned int m_height; /**< The image height */
 
-	mv_colorspace_e m_colorspace;    /**< The image colorspace */
+	mv_colorspace_e m_colorspace; /**< The image colorspace */
 };
 
 } /* Common */
diff --git a/mv_common/include/mv_common_c.h b/mv_common/include/mv_common_c.h
index 234fc52..cbcb731 100644
--- a/mv_common/include/mv_common_c.h
+++ b/mv_common/include/mv_common_c.h
@@ -41,8 +41,7 @@ extern "C" {
  *
  * @see mv_destroy_source_c()
  */
-int mv_create_source_c(
-		mv_source_h *source);
+int mv_create_source_c(mv_source_h *source);
 
 /**
  * @brief Destroys the source handle and releases all its resources.
@@ -55,8 +54,7 @@ int mv_create_source_c(
  *
  * @see mv_create_source_c()
  */
-int mv_destroy_source_c(
-		mv_source_h source);
+int mv_destroy_source_c(mv_source_h source);
 
 /**
  * @brief Fills the media source based on the media packet.
@@ -77,9 +75,7 @@ int mv_destroy_source_c(
  * @see mv_create_source_c()
  * @see mv_destroy_source_c()
  */
-int mv_source_fill_by_media_packet_c(
-		mv_source_h source,
-		media_packet_h media_packet);
+int mv_source_fill_by_media_packet_c(mv_source_h source, media_packet_h media_packet);
 
 /**
  * @brief Fills the media source based on the buffer and metadata.
@@ -100,13 +96,8 @@ int mv_source_fill_by_media_packet_c(
  *
  * @see mv_source_clear_c()
  */
-int mv_source_fill_by_buffer_c(
-		mv_source_h source,
-		unsigned char *data_buffer,
-		unsigned int buffer_size,
-		unsigned int image_width,
-		unsigned int image_height,
-		mv_colorspace_e image_colorspace);
+int mv_source_fill_by_buffer_c(mv_source_h source, unsigned char *data_buffer, unsigned int buffer_size,
+							   unsigned int image_width, unsigned int image_height, mv_colorspace_e image_colorspace);
 
 /**
  * @brief Clears the buffer of the media source.
@@ -119,8 +110,7 @@ int mv_source_fill_by_buffer_c(
  *
  * @see mv_source_fill_by_buffer_c()
  */
-int mv_source_clear_c(
-		mv_source_h source);
+int mv_source_clear_c(mv_source_h source);
 
 /**
  * @brief Gets buffer of the media source.
@@ -141,10 +131,7 @@ int mv_source_clear_c(
  * @see mv_source_get_height_c()
  * @see mv_source_get_colorspace_c()
  */
-int mv_source_get_buffer_c(
-		mv_source_h source,
-		unsigned char **data_buffer,
-		unsigned int *buffer_size);
+int mv_source_get_buffer_c(mv_source_h source, unsigned char **data_buffer, unsigned int *buffer_size);
 
 /**
  * @brief Gets height of the media source.
@@ -160,9 +147,7 @@ int mv_source_get_buffer_c(
  * @see mv_source_get_colorspace_c()
  * @see mv_source_get_buffer_c()
  */
-int mv_source_get_height_c(
-		mv_source_h source,
-		unsigned int *image_height);
+int mv_source_get_height_c(mv_source_h source, unsigned int *image_height);
 
 /**
  * @brief Gets width of the media source.
@@ -178,9 +163,7 @@ int mv_source_get_height_c(
  * @see mv_source_get_colorspace_c()
  * @see mv_source_get_buffer_c()
  */
-int mv_source_get_width_c(
-		mv_source_h source,
-		unsigned int *image_width);
+int mv_source_get_width_c(mv_source_h source, unsigned int *image_width);
 
 /**
  * @brief Gets colorspace of the media source.
@@ -196,9 +179,7 @@ int mv_source_get_width_c(
  * @see mv_source_get_height_c()
  * @see mv_source_get_buffer_c()
  */
-int mv_source_get_colorspace_c(
-		mv_source_h source,
-		mv_colorspace_e *image_colorspace);
+int mv_source_get_colorspace_c(mv_source_h source, mv_colorspace_e *image_colorspace);
 
 /**
  * @brief Creates the handle to the configuration of engine.
@@ -221,8 +202,7 @@ int mv_source_get_colorspace_c(
  * @see mv_engine_config_get_bool_attribute_c()
  * @see mv_engine_config_get_string_attribute_c()
  */
-int mv_create_engine_config_c(
-		mv_engine_config_h *engine_cfg);
+int mv_create_engine_config_c(mv_engine_config_h *engine_cfg);
 
 /**
  * @brief Destroys the engine configuration handle and releases all its
@@ -238,8 +218,7 @@ int mv_create_engine_config_c(
  * @see mv_engine_config_h
  * @see mv_create_engine_config_c()
  */
-int mv_destroy_engine_config_c(
-		mv_engine_config_h engine_cfg);
+int mv_destroy_engine_config_c(mv_engine_config_h engine_cfg);
 
 /**
  * @brief Sets the double attribute to the configuration.
@@ -260,10 +239,7 @@ int mv_destroy_engine_config_c(
  * @see mv_engine_config_set_bool_attribute_c()
  * @see mv_engine_config_set_string_attribute_c()
  */
-int mv_engine_config_set_double_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		double value);
+int mv_engine_config_set_double_attribute_c(mv_engine_config_h engine_cfg, const char *name, double value);
 
 /**
  * @brief Sets the integer attribute to the configuration.
@@ -284,10 +260,7 @@ int mv_engine_config_set_double_attribute_c(
  * @see mv_engine_config_set_bool_attribute_c()
  * @see mv_engine_config_set_string_attribute_c()
  */
-int mv_engine_config_set_int_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		int value);
+int mv_engine_config_set_int_attribute_c(mv_engine_config_h engine_cfg, const char *name, int value);
 
 /**
  * @brief Sets the boolean attribute to the configuration.
@@ -308,10 +281,7 @@ int mv_engine_config_set_int_attribute_c(
  * @see mv_engine_config_set_int_attribute_c()
  * @see mv_engine_config_set_string_attribute_c()
  */
-int mv_engine_config_set_bool_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		bool attribute);
+int mv_engine_config_set_bool_attribute_c(mv_engine_config_h engine_cfg, const char *name, bool attribute);
 
 /**
  * @brief Sets the string attribute to the configuration.
@@ -332,10 +302,7 @@ int mv_engine_config_set_bool_attribute_c(
  * @see mv_engine_config_set_int_attribute_c()
  * @see mv_engine_config_set_bool_attribute_c()
  */
-int mv_engine_config_set_string_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		const char *value);
+int mv_engine_config_set_string_attribute_c(mv_engine_config_h engine_cfg, const char *name, const char *value);
 
 /**
  * @brief Sets the array of string attribute to the configuration.
@@ -354,11 +321,8 @@ int mv_engine_config_set_string_attribute_c(
  *
  * @see mv_engine_config_get_array_string_attribute_c()
  */
-int mv_engine_config_set_array_string_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		const char **values,
-		unsigned int size);
+int mv_engine_config_set_array_string_attribute_c(mv_engine_config_h engine_cfg, const char *name, const char **values,
+												  unsigned int size);
 
 /**
  * @brief Gets the double attribute from the configuration dictionary.
@@ -381,10 +345,7 @@ int mv_engine_config_set_array_string_attribute_c(
  * @see mv_engine_config_get_bool_attribute_c()
  * @see mv_engine_config_get_string_attribute_c()
  */
-int mv_engine_config_get_double_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		double *value);
+int mv_engine_config_get_double_attribute_c(mv_engine_config_h engine_cfg, const char *name, double *value);
 
 /**
  * @brief Gets the integer attribute from the configuration dictionary.
@@ -407,10 +368,7 @@ int mv_engine_config_get_double_attribute_c(
  * @see mv_engine_config_get_bool_attribute_c()
  * @see mv_engine_config_get_string_attribute_c()
  */
-int mv_engine_config_get_int_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		int *value);
+int mv_engine_config_get_int_attribute_c(mv_engine_config_h engine_cfg, const char *name, int *value);
 
 /**
  * @brief Gets the boolean attribute from the configuration dictionary.
@@ -433,10 +391,7 @@ int mv_engine_config_get_int_attribute_c(
  * @see mv_engine_config_get_int_attribute_c()
  * @see mv_engine_config_get_string_attribute_c()
  */
-int mv_engine_config_get_bool_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		bool *value);
+int mv_engine_config_get_bool_attribute_c(mv_engine_config_h engine_cfg, const char *name, bool *value);
 
 /**
  * @brief Gets the string attribute from the configuration dictionary.
@@ -461,10 +416,7 @@ int mv_engine_config_get_bool_attribute_c(
  * @see mv_engine_config_get_int_attribute_c()
  * @see mv_engine_config_get_bool_attribute_c()
  */
-int mv_engine_config_get_string_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		char **value);
+int mv_engine_config_get_string_attribute_c(mv_engine_config_h engine_cfg, const char *name, char **value);
 
 /**
  * @brief Gets the array of string attribute from the configuration dictionary.
@@ -487,11 +439,8 @@ int mv_engine_config_get_string_attribute_c(
  *
  * @see mv_engine_config_set_array_string_attribute_c()
  */
-int mv_engine_config_get_array_string_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		char ***values,
-		int *size);
+int mv_engine_config_get_array_string_attribute_c(mv_engine_config_h engine_cfg, const char *name, char ***values,
+												  int *size);
 
 /**
  * @brief Traverses the list of supported attribute names and types.
@@ -531,9 +480,7 @@ int mv_engine_config_get_array_string_attribute_c(
  * @see mv_engine_config_get_bool_attribute_c()
  * @see mv_engine_config_get_string_attribute_c()
  */
-int mv_engine_config_foreach_supported_attribute_c(
-		mv_supported_attribute_cb callback,
-		void *user_data);
+int mv_engine_config_foreach_supported_attribute_c(mv_supported_attribute_cb callback, void *user_data);
 
 #ifdef __cplusplus
 }
diff --git a/mv_common/include/util.h b/mv_common/include/util.h
index 5cb6b8e..adc6aca 100644
--- a/mv_common/include/util.h
+++ b/mv_common/include/util.h
@@ -28,55 +28,52 @@ namespace common
 {
 namespace util
 {
+static int ConvertToCvSource(std::vector<mv_source_h> &mv_srcs, std::vector<cv::Mat> &cv_srcs,
+							 std::vector<mv_rectangle_s> &rects)
+{
+	unsigned int rect_idx = 0;
+
+	for (auto &mv_src : mv_srcs) {
+		mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
+		mv_rectangle_s *roi = &rects[rect_idx++];
+		unsigned int width = 0, height = 0;
+		unsigned int bufferSize = 0;
+		unsigned char *buffer = NULL;
+
+		if (mv_source_get_width(mv_src, &width) != MEDIA_VISION_ERROR_NONE ||
+			mv_source_get_height(mv_src, &height) != MEDIA_VISION_ERROR_NONE ||
+			mv_source_get_colorspace(mv_src, &colorspace) != MEDIA_VISION_ERROR_NONE ||
+			mv_source_get_buffer(mv_src, &buffer, &bufferSize))
+			return MEDIA_VISION_ERROR_INTERNAL;
+
+		// TODO. Let's support various color spaces.
+
+		if (colorspace != MEDIA_VISION_COLORSPACE_RGB888) {
+			LOGE("Not Supported format.");
+			return MEDIA_VISION_ERROR_NOT_SUPPORTED_FORMAT;
+		}
 
-	static int ConvertToCvSource(std::vector<mv_source_h> &mv_srcs, std::vector<cv::Mat>& cv_srcs, std::vector<mv_rectangle_s>& rects)
-	{
-		unsigned int rect_idx = 0;
-
-		for (auto& mv_src : mv_srcs) {
-			mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
-			mv_rectangle_s *roi = &rects[rect_idx++];
-			unsigned int width = 0, height = 0;
-			unsigned int bufferSize = 0;
-			unsigned char *buffer = NULL;
-
-			if (mv_source_get_width(mv_src, &width) != MEDIA_VISION_ERROR_NONE ||
-				mv_source_get_height(mv_src, &height) !=
-						MEDIA_VISION_ERROR_NONE ||
-				mv_source_get_colorspace(mv_src, &colorspace) !=
-						MEDIA_VISION_ERROR_NONE ||
-				mv_source_get_buffer(mv_src, &buffer, &bufferSize))
-				return MEDIA_VISION_ERROR_INTERNAL;
-
-			// TODO. Let's support various color spaces.
-
-			if (colorspace != MEDIA_VISION_COLORSPACE_RGB888) {
-				LOGE("Not Supported format.");
-				return MEDIA_VISION_ERROR_NOT_SUPPORTED_FORMAT;
-			}
-
-			/* convert mv_source to cv::Mat */
-			cv::Mat cvSource;
-
-			if (roi == NULL) {
-				cvSource = cv::Mat(cv::Size(width, height), CV_MAKETYPE(CV_8U, 3), buffer).clone();
-			} else {
-				cv::Rect cvRoi;
+		/* convert mv_source to cv::Mat */
+		cv::Mat cvSource;
 
-				cvRoi.x = roi->point.x;
-				cvRoi.y = roi->point.y;
-				cvRoi.width = unsigned(roi->point.x + roi->width) >= width ? width - roi->point.x : roi->width;
-				cvRoi.height = unsigned(roi->point.y + roi->height) >= height ? height - roi->point.y : roi->height;
-				cvSource = cv::Mat(cv::Size(width, height), CV_MAKETYPE(CV_8U, 3), buffer)(cvRoi).clone();
-			}
+		if (roi == NULL) {
+			cvSource = cv::Mat(cv::Size(width, height), CV_MAKETYPE(CV_8U, 3), buffer).clone();
+		} else {
+			cv::Rect cvRoi;
 
-			cv_srcs.push_back(cvSource);
-			LOGI("Size: w:%u, h:%u", cvSource.size().width, cvSource.size().height);
+			cvRoi.x = roi->point.x;
+			cvRoi.y = roi->point.y;
+			cvRoi.width = unsigned(roi->point.x + roi->width) >= width ? width - roi->point.x : roi->width;
+			cvRoi.height = unsigned(roi->point.y + roi->height) >= height ? height - roi->point.y : roi->height;
+			cvSource = cv::Mat(cv::Size(width, height), CV_MAKETYPE(CV_8U, 3), buffer)(cvRoi).clone();
 		}
 
-		return MEDIA_VISION_ERROR_NONE;
+		cv_srcs.push_back(cvSource);
+		LOGI("Size: w:%u, h:%u", cvSource.size().width, cvSource.size().height);
 	}
 
+	return MEDIA_VISION_ERROR_NONE;
+}
 
 } // util
 } // common
diff --git a/mv_common/src/CommonUtils.cpp b/mv_common/src/CommonUtils.cpp
index a90b73e..7035205 100644
--- a/mv_common/src/CommonUtils.cpp
+++ b/mv_common/src/CommonUtils.cpp
@@ -18,11 +18,11 @@
 
 #include <CommonUtils.h>
 
-namespace MediaVision {
-namespace Common {
-
-
-int convertSourceMV2GrayCV(mv_source_h mvSource, cv::Mat& cvSource)
+namespace MediaVision
+{
+namespace Common
+{
+int convertSourceMV2GrayCV(mv_source_h mvSource, cv::Mat &cvSource)
 {
 	MEDIA_VISION_INSTANCE_CHECK(mvSource);
 
@@ -34,17 +34,13 @@ int convertSourceMV2GrayCV(mv_source_h mvSource, cv::Mat& cvSource)
 
 	mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
 
-	MEDIA_VISION_ASSERT(mv_source_get_width(mvSource, &width),
-			"Failed to get the width.");
-	MEDIA_VISION_ASSERT(mv_source_get_height(mvSource, &height),
-			"Failed to get the height.");
-	MEDIA_VISION_ASSERT(mv_source_get_colorspace(mvSource, &colorspace),
-			"Failed to get the colorspace.");
-	MEDIA_VISION_ASSERT(mv_source_get_buffer(mvSource, &buffer, &bufferSize),
-			"Failed to get the buffer size.");
+	MEDIA_VISION_ASSERT(mv_source_get_width(mvSource, &width), "Failed to get the width.");
+	MEDIA_VISION_ASSERT(mv_source_get_height(mvSource, &height), "Failed to get the height.");
+	MEDIA_VISION_ASSERT(mv_source_get_colorspace(mvSource, &colorspace), "Failed to get the colorspace.");
+	MEDIA_VISION_ASSERT(mv_source_get_buffer(mvSource, &buffer, &bufferSize), "Failed to get the buffer size.");
 
 	int conversionType;
-	switch(colorspace) {
+	switch (colorspace) {
 	case MEDIA_VISION_COLORSPACE_INVALID:
 		LOGE("Error: mv_source has invalid colorspace.");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -103,19 +99,16 @@ int convertSourceMV2GrayCV(mv_source_h mvSource, cv::Mat& cvSource)
 	}
 
 	if (bufferSize < width * height * channelsNumber) {
-		LOGE("bufferSize : %u is too small for image w: %u, h: %u, c: %u",
-				bufferSize, width, height, channelsNumber);
+		LOGE("bufferSize : %u is too small for image w: %u, h: %u, c: %u", bufferSize, width, height, channelsNumber);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	if (conversionType == -1) {/* Without conversion */
-		cvSource = cv::Mat(cv::Size(width, height),
-					CV_MAKETYPE(depth, channelsNumber), buffer).clone();
-	} else {/* With conversion */
+	if (conversionType == -1) { /* Without conversion */
+		cvSource = cv::Mat(cv::Size(width, height), CV_MAKETYPE(depth, channelsNumber), buffer).clone();
+	} else { /* With conversion */
 		/* Class for representation the given image as cv::Mat before conversion */
 		try {
-			cv::Mat origin = cv::Mat(cv::Size(width, height),
-						CV_MAKETYPE(depth, channelsNumber), buffer);
+			cv::Mat origin = cv::Mat(cv::Size(width, height), CV_MAKETYPE(depth, channelsNumber), buffer);
 
 			cv::cvtColor(origin, cvSource, conversionType);
 		} catch (const cv::Exception &e) {
diff --git a/mv_common/src/EngineConfig.cpp b/mv_common/src/EngineConfig.cpp
index bbcdfdd..212be17 100644
--- a/mv_common/src/EngineConfig.cpp
+++ b/mv_common/src/EngineConfig.cpp
@@ -25,9 +25,10 @@
  * @brief  Engine Configuration class methods implementation.
  */
 
-namespace MediaVision {
-namespace Common {
-
+namespace MediaVision
+{
+namespace Common
+{
 EngineConfig::EngineConfig(std::string config_file_path)
 {
 	LOGI("Default Engine config file location is %s", config_file_path.c_str());
@@ -43,10 +44,9 @@ EngineConfig::~EngineConfig()
 	; /* NULL */
 }
 
-int EngineConfig::setAttribute(const std::string& key, const double value)
+int EngineConfig::setAttribute(const std::string &key, const double value)
 {
-	LOGI("Set double attribute for the engine config %p. [%s] = %f",
-			this, key.c_str(), value);
+	LOGI("Set double attribute for the engine config %p. [%s] = %f", this, key.c_str(), value);
 
 	if (__dblDict.find(key) == __dblDict.end()) {
 		LOGE("Double attribute [%s] can't be set because isn't supported", key.c_str());
@@ -58,10 +58,9 @@ int EngineConfig::setAttribute(const std::string& key, const double value)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int EngineConfig::setAttribute(const std::string& key, const int value)
+int EngineConfig::setAttribute(const std::string &key, const int value)
 {
-	LOGI("Set integer attribute for the engine config %p. [%s] = %i",
-			this, key.c_str(), value);
+	LOGI("Set integer attribute for the engine config %p. [%s] = %i", this, key.c_str(), value);
 
 	if (__intDict.find(key) == __intDict.end()) {
 		LOGE("Integer attribute [%s] can't be set because isn't supported", key.c_str());
@@ -73,10 +72,9 @@ int EngineConfig::setAttribute(const std::string& key, const int value)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int EngineConfig::setAttribute(const std::string& key, const bool value)
+int EngineConfig::setAttribute(const std::string &key, const bool value)
 {
-	LOGI("Set boolean attribute for the engine config %p. [%s] = %s",
-			this, key.c_str(), value ? "TRUE" : "FALSE");
+	LOGI("Set boolean attribute for the engine config %p. [%s] = %s", this, key.c_str(), value ? "TRUE" : "FALSE");
 
 	if (__boolDict.find(key) == __boolDict.end()) {
 		LOGE("Boolean attribute [%s] can't be set because isn't supported", key.c_str());
@@ -88,10 +86,9 @@ int EngineConfig::setAttribute(const std::string& key, const bool value)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int EngineConfig::setAttribute(const std::string& key, const std::string& value)
+int EngineConfig::setAttribute(const std::string &key, const std::string &value)
 {
-	LOGI("Set string attribute for the engine config %p. [%s] = %s",
-			this, key.c_str(), value.c_str());
+	LOGI("Set string attribute for the engine config %p. [%s] = %s", this, key.c_str(), value.c_str());
 
 	if (__strDict.find(key) == __strDict.end()) {
 		LOGE("String attribute [%s] can't be set because isn't supported", key.c_str());
@@ -103,10 +100,10 @@ int EngineConfig::setAttribute(const std::string& key, const std::string& value)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int EngineConfig::setAttribute(const std::string& key, const std::vector<std::string>& value)
+int EngineConfig::setAttribute(const std::string &key, const std::vector<std::string> &value)
 {
-	LOGI("Set vector attribute of string for the engine config %p. [%s] = [%s, ...]",
-			this, key.c_str(), value[0].c_str());
+	LOGI("Set vector attribute of string for the engine config %p. [%s] = [%s, ...]", this, key.c_str(),
+		 value[0].c_str());
 
 	if (__vecStrDict.find(key) == __vecStrDict.end()) {
 		LOGE("Vector attribute of string [%s] can't be set because isn't supported", key.c_str());
@@ -118,118 +115,121 @@ int EngineConfig::setAttribute(const std::string& key, const std::vector<std::st
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int EngineConfig::getDoubleAttribute(const std::string& key, double *value) const
+int EngineConfig::getDoubleAttribute(const std::string &key, double *value) const
 {
 	DictDblConstIter dictIter = __dblDict.find(key);
 	if (dictIter == __dblDict.end()) {
 		LOGE("Attempt to access to the unsupported double attribute [%s] "
-				"of the engine config %p", key.c_str(), this);
+			 "of the engine config %p",
+			 key.c_str(), this);
 		return MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE;
 	}
 
-	LOGD("Get double attribute from the engine config %p. [%s] = %f",
-			this, dictIter->first.c_str(), dictIter->second);
+	LOGD("Get double attribute from the engine config %p. [%s] = %f", this, dictIter->first.c_str(), dictIter->second);
 
 	*value = dictIter->second;
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int EngineConfig::getIntegerAttribute(const std::string& key, int *value) const
+int EngineConfig::getIntegerAttribute(const std::string &key, int *value) const
 {
 	DictIntConstIter dictIter = __intDict.find(key);
 	if (dictIter == __intDict.end()) {
 		LOGE("Attempt to access to the unsupported integer attribute [%s] "
-				"of the engine config %p", key.c_str(), this);
+			 "of the engine config %p",
+			 key.c_str(), this);
 		return MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE;
 	}
 
-	LOGD("Get integer attribute from the engine config %p. [%s] = %i",
-			this, dictIter->first.c_str(), dictIter->second);
+	LOGD("Get integer attribute from the engine config %p. [%s] = %i", this, dictIter->first.c_str(), dictIter->second);
 
 	*value = dictIter->second;
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int EngineConfig::getBooleanAttribute(const std::string& key, bool *value) const
+int EngineConfig::getBooleanAttribute(const std::string &key, bool *value) const
 {
 	DictBoolConstIter dictIter = __boolDict.find(key);
 	if (dictIter == __boolDict.end()) {
 		LOGE("Attempt to access to the unsupported boolean attribute [%s] "
-				"of the engine config %p", key.c_str(), this);
+			 "of the engine config %p",
+			 key.c_str(), this);
 		return MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE;
 	}
 
-	LOGD("Get boolean attribute from the engine config %p. [%s] = %s",
-			this, dictIter->first.c_str(), dictIter->second ? "TRUE" : "FALSE");
+	LOGD("Get boolean attribute from the engine config %p. [%s] = %s", this, dictIter->first.c_str(),
+		 dictIter->second ? "TRUE" : "FALSE");
 
 	*value = dictIter->second;
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int EngineConfig::getStringAttribute(const std::string& key, std::string *value) const
+int EngineConfig::getStringAttribute(const std::string &key, std::string *value) const
 {
 	DictStrConstIter dictIter = __strDict.find(key);
 
 	if (dictIter == __strDict.end()) {
 		LOGE("Attempt to access to the unsupported string attribute [%s] "
-				"of the engine config %p", key.c_str(), this);
+			 "of the engine config %p",
+			 key.c_str(), this);
 		return MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE;
 	}
 
-	LOGD("Get string attribute from the engine config %p. [%s] = %s",
-			this, dictIter->first.c_str(), dictIter->second.c_str());
+	LOGD("Get string attribute from the engine config %p. [%s] = %s", this, dictIter->first.c_str(),
+		 dictIter->second.c_str());
 
 	*value = dictIter->second;
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int EngineConfig::getStringAttribute(const std::string& key, std::vector<std::string> *value) const
+int EngineConfig::getStringAttribute(const std::string &key, std::vector<std::string> *value) const
 {
 	DictVecStrConstIter dictIter = __vecStrDict.find(key);
 	if (dictIter == __vecStrDict.end()) {
 		LOGE("Attempt to access to the unsupported vector attribute [%s] of string "
-				"of the engine config %p", key.c_str(), this);
+			 "of the engine config %p",
+			 key.c_str(), this);
 		return MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE;
 	}
 
-	LOGD("Get vector attribute of string from the engine config %p. [%s] = [%s,...]",
-			this, dictIter->first.c_str(), dictIter->second[0].c_str());
+	LOGD("Get vector attribute of string from the engine config %p. [%s] = [%s,...]", this, dictIter->first.c_str(),
+		 dictIter->second[0].c_str());
 
 	*value = dictIter->second;
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-const std::map<std::string, double>& EngineConfig::getDefaultDblDict()
+const std::map<std::string, double> &EngineConfig::getDefaultDblDict()
 {
 	return __dblDict;
 }
 
-const std::map<std::string, int>& EngineConfig::getDefaultIntDict()
+const std::map<std::string, int> &EngineConfig::getDefaultIntDict()
 {
 	return __intDict;
 }
 
-const std::map<std::string, bool>& EngineConfig::getDefaultBoolDict()
+const std::map<std::string, bool> &EngineConfig::getDefaultBoolDict()
 {
 	return __boolDict;
 }
 
-const std::map<std::string, std::string>& EngineConfig::getDefaultStrDict()
+const std::map<std::string, std::string> &EngineConfig::getDefaultStrDict()
 {
 	return __strDict;
 }
 
-const std::map<std::string, std::vector<std::string>>& EngineConfig::getDefaultVecStrDict()
+const std::map<std::string, std::vector<std::string> > &EngineConfig::getDefaultVecStrDict()
 {
 	return __vecStrDict;
 }
 
-int EngineConfig::loadDictionaries(std::string& config_file_path)
+int EngineConfig::loadDictionaries(std::string &config_file_path)
 {
 	LOGI("Start to cache default attributes from engine configuration file.");
 
@@ -254,7 +254,7 @@ int EngineConfig::loadDictionaries(std::string& config_file_path)
 	JsonNode *root = json_parser_get_root(parser);
 	if (JSON_NODE_OBJECT != json_node_get_node_type(root)) {
 		LOGW("Can't parse tests configuration file. "
-			"Incorrect json markup.");
+			 "Incorrect json markup.");
 		g_object_unref(parser);
 		return MEDIA_VISION_ERROR_NO_DATA;
 	}
@@ -263,7 +263,7 @@ int EngineConfig::loadDictionaries(std::string& config_file_path)
 
 	if (!json_object_has_member(jobj, "attributes")) {
 		LOGW("Can't parse tests configuration file. "
-				"No 'attributes' section.");
+			 "No 'attributes' section.");
 		g_object_unref(parser);
 		return MEDIA_VISION_ERROR_NO_DATA;
 	}
@@ -272,7 +272,7 @@ int EngineConfig::loadDictionaries(std::string& config_file_path)
 
 	if (JSON_NODE_ARRAY != json_node_get_node_type(attr_node)) {
 		LOGW("Can't parse tests configuration file. "
-				"'attributes' section isn't array.");
+			 "'attributes' section isn't array.");
 		g_object_unref(parser);
 		return MEDIA_VISION_ERROR_NO_DATA;
 	}
@@ -291,32 +291,32 @@ int EngineConfig::loadDictionaries(std::string& config_file_path)
 
 		JsonObject *attr_obj = json_node_get_object(attr_node);
 
-		if (!json_object_has_member(attr_obj, "name") ||
-				!json_object_has_member(attr_obj, "type") ||
-				!json_object_has_member(attr_obj, "value")) {
+		if (!json_object_has_member(attr_obj, "name") || !json_object_has_member(attr_obj, "type") ||
+			!json_object_has_member(attr_obj, "value")) {
 			LOGW("Attribute %u wasn't parsed from json file.", attrInd);
 			continue;
 		}
 
-		const char *nameStr = (const char*)json_object_get_string_member(attr_obj, "name");
-		const char *typeStr = (const char*)json_object_get_string_member(attr_obj, "type");
+		const char *nameStr = (const char *) json_object_get_string_member(attr_obj, "name");
+		const char *typeStr = (const char *) json_object_get_string_member(attr_obj, "type");
 
 		if (NULL == nameStr || NULL == typeStr) {
 			LOGW("Attribute %i wasn't parsed from json file. name and/or "
-					"type of the attribute are parsed as NULL.", attrInd);
+				 "type of the attribute are parsed as NULL.",
+				 attrInd);
 			continue;
 		}
 
 		if (0 == strcmp("double", typeStr)) {
-			__dblDict[std::string(nameStr)] = (double)json_object_get_double_member(attr_obj, "value");
+			__dblDict[std::string(nameStr)] = (double) json_object_get_double_member(attr_obj, "value");
 		} else if (0 == strcmp("integer", typeStr)) {
-			__intDict[std::string(nameStr)] = (int)json_object_get_int_member(attr_obj, "value");
+			__intDict[std::string(nameStr)] = (int) json_object_get_int_member(attr_obj, "value");
 		} else if (0 == strcmp("boolean", typeStr)) {
 			__boolDict[std::string(nameStr)] = json_object_get_boolean_member(attr_obj, "value") ? true : false;
 		} else if (0 == strcmp("string", typeStr)) {
-			__strDict[std::string(nameStr)] = (char*)json_object_get_string_member(attr_obj, "value");
+			__strDict[std::string(nameStr)] = (char *) json_object_get_string_member(attr_obj, "value");
 		} else if (0 == strcmp("array", typeStr)) {
-			const char *subTypeStr = (const char*)json_object_get_string_member(attr_obj, "subtype");
+			const char *subTypeStr = (const char *) json_object_get_string_member(attr_obj, "subtype");
 
 			if (NULL == subTypeStr)
 				continue;
@@ -329,12 +329,12 @@ int EngineConfig::loadDictionaries(std::string& config_file_path)
 					defaultVecStr.push_back(std::string(json_array_get_string_element(attr_array, item)));
 				}
 				__vecStrDict[std::string(nameStr)] = defaultVecStr;
-
 			}
 			//TO-DO: add other subtypes
 		} else {
 			LOGW("Attribute %i:%s wasn't parsed from json file. "
-					"Type isn't supported.", attrInd, nameStr);
+				 "Type isn't supported.",
+				 attrInd, nameStr);
 			continue;
 		}
 	}
diff --git a/mv_common/src/MediaSource.cpp b/mv_common/src/MediaSource.cpp
index 50f956c..84d815b 100644
--- a/mv_common/src/MediaSource.cpp
+++ b/mv_common/src/MediaSource.cpp
@@ -21,25 +21,20 @@
 #include <cstring>
 #include <new>
 
-namespace MediaVision {
-namespace Common {
-
-MediaSource::MediaSource() :
-	m_pBuffer(NULL),
-	m_bufferSize(0),
-	m_width(0),
-	m_height(0),
-	m_colorspace(MEDIA_VISION_COLORSPACE_INVALID)
+namespace MediaVision
 {
-}
+namespace Common
+{
+MediaSource::MediaSource()
+		: m_pBuffer(NULL), m_bufferSize(0), m_width(0), m_height(0), m_colorspace(MEDIA_VISION_COLORSPACE_INVALID)
+{}
 
 MediaSource::~MediaSource()
 {
 	clear();
 }
 
-bool MediaSource::alloc(unsigned int bufferSize,
-		unsigned int width, unsigned int height, mv_colorspace_e colorspace)
+bool MediaSource::alloc(unsigned int bufferSize, unsigned int width, unsigned int height, mv_colorspace_e colorspace)
 {
 	if (bufferSize == 0)
 		return false;
@@ -47,23 +42,26 @@ bool MediaSource::alloc(unsigned int bufferSize,
 	LOGD("Call clear() first for media source %p", this);
 	clear();
 
-	m_pBuffer = new (std::nothrow)unsigned char[bufferSize];
+	m_pBuffer = new (std::nothrow) unsigned char[bufferSize];
 	if (m_pBuffer == NULL) {
 		LOGE("Memory allocating for buffer in media source %p failed!", this);
 		return false;
 	}
 
 	LOGD("Assign new size of the internal buffer of media source %p. "
-			"New size is %ui.", this, bufferSize);
+		 "New size is %ui.",
+		 this, bufferSize);
 	m_bufferSize = bufferSize;
 
 	LOGD("Assign new size (%ui x %ui) of the internal buffer image for "
-			"the media source %p", width, height, this);
+		 "the media source %p",
+		 width, height, this);
 	m_width = width;
 	m_height = height;
 
 	LOGD("Assign new colorspace (%i) of the internal buffer image for "
-			"the media source %p", colorspace, this);
+		 "the media source %p",
+		 colorspace, this);
 	m_colorspace = colorspace;
 
 	return true;
@@ -76,8 +74,9 @@ void MediaSource::clear(void)
 		delete[] m_pBuffer;
 	}
 	LOGD("Set defaults for media source %p : buffer = NULL; "
-			"bufferSize = 0; width = 0; height = 0; "
-			"colorspace = MEDIA_VISION_COLORSPACE_INVALID", this);
+		 "bufferSize = 0; width = 0; height = 0; "
+		 "colorspace = MEDIA_VISION_COLORSPACE_INVALID",
+		 this);
 	m_pBuffer = NULL;
 	m_bufferSize = 0;
 	m_width = 0;
@@ -85,8 +84,8 @@ void MediaSource::clear(void)
 	m_colorspace = MEDIA_VISION_COLORSPACE_INVALID;
 }
 
-bool MediaSource::fill(const unsigned char *buffer, unsigned int bufferSize,
-		unsigned int width, unsigned int height, mv_colorspace_e colorspace)
+bool MediaSource::fill(const unsigned char *buffer, unsigned int bufferSize, unsigned int width, unsigned int height,
+					   mv_colorspace_e colorspace)
 {
 	if (bufferSize == 0 || buffer == NULL)
 		return false;
@@ -96,37 +95,43 @@ bool MediaSource::fill(const unsigned char *buffer, unsigned int bufferSize,
 
 	LOGD("Allocate memory [%i] for buffer in media source %p", bufferSize, this);
 	LOGD("Assign new size (%ui x %ui) of the internal buffer image for "
-			"the media source %p", width, height, this);
+		 "the media source %p",
+		 width, height, this);
 	LOGD("Assign new colorspace (%i) of the internal buffer image for "
-		"the media source %p", colorspace, this);
-	m_pBuffer = new (std::nothrow)unsigned char[bufferSize];
+		 "the media source %p",
+		 colorspace, this);
+	m_pBuffer = new (std::nothrow) unsigned char[bufferSize];
 	if (m_pBuffer == NULL) {
 		LOGE("Memory allocating for buffer in media source %p failed!", this);
 		return false;
 	}
 
 	LOGD("Copy data from external buffer (%p) to the internal buffer (%p) of "
-			"media source %p", buffer, m_pBuffer, this);
+		 "media source %p",
+		 buffer, m_pBuffer, this);
 	std::memcpy(m_pBuffer, buffer, bufferSize);
 
 	LOGD("Assign new size of the internal buffer of media source %p. "
-			"New size is %ui.", this, bufferSize);
+		 "New size is %ui.",
+		 this, bufferSize);
 	m_bufferSize = bufferSize;
 
 	LOGD("Assign new size (%ui x %ui) of the internal buffer image for "
-			"the media source %p", width, height, this);
+		 "the media source %p",
+		 width, height, this);
 	m_width = width;
 	m_height = height;
 
 	LOGD("Assign new colorspace (%i) of the internal buffer image for "
-			"the media source %p", colorspace, this);
+		 "the media source %p",
+		 colorspace, this);
 	m_colorspace = colorspace;
 
 	return true;
 }
 
-bool MediaSource::fill(const unsigned char *buffer, unsigned int bufferSize,
-		unsigned int width, unsigned int height, size_t offset)
+bool MediaSource::fill(const unsigned char *buffer, unsigned int bufferSize, unsigned int width, unsigned int height,
+					   size_t offset)
 {
 	if (bufferSize == 0 || buffer == NULL) {
 		LOGE("bufferSize is %d and buffer[%p]", bufferSize, buffer);
@@ -140,10 +145,12 @@ bool MediaSource::fill(const unsigned char *buffer, unsigned int bufferSize,
 
 	LOGD("Allocate memory [%i] for buffer in media source %p", bufferSize, this);
 	LOGD("Assign new size (%ui x %ui) of the internal buffer image for "
-			"the media source %p", width, height, this);
+		 "the media source %p",
+		 width, height, this);
 
 	LOGD("Copy data from external buffer (%p) to the internal buffer (%p + %zd) of "
-			"media source %p", buffer, m_pBuffer, offset, this);
+		 "media source %p",
+		 buffer, m_pBuffer, offset, this);
 	std::memcpy(m_pBuffer + offset, buffer, bufferSize);
 
 	LOGD("size is %ui x %ui [%ui] on buffer(%p).", width, height, bufferSize, this);
diff --git a/mv_common/src/mv_common.c b/mv_common/src/mv_common.c
index 573945a..19b5432 100644
--- a/mv_common/src/mv_common.c
+++ b/mv_common/src/mv_common.c
@@ -18,8 +18,7 @@
 #include "mv_common.h"
 #include "mv_common_c.h"
 
-int mv_create_source(
-		mv_source_h *source)
+int mv_create_source(mv_source_h *source)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(source);
@@ -31,8 +30,7 @@ int mv_create_source(
 	return ret;
 }
 
-int mv_destroy_source(
-		mv_source_h source)
+int mv_destroy_source(mv_source_h source)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -44,9 +42,7 @@ int mv_destroy_source(
 	return ret;
 }
 
-int mv_source_fill_by_media_packet(
-		mv_source_h source,
-		media_packet_h media_packet)
+int mv_source_fill_by_media_packet(mv_source_h source, media_packet_h media_packet)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -59,29 +55,21 @@ int mv_source_fill_by_media_packet(
 	return ret;
 }
 
-int mv_source_fill_by_buffer(
-		mv_source_h source,
-		unsigned char *data_buffer,
-		unsigned int buffer_size,
-		unsigned int image_width,
-		unsigned int image_height,
-		mv_colorspace_e image_colorspace)
+int mv_source_fill_by_buffer(mv_source_h source, unsigned char *data_buffer, unsigned int buffer_size,
+							 unsigned int image_width, unsigned int image_height, mv_colorspace_e image_colorspace)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
 	MEDIA_VISION_NULL_ARG_CHECK(data_buffer);
 
 	MEDIA_VISION_FUNCTION_ENTER();
-	int ret = mv_source_fill_by_buffer_c(
-		source, data_buffer, buffer_size, image_width, image_height,
-		image_colorspace);
+	int ret = mv_source_fill_by_buffer_c(source, data_buffer, buffer_size, image_width, image_height, image_colorspace);
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_source_clear(
-		mv_source_h source)
+int mv_source_clear(mv_source_h source)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -93,10 +81,7 @@ int mv_source_clear(
 	return ret;
 }
 
-int mv_source_get_buffer(
-		mv_source_h source,
-		unsigned char **data_buffer,
-		unsigned int *buffer_size)
+int mv_source_get_buffer(mv_source_h source, unsigned char **data_buffer, unsigned int *buffer_size)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -110,9 +95,7 @@ int mv_source_get_buffer(
 	return ret;
 }
 
-int mv_source_get_height(
-		mv_source_h source,
-		unsigned int *image_height)
+int mv_source_get_height(mv_source_h source, unsigned int *image_height)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -125,9 +108,7 @@ int mv_source_get_height(
 	return ret;
 }
 
-int mv_source_get_width(
-		mv_source_h source,
-		unsigned int *image_width)
+int mv_source_get_width(mv_source_h source, unsigned int *image_width)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -140,9 +121,7 @@ int mv_source_get_width(
 	return ret;
 }
 
-int mv_source_get_colorspace(
-		mv_source_h source,
-		mv_colorspace_e *image_colorspace)
+int mv_source_get_colorspace(mv_source_h source, mv_colorspace_e *image_colorspace)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -155,8 +134,7 @@ int mv_source_get_colorspace(
 	return ret;
 }
 
-int mv_create_engine_config(
-		mv_engine_config_h *engine_cfg)
+int mv_create_engine_config(mv_engine_config_h *engine_cfg)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(engine_cfg);
@@ -168,8 +146,7 @@ int mv_create_engine_config(
 	return ret;
 }
 
-int mv_destroy_engine_config(
-		mv_engine_config_h engine_cfg)
+int mv_destroy_engine_config(mv_engine_config_h engine_cfg)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(engine_cfg);
@@ -181,61 +158,46 @@ int mv_destroy_engine_config(
 	return ret;
 }
 
-int mv_engine_config_set_double_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		double value)
+int mv_engine_config_set_double_attribute(mv_engine_config_h engine_cfg, const char *name, double value)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(engine_cfg);
 	MEDIA_VISION_NULL_ARG_CHECK(name);
 
 	MEDIA_VISION_FUNCTION_ENTER();
-	int ret = mv_engine_config_set_double_attribute_c(
-					engine_cfg, name, value);
+	int ret = mv_engine_config_set_double_attribute_c(engine_cfg, name, value);
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_engine_config_set_int_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		int value)
+int mv_engine_config_set_int_attribute(mv_engine_config_h engine_cfg, const char *name, int value)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(engine_cfg);
 	MEDIA_VISION_NULL_ARG_CHECK(name);
 
 	MEDIA_VISION_FUNCTION_ENTER();
-	int ret = mv_engine_config_set_int_attribute_c(
-					engine_cfg, name, value);
+	int ret = mv_engine_config_set_int_attribute_c(engine_cfg, name, value);
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_engine_config_set_bool_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		bool value)
+int mv_engine_config_set_bool_attribute(mv_engine_config_h engine_cfg, const char *name, bool value)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(engine_cfg);
 	MEDIA_VISION_NULL_ARG_CHECK(name);
 
 	MEDIA_VISION_FUNCTION_ENTER();
-	int ret = mv_engine_config_set_bool_attribute_c(
-					engine_cfg, name, value);
+	int ret = mv_engine_config_set_bool_attribute_c(engine_cfg, name, value);
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_engine_config_set_string_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		const char *value)
+int mv_engine_config_set_string_attribute(mv_engine_config_h engine_cfg, const char *name, const char *value)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(engine_cfg);
@@ -243,18 +205,14 @@ int mv_engine_config_set_string_attribute(
 	MEDIA_VISION_NULL_ARG_CHECK(value);
 
 	MEDIA_VISION_FUNCTION_ENTER();
-	int ret = mv_engine_config_set_string_attribute_c(
-					engine_cfg, name, value);
+	int ret = mv_engine_config_set_string_attribute_c(engine_cfg, name, value);
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_engine_config_set_array_string_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		const char **values,
-		unsigned int size)
+int mv_engine_config_set_array_string_attribute(mv_engine_config_h engine_cfg, const char *name, const char **values,
+												unsigned int size)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(engine_cfg);
@@ -263,17 +221,13 @@ int mv_engine_config_set_array_string_attribute(
 
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	int ret = mv_engine_config_set_array_string_attribute_c(
-					engine_cfg, name, values, size);
+	int ret = mv_engine_config_set_array_string_attribute_c(engine_cfg, name, values, size);
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_engine_config_get_double_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		double *value)
+int mv_engine_config_get_double_attribute(mv_engine_config_h engine_cfg, const char *name, double *value)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(engine_cfg);
@@ -281,17 +235,13 @@ int mv_engine_config_get_double_attribute(
 	MEDIA_VISION_NULL_ARG_CHECK(value);
 
 	MEDIA_VISION_FUNCTION_ENTER();
-	int ret = mv_engine_config_get_double_attribute_c(
-					engine_cfg, name, value);
+	int ret = mv_engine_config_get_double_attribute_c(engine_cfg, name, value);
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_engine_config_get_int_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		int *value)
+int mv_engine_config_get_int_attribute(mv_engine_config_h engine_cfg, const char *name, int *value)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(engine_cfg);
@@ -299,17 +249,13 @@ int mv_engine_config_get_int_attribute(
 	MEDIA_VISION_NULL_ARG_CHECK(value);
 
 	MEDIA_VISION_FUNCTION_ENTER();
-	int ret = mv_engine_config_get_int_attribute_c(
-		engine_cfg, name, value);
+	int ret = mv_engine_config_get_int_attribute_c(engine_cfg, name, value);
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_engine_config_get_bool_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		bool *value)
+int mv_engine_config_get_bool_attribute(mv_engine_config_h engine_cfg, const char *name, bool *value)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(engine_cfg);
@@ -317,17 +263,13 @@ int mv_engine_config_get_bool_attribute(
 	MEDIA_VISION_NULL_ARG_CHECK(value);
 
 	MEDIA_VISION_FUNCTION_ENTER();
-	int ret = mv_engine_config_get_bool_attribute_c(
-					engine_cfg, name, value);
+	int ret = mv_engine_config_get_bool_attribute_c(engine_cfg, name, value);
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_engine_config_get_string_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		char **value)
+int mv_engine_config_get_string_attribute(mv_engine_config_h engine_cfg, const char *name, char **value)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(engine_cfg);
@@ -335,18 +277,14 @@ int mv_engine_config_get_string_attribute(
 	MEDIA_VISION_NULL_ARG_CHECK(value);
 
 	MEDIA_VISION_FUNCTION_ENTER();
-	int ret = mv_engine_config_get_string_attribute_c(
-					engine_cfg, name, value);
+	int ret = mv_engine_config_get_string_attribute_c(engine_cfg, name, value);
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_engine_config_get_array_string_attribute(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		char ***values,
-		int *size)
+int mv_engine_config_get_array_string_attribute(mv_engine_config_h engine_cfg, const char *name, char ***values,
+												int *size)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(engine_cfg);
@@ -354,23 +292,19 @@ int mv_engine_config_get_array_string_attribute(
 	MEDIA_VISION_NULL_ARG_CHECK(values);
 
 	MEDIA_VISION_FUNCTION_ENTER();
-	int ret = mv_engine_config_get_array_string_attribute_c(
-					engine_cfg, name, values, size);
+	int ret = mv_engine_config_get_array_string_attribute_c(engine_cfg, name, values, size);
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_engine_config_foreach_supported_attribute(
-		mv_supported_attribute_cb callback,
-		void *user_data)
+int mv_engine_config_foreach_supported_attribute(mv_supported_attribute_cb callback, void *user_data)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(callback);
 
 	MEDIA_VISION_FUNCTION_ENTER();
-	int ret = mv_engine_config_foreach_supported_attribute_c(
-					callback, user_data);
+	int ret = mv_engine_config_foreach_supported_attribute_c(callback, user_data);
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
diff --git a/mv_common/src/mv_common_c.cpp b/mv_common/src/mv_common_c.cpp
index 76b249b..67ac10e 100644
--- a/mv_common/src/mv_common_c.cpp
+++ b/mv_common/src/mv_common_c.cpp
@@ -27,15 +27,13 @@
 #include <stdlib.h>
 #include <media_packet.h>
 
-int mv_create_source_c(
-		mv_source_h *source_ptr)
+int mv_create_source_c(mv_source_h *source_ptr)
 {
 	if (source_ptr == NULL)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 
 	LOGD("Creating media vision source");
-	(*source_ptr) = (static_cast<mv_source_h>
-			(new (std::nothrow)MediaVision::Common::MediaSource()));
+	(*source_ptr) = (static_cast<mv_source_h>(new (std::nothrow) MediaVision::Common::MediaSource()));
 
 	if (*source_ptr == NULL) {
 		LOGE("Failed to create media vision source");
@@ -46,8 +44,7 @@ int mv_create_source_c(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_destroy_source_c(
-		mv_source_h source)
+int mv_destroy_source_c(mv_source_h source)
 {
 	if (!source) {
 		LOGE("Media source can't be destroyed because handle is NULL");
@@ -55,20 +52,19 @@ int mv_destroy_source_c(
 	}
 
 	LOGD("Destroying media vision source [%p]", source);
-	delete (static_cast<MediaVision::Common::MediaSource*>(source));
+	delete (static_cast<MediaVision::Common::MediaSource *>(source));
 	LOGD("Media vision source has been destroyed");
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_source_fill_by_media_packet_c(
-		mv_source_h source,
-		media_packet_h media_packet)
+int mv_source_fill_by_media_packet_c(mv_source_h source, media_packet_h media_packet)
 {
 	if (!source || !media_packet) {
 		LOGE("Media source can't be filled by media_packet handle because "
-				"one of the source or media_packet handles is NULL. "
-				"source = %p; media_packet = %p", source, media_packet);
+			 "one of the source or media_packet handles is NULL. "
+			 "source = %p; media_packet = %p",
+			 source, media_packet);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
@@ -78,10 +74,16 @@ int mv_source_fill_by_media_packet_c(
 	int image_width = 0;
 	int image_height = 0;
 
-	int plane_width[4] = {0, };
-	int plane_height[4] = {0, };
-	uint64_t plane_size[4] = {0, };
-	size_t  offset = 0;
+	int plane_width[4] = {
+		0,
+	};
+	int plane_height[4] = {
+		0,
+	};
+	uint64_t plane_size[4] = {
+		0,
+	};
+	size_t offset = 0;
 	media_format_h format = NULL;
 	media_format_mimetype_e mimetype = MEDIA_FORMAT_I420;
 	unsigned char *data_buffer = NULL;
@@ -105,8 +107,7 @@ int mv_source_fill_by_media_packet_c(
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	ret = media_format_get_video_info(
-			format, &mimetype, &image_width, &image_height, NULL, NULL);
+	ret = media_format_get_video_info(format, &mimetype, &image_width, &image_height, NULL, NULL);
 	if (ret != MEDIA_PACKET_ERROR_NONE) {
 		LOGE("media_format_get_video_info() failed, mv_source_h fill skipped");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -150,7 +151,8 @@ int mv_source_fill_by_media_packet_c(
 		break;
 	default:
 		LOGE("Format of the media packet buffer is not supported by media "
-				"vision source (media_format_h mimetype=%i)", mimetype);
+			 "vision source (media_format_h mimetype=%i)",
+			 mimetype);
 		return MEDIA_VISION_ERROR_NOT_SUPPORTED_FORMAT;
 	}
 
@@ -180,23 +182,24 @@ int mv_source_fill_by_media_packet_c(
 		buffer_size += plane_size[ind];
 	}
 
-	if (!(static_cast<MediaVision::Common::MediaSource*>(source))->alloc(buffer_size,
-			static_cast<unsigned int>(plane_width[0]),
-			static_cast<unsigned int>(plane_height[0]), image_colorspace)) {
+	if (!(static_cast<MediaVision::Common::MediaSource *>(source))
+				 ->alloc(buffer_size, static_cast<unsigned int>(plane_width[0]),
+						 static_cast<unsigned int>(plane_height[0]), image_colorspace)) {
 		LOGE("mv_source_h alloc from media_packet_h failed");
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 	}
 
 	for (ind = 0; ind < plane_num; ++ind) {
-		ret = media_packet_get_video_plane_data_ptr(media_packet, ind, (void**)&data_buffer);
+		ret = media_packet_get_video_plane_data_ptr(media_packet, ind, (void **) &data_buffer);
 		if (ret != MEDIA_PACKET_ERROR_NONE) {
 			LOGE("media_packet_get_video_plane_data_ptr() plane[%d] failed, mv_source_h fill skipped", ind);
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 		}
 
-		offset = (ind == 0) ? 0 : plane_size[ind-1]*sizeof(char);
-		if (!(static_cast<MediaVision::Common::MediaSource*>(source))->fill(data_buffer, plane_size[ind],
-			static_cast<unsigned int>(plane_width[ind]), static_cast<unsigned int>(plane_height[ind]), offset)) {
+		offset = (ind == 0) ? 0 : plane_size[ind - 1] * sizeof(char);
+		if (!(static_cast<MediaVision::Common::MediaSource *>(source))
+					 ->fill(data_buffer, plane_size[ind], static_cast<unsigned int>(plane_width[ind]),
+							static_cast<unsigned int>(plane_height[ind]), offset)) {
 			LOGE("mv_source_h filling from media_packet_h failed");
 			return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 		}
@@ -207,24 +210,19 @@ int mv_source_fill_by_media_packet_c(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_source_fill_by_buffer_c(
-		mv_source_h source,
-		unsigned char *data_buffer,
-		unsigned int buffer_size,
-		unsigned int image_width,
-		unsigned int image_height,
-		mv_colorspace_e image_colorspace)
+int mv_source_fill_by_buffer_c(mv_source_h source, unsigned char *data_buffer, unsigned int buffer_size,
+							   unsigned int image_width, unsigned int image_height, mv_colorspace_e image_colorspace)
 {
 	if (!source || buffer_size == 0 || data_buffer == NULL) {
 		LOGE("Media source can't be filled by buffer because "
-				"one of the source or data_buffer is NULL or buffer_size = 0. "
-				"source = %p; data_buffer = %p; buffer_size = %u",
-				source, data_buffer, buffer_size);
+			 "one of the source or data_buffer is NULL or buffer_size = 0. "
+			 "source = %p; data_buffer = %p; buffer_size = %u",
+			 source, data_buffer, buffer_size);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	if (!(static_cast<MediaVision::Common::MediaSource*>(source))->fill(data_buffer,
-			buffer_size, image_width, image_height, image_colorspace)) {
+	if (!(static_cast<MediaVision::Common::MediaSource *>(source))
+				 ->fill(data_buffer, buffer_size, image_width, image_height, image_colorspace)) {
 		LOGE("mv_source_h filling from buffer failed");
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 	}
@@ -233,8 +231,7 @@ int mv_source_fill_by_buffer_c(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_source_clear_c(
-		mv_source_h source)
+int mv_source_clear_c(mv_source_h source)
 {
 	if (!source) {
 		LOGE("Media source can't be cleared because source handle is NULL");
@@ -242,16 +239,13 @@ int mv_source_clear_c(
 	}
 
 	LOGD("Clear media vision source [%p]", source);
-	(static_cast<MediaVision::Common::MediaSource*>(source))->clear();
+	(static_cast<MediaVision::Common::MediaSource *>(source))->clear();
 	LOGD("Media vision source [%p] has been cleared", source);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_source_get_buffer_c(
-		mv_source_h source,
-		unsigned char **buffer,
-		unsigned int *size)
+int mv_source_get_buffer_c(mv_source_h source, unsigned char **buffer, unsigned int *size)
 {
 	if (!source) {
 		LOGE("Impossible to get buffer for NULL mv_source_h handle");
@@ -259,16 +253,14 @@ int mv_source_get_buffer_c(
 	}
 
 	LOGD("Get media vision source [%p] buffer and buffer size to be returned", source);
-	*buffer = (static_cast<MediaVision::Common::MediaSource*>(source))->getBuffer();
-	*size = (static_cast<MediaVision::Common::MediaSource*>(source))->getBufferSize();
+	*buffer = (static_cast<MediaVision::Common::MediaSource *>(source))->getBuffer();
+	*size = (static_cast<MediaVision::Common::MediaSource *>(source))->getBufferSize();
 	LOGD("Media vision source [%p] buffer (%p) and buffer size (%ui) has been returned", source, buffer, *size);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_source_get_height_c(
-		mv_source_h source,
-		unsigned int *height)
+int mv_source_get_height_c(mv_source_h source, unsigned int *height)
 {
 	if (!source) {
 		LOGE("Impossible to get height for NULL mv_source_h handle");
@@ -276,15 +268,13 @@ int mv_source_get_height_c(
 	}
 
 	LOGD("Get media vision source [%p] height to be returned", source);
-	*height = (static_cast<MediaVision::Common::MediaSource*>(source))->getHeight();
+	*height = (static_cast<MediaVision::Common::MediaSource *>(source))->getHeight();
 	LOGD("Media vision source [%p] height (%ui) has been returned", source, *height);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_source_get_width_c(
-		mv_source_h source,
-		unsigned int *width)
+int mv_source_get_width_c(mv_source_h source, unsigned int *width)
 {
 	if (!source) {
 		LOGE("Impossible to get width for NULL mv_source_h handle");
@@ -292,15 +282,13 @@ int mv_source_get_width_c(
 	}
 
 	LOGD("Get media vision source [%p] width to be returned", source);
-	*width = (static_cast<MediaVision::Common::MediaSource*>(source))->getWidth();
+	*width = (static_cast<MediaVision::Common::MediaSource *>(source))->getWidth();
 	LOGD("Media vision source [%p] width (%ui) has been returned", source, *width);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_source_get_colorspace_c(
-		mv_source_h source,
-		mv_colorspace_e *colorspace)
+int mv_source_get_colorspace_c(mv_source_h source, mv_colorspace_e *colorspace)
 {
 	if (!source) {
 		LOGE("Impossible to get colorspace for NULL mv_source_h handle");
@@ -308,14 +296,13 @@ int mv_source_get_colorspace_c(
 	}
 
 	LOGD("Get media vision source [%p] colorspace to be returned", source);
-	*colorspace = (static_cast<MediaVision::Common::MediaSource*>(source))->getColorspace();
+	*colorspace = (static_cast<MediaVision::Common::MediaSource *>(source))->getColorspace();
 	LOGD("Media vision source [%p] colorspace (%i) has been returned", source, *colorspace);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_create_engine_config_c(
-		mv_engine_config_h *engine_cfg)
+int mv_create_engine_config_c(mv_engine_config_h *engine_cfg)
 {
 	if (engine_cfg == NULL) {
 		LOGE("Impossible to create mv_engine_config_h handle");
@@ -324,8 +311,7 @@ int mv_create_engine_config_c(
 
 	LOGD("Creating media vision engine config");
 	try {
-		(*engine_cfg) = static_cast<mv_engine_config_h>
-			(new MediaVision::Common::EngineConfig());
+		(*engine_cfg) = static_cast<mv_engine_config_h>(new MediaVision::Common::EngineConfig());
 	} catch (...) {
 		LOGE("Failed to create mv_engine_config_h handle");
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
@@ -335,8 +321,7 @@ int mv_create_engine_config_c(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_destroy_engine_config_c(
-		mv_engine_config_h engine_cfg)
+int mv_destroy_engine_config_c(mv_engine_config_h engine_cfg)
 {
 	if (!engine_cfg) {
 		LOGE("Impossible to destroy NULL mv_engine_config_h handle");
@@ -344,30 +329,25 @@ int mv_destroy_engine_config_c(
 	}
 
 	LOGD("Destroying media vision engine config [%p]", engine_cfg);
-	delete (static_cast<MediaVision::Common::EngineConfig*>(engine_cfg));
+	delete (static_cast<MediaVision::Common::EngineConfig *>(engine_cfg));
 	LOGD("Media vision engine config has been destroyed");
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_engine_config_set_double_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		double value)
+int mv_engine_config_set_double_attribute_c(mv_engine_config_h engine_cfg, const char *name, double value)
 {
 	if (!engine_cfg || name == NULL) {
 		LOGE("Impossible to set attribute. One of the required parameters is "
-				"NULL. engine_cfg = %p; name = %p;",
-				engine_cfg, name);
+			 "NULL. engine_cfg = %p; name = %p;",
+			 engine_cfg, name);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	int ret = (static_cast<MediaVision::Common::EngineConfig*>(engine_cfg))->setAttribute(
-			std::string(name), value);
+	int ret = (static_cast<MediaVision::Common::EngineConfig *>(engine_cfg))->setAttribute(std::string(name), value);
 
 	if (ret != MEDIA_VISION_ERROR_NONE) {
-		LOGE("Failed to set attribute [%s] with value %f. Error code (0x%08x)",
-				name, value, ret);
+		LOGE("Failed to set attribute [%s] with value %f. Error code (0x%08x)", name, value, ret);
 		return ret;
 	}
 
@@ -375,24 +355,19 @@ int mv_engine_config_set_double_attribute_c(
 	return ret;
 }
 
-int mv_engine_config_set_int_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		int value)
+int mv_engine_config_set_int_attribute_c(mv_engine_config_h engine_cfg, const char *name, int value)
 {
 	if (!engine_cfg || name == NULL) {
 		LOGE("Impossible to set attribute. One of the required parameters is "
-				"NULL. engine_cfg = %p; name = %p;",
-				engine_cfg, name);
+			 "NULL. engine_cfg = %p; name = %p;",
+			 engine_cfg, name);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	int ret = (static_cast<MediaVision::Common::EngineConfig*>(engine_cfg))->setAttribute(
-			std::string(name), value);
+	int ret = (static_cast<MediaVision::Common::EngineConfig *>(engine_cfg))->setAttribute(std::string(name), value);
 
 	if (ret != MEDIA_VISION_ERROR_NONE) {
-		LOGE("Failed to set attribute [%s] with value %i. Error code (0x%08x)",
-				name, value, ret);
+		LOGE("Failed to set attribute [%s] with value %i. Error code (0x%08x)", name, value, ret);
 		return ret;
 	}
 
@@ -401,50 +376,40 @@ int mv_engine_config_set_int_attribute_c(
 	return ret;
 }
 
-int mv_engine_config_set_bool_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		bool value)
+int mv_engine_config_set_bool_attribute_c(mv_engine_config_h engine_cfg, const char *name, bool value)
 {
 	if (!engine_cfg || name == NULL) {
 		LOGE("Impossible to set attribute. One of the required parameters is "
-				"NULL. engine_cfg = %p; name = %p;",
-				engine_cfg, name);
+			 "NULL. engine_cfg = %p; name = %p;",
+			 engine_cfg, name);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	int ret = (static_cast<MediaVision::Common::EngineConfig*>(engine_cfg))->setAttribute(
-			std::string(name), value);
+	int ret = (static_cast<MediaVision::Common::EngineConfig *>(engine_cfg))->setAttribute(std::string(name), value);
 
 	if (ret != MEDIA_VISION_ERROR_NONE) {
-		LOGE("Failed to set attribute [%s] with value %s. Error code (0x%08x)",
-				name, value ? "TRUE" : "FALSE", ret);
+		LOGE("Failed to set attribute [%s] with value %s. Error code (0x%08x)", name, value ? "TRUE" : "FALSE", ret);
 		return ret;
 	}
 
-	LOGD("Attribute [%s] (value %s) has been set",
-			name, value ? "TRUE" : "FALSE");
+	LOGD("Attribute [%s] (value %s) has been set", name, value ? "TRUE" : "FALSE");
 	return ret;
 }
 
-int mv_engine_config_set_string_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		const char *value)
+int mv_engine_config_set_string_attribute_c(mv_engine_config_h engine_cfg, const char *name, const char *value)
 {
 	if (!engine_cfg || name == NULL || value == NULL) {
 		LOGE("Impossible to set attribute. One of the required parameters is "
-				"NULL. engine_cfg = %p; name = %p; value = %p;",
-				engine_cfg, name, value);
+			 "NULL. engine_cfg = %p; name = %p; value = %p;",
+			 engine_cfg, name, value);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	int ret = (static_cast<MediaVision::Common::EngineConfig*>(engine_cfg))->setAttribute(
-			std::string(name), std::string(value));
+	int ret = (static_cast<MediaVision::Common::EngineConfig *>(engine_cfg))
+					  ->setAttribute(std::string(name), std::string(value));
 
 	if (ret != MEDIA_VISION_ERROR_NONE) {
-		LOGE("Failed to set attribute [%s] with value %s. Error code (0x%08x)",
-				name, value, ret);
+		LOGE("Failed to set attribute [%s] with value %s. Error code (0x%08x)", name, value, ret);
 		return ret;
 	}
 
@@ -452,16 +417,13 @@ int mv_engine_config_set_string_attribute_c(
 	return ret;
 }
 
-int mv_engine_config_set_array_string_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		const char **values,
-		unsigned int size)
+int mv_engine_config_set_array_string_attribute_c(mv_engine_config_h engine_cfg, const char *name, const char **values,
+												  unsigned int size)
 {
 	if (!engine_cfg || name == NULL || values == NULL) {
 		LOGE("Impossible to set attribute. One of the required parameters is "
-				"NULL. engine_cfg = %p; name = %p; values = %p;",
-				engine_cfg, name, values);
+			 "NULL. engine_cfg = %p; name = %p; values = %p;",
+			 engine_cfg, name, values);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
@@ -476,8 +438,8 @@ int mv_engine_config_set_array_string_attribute_c(
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	int ret = (static_cast<MediaVision::Common::EngineConfig*>(engine_cfg))->setAttribute(
-			std::string(name), arrayValues);
+	int ret =
+			(static_cast<MediaVision::Common::EngineConfig *>(engine_cfg))->setAttribute(std::string(name), arrayValues);
 
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Failed to set attribute [%s]. Error code (0x%08x)", name, ret);
@@ -488,109 +450,90 @@ int mv_engine_config_set_array_string_attribute_c(
 	return ret;
 }
 
-int mv_engine_config_get_double_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		double *value)
+int mv_engine_config_get_double_attribute_c(mv_engine_config_h engine_cfg, const char *name, double *value)
 {
 	if (!engine_cfg || name == NULL || value == NULL) {
 		LOGE("Impossible to get attribute. One of the required parameters is "
-				"NULL. engine_cfg = %p; name = %p; value = %p;",
-				engine_cfg, name, value);
+			 "NULL. engine_cfg = %p; name = %p; value = %p;",
+			 engine_cfg, name, value);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	int ret = (static_cast<MediaVision::Common::EngineConfig*>(engine_cfg))->getDoubleAttribute(
-			std::string(name), value);
+	int ret =
+			(static_cast<MediaVision::Common::EngineConfig *>(engine_cfg))->getDoubleAttribute(std::string(name), value);
 
 	if (ret != MEDIA_VISION_ERROR_NONE) {
-		LOGE("Failed to get attribute [%s]. Error code (0x%08x)",
-				name, ret);
+		LOGE("Failed to get attribute [%s]. Error code (0x%08x)", name, ret);
 		return ret;
 	}
 
-	LOGD("Attribute [%s] (value %f) has been gotten",
-			name, *value);
+	LOGD("Attribute [%s] (value %f) has been gotten", name, *value);
 	return ret;
 }
 
-int mv_engine_config_get_int_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		int *value)
+int mv_engine_config_get_int_attribute_c(mv_engine_config_h engine_cfg, const char *name, int *value)
 {
 	if (!engine_cfg || name == NULL || value == NULL) {
 		LOGE("Impossible to get attribute. One of the required parameters is "
-				"NULL. engine_cfg = %p; name = %p; value = %p;",
-				engine_cfg, name, value);
+			 "NULL. engine_cfg = %p; name = %p; value = %p;",
+			 engine_cfg, name, value);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	int ret = (static_cast<MediaVision::Common::EngineConfig*>(engine_cfg))->getIntegerAttribute(
-			std::string(name), value);
+	int ret = (static_cast<MediaVision::Common::EngineConfig *>(engine_cfg))
+					  ->getIntegerAttribute(std::string(name), value);
 
 	if (ret != MEDIA_VISION_ERROR_NONE) {
-		LOGE("Failed to get attribute [%s]. Error code (0x%08x)",
-				name, ret);
+		LOGE("Failed to get attribute [%s]. Error code (0x%08x)", name, ret);
 		return ret;
 	}
 
-	LOGD("Attribute [%s] (value %i) has been gotten",
-			name, *value);
+	LOGD("Attribute [%s] (value %i) has been gotten", name, *value);
 	return ret;
 }
 
-int mv_engine_config_get_bool_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		bool *value)
+int mv_engine_config_get_bool_attribute_c(mv_engine_config_h engine_cfg, const char *name, bool *value)
 {
 	if (!engine_cfg || name == NULL || value == NULL) {
 		LOGE("Impossible to get attribute. One of the required parameters is "
-				"NULL. engine_cfg = %p; name = %p; value = %p;",
-				engine_cfg, name, value);
+			 "NULL. engine_cfg = %p; name = %p; value = %p;",
+			 engine_cfg, name, value);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	int ret = (static_cast<MediaVision::Common::EngineConfig*>(engine_cfg))->getBooleanAttribute(
-			std::string(name), value);
+	int ret = (static_cast<MediaVision::Common::EngineConfig *>(engine_cfg))
+					  ->getBooleanAttribute(std::string(name), value);
 
 	if (ret != MEDIA_VISION_ERROR_NONE) {
-		LOGE("Failed to get attribute [%s]. Error code (0x%08x)",
-				name, ret);
+		LOGE("Failed to get attribute [%s]. Error code (0x%08x)", name, ret);
 		return ret;
 	}
 
-	LOGD("Attribute [%s] (value %s) has been gotten",
-			name, *value ? "TRUE" : "FALSE");
+	LOGD("Attribute [%s] (value %s) has been gotten", name, *value ? "TRUE" : "FALSE");
 	return ret;
 }
 
-int mv_engine_config_get_string_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		char **value)
+int mv_engine_config_get_string_attribute_c(mv_engine_config_h engine_cfg, const char *name, char **value)
 {
 	if (!engine_cfg || name == NULL || value == NULL) {
 		LOGE("Impossible to get attribute. One of the required parameters is "
-				"NULL. engine_cfg = %p; name = %p; value = %p;",
-				engine_cfg, name, value);
+			 "NULL. engine_cfg = %p; name = %p; value = %p;",
+			 engine_cfg, name, value);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
 	std::string attributeValue;
-	int ret = (static_cast<MediaVision::Common::EngineConfig*>(engine_cfg))->getStringAttribute(
-			std::string(name), &attributeValue);
+	int ret = (static_cast<MediaVision::Common::EngineConfig *>(engine_cfg))
+					  ->getStringAttribute(std::string(name), &attributeValue);
 
 	if (ret != MEDIA_VISION_ERROR_NONE) {
-		LOGE("Failed to get attribute [%s]. Error code (0x%08x)",
-				name, ret);
+		LOGE("Failed to get attribute [%s]. Error code (0x%08x)", name, ret);
 		return ret;
 	}
 
 	LOGD("Convert string to char*");
 	int stringSize = attributeValue.size();
-	(*value) = (char*)malloc(sizeof(char) * (stringSize + 1));
+	(*value) = (char *) malloc(sizeof(char) * (stringSize + 1));
 	if ((*value) == NULL) {
 		LOGE("Failed to convert string to char*");
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
@@ -604,7 +547,7 @@ int mv_engine_config_get_string_attribute_c(
 			(*value) = NULL;
 			return MEDIA_VISION_ERROR_INVALID_OPERATION;
 		}
-	} catch (std::out_of_range& e) {
+	} catch (std::out_of_range &e) {
 		LOGE("Conversion from string to char* failed");
 		free(*value);
 		(*value) = NULL;
@@ -612,38 +555,33 @@ int mv_engine_config_get_string_attribute_c(
 	}
 	(*value)[stringSize] = '\0';
 
-	LOGD("Attribute [%s] (value %s) has been gotten",
-			name, *value);
+	LOGD("Attribute [%s] (value %s) has been gotten", name, *value);
 	return ret;
 }
 
-int mv_engine_config_get_array_string_attribute_c(
-		mv_engine_config_h engine_cfg,
-		const char *name,
-		char ***values,
-		int *size)
+int mv_engine_config_get_array_string_attribute_c(mv_engine_config_h engine_cfg, const char *name, char ***values,
+												  int *size)
 {
 	if (!engine_cfg || name == NULL || values == NULL) {
 		LOGE("Impossible to get attribute. One of the required parameters is "
-				"NULL. engine_cfg = %p; name = %p; values = %p;",
-				engine_cfg, name, values);
+			 "NULL. engine_cfg = %p; name = %p; values = %p;",
+			 engine_cfg, name, values);
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
 	std::vector<std::string> attributeValue;
-	int ret = (static_cast<MediaVision::Common::EngineConfig*>(engine_cfg))->getStringAttribute(
-			std::string(name), &attributeValue);
+	int ret = (static_cast<MediaVision::Common::EngineConfig *>(engine_cfg))
+					  ->getStringAttribute(std::string(name), &attributeValue);
 
 	if (ret != MEDIA_VISION_ERROR_NONE) {
-		LOGE("Failed to get attribute [%s]. Error code (0x%08x)",
-				name, ret);
+		LOGE("Failed to get attribute [%s]. Error code (0x%08x)", name, ret);
 		return ret;
 	}
 
 	int attributeSize = attributeValue.size();
 	LOGD("Allocating %d arrays", attributeSize);
 
-	(*values) = (char**)malloc(sizeof(char*) * attributeSize);
+	(*values) = (char **) malloc(sizeof(char *) * attributeSize);
 	if ((*values) == NULL) {
 		LOGE("Failed allocation");
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
@@ -651,10 +589,10 @@ int mv_engine_config_get_array_string_attribute_c(
 	(*size) = attributeSize;
 
 	int stringSize = 0;
-	for(int idx = 0; idx < attributeSize; ++idx) {
+	for (int idx = 0; idx < attributeSize; ++idx) {
 		stringSize = attributeValue[idx].size();
 		LOGE("Converting %s with length %d to char*", attributeValue[idx].c_str(), stringSize);
-		(*values)[idx] = (char*)malloc(sizeof(char) * (stringSize + 1));
+		(*values)[idx] = (char *) malloc(sizeof(char) * (stringSize + 1));
 		if ((*values)[idx] == NULL) {
 			LOGE("Failed to convert string to char*");
 
@@ -680,20 +618,17 @@ int mv_engine_config_get_array_string_attribute_c(
 		}
 		((*values)[idx])[stringSize] = '\0';
 
-		LOGD("Attribute [%s] (value[%d] %s) has been gotten",
-			name, idx, (*values)[idx]);
+		LOGD("Attribute [%s] (value[%d] %s) has been gotten", name, idx, (*values)[idx]);
 	}
 
 	return ret;
 }
 
-int mv_engine_config_foreach_supported_attribute_c(
-		mv_supported_attribute_cb callback,
-		void *user_data)
+int mv_engine_config_foreach_supported_attribute_c(mv_supported_attribute_cb callback, void *user_data)
 {
 	if (NULL == callback) {
 		LOGE("Impossible to traverse supported by Media Vision engine "
-				"configuration attributes. Callback is NULL");
+			 "configuration attributes. Callback is NULL");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
@@ -702,15 +637,14 @@ int mv_engine_config_foreach_supported_attribute_c(
 
 	try {
 		config = std::make_unique<EngineConfig>();
-	} catch(int& exception) {
+	} catch (int &exception) {
 		return exception;
 	}
 
 	DictDblConstIter dblDictIter = config->getDefaultDblDict().begin();
 
 	while (dblDictIter != config->getDefaultDblDict().end()) {
-		if (!callback(MV_ENGINE_CONFIG_ATTR_TYPE_DOUBLE,
-				dblDictIter->first.c_str(), user_data)) {
+		if (!callback(MV_ENGINE_CONFIG_ATTR_TYPE_DOUBLE, dblDictIter->first.c_str(), user_data)) {
 			LOGD("Attribute names/types traverse has been stopped by the user");
 			return MEDIA_VISION_ERROR_NONE;
 		}
@@ -720,8 +654,7 @@ int mv_engine_config_foreach_supported_attribute_c(
 	DictIntConstIter intDictIter = config->getDefaultIntDict().begin();
 
 	while (intDictIter != config->getDefaultIntDict().end()) {
-		if (!callback(MV_ENGINE_CONFIG_ATTR_TYPE_INTEGER,
-				intDictIter->first.c_str(), user_data)) {
+		if (!callback(MV_ENGINE_CONFIG_ATTR_TYPE_INTEGER, intDictIter->first.c_str(), user_data)) {
 			LOGD("Attribute names/types traverse has been stopped by the user");
 			return MEDIA_VISION_ERROR_NONE;
 		}
@@ -731,8 +664,7 @@ int mv_engine_config_foreach_supported_attribute_c(
 	DictBoolConstIter boolDictIter = config->getDefaultBoolDict().begin();
 
 	while (boolDictIter != config->getDefaultBoolDict().end()) {
-		if (!callback(MV_ENGINE_CONFIG_ATTR_TYPE_BOOLEAN,
-				boolDictIter->first.c_str(), user_data)) {
+		if (!callback(MV_ENGINE_CONFIG_ATTR_TYPE_BOOLEAN, boolDictIter->first.c_str(), user_data)) {
 			LOGD("Attribute names/types traverse has been stopped by the user");
 			return MEDIA_VISION_ERROR_NONE;
 		}
@@ -742,8 +674,7 @@ int mv_engine_config_foreach_supported_attribute_c(
 	DictStrConstIter strDictIter = config->getDefaultStrDict().begin();
 
 	while (strDictIter != config->getDefaultStrDict().end()) {
-		if (!callback(MV_ENGINE_CONFIG_ATTR_TYPE_STRING,
-				strDictIter->first.c_str(), user_data)) {
+		if (!callback(MV_ENGINE_CONFIG_ATTR_TYPE_STRING, strDictIter->first.c_str(), user_data)) {
 			LOGD("Attribute names/types traverse has been stopped by the user");
 			return MEDIA_VISION_ERROR_NONE;
 		}
diff --git a/mv_common/src/mv_private.c b/mv_common/src/mv_private.c
index 56ac8ca..84be33a 100644
--- a/mv_common/src/mv_private.c
+++ b/mv_common/src/mv_private.c
@@ -23,12 +23,12 @@
 static gpointer __get_system_info_feature_once(gpointer data)
 {
 	bool supported = false;
-	gchar *feature = (gchar *)data;
+	gchar *feature = (gchar *) data;
 
 	if (system_info_get_platform_bool(feature, &supported) != SYSTEM_INFO_ERROR_NONE)
 		LOGE("SYSTEM_INFO_ERROR: %s", feature);
 
-	return (gpointer)supported;
+	return (gpointer) supported;
 }
 
 bool _mv_check_system_info_feature_supported(void)
@@ -40,93 +40,83 @@ bool _mv_check_system_info_feature_supported(void)
 	bool isInferenceImageSupported = false;
 	bool isInferenceFaceSupported = false;
 
-	const int nRetVal1 = system_info_get_platform_bool(
-					"http://tizen.org/feature/vision.barcode_detection",
-					&isBarcodeDetectionSupported);
+	const int nRetVal1 = system_info_get_platform_bool("http://tizen.org/feature/vision.barcode_detection",
+													   &isBarcodeDetectionSupported);
 
 	if (nRetVal1 != SYSTEM_INFO_ERROR_NONE) {
 		LOGE("SYSTEM_INFO_ERROR: vision.barcode_detection");
 		return false;
 	}
 
-	const int nRetVal2 = system_info_get_platform_bool(
-					"http://tizen.org/feature/vision.barcode_generation",
-					&isBarcodeGenerationSupported);
+	const int nRetVal2 = system_info_get_platform_bool("http://tizen.org/feature/vision.barcode_generation",
+													   &isBarcodeGenerationSupported);
 
 	if (nRetVal2 != SYSTEM_INFO_ERROR_NONE) {
 		LOGE("SYSTEM_INFO_ERROR: vision.barcode_generation");
 		return false;
 	}
 
-	const int nRetVal3 = system_info_get_platform_bool(
-					"http://tizen.org/feature/vision.face_recognition",
-					&isFaceRecognitionSupported);
+	const int nRetVal3 = system_info_get_platform_bool("http://tizen.org/feature/vision.face_recognition",
+													   &isFaceRecognitionSupported);
 
 	if (nRetVal3 != SYSTEM_INFO_ERROR_NONE) {
 		LOGE("SYSTEM_INFO_ERROR: vision.face_recognition");
 		return false;
 	}
 
-	const int nRetVal4 = system_info_get_platform_bool(
-					"http://tizen.org/feature/vision.image_recognition",
-					&isImageRecognitionSupported);
+	const int nRetVal4 = system_info_get_platform_bool("http://tizen.org/feature/vision.image_recognition",
+													   &isImageRecognitionSupported);
 
 	if (nRetVal4 != SYSTEM_INFO_ERROR_NONE) {
 		LOGE("SYSTEM_INFO_ERROR: vision.image_recognition");
 		return false;
 	}
-	const int nRetVal5 = system_info_get_platform_bool(
-					"http://tizen.org/feature/vision.inference.image",
-					&isInferenceImageSupported);
+	const int nRetVal5 = system_info_get_platform_bool("http://tizen.org/feature/vision.inference.image",
+													   &isInferenceImageSupported);
 
 	if (nRetVal5 != SYSTEM_INFO_ERROR_NONE) {
 		LOGE("SYSTEM_INFO_ERROR: vision.inference.image");
 		return false;
 	}
 
-	const int nRetVal6 = system_info_get_platform_bool(
-					"http://tizen.org/feature/vision.inference.face",
-					&isInferenceFaceSupported);
+	const int nRetVal6 =
+			system_info_get_platform_bool("http://tizen.org/feature/vision.inference.face", &isInferenceFaceSupported);
 
 	if (nRetVal6 != SYSTEM_INFO_ERROR_NONE) {
 		LOGE("SYSTEM_INFO_ERROR: vision.inference.face");
 		return false;
 	}
-	(isBarcodeDetectionSupported || isBarcodeGenerationSupported ||
-		isFaceRecognitionSupported  || isImageRecognitionSupported ||
-		isInferenceImageSupported || isInferenceFaceSupported) ?
+	(isBarcodeDetectionSupported || isBarcodeGenerationSupported || isFaceRecognitionSupported ||
+	 isImageRecognitionSupported || isInferenceImageSupported || isInferenceFaceSupported) ?
 			LOGI("system_info_get_platform_bool returned "
-					"Supported one feature among barcode detection, "
-					"barcode generation, face recognition, "
-					"image recognition, and inference capability\n") :
+				 "Supported one feature among barcode detection, "
+				 "barcode generation, face recognition, "
+				 "image recognition, and inference capability\n") :
 			LOGE("system_info_get_platform_bool returned "
-					"Unsupported all features of barcode detection, "
-					"barcode generation, face recognition, "
-					"image recognition, inference capability\n") ;
+				 "Unsupported all features of barcode detection, "
+				 "barcode generation, face recognition, "
+				 "image recognition, inference capability\n");
 
-	return (isBarcodeDetectionSupported || isBarcodeGenerationSupported ||
-			isFaceRecognitionSupported  || isImageRecognitionSupported ||
-			isInferenceImageSupported   || isInferenceFaceSupported);
+	return (isBarcodeDetectionSupported || isBarcodeGenerationSupported || isFaceRecognitionSupported ||
+			isImageRecognitionSupported || isInferenceImageSupported || isInferenceFaceSupported);
 }
 
 bool _mv_barcode_detect_check_system_info_feature_supported(void)
 {
 	bool isBarcodeDetectionSupported = false;
 
-	const int nRetVal = system_info_get_platform_bool(
-					"http://tizen.org/feature/vision.barcode_detection",
-					&isBarcodeDetectionSupported);
+	const int nRetVal = system_info_get_platform_bool("http://tizen.org/feature/vision.barcode_detection",
+													  &isBarcodeDetectionSupported);
 
 	if (nRetVal != SYSTEM_INFO_ERROR_NONE) {
 		LOGE("SYSTEM_INFO_ERROR: vision.barcode_detection");
 		return false;
 	}
 
-	isBarcodeDetectionSupported ?
-			LOGI("system_info_get_platform_bool returned "
-					"Supported barcode detection feature capability\n") :
-			LOGE("system_info_get_platform_bool returned "
-					"Unsupported barcode detection feature capability\n");
+	isBarcodeDetectionSupported ? LOGI("system_info_get_platform_bool returned "
+									   "Supported barcode detection feature capability\n") :
+								  LOGE("system_info_get_platform_bool returned "
+									   "Unsupported barcode detection feature capability\n");
 
 	return isBarcodeDetectionSupported;
 }
@@ -135,20 +125,18 @@ bool _mv_barcode_generate_check_system_info_feature_supported(void)
 {
 	bool isBarcodeGenerationSupported = false;
 
-	const int nRetVal = system_info_get_platform_bool(
-					"http://tizen.org/feature/vision.barcode_generation",
-					&isBarcodeGenerationSupported);
+	const int nRetVal = system_info_get_platform_bool("http://tizen.org/feature/vision.barcode_generation",
+													  &isBarcodeGenerationSupported);
 
 	if (nRetVal != SYSTEM_INFO_ERROR_NONE) {
 		LOGE("SYSTEM_INFO_ERROR: vision.barcode_generation");
 		return false;
 	}
 
-	isBarcodeGenerationSupported ?
-			LOGI("system_info_get_platform_bool returned "
-					"Supported barcode generation feature capability\n") :
-			LOGE("system_info_get_platform_bool returned "
-					"Unsupported barcode generation feature capability\n");
+	isBarcodeGenerationSupported ? LOGI("system_info_get_platform_bool returned "
+										"Supported barcode generation feature capability\n") :
+								   LOGE("system_info_get_platform_bool returned "
+										"Unsupported barcode generation feature capability\n");
 
 	return isBarcodeGenerationSupported;
 }
@@ -157,20 +145,18 @@ bool _mv_face_check_system_info_feature_supported(void)
 {
 	bool isFaceRecognitionSupported = false;
 
-	const int nRetVal = system_info_get_platform_bool(
-					"http://tizen.org/feature/vision.face_recognition",
-					&isFaceRecognitionSupported);
+	const int nRetVal = system_info_get_platform_bool("http://tizen.org/feature/vision.face_recognition",
+													  &isFaceRecognitionSupported);
 
 	if (nRetVal != SYSTEM_INFO_ERROR_NONE) {
 		LOGE("SYSTEM_INFO_ERROR: vision.face_recognition");
 		return false;
 	}
 
-	isFaceRecognitionSupported ?
-			LOGI("system_info_get_platform_bool returned "
-					"Supported face recognition feature capability\n") :
-			LOGE("system_info_get_platform_bool returned "
-					"Unsupported face recognition feature capability\n");
+	isFaceRecognitionSupported ? LOGI("system_info_get_platform_bool returned "
+									  "Supported face recognition feature capability\n") :
+								 LOGE("system_info_get_platform_bool returned "
+									  "Unsupported face recognition feature capability\n");
 
 	return isFaceRecognitionSupported;
 }
@@ -179,20 +165,18 @@ bool _mv_image_check_system_info_feature_supported(void)
 {
 	bool isImageRecognitionSupported = false;
 
-	const int nRetVal = system_info_get_platform_bool(
-					"http://tizen.org/feature/vision.image_recognition",
-					&isImageRecognitionSupported);
+	const int nRetVal = system_info_get_platform_bool("http://tizen.org/feature/vision.image_recognition",
+													  &isImageRecognitionSupported);
 
 	if (nRetVal != SYSTEM_INFO_ERROR_NONE) {
 		LOGE("SYSTEM_INFO_ERROR: vision.image_recognition");
 		return false;
 	}
 
-	isImageRecognitionSupported ?
-			LOGI("system_info_get_platform_bool returned "
-					"Supported image recognition feature capability\n") :
-			LOGE("system_info_get_platform_bool returned "
-					"Unsupported image recognition feature capability\n");
+	isImageRecognitionSupported ? LOGI("system_info_get_platform_bool returned "
+									   "Supported image recognition feature capability\n") :
+								  LOGE("system_info_get_platform_bool returned "
+									   "Unsupported image recognition feature capability\n");
 
 	return isImageRecognitionSupported;
 }
@@ -202,29 +186,26 @@ bool _mv_inference_check_system_info_feature_supported(void)
 	bool isInferenceImageSupported = false;
 	bool isInferenceFaceSupported = false;
 
-	const int nRetVal1 = system_info_get_platform_bool(
-					"http://tizen.org/feature/vision.inference.image",
-					&isInferenceImageSupported);
+	const int nRetVal1 = system_info_get_platform_bool("http://tizen.org/feature/vision.inference.image",
+													   &isInferenceImageSupported);
 
 	if (nRetVal1 != SYSTEM_INFO_ERROR_NONE) {
 		LOGE("SYSTEM_INFO_ERROR: vision.inference.image");
 		return false;
 	}
 
-	const int nRetVal2 = system_info_get_platform_bool(
-					"http://tizen.org/feature/vision.inference.face",
-					&isInferenceFaceSupported);
+	const int nRetVal2 =
+			system_info_get_platform_bool("http://tizen.org/feature/vision.inference.face", &isInferenceFaceSupported);
 
 	if (nRetVal2 != SYSTEM_INFO_ERROR_NONE) {
 		LOGE("SYSTEM_INFO_ERROR: vision.inference.face");
 		return false;
 	}
 
-	(isInferenceImageSupported || isInferenceFaceSupported) ?
-			LOGI("system_info_get_platform_bool returned "
-					"Supported inference feature capability\n") :
-			LOGE("system_info_get_platform_bool returned "
-					"Unsupported inference feature capability\n");
+	(isInferenceImageSupported || isInferenceFaceSupported) ? LOGI("system_info_get_platform_bool returned "
+																   "Supported inference feature capability\n") :
+															  LOGE("system_info_get_platform_bool returned "
+																   "Unsupported inference feature capability\n");
 
 	return (isInferenceImageSupported || isInferenceFaceSupported);
 }
@@ -233,20 +214,18 @@ bool _mv_inference_image_check_system_info_feature_supported(void)
 {
 	bool isInferenceImageSupported = false;
 
-	const int nRetVal = system_info_get_platform_bool(
-					"http://tizen.org/feature/vision.inference.image",
-					&isInferenceImageSupported);
+	const int nRetVal = system_info_get_platform_bool("http://tizen.org/feature/vision.inference.image",
+													  &isInferenceImageSupported);
 
 	if (nRetVal != SYSTEM_INFO_ERROR_NONE) {
 		LOGE("SYSTEM_INFO_ERROR: vision.inference.image");
 		return false;
 	}
 
-	isInferenceImageSupported ?
-			LOGI("system_info_get_platform_bool returned "
-					"Supported inference image feature capability\n") :
-			LOGE("system_info_get_platform_bool returned "
-					"Unsupported inference image feature capability\n");
+	isInferenceImageSupported ? LOGI("system_info_get_platform_bool returned "
+									 "Supported inference image feature capability\n") :
+								LOGE("system_info_get_platform_bool returned "
+									 "Unsupported inference image feature capability\n");
 
 	return isInferenceImageSupported;
 }
@@ -255,20 +234,18 @@ bool _mv_inference_face_check_system_info_feature_supported(void)
 {
 	bool isInferenceFaceSupported = false;
 
-	const int nRetVal = system_info_get_platform_bool(
-					"http://tizen.org/feature/vision.inference.face",
-					&isInferenceFaceSupported);
+	const int nRetVal =
+			system_info_get_platform_bool("http://tizen.org/feature/vision.inference.face", &isInferenceFaceSupported);
 
 	if (nRetVal != SYSTEM_INFO_ERROR_NONE) {
 		LOGE("SYSTEM_INFO_ERROR: vision.inference.face");
 		return false;
 	}
 
-	isInferenceFaceSupported ?
-			LOGI("system_info_get_platform_bool returned "
-					"Supported inference face feature capability\n") :
-			LOGE("system_info_get_platform_bool returned "
-					"Unsupported inference face feature capability\n");
+	isInferenceFaceSupported ? LOGI("system_info_get_platform_bool returned "
+									"Supported inference face feature capability\n") :
+							   LOGE("system_info_get_platform_bool returned "
+									"Unsupported inference face feature capability\n");
 
 	return isInferenceFaceSupported;
 }
@@ -276,7 +253,7 @@ bool _mv_inference_face_check_system_info_feature_supported(void)
 bool _mv_roi_tracking_check_system_info_feature_supported(void)
 {
 	static GOnce once = G_ONCE_INIT;
-	bool supported = (bool)g_once(&once, __get_system_info_feature_once, VISION_FEATURE_ROI_TRACKING);
+	bool supported = (bool) g_once(&once, __get_system_info_feature_once, VISION_FEATURE_ROI_TRACKING);
 
 	LOGI("Feature[%s] : %d", VISION_FEATURE_ROI_TRACKING, supported);
 
diff --git a/mv_face/face/include/FaceDetector.h b/mv_face/face/include/FaceDetector.h
index 55c0132..19176a6 100644
--- a/mv_face/face/include/FaceDetector.h
+++ b/mv_face/face/include/FaceDetector.h
@@ -27,8 +27,10 @@
  *        detection functionality.
  */
 
-namespace MediaVision {
-namespace Face {
+namespace MediaVision
+{
+namespace Face
+{
 /**
  * @class   FaceDetector
  * @brief   The Face Detector container.
@@ -36,7 +38,8 @@ namespace Face {
  *
  * @since_tizen 3.0
  */
-class FaceDetector {
+class FaceDetector
+{
 public:
 	/**
 	 * @brief   Creates a FaceDetector.
@@ -68,11 +71,8 @@ public:
 	 *
 	 * @see setHaarcascadeFilepath()
 	 */
-	bool detectFaces(
-			const cv::Mat& image,
-			const cv::Rect& roi,
-			const cv::Size& minSize,
-			std::vector<cv::Rect>& faceLocations);
+	bool detectFaces(const cv::Mat &image, const cv::Rect &roi, const cv::Size &minSize,
+					 std::vector<cv::Rect> &faceLocations);
 
 	/**
 	 * @brief Loads haar cascade classifier for detection process.
@@ -85,13 +85,13 @@ public:
 	 * @return true if cascade is loaded from file and ready for detecting
 	 *         process. Otherwise is false.
 	 */
-	bool loadHaarcascade(const std::string& haarcascadeFilepath);
+	bool loadHaarcascade(const std::string &haarcascadeFilepath);
 
 private:
 	cv::CascadeClassifier m_faceCascade; /**< Cascade classifier of the face
 												detecting process. */
 
-	std::string m_haarcascadeFilepath;   /**< Path to the file, which contains
+	std::string m_haarcascadeFilepath; /**< Path to the file, which contains
 												cascade classifier information. */
 
 	bool m_faceCascadeIsLoaded; /**< Flag to determine the state of the
diff --git a/mv_face/face/include/FaceExpressionRecognizer.h b/mv_face/face/include/FaceExpressionRecognizer.h
index 496e407..8efbf7c 100644
--- a/mv_face/face/include/FaceExpressionRecognizer.h
+++ b/mv_face/face/include/FaceExpressionRecognizer.h
@@ -29,14 +29,17 @@
  *        the facial expressions recognition functionality.
  */
 
-namespace MediaVision {
-namespace Face {
+namespace MediaVision
+{
+namespace Face
+{
 /**
  * @brief Face expression recognition configuration.
  *
  * @since_tizen 3.0
  */
-struct FaceRecognizerConfig {
+struct FaceRecognizerConfig
+{
 	FaceRecognizerConfig();
 	std::string mHaarcascadeFilepath;
 };
@@ -48,7 +51,8 @@ struct FaceRecognizerConfig {
  *
  * @since_tizen 3.0
  */
-class FaceExpressionRecognizer {
+class FaceExpressionRecognizer
+{
 public:
 	/**
 	 * @brief Recognizes facial expression on the image with known face location.
@@ -63,11 +67,9 @@ public:
 	 *
 	 * @see MediaVision::Face::FaceRecognizerConfig
 	 */
-	static int recognizeFaceExpression(
-					const cv::Mat& grayImage,
-					const mv_rectangle_s& faceLocation,
-					mv_face_facial_expression_e *faceExpression,
-					const FaceRecognizerConfig& config = FaceRecognizerConfig());
+	static int recognizeFaceExpression(const cv::Mat &grayImage, const mv_rectangle_s &faceLocation,
+									   mv_face_facial_expression_e *faceExpression,
+									   const FaceRecognizerConfig &config = FaceRecognizerConfig());
 };
 
 } /* Face */
diff --git a/mv_face/face/include/FaceEyeCondition.h b/mv_face/face/include/FaceEyeCondition.h
index cc7a9bc..c301f47 100644
--- a/mv_face/face/include/FaceEyeCondition.h
+++ b/mv_face/face/include/FaceEyeCondition.h
@@ -28,8 +28,10 @@
  *        eye condition recognition functionality.
  */
 
-namespace MediaVision {
-namespace Face {
+namespace MediaVision
+{
+namespace Face
+{
 /**
  * @class FaceEyeCondition
  * @brief The FaceEyeCondition implements the face
@@ -37,7 +39,8 @@ namespace Face {
  *
  * @since_tizen 3.0
  */
-class FaceEyeCondition {
+class FaceEyeCondition
+{
 public:
 	/**
 	 * @brief Recognizes eye condition on the image with face location.
@@ -49,19 +52,17 @@ public:
 	 * @param [out] eyeCondition    The eye condition which was recognized
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	static int recognizeEyeCondition(
-					const cv::Mat& grayImage,
-					mv_rectangle_s faceLocation,
-					mv_face_eye_condition_e *eyeCondition);
+	static int recognizeEyeCondition(const cv::Mat &grayImage, mv_rectangle_s faceLocation,
+									 mv_face_eye_condition_e *eyeCondition);
 
 private:
 	static void splitEyes(
-					/*[in]*/ const cv::Mat& grayImage,
-					/*[in]*/ mv_rectangle_s faceLocation,
-					/*[out]*/ cv::Mat& leftEye,
-					/*[out]*/ cv::Mat& rightEye);
+			/*[in]*/ const cv::Mat &grayImage,
+			/*[in]*/ mv_rectangle_s faceLocation,
+			/*[out]*/ cv::Mat &leftEye,
+			/*[out]*/ cv::Mat &rightEye);
 
-	static int isEyeOpen(/*[in]*/const cv::Mat& eye);
+	static int isEyeOpen(/*[in]*/ const cv::Mat &eye);
 };
 
 } /* Face */
diff --git a/mv_face/face/include/FaceRecognitionModel.h b/mv_face/face/include/FaceRecognitionModel.h
index 8a8f3ae..8a7118c 100644
--- a/mv_face/face/include/FaceRecognitionModel.h
+++ b/mv_face/face/include/FaceRecognitionModel.h
@@ -33,14 +33,17 @@
  *        provides face recognition model interface.
  */
 
-namespace MediaVision {
-namespace Face {
+namespace MediaVision
+{
+namespace Face
+{
 /**
  * @brief Structure containing supported recognition algorithms settings.
  *
  * @since_tizen 3.0
  */
-struct FaceRecognitionModelConfig {
+struct FaceRecognitionModelConfig
+{
 	/**
 	 * @brief Default constructor for the @ref FaceRecognitionModelConfig
 	 *
@@ -48,33 +51,32 @@ struct FaceRecognitionModelConfig {
 	 */
 	FaceRecognitionModelConfig();
 
-	bool operator!=(
-			const FaceRecognitionModelConfig& other) const;
+	bool operator!=(const FaceRecognitionModelConfig &other) const;
 
 	FaceRecognitionModelType mModelType; /**<
 								Type of the recognition algorithm */
 
-	int mNumComponents;    /**< How many principal components will be included
+	int mNumComponents; /**< How many principal components will be included
 								to the Eigenvectors */
 
-	double mThreshold;     /**< Minimal distance between principal components of
+	double mThreshold; /**< Minimal distance between principal components of
 								the model allowed */
 
-	int mRadius;           /**< Radius of the local features for LBHP algorithm */
+	int mRadius; /**< Radius of the local features for LBHP algorithm */
 
-	int mNeighbors;        /**< How many neighboring pixels has to be analyzed
+	int mNeighbors; /**< How many neighboring pixels has to be analyzed
 								when LBHP learning applied. Usually set as
 								8*radius */
 
-	int mGridX;            /**< X size of the spatial histogram (LBPH) */
+	int mGridX; /**< X size of the spatial histogram (LBPH) */
 
-	int mGridY;            /**< Y size of the spatial histogram (LBPH) */
+	int mGridY; /**< Y size of the spatial histogram (LBPH) */
 
-	int mImgWidth;         /**< Width of the image to resize the samples for
+	int mImgWidth; /**< Width of the image to resize the samples for
 								Eigenfaces and Fisherfaces algorithms working
 								on the samples of the same size */
 
-	int mImgHeight;        /**< Height of the image to resize the samples for
+	int mImgHeight; /**< Height of the image to resize the samples for
 								Eigenfaces and Fisherfaces algorithms working
 								on the samples of the same size */
 };
@@ -86,7 +88,8 @@ struct FaceRecognitionModelConfig {
  *
  * @since_tizen 3.0
  */
-struct FaceRecognitionResults {
+struct FaceRecognitionResults
+{
 	/**
 	 * @brief Default constructor for the @ref FaceRecognitionResults
 	 *
@@ -94,12 +97,12 @@ struct FaceRecognitionResults {
 	 */
 	FaceRecognitionResults();
 
-	bool mIsRecognized;               /**< The flag indication success of the
+	bool mIsRecognized; /**< The flag indication success of the
 											recognition */
-	cv::Rect_<int> mFaceLocation;     /**< Location of the face where face has
+	cv::Rect_<int> mFaceLocation; /**< Location of the face where face has
 											been recognized */
-	int mFaceLabel;                   /**< Unique label of the face */
-	double mConfidence;               /**< Recognition confidence level */
+	int mFaceLabel; /**< Unique label of the face */
+	double mConfidence; /**< Recognition confidence level */
 };
 
 /**
@@ -108,7 +111,8 @@ struct FaceRecognitionResults {
  *
  * @since_tizen 3.0
  */
-class FaceRecognitionModel {
+class FaceRecognitionModel
+{
 public:
 	/**
 	 * @brief    Creates a FaceRecognitionModel class instance.
@@ -125,7 +129,7 @@ public:
 	 * @param [in] origin    The FaceRecognitionModel object that will be used
 	 *                       for creation of new one
 	 */
-	FaceRecognitionModel(const FaceRecognitionModel& origin);
+	FaceRecognitionModel(const FaceRecognitionModel &origin);
 
 	/**
 	 * @brief @ref FaceRecognitionModel copy assignment operator.
@@ -135,7 +139,7 @@ public:
 	 * @param [in] copy      @ref FaceRecognitionModel object which will be
 	 *                       copied
 	 */
-	FaceRecognitionModel& operator=(const FaceRecognitionModel& copy);
+	FaceRecognitionModel &operator=(const FaceRecognitionModel &copy);
 
 	/**
 	 * @brief    Destroys the FaceRecognitionModel class instance including all
@@ -155,7 +159,7 @@ public:
 	 *
 	 * @see FaceRecognitionModel::load()
 	 */
-	int save(const std::string& fileName);
+	int save(const std::string &fileName);
 
 	/**
 	 * @brief Deserializes FaceRecognitionModel object from the file.
@@ -167,7 +171,7 @@ public:
 	 *
 	 * @see FaceRecognitionModel::save()
 	 */
-	int load(const std::string& fileName);
+	int load(const std::string &fileName);
 
 	/**
 	 * @brief Adds face image example for face labeled by @a faceLabel
@@ -179,7 +183,7 @@ public:
 	 *
 	 * @see FaceRecognitionModel::resetFaceExamples()
 	 */
-	int addFaceExample(const cv::Mat& faceImage, int faceLabel);
+	int addFaceExample(const cv::Mat &faceImage, int faceLabel);
 
 	/**
 	 * @brief Clears the internal set of face image examples.
@@ -220,7 +224,7 @@ public:
 	 * @see FaceRecognitionModel::addFaceExample()
 	 * @see FaceRecognitionModel::learn()
 	 */
-	const std::set<int>& getFaceLabels(void) const;
+	const std::set<int> &getFaceLabels(void) const;
 
 	/**
 	 * @brief Learns recognition model based on the set of collected face image
@@ -233,7 +237,7 @@ public:
 	 *
 	 * @see FaceRecognitionModel::addFaceExample()
 	 */
-	int learn(const FaceRecognitionModelConfig& config = FaceRecognitionModelConfig());
+	int learn(const FaceRecognitionModelConfig &config = FaceRecognitionModelConfig());
 
 	/**
 	 * @brief Recognizes faces in the image and outputs recognition results to
@@ -247,16 +251,15 @@ public:
 	 *
 	 * @see FaceRecognitionModel::learn()
 	 */
-	int recognize(const cv::Mat& image, FaceRecognitionResults& results);
+	int recognize(const cv::Mat &image, FaceRecognitionResults &results);
 
 private:
 	/**
 	 * Factory method for creating of the recognition algorithm based on input
 	 * configuration:
 	 */
-	static cv::Ptr<cv::face::FaceRecognizer> CreateRecognitionAlgorithm(
-			const FaceRecognitionModelConfig& config =
-			FaceRecognitionModelConfig());
+	static cv::Ptr<cv::face::FaceRecognizer>
+	CreateRecognitionAlgorithm(const FaceRecognitionModelConfig &config = FaceRecognitionModelConfig());
 
 private:
 	bool m_canRecognize; /**< The flag showing possibility to recognize with
diff --git a/mv_face/face/include/FaceTracker.h b/mv_face/face/include/FaceTracker.h
index fc484c9..fe21752 100644
--- a/mv_face/face/include/FaceTracker.h
+++ b/mv_face/face/include/FaceTracker.h
@@ -46,8 +46,8 @@
 #include <opencv2/tracking.hpp>
 #include <opencv2/tracking/tracking_legacy.hpp>
 
-namespace cv {
-
+namespace cv
+{
 //class TrackerMedianFlowModel;
 
 /** @brief Median Flow tracker implementation.
@@ -60,90 +60,80 @@ by authors to outperform MIL). During the implementation period the code at
 <http://www.aonsquared.co.uk/node/5>, the courtesy of the author Arthur Amarra, was used for the
 reference purpose.
  */
-class FaceTracker : public legacy::TrackerMedianFlow {
+class FaceTracker : public legacy::TrackerMedianFlow
+{
 public:
-	struct Params {
+	struct Params
+	{
 		/**
 		 * @brief TrackerMedianFlow algorithm parameters constructor
 		 */
 		Params();
-		void read(const FileNode& fn);
-		void write(FileStorage& fs) const;
+		void read(const FileNode &fn);
+		void write(FileStorage &fs) const;
 
 		int mPointsInGrid; /**< Square root of number of keypoints used.
 								Increase it to trade accurateness for speed.
 								Default value is sensible and recommended */
 
-		Size mWindowSize;  /**< Size of the search window at each pyramid level
+		Size mWindowSize; /**< Size of the search window at each pyramid level
 								for Lucas-Kanade optical flow search used for
 								tracking */
 
-		int mPyrMaxLevel;  /**< Number of pyramid levels for Lucas-Kanade optical
+		int mPyrMaxLevel; /**< Number of pyramid levels for Lucas-Kanade optical
 								flow search used for tracking */
 	};
 
 	FaceTracker(Params paramsIn = Params());
 
-	bool copyTo(FaceTracker& copy) const;
+	bool copyTo(FaceTracker &copy) const;
 
-	bool initImpl(const Mat& image, const Rect2d& boundingBox);
-	bool updateImpl(const Mat& image, Rect2d& boundingBox);
+	bool initImpl(const Mat &image, const Rect2d &boundingBox);
+	bool updateImpl(const Mat &image, Rect2d &boundingBox);
 
 	bool isInited() const;
 
 	float getLastConfidence() const;
 	Rect_<float> getLastBoundingBox() const;
 
-	void read(FileStorage& fn);
-	void write(FileStorage& fs) const;
-	void read( const FileNode& fn );
+	void read(FileStorage &fn);
+	void write(FileStorage &fs) const;
+	void read(const FileNode &fn);
 
 private:
 	bool m_isInit;
 
-	bool medianFlowImpl(Mat oldImage, Mat newImage, Rect2f& oldBox);
+	bool medianFlowImpl(Mat oldImage, Mat newImage, Rect2f &oldBox);
 
-	Rect_<float> vote(
-			const std::vector<Point2f>& oldPoints,
-			const std::vector<Point2f>& newPoints,
-			const Rect_<float>& oldRect,
-			Point2f& mD);
+	Rect_<float> vote(const std::vector<Point2f> &oldPoints, const std::vector<Point2f> &newPoints,
+					  const Rect_<float> &oldRect, Point2f &mD);
 
-	template<typename T>
-	T getMedian(
-			std::vector<T>& values, int size = -1);
+	template<typename T> T getMedian(std::vector<T> &values, int size = -1);
 
-	void check_FB(
-			std::vector<Mat> newPyramid,
-			const std::vector<Point2f>& oldPoints,
-			const std::vector<Point2f>& newPoints,
-			std::vector<bool>& status);
+	void check_FB(std::vector<Mat> newPyramid, const std::vector<Point2f> &oldPoints,
+				  const std::vector<Point2f> &newPoints, std::vector<bool> &status);
 
-	void check_NCC(
-			const Mat& oldImage,
-			const Mat& newImage,
-			const std::vector<Point2f>& oldPoints,
-			const std::vector<Point2f>& newPoints,
-			std::vector<bool>& status);
+	void check_NCC(const Mat &oldImage, const Mat &newImage, const std::vector<Point2f> &oldPoints,
+				   const std::vector<Point2f> &newPoints, std::vector<bool> &status);
 
 	inline float l2distance(Point2f p1, Point2f p2);
 
-	Params m_params;               /**< Parameters used during tracking, see
+	Params m_params; /**< Parameters used during tracking, see
 										@ref TrackerMedianFlow::Params */
 
-	TermCriteria m_termcrit;       /**< Terminating criteria for OpenCV
+	TermCriteria m_termcrit; /**< Terminating criteria for OpenCV
 										Lucas–Kanade optical flow algorithm used
 										during tracking */
 
-	Rect2d m_boundingBox;  /**< Tracking object bounding box */
+	Rect2d m_boundingBox; /**< Tracking object bounding box */
 
-	float m_confidence;          /**< Confidence that face was tracked correctly
+	float m_confidence; /**< Confidence that face was tracked correctly
 										at the last tracking iteration */
 
-	Mat m_image;                 /**< Last image for which tracking was
+	Mat m_image; /**< Last image for which tracking was
 										performed */
 
-	std::vector<Mat> m_pyramid;  /**< The pyramid had been calculated for
+	std::vector<Mat> m_pyramid; /**< The pyramid had been calculated for
 										the previous frame or when
 										initialize the model */
 };
diff --git a/mv_face/face/include/FaceTrackingModel.h b/mv_face/face/include/FaceTrackingModel.h
index 95f8d6e..3361133 100644
--- a/mv_face/face/include/FaceTrackingModel.h
+++ b/mv_face/face/include/FaceTrackingModel.h
@@ -20,22 +20,24 @@
 #include <opencv2/core.hpp>
 #include "FaceTracker.h"
 
-
 /**
  * @file FaceTrackingModel.h
  * @brief This file contains the FaceTrackingModel class definition which
  *        provides face tracking model interface.
  */
 
-namespace MediaVision {
-namespace Face {
+namespace MediaVision
+{
+namespace Face
+{
 /**
  * @brief Structure where results of
  *        @ref MediaVision::Face::FaceTrackingModel::track() call are stored.
  *
  * @since_tizen 3.0
  */
-struct FaceTrackingResults {
+struct FaceTrackingResults
+{
 	/**
 	 * @brief Default constructor for the @ref FaceTrackingResults
 	 *
@@ -43,12 +45,12 @@ struct FaceTrackingResults {
 	 */
 	FaceTrackingResults();
 
-	bool mIsTracked;                  /**< The flag indication success of the
+	bool mIsTracked; /**< The flag indication success of the
 											tracking */
-	cv::Rect_<float> mFaceLocation;   /**< Location of the face at the current
+	cv::Rect_<float> mFaceLocation; /**< Location of the face at the current
 											track iteration where face position
 											is predicted */
-	float mConfidence;                /**< Tracking confidence level
+	float mConfidence; /**< Tracking confidence level
 											(0.0 .. 1.0) */
 };
 
@@ -58,7 +60,8 @@ struct FaceTrackingResults {
  *
  * @since_tizen 3.0
  */
-class FaceTrackingModel {
+class FaceTrackingModel
+{
 public:
 	/**
 	 * @brief    Creates a FaceTrackingModel class instance.
@@ -75,7 +78,7 @@ public:
 	 * @param [in] origin    The FaceTrackingModel object that will be used
 	 *                       for creation of new one
 	 */
-	FaceTrackingModel(const FaceTrackingModel& origin);
+	FaceTrackingModel(const FaceTrackingModel &origin);
 
 	/**
 	 * @brief @ref FaceTrackingModel copy assignment operator.
@@ -85,7 +88,7 @@ public:
 	 * @param [in] copy      @ref FaceTrackingModel object which will be
 	 *                       copied
 	 */
-	FaceTrackingModel& operator=(const FaceTrackingModel& copy);
+	FaceTrackingModel &operator=(const FaceTrackingModel &copy);
 
 	/**
 	 * @brief    Destroys the FaceTrackingModel class instance including all
@@ -105,7 +108,7 @@ public:
 	 *
 	 * @see FaceTrackingModel::load()
 	 */
-	int save(const std::string& fileName);
+	int save(const std::string &fileName);
 
 	/**
 	 * @brief Deserializes FaceTrackingModel object from the file.
@@ -117,7 +120,7 @@ public:
 	 *
 	 * @see FaceTrackingModel::save()
 	 */
-	int load(const std::string& fileName);
+	int load(const std::string &fileName);
 
 	/**
 	 * @brief Prepares FaceTrackingModel object to the next tracking session.
@@ -129,7 +132,7 @@ public:
 	 *
 	 * @see FaceTrackingModel::save()
 	 */
-	int prepare(const cv::Mat& image);
+	int prepare(const cv::Mat &image);
 
 	/**
 	 * @brief Prepares FaceTrackingModel object to the next tracking session.
@@ -143,7 +146,7 @@ public:
 	 *
 	 * @see FaceTrackingModel::save()
 	 */
-	int prepare(const cv::Mat& image, const cv::Rect_<float>& boundingBox);
+	int prepare(const cv::Mat &image, const cv::Rect_<float> &boundingBox);
 
 	/**
 	 * @brief Performs one tracking iteration for the video frame or image
@@ -153,10 +156,10 @@ public:
 	 * @param [in]  image
 	 * @param [out] boundingBox
 	 */
-	int track(const cv::Mat& image, FaceTrackingResults& results);
+	int track(const cv::Mat &image, FaceTrackingResults &results);
 
 private:
-	bool m_canTrack;                          /**< The flag showing possibility
+	bool m_canTrack; /**< The flag showing possibility
 													of the tracking model to
 													perform track */
 
diff --git a/mv_face/face/include/FaceUtil.h b/mv_face/face/include/FaceUtil.h
index 0bbe521..85734b3 100644
--- a/mv_face/face/include/FaceUtil.h
+++ b/mv_face/face/include/FaceUtil.h
@@ -25,18 +25,21 @@
  * @file FaceUtil.h
  * @brief This file contains the useful functionality for Face module.
  */
-namespace MediaVision {
-namespace Face {
+namespace MediaVision
+{
+namespace Face
+{
 /**
  * @brief Enumeration of supported learning algorithms.
  *
  * @since_tizen 3.0
  */
-enum FaceRecognitionModelType {
-	MEDIA_VISION_FACE_MODEL_TYPE_UNKNOWN = 0,     /**< Unknown algorithm type */
-	MEDIA_VISION_FACE_MODEL_TYPE_EIGENFACES = 1,  /**< Eigenfaces algorithm */
+enum FaceRecognitionModelType
+{
+	MEDIA_VISION_FACE_MODEL_TYPE_UNKNOWN = 0, /**< Unknown algorithm type */
+	MEDIA_VISION_FACE_MODEL_TYPE_EIGENFACES = 1, /**< Eigenfaces algorithm */
 	MEDIA_VISION_FACE_MODEL_TYPE_FISHERFACES = 2, /**< Fisherfaces algorithm */
-	MEDIA_VISION_FACE_MODEL_TYPE_LBPH = 3         /**< Local Binary Patterns
+	MEDIA_VISION_FACE_MODEL_TYPE_LBPH = 3 /**< Local Binary Patterns
 														Histograms algorithm */
 };
 
@@ -45,12 +48,13 @@ enum FaceRecognitionModelType {
  *
  * @since_tizen 3.0
  */
-struct RecognitionParams {
+struct RecognitionParams
+{
 	RecognitionParams(FaceRecognitionModelType algType);
 
 	RecognitionParams();
 
-	FaceRecognitionModelType mRecognitionAlgType;  /**< The type of
+	FaceRecognitionModelType mRecognitionAlgType; /**< The type of
 														the learning algorithm */
 };
 
diff --git a/mv_face/face/include/mv_face_open.h b/mv_face/face/include/mv_face_open.h
index bc8b054..e2d092a 100644
--- a/mv_face/face/include/mv_face_open.h
+++ b/mv_face/face/include/mv_face_open.h
@@ -64,12 +64,8 @@ extern "C" {
  *
  * @see mv_face_detected_cb
  */
-int mv_face_detect_open(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_face_detected_cb detected_cb,
-		void *user_data);
-
+int mv_face_detect_open(mv_source_h source, mv_engine_config_h engine_cfg, mv_face_detected_cb detected_cb,
+						void *user_data);
 
 /********************/
 /* Face recognition */
@@ -125,14 +121,9 @@ int mv_face_detect_open(
  *
  * @see mv_face_recognized_cb
  */
-int mv_face_recognize_open(
-		mv_source_h source,
-		mv_face_recognition_model_h recognition_model,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s *face_location,
-		mv_face_recognized_cb recognized_cb,
-		void *user_data);
-
+int mv_face_recognize_open(mv_source_h source, mv_face_recognition_model_h recognition_model,
+						   mv_engine_config_h engine_cfg, mv_rectangle_s *face_location,
+						   mv_face_recognized_cb recognized_cb, void *user_data);
 
 /*****************/
 /* Face tracking */
@@ -189,14 +180,8 @@ int mv_face_recognize_open(
  *
  * @see mv_face_tracked_cb
  */
-int mv_face_track_open(
-		mv_source_h source,
-		mv_face_tracking_model_h tracking_model,
-		mv_engine_config_h engine_cfg,
-		mv_face_tracked_cb tracked_cb,
-		bool do_learn,
-		void *user_data);
-
+int mv_face_track_open(mv_source_h source, mv_face_tracking_model_h tracking_model, mv_engine_config_h engine_cfg,
+					   mv_face_tracked_cb tracked_cb, bool do_learn, void *user_data);
 
 /********************************/
 /* Recognition of eye condition */
@@ -232,13 +217,10 @@ int mv_face_track_open(
  *
  * @see mv_face_eye_condition_recognized_cb
  */
-int mv_face_eye_condition_recognize_open(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s face_location,
-		mv_face_eye_condition_recognized_cb eye_condition_recognized_cb,
-		void *user_data);
-
+int mv_face_eye_condition_recognize_open(mv_source_h source, mv_engine_config_h engine_cfg,
+										 mv_rectangle_s face_location,
+										 mv_face_eye_condition_recognized_cb eye_condition_recognized_cb,
+										 void *user_data);
 
 /************************************/
 /* Recognition of facial expression */
@@ -273,12 +255,10 @@ int mv_face_eye_condition_recognize_open(
  *
  * @see mv_face_facial_expression_recognized_cb
  */
-int mv_face_facial_expression_recognize_open(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s face_location,
-		mv_face_facial_expression_recognized_cb expression_recognized_cb,
-		void *user_data);
+int mv_face_facial_expression_recognize_open(mv_source_h source, mv_engine_config_h engine_cfg,
+											 mv_rectangle_s face_location,
+											 mv_face_facial_expression_recognized_cb expression_recognized_cb,
+											 void *user_data);
 
 /*******************************/
 /* Recognition model behavior */
@@ -312,8 +292,7 @@ int mv_face_facial_expression_recognize_open(
  *
  * @see mv_face_recognition_model_destroy_open()
  */
-int mv_face_recognition_model_create_open(
-		mv_face_recognition_model_h *recognition_model);
+int mv_face_recognition_model_create_open(mv_face_recognition_model_h *recognition_model);
 
 /**
  * @brief Destroys the face recognition model handle and releases all its
@@ -328,8 +307,7 @@ int mv_face_recognition_model_create_open(
  *
  * @see mv_face_recognition_model_create_open()
  */
-int mv_face_recognition_model_destroy_open(
-		mv_face_recognition_model_h recognition_model);
+int mv_face_recognition_model_destroy_open(mv_face_recognition_model_h recognition_model);
 
 /**
  * @brief Creates a copy of existed recognition model handle and clones all its
@@ -352,9 +330,7 @@ int mv_face_recognition_model_destroy_open(
  *
  * @see mv_face_recognition_model_create_open()
  */
-int mv_face_recognition_model_clone_open(
-		mv_face_recognition_model_h src,
-		mv_face_recognition_model_h *dst);
+int mv_face_recognition_model_clone_open(mv_face_recognition_model_h src, mv_face_recognition_model_h *dst);
 
 /**
  * @brief Saves recognition model to the file.
@@ -386,9 +362,7 @@ int mv_face_recognition_model_clone_open(
  * @see mv_face_recognition_model_load_open()
  * @see mv_face_recognition_model_create_open()
  */
-int mv_face_recognition_model_save_open(
-		const char *file_name,
-		mv_face_recognition_model_h recognition_model);
+int mv_face_recognition_model_save_open(const char *file_name, mv_face_recognition_model_h recognition_model);
 
 /**
  * @brief Loads recognition model from file.
@@ -419,9 +393,7 @@ int mv_face_recognition_model_save_open(
  * @see mv_face_recognition_model_save_open()
  * @see mv_face_recognition_model_destroy_open()
  */
-int mv_face_recognition_model_load_open(
-		const char *file_name,
-		mv_face_recognition_model_h *recognition_model);
+int mv_face_recognition_model_load_open(const char *file_name, mv_face_recognition_model_h *recognition_model);
 
 /**
  * @brief Adds face image example to be used for face recognition model learning
@@ -459,11 +431,8 @@ int mv_face_recognition_model_load_open(
  * @see mv_face_recognition_model_reset_open()
  * @see mv_face_recognition_model_learn_open()
  */
-int mv_face_recognition_model_add_open(
-		const mv_source_h source,
-		mv_face_recognition_model_h recognition_model,
-		const mv_rectangle_s *example_location,
-		int face_label);
+int mv_face_recognition_model_add_open(const mv_source_h source, mv_face_recognition_model_h recognition_model,
+									   const mv_rectangle_s *example_location, int face_label);
 
 /**
  * @brief Remove from @a recognition_model all collected with
@@ -497,9 +466,7 @@ int mv_face_recognition_model_add_open(
  * @see mv_face_recognition_model_add_open()
  * @see mv_face_recognition_model_learn_open()
  */
-int mv_face_recognition_model_reset_open(
-		mv_face_recognition_model_h recognition_model,
-		const int *face_label);
+int mv_face_recognition_model_reset_open(mv_face_recognition_model_h recognition_model, const int *face_label);
 
 /**
  * @brief Learns face recognition model.
@@ -554,9 +521,7 @@ int mv_face_recognition_model_reset_open(
  * @see mv_face_recognition_model_reset_open()
  * @see mv_face_recognize_open()
  */
-int mv_face_recognition_model_learn_open(
-		mv_engine_config_h engine_cfg,
-		mv_face_recognition_model_h recognition_model);
+int mv_face_recognition_model_learn_open(mv_engine_config_h engine_cfg, mv_face_recognition_model_h recognition_model);
 
 /**
  * @brief Queries labels list and number of labels had been learned by the model.
@@ -584,10 +549,8 @@ int mv_face_recognition_model_learn_open(
  * @see mv_face_recognition_model_reset_open()
  * @see mv_face_recognition_model_learn_open()
  */
-int mv_face_recognition_model_query_labels_open(
-		mv_face_recognition_model_h recognition_model,
-		int **labels,
-		unsigned int *number_of_labels);
+int mv_face_recognition_model_query_labels_open(mv_face_recognition_model_h recognition_model, int **labels,
+												unsigned int *number_of_labels);
 
 /***************************/
 /* Tracking model behavior */
@@ -627,8 +590,7 @@ int mv_face_recognition_model_query_labels_open(
  * @see mv_face_tracking_model_prepare_open()
  * @see mv_face_tracking_model_load_open()
  */
-int mv_face_tracking_model_create_open(
-		mv_face_tracking_model_h *tracking_model);
+int mv_face_tracking_model_create_open(mv_face_tracking_model_h *tracking_model);
 
 /**
  * @brief Call this function to destroy the face tracking model handle and
@@ -644,8 +606,7 @@ int mv_face_tracking_model_create_open(
  *
  * @see mv_face_tracking_model_create_open()
  */
-int mv_face_tracking_model_destroy_open(
-		mv_face_tracking_model_h tracking_model);
+int mv_face_tracking_model_destroy_open(mv_face_tracking_model_h tracking_model);
 
 /**
  * @brief Call this function to initialize tracking model by the location of the
@@ -688,11 +649,8 @@ int mv_face_tracking_model_destroy_open(
  * @see mv_face_tracking_model_create_open()
  * @see mv_face_track_open()
  */
-int mv_face_tracking_model_prepare_open(
-		mv_face_tracking_model_h tracking_model,
-		mv_engine_config_h engine_cfg,
-		mv_source_h source,
-		mv_quadrangle_s */*location*/);
+int mv_face_tracking_model_prepare_open(mv_face_tracking_model_h tracking_model, mv_engine_config_h engine_cfg,
+										mv_source_h source, mv_quadrangle_s * /*location*/);
 
 /**
  * @brief Call this function to make a copy of existed tracking model handle and
@@ -716,9 +674,7 @@ int mv_face_tracking_model_prepare_open(
  *
  * @see mv_face_tracking_model_create_open()
  */
-int mv_face_tracking_model_clone_open(
-		mv_face_tracking_model_h src,
-		mv_face_tracking_model_h *dst);
+int mv_face_tracking_model_clone_open(mv_face_tracking_model_h src, mv_face_tracking_model_h *dst);
 
 /**
  * @brief Call this method to save tracking model to the file.
@@ -746,9 +702,7 @@ int mv_face_tracking_model_clone_open(
  * @see mv_face_tracking_model_load_open()
  * @see mv_face_tracking_model_create_open()
  */
-int mv_face_tracking_model_save_open(
-		const char *file_name,
-		mv_face_tracking_model_h tracking_model);
+int mv_face_tracking_model_save_open(const char *file_name, mv_face_tracking_model_h tracking_model);
 
 /**
  * @brief Call this method to load a tracking model from file.
@@ -780,9 +734,7 @@ int mv_face_tracking_model_save_open(
  * @see mv_face_tracking_model_save_open()
  * @see mv_face_tracking_model_destroy_open()
  */
-int mv_face_tracking_model_load_open(
-		const char *file_name,
-		mv_face_tracking_model_h *tracking_model);
+int mv_face_tracking_model_load_open(const char *file_name, mv_face_tracking_model_h *tracking_model);
 
 #ifdef __cplusplus
 }
diff --git a/mv_face/face/src/FaceDetector.cpp b/mv_face/face/src/FaceDetector.cpp
index 9b66368..756d536 100644
--- a/mv_face/face/src/FaceDetector.cpp
+++ b/mv_face/face/src/FaceDetector.cpp
@@ -16,13 +16,11 @@
 
 #include "FaceDetector.h"
 
-namespace MediaVision {
-namespace Face {
-
-FaceDetector::FaceDetector() :
-		m_faceCascade(),
-		m_haarcascadeFilepath(),
-		m_faceCascadeIsLoaded(false)
+namespace MediaVision
+{
+namespace Face
+{
+FaceDetector::FaceDetector() : m_faceCascade(), m_haarcascadeFilepath(), m_faceCascadeIsLoaded(false)
 {
 	; /* NULL */
 }
@@ -32,11 +30,8 @@ FaceDetector::~FaceDetector()
 	; /* NULL */
 }
 
-bool FaceDetector::detectFaces(
-		const cv::Mat& image,
-		const cv::Rect& roi,
-		const cv::Size& minSize,
-		std::vector<cv::Rect>& faceLocations)
+bool FaceDetector::detectFaces(const cv::Mat &image, const cv::Rect &roi, const cv::Size &minSize,
+							   std::vector<cv::Rect> &faceLocations)
 {
 	if (!m_faceCascadeIsLoaded)
 		return false;
@@ -46,21 +41,14 @@ bool FaceDetector::detectFaces(
 	cv::Mat intrestingRegion = image;
 
 	bool roiIsUsed = false;
-	if (roi.x >= 0 && roi.y >= 0 && roi.width > 0 && roi.height > 0 &&
-			(roi.x + roi.width) <= image.cols &&
-			(roi.y + roi.height) <= image.rows) {
+	if (roi.x >= 0 && roi.y >= 0 && roi.width > 0 && roi.height > 0 && (roi.x + roi.width) <= image.cols &&
+		(roi.y + roi.height) <= image.rows) {
 		intrestingRegion = intrestingRegion(roi);
 		roiIsUsed = true;
 	}
 
 	try {
-		m_faceCascade.detectMultiScale(
-				intrestingRegion,
-				faceLocations,
-				1.1,
-				3,
-				0,
-				minSize);
+		m_faceCascade.detectMultiScale(intrestingRegion, faceLocations, 1.1, 3, 0, minSize);
 	} catch (cv::Exception &e) {
 		return false;
 	}
@@ -76,10 +64,9 @@ bool FaceDetector::detectFaces(
 	return true;
 }
 
-bool FaceDetector::loadHaarcascade(const std::string& haarcascadeFilepath)
+bool FaceDetector::loadHaarcascade(const std::string &haarcascadeFilepath)
 {
-	if (!m_faceCascadeIsLoaded ||
-			m_haarcascadeFilepath != haarcascadeFilepath) {
+	if (!m_faceCascadeIsLoaded || m_haarcascadeFilepath != haarcascadeFilepath) {
 		if (!(m_faceCascadeIsLoaded = m_faceCascade.load(haarcascadeFilepath)))
 			return false;
 
diff --git a/mv_face/face/src/FaceExpressionRecognizer.cpp b/mv_face/face/src/FaceExpressionRecognizer.cpp
index 54f5309..fd345ae 100644
--- a/mv_face/face/src/FaceExpressionRecognizer.cpp
+++ b/mv_face/face/src/FaceExpressionRecognizer.cpp
@@ -20,46 +20,37 @@
 
 #include <vector>
 
-
-namespace MediaVision {
-namespace Face {
-
+namespace MediaVision
+{
+namespace Face
+{
 static const int MIN_DETECTION_WIDTH = 30;
 static const int MIN_DETECTION_HEIGHT = 30;
 
-FaceRecognizerConfig::FaceRecognizerConfig() :
-		mHaarcascadeFilepath(
-				"/usr/share/OpenCV/haarcascades/haarcascade_smile.xml")
+FaceRecognizerConfig::FaceRecognizerConfig()
+		: mHaarcascadeFilepath("/usr/share/OpenCV/haarcascades/haarcascade_smile.xml")
 {
 	; /* NULL */
 }
 
-int FaceExpressionRecognizer::recognizeFaceExpression(
-		const cv::Mat& grayImage,
-		const mv_rectangle_s& faceLocation,
-		mv_face_facial_expression_e *faceExpression,
-		const FaceRecognizerConfig& config)
+int FaceExpressionRecognizer::recognizeFaceExpression(const cv::Mat &grayImage, const mv_rectangle_s &faceLocation,
+													  mv_face_facial_expression_e *faceExpression,
+													  const FaceRecognizerConfig &config)
 {
 	if (NULL == faceExpression)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 
-	const int smileRectHeight = cvRound((float)faceLocation.height / 2);
+	const int smileRectHeight = cvRound((float) faceLocation.height / 2);
 
-	const cv::Rect roi(
-					faceLocation.point.x,
-					faceLocation.point.y + faceLocation.height - smileRectHeight,
-					faceLocation.width,
-					smileRectHeight);
+	const cv::Rect roi(faceLocation.point.x, faceLocation.point.y + faceLocation.height - smileRectHeight,
+					   faceLocation.width, smileRectHeight);
 
-	if (roi.width < MIN_DETECTION_WIDTH ||
-			roi.height < MIN_DETECTION_HEIGHT) {
+	if (roi.width < MIN_DETECTION_WIDTH || roi.height < MIN_DETECTION_HEIGHT) {
 		(*faceExpression) = MV_FACE_UNKNOWN;
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	if (0 > roi.x || 0 > roi.y ||
-			roi.x + roi.width > grayImage.cols ||
-			roi.y + roi.height > grayImage.rows)
+	if (0 > roi.x || 0 > roi.y || roi.x + roi.width > grayImage.cols || roi.y + roi.height > grayImage.rows)
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 
 	const cv::Mat mouthImg(grayImage, roi);
@@ -68,15 +59,10 @@ int FaceExpressionRecognizer::recognizeFaceExpression(
 
 	cv::CascadeClassifier smileClassifier;
 	smileClassifier.load(config.mHaarcascadeFilepath);
-	smileClassifier.detectMultiScale(
-			mouthImg,
-			areas,
-			1.1,
-			80,
-			cv::CASCADE_FIND_BIGGEST_OBJECT |
-			cv::CASCADE_DO_CANNY_PRUNING    |
-			cv::CASCADE_SCALE_IMAGE,
-			cv::Size(MIN_DETECTION_WIDTH, MIN_DETECTION_HEIGHT));
+	smileClassifier.detectMultiScale(mouthImg, areas, 1.1, 80,
+									 cv::CASCADE_FIND_BIGGEST_OBJECT | cv::CASCADE_DO_CANNY_PRUNING |
+											 cv::CASCADE_SCALE_IMAGE,
+									 cv::Size(MIN_DETECTION_WIDTH, MIN_DETECTION_HEIGHT));
 
 	(*faceExpression) = MV_FACE_UNKNOWN;
 	const size_t smilesFoundSize = areas.size();
diff --git a/mv_face/face/src/FaceEyeCondition.cpp b/mv_face/face/src/FaceEyeCondition.cpp
index 7e953c6..26276ce 100644
--- a/mv_face/face/src/FaceEyeCondition.cpp
+++ b/mv_face/face/src/FaceEyeCondition.cpp
@@ -21,43 +21,29 @@
 #include <vector>
 #include <opencv2/imgproc/imgproc_c.h>
 
-namespace MediaVision {
-namespace Face {
-void FaceEyeCondition::splitEyes(
-							const cv::Mat& grayImage,
-							mv_rectangle_s faceLocation,
-							cv::Mat& leftEye,
-							cv::Mat& rightEye)
+namespace MediaVision
+{
+namespace Face
+{
+void FaceEyeCondition::splitEyes(const cv::Mat &grayImage, mv_rectangle_s faceLocation, cv::Mat &leftEye,
+								 cv::Mat &rightEye)
 {
 	leftEye = grayImage.rowRange(0, grayImage.rows / 2 - grayImage.rows / 10)
-						.colRange(grayImage.cols / 2 + grayImage.cols / 10,
-								grayImage.cols)
-						.clone();
-
-	rightEye = grayImage.rowRange(grayImage.rows / 2 + grayImage.rows / 10,
-									grayImage.rows)
-						.colRange(grayImage.cols / 2 + grayImage.cols / 10,
-									grayImage.cols)
-						.clone();
-
-	const cv::Rect faceRect(
-						faceLocation.point.x,
-						faceLocation.point.y,
-						faceLocation.width,
-						faceLocation.height);
-
-	const cv::Rect eyeAreaRight(
-						faceRect.x + faceRect.width / 16,
-						(int) (faceRect.y + (faceRect.height / 4.5)),
-						(faceRect.width - 2 * faceRect.width / 16) / 2,
-						(int) (faceRect.height / 3.0));
-
-	const cv::Rect eyeAreaLeft(
-						faceRect.x + faceRect.width / 16
-						+ (faceRect.width - 2 * faceRect.width / 16) / 2,
-						(int) (faceRect.y + (faceRect.height / 4.5)),
-						(faceRect.width - 2 * faceRect.width / 16) / 2,
-						(int) (faceRect.height / 3.0));
+					  .colRange(grayImage.cols / 2 + grayImage.cols / 10, grayImage.cols)
+					  .clone();
+
+	rightEye = grayImage.rowRange(grayImage.rows / 2 + grayImage.rows / 10, grayImage.rows)
+					   .colRange(grayImage.cols / 2 + grayImage.cols / 10, grayImage.cols)
+					   .clone();
+
+	const cv::Rect faceRect(faceLocation.point.x, faceLocation.point.y, faceLocation.width, faceLocation.height);
+
+	const cv::Rect eyeAreaRight(faceRect.x + faceRect.width / 16, (int) (faceRect.y + (faceRect.height / 4.5)),
+								(faceRect.width - 2 * faceRect.width / 16) / 2, (int) (faceRect.height / 3.0));
+
+	const cv::Rect eyeAreaLeft(faceRect.x + faceRect.width / 16 + (faceRect.width - 2 * faceRect.width / 16) / 2,
+							   (int) (faceRect.y + (faceRect.height / 4.5)),
+							   (faceRect.width - 2 * faceRect.width / 16) / 2, (int) (faceRect.height / 3.0));
 
 	const double xLeftEyeCenter = (2 * eyeAreaLeft.x + eyeAreaLeft.width) / 2.;
 	const double yLeftEyeCenter = (2 * eyeAreaLeft.y + eyeAreaLeft.height) / 2.;
@@ -65,27 +51,19 @@ void FaceEyeCondition::splitEyes(
 	const double xRightEyeCenter = (2 * eyeAreaRight.x + eyeAreaRight.width) / 2.;
 	const double yRightEyeCenter = (2 * eyeAreaRight.y + eyeAreaRight.height) / 2.;
 
-	const cv::Rect leftEyeRect((int)(xLeftEyeCenter - (double)eyeAreaLeft.width / 4),
-								(int)(yLeftEyeCenter - (double)eyeAreaLeft.height / 4),
-								eyeAreaLeft.width / 2,
-								eyeAreaLeft.height / 2);
+	const cv::Rect leftEyeRect((int) (xLeftEyeCenter - (double) eyeAreaLeft.width / 4),
+							   (int) (yLeftEyeCenter - (double) eyeAreaLeft.height / 4), eyeAreaLeft.width / 2,
+							   eyeAreaLeft.height / 2);
 
-	const cv::Rect rightEyeRect((int)(xRightEyeCenter - (double)eyeAreaRight.width / 4),
-								(int)(yRightEyeCenter - (double)eyeAreaRight.height / 4),
-								eyeAreaRight.width / 2,
+	const cv::Rect rightEyeRect((int) (xRightEyeCenter - (double) eyeAreaRight.width / 4),
+								(int) (yRightEyeCenter - (double) eyeAreaRight.height / 4), eyeAreaRight.width / 2,
 								eyeAreaRight.height / 2);
 
-	cv::resize(
-			grayImage(leftEyeRect),
-			leftEye,
-			leftEye.size());
-	cv::resize(
-			grayImage(rightEyeRect),
-			rightEye,
-			rightEye.size());
+	cv::resize(grayImage(leftEyeRect), leftEye, leftEye.size());
+	cv::resize(grayImage(rightEyeRect), rightEye, rightEye.size());
 }
 
-int FaceEyeCondition::isEyeOpen(const cv::Mat& eye)
+int FaceEyeCondition::isEyeOpen(const cv::Mat &eye)
 {
 	int isOpen = MV_FACE_EYES_CLOSED;
 
@@ -98,12 +76,7 @@ int FaceEyeCondition::isEyeOpen(const cv::Mat& eye)
 	std::vector<std::vector<cv::Point> > contours;
 	std::vector<cv::Vec4i> hierarchy;
 
-	cv::findContours(
-			eyeEqualized,
-			contours,
-			hierarchy,
-			CV_RETR_CCOMP,
-			CV_CHAIN_APPROX_SIMPLE);
+	cv::findContours(eyeEqualized, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE);
 
 	const size_t contoursSize = contours.size();
 
@@ -126,14 +99,11 @@ int FaceEyeCondition::isEyeOpen(const cv::Mat& eye)
 		const cv::Rect currentRect = cv::boundingRect(contours[i]);
 		const double currentArea = cv::contourArea(contours[i]);
 
-		if (boundThresold.contains(currentRect.br()) &&
-				boundThresold.contains(currentRect.tl()) &&
-				currentArea > areaRatio * boundThresold.area() &&
-				currentRect.width < widthHeightRatio * currentRect.height)
+		if (boundThresold.contains(currentRect.br()) && boundThresold.contains(currentRect.tl()) &&
+			currentArea > areaRatio * boundThresold.area() && currentRect.width < widthHeightRatio * currentRect.height)
 			isOpen = MV_FACE_EYES_OPEN;
-		else if (boundThresold.contains(currentRect.br()) &&
-				boundThresold.contains(currentRect.tl()) &&
-				currentArea > areaSmallRatio * boundThresold.area())
+		else if (boundThresold.contains(currentRect.br()) && boundThresold.contains(currentRect.tl()) &&
+				 currentArea > areaSmallRatio * boundThresold.area())
 			++rectanglesInsideCount;
 	}
 
@@ -143,10 +113,8 @@ int FaceEyeCondition::isEyeOpen(const cv::Mat& eye)
 	return isOpen;
 }
 
-int FaceEyeCondition::recognizeEyeCondition(
-		const cv::Mat& grayImage,
-		mv_rectangle_s faceLocation,
-		mv_face_eye_condition_e *eyeCondition)
+int FaceEyeCondition::recognizeEyeCondition(const cv::Mat &grayImage, mv_rectangle_s faceLocation,
+											mv_face_eye_condition_e *eyeCondition)
 {
 	if (grayImage.empty()) {
 		*eyeCondition = MV_FACE_EYES_NOT_FOUND;
@@ -160,8 +128,7 @@ int FaceEyeCondition::recognizeEyeCondition(
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	if (faceLocation.height <= 0 || faceLocation.width <= 0 ||
-		faceLocation.point.x < 0 || faceLocation.point.y < 0 ||
+	if (faceLocation.height <= 0 || faceLocation.width <= 0 || faceLocation.point.x < 0 || faceLocation.point.y < 0 ||
 		(faceLocation.point.x + faceLocation.width) > grayImage.cols ||
 		(faceLocation.point.y + faceLocation.height) > grayImage.rows) {
 		*eyeCondition = MV_FACE_EYES_NOT_FOUND;
diff --git a/mv_face/face/src/FaceRecognitionModel.cpp b/mv_face/face/src/FaceRecognitionModel.cpp
index 1cc519f..e104147 100644
--- a/mv_face/face/src/FaceRecognitionModel.cpp
+++ b/mv_face/face/src/FaceRecognitionModel.cpp
@@ -25,14 +25,16 @@
 #include <unistd.h>
 #include <fstream>
 
-namespace MediaVision {
-namespace Face {
-namespace {
-
+namespace MediaVision
+{
+namespace Face
+{
+namespace
+{
 unsigned int DefaultUnisizeWidth = 200;
 unsigned int DefaultUnisizeHeight = 200;
 
-bool isEmptyAlgorithmParam(const std::string& path)
+bool isEmptyAlgorithmParam(const std::string &path)
 {
 	char valid[256] = "";
 	std::ifstream ifs;
@@ -56,8 +58,8 @@ bool isEmptyAlgorithmParam(const std::string& path)
 	return false;
 }
 
-int CopyOpenCVAlgorithmParameters(const cv::Ptr<cv::face::FaceRecognizer>& srcAlg,
-		cv::Ptr<cv::face::FaceRecognizer>& dstAlg)
+int CopyOpenCVAlgorithmParameters(const cv::Ptr<cv::face::FaceRecognizer> &srcAlg,
+								  cv::Ptr<cv::face::FaceRecognizer> &dstAlg)
 {
 	char tempPath[1024] = "";
 
@@ -122,9 +124,7 @@ int CopyOpenCVAlgorithmParameters(const cv::Ptr<cv::face::FaceRecognizer>& srcAl
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-void ParseOpenCVLabels(
-		const cv::Mat labels,
-		std::set<int>& outLabels)
+void ParseOpenCVLabels(const cv::Mat labels, std::set<int> &outLabels)
 {
 	if (!labels.empty()) {
 		for (int i = 0; i < labels.rows; ++i)
@@ -134,62 +134,50 @@ void ParseOpenCVLabels(
 
 } /* anonymous namespace */
 
-FaceRecognitionModelConfig::FaceRecognitionModelConfig() :
-		mModelType(MEDIA_VISION_FACE_MODEL_TYPE_UNKNOWN),
-		mNumComponents(0),
-		mThreshold(DBL_MAX),
-		mRadius(1),
-		mNeighbors(8),
-		mGridX(8),
-		mGridY(8),
-		mImgWidth(DefaultUnisizeWidth),
-		mImgHeight(DefaultUnisizeHeight)
+FaceRecognitionModelConfig::FaceRecognitionModelConfig()
+		: mModelType(MEDIA_VISION_FACE_MODEL_TYPE_UNKNOWN)
+		, mNumComponents(0)
+		, mThreshold(DBL_MAX)
+		, mRadius(1)
+		, mNeighbors(8)
+		, mGridX(8)
+		, mGridY(8)
+		, mImgWidth(DefaultUnisizeWidth)
+		, mImgHeight(DefaultUnisizeHeight)
 {
 	; /* NULL */
 }
 
-FaceRecognitionResults::FaceRecognitionResults() :
-		mIsRecognized(false),
-		mFaceLabel(-1),
-		mConfidence(0.0)
+FaceRecognitionResults::FaceRecognitionResults() : mIsRecognized(false), mFaceLabel(-1), mConfidence(0.0)
 {
 	; /* NULL */
 }
 
-bool FaceRecognitionModelConfig::operator!=(
-		const FaceRecognitionModelConfig& other) const
+bool FaceRecognitionModelConfig::operator!=(const FaceRecognitionModelConfig &other) const
 {
-	return mModelType      != other.mModelType     ||
-			mNumComponents != other.mNumComponents ||
-			mThreshold     != other.mThreshold     ||
-			mRadius        != other.mRadius        ||
-			mNeighbors     != other.mNeighbors     ||
-			mGridX         != other.mGridX         ||
-			mGridY         != other.mGridY         ||
-			mImgWidth      != other.mImgWidth      ||
-			mImgHeight     != other.mImgHeight;
+	return mModelType != other.mModelType || mNumComponents != other.mNumComponents || mThreshold != other.mThreshold ||
+		   mRadius != other.mRadius || mNeighbors != other.mNeighbors || mGridX != other.mGridX ||
+		   mGridY != other.mGridY || mImgWidth != other.mImgWidth || mImgHeight != other.mImgHeight;
 }
 
-FaceRecognitionModel::FaceRecognitionModel() :
-		m_canRecognize(false),
-		m_recognizer() // The default constructor creates a null Ptr
+FaceRecognitionModel::FaceRecognitionModel()
+		: m_canRecognize(false), m_recognizer() // The default constructor creates a null Ptr
 {
 	; /* NULL */
 }
 
-FaceRecognitionModel::FaceRecognitionModel(const FaceRecognitionModel& origin) :
-		m_canRecognize(origin.m_canRecognize),
-		m_faceSamples(origin.m_faceSamples),
-		m_learnAlgorithmConfig(origin.m_learnAlgorithmConfig),
-		m_recognizer(CreateRecognitionAlgorithm(origin.m_learnAlgorithmConfig)),
-		m_learnedLabels(origin.m_learnedLabels)
+FaceRecognitionModel::FaceRecognitionModel(const FaceRecognitionModel &origin)
+		: m_canRecognize(origin.m_canRecognize)
+		, m_faceSamples(origin.m_faceSamples)
+		, m_learnAlgorithmConfig(origin.m_learnAlgorithmConfig)
+		, m_recognizer(CreateRecognitionAlgorithm(origin.m_learnAlgorithmConfig))
+		, m_learnedLabels(origin.m_learnedLabels)
 {
 	if (!m_recognizer.empty())
 		CopyOpenCVAlgorithmParameters(origin.m_recognizer, m_recognizer);
 }
 
-FaceRecognitionModel& FaceRecognitionModel::operator=(
-		const FaceRecognitionModel& copy)
+FaceRecognitionModel &FaceRecognitionModel::operator=(const FaceRecognitionModel &copy)
 {
 	if (this != &copy) {
 		m_canRecognize = copy.m_canRecognize;
@@ -210,7 +198,7 @@ FaceRecognitionModel::~FaceRecognitionModel()
 	; /* NULL */
 }
 
-int FaceRecognitionModel::save(const std::string& fileName)
+int FaceRecognitionModel::save(const std::string &fileName)
 {
 	if (!m_recognizer.empty()) {
 		std::string filePath;
@@ -226,7 +214,7 @@ int FaceRecognitionModel::save(const std::string& fileName)
 
 				return MEDIA_VISION_ERROR_INVALID_PATH;
 			}
-		} catch (const std::out_of_range& e) {
+		} catch (const std::out_of_range &e) {
 			LOGE("Can't save recognition model. Path[%s] doesn't exist.", filePath.c_str());
 			return MEDIA_VISION_ERROR_INVALID_PATH;
 		}
@@ -239,17 +227,20 @@ int FaceRecognitionModel::save(const std::string& fileName)
 
 		switch (m_learnAlgorithmConfig.mModelType) {
 		case MEDIA_VISION_FACE_MODEL_TYPE_EIGENFACES:
-			storage << "algorithm" << "Eigenfaces";
+			storage << "algorithm"
+					<< "Eigenfaces";
 			storage << "resizeW" << m_learnAlgorithmConfig.mImgWidth;
 			storage << "resizeH" << m_learnAlgorithmConfig.mImgHeight;
 			break;
 		case MEDIA_VISION_FACE_MODEL_TYPE_FISHERFACES:
-			storage << "algorithm" << "Fisherfaces";
+			storage << "algorithm"
+					<< "Fisherfaces";
 			storage << "resizeW" << m_learnAlgorithmConfig.mImgWidth;
 			storage << "resizeH" << m_learnAlgorithmConfig.mImgHeight;
 			break;
 		case MEDIA_VISION_FACE_MODEL_TYPE_LBPH:
-			storage << "algorithm" << "LBPH";
+			storage << "algorithm"
+					<< "LBPH";
 			break;
 		default:
 			storage.release();
@@ -268,7 +259,7 @@ int FaceRecognitionModel::save(const std::string& fileName)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int FaceRecognitionModel::load(const std::string& fileName)
+int FaceRecognitionModel::load(const std::string &fileName)
 {
 	std::string filePath;
 
@@ -304,9 +295,8 @@ int FaceRecognitionModel::load(const std::string& fileName)
 		storage["resizeW"] >> tempConfig.mImgWidth;
 		storage["resizeH"] >> tempConfig.mImgHeight;
 		tempRecognizer->read(storage.root());
-		tempConfig.mModelType =
-				MEDIA_VISION_FACE_MODEL_TYPE_EIGENFACES;
-		cv::face::EigenFaceRecognizer* recognizer = dynamic_cast<cv::face::EigenFaceRecognizer*>(tempRecognizer.get());
+		tempConfig.mModelType = MEDIA_VISION_FACE_MODEL_TYPE_EIGENFACES;
+		cv::face::EigenFaceRecognizer *recognizer = dynamic_cast<cv::face::EigenFaceRecognizer *>(tempRecognizer.get());
 		if (recognizer != NULL) {
 			tempConfig.mNumComponents = recognizer->getNumComponents();
 			labels = recognizer->getLabels();
@@ -318,9 +308,9 @@ int FaceRecognitionModel::load(const std::string& fileName)
 		storage["resizeW"] >> tempConfig.mImgWidth;
 		storage["resizeH"] >> tempConfig.mImgHeight;
 		tempRecognizer->read(storage.root());
-		tempConfig.mModelType =
-				MEDIA_VISION_FACE_MODEL_TYPE_FISHERFACES;
-		cv::face::FisherFaceRecognizer* recognizer = dynamic_cast<cv::face::FisherFaceRecognizer*>(tempRecognizer.get());
+		tempConfig.mModelType = MEDIA_VISION_FACE_MODEL_TYPE_FISHERFACES;
+		cv::face::FisherFaceRecognizer *recognizer =
+				dynamic_cast<cv::face::FisherFaceRecognizer *>(tempRecognizer.get());
 		if (recognizer != NULL) {
 			tempConfig.mNumComponents = recognizer->getNumComponents();
 			labels = recognizer->getLabels();
@@ -330,10 +320,9 @@ int FaceRecognitionModel::load(const std::string& fileName)
 	} else if (algName == "LBPH") {
 		tempRecognizer = cv::face::LBPHFaceRecognizer::create();
 		tempRecognizer->read(storage.root());
-		cv::face::LBPHFaceRecognizer* recognizer = dynamic_cast<cv::face::LBPHFaceRecognizer*>(tempRecognizer.get());
+		cv::face::LBPHFaceRecognizer *recognizer = dynamic_cast<cv::face::LBPHFaceRecognizer *>(tempRecognizer.get());
 		if (recognizer != NULL) {
-			tempConfig.mModelType =
-					MEDIA_VISION_FACE_MODEL_TYPE_LBPH;
+			tempConfig.mModelType = MEDIA_VISION_FACE_MODEL_TYPE_LBPH;
 			tempConfig.mGridX = recognizer->getGridX();
 			tempConfig.mGridY = recognizer->getGridY();
 			tempConfig.mNeighbors = recognizer->getNeighbors();
@@ -345,7 +334,7 @@ int FaceRecognitionModel::load(const std::string& fileName)
 	} else {
 		tempConfig = FaceRecognitionModelConfig();
 		LOGE("Failed to load face recognition model from file. File is in "
-				"unsupported format");
+			 "unsupported format");
 
 		storage.release();
 
@@ -354,8 +343,7 @@ int FaceRecognitionModel::load(const std::string& fileName)
 	ParseOpenCVLabels(labels, tempLearnedLabels);
 	tempConfig.mThreshold = tempRecognizer->getThreshold();
 
-	LOGD("Recognition model of [%s] type has been loaded from file",
-			algName.c_str());
+	LOGD("Recognition model of [%s] type has been loaded from file", algName.c_str());
 
 	storage.release();
 
@@ -368,14 +356,11 @@ int FaceRecognitionModel::load(const std::string& fileName)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int FaceRecognitionModel::addFaceExample(
-		const cv::Mat& faceImage,
-		int faceLabel)
+int FaceRecognitionModel::addFaceExample(const cv::Mat &faceImage, int faceLabel)
 {
 	m_faceSamples[faceLabel].push_back(faceImage);
 
-	LOGD("Added face image example for label %i for recognition model",
-			faceLabel);
+	LOGD("Added face image example for label %i for recognition model", faceLabel);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
@@ -393,31 +378,32 @@ int FaceRecognitionModel::resetFaceExamples(int faceLabel)
 {
 	if (1 > m_faceSamples.erase(faceLabel)) {
 		LOGD("Failed to remove face image examples for label %i. "
-				"No such examples", faceLabel);
+			 "No such examples",
+			 faceLabel);
 
 		return MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE;
 	}
 
 	LOGD("Face image examples for label %i have been removed from "
-			"recognition model", faceLabel);
+		 "recognition model",
+		 faceLabel);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-const std::set<int>& FaceRecognitionModel::getFaceLabels(void) const
+const std::set<int> &FaceRecognitionModel::getFaceLabels(void) const
 {
 	return m_learnedLabels;
 }
 
-int FaceRecognitionModel::learn(const FaceRecognitionModelConfig& config)
+int FaceRecognitionModel::learn(const FaceRecognitionModelConfig &config)
 {
 	/* Check number of classes collected for learning, some algorithms
 	 * require specific class number constraints. For example, Fisherfaces
 	 * requires more that 1 class in training set */
-	if (MEDIA_VISION_FACE_MODEL_TYPE_FISHERFACES == config.mModelType &&
-			m_faceSamples.size() < 2) {
+	if (MEDIA_VISION_FACE_MODEL_TYPE_FISHERFACES == config.mModelType && m_faceSamples.size() < 2) {
 		LOGE("Can't apply Fisherfaces learning algorithm. It requires at "
-				"least two classes (face labes) to learn on.");
+			 "least two classes (face labes) to learn on.");
 
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
@@ -429,7 +415,7 @@ int FaceRecognitionModel::learn(const FaceRecognitionModelConfig& config)
 		isIncremental = true;
 
 	if (MEDIA_VISION_FACE_MODEL_TYPE_EIGENFACES == config.mModelType ||
-			MEDIA_VISION_FACE_MODEL_TYPE_FISHERFACES == config.mModelType)
+		MEDIA_VISION_FACE_MODEL_TYPE_FISHERFACES == config.mModelType)
 		isUnisize = true;
 
 	std::vector<cv::Mat> samples;
@@ -447,16 +433,13 @@ int FaceRecognitionModel::learn(const FaceRecognitionModelConfig& config)
 		learnedLabels.insert(it->first);
 
 		if (!isUnisize) {
-			LOGD("%zu examples has been added with label %i",
-					it->second.size(), it->first);
+			LOGD("%zu examples has been added with label %i", it->second.size(), it->first);
 			samples.insert(samples.end(), it->second.begin(), it->second.end());
 		} else {
 			for (size_t sampleInd = 0; sampleInd < faceClassSamplesSize; ++sampleInd) {
 				cv::Mat resizedSample;
-				cv::resize(it->second[sampleInd],
-						resizedSample,
-						cv::Size(config.mImgWidth, config.mImgHeight),
-						0.0, 0.0, cv::INTER_CUBIC);
+				cv::resize(it->second[sampleInd], resizedSample, cv::Size(config.mImgWidth, config.mImgHeight), 0.0,
+						   0.0, cv::INTER_CUBIC);
 				samples.push_back(resizedSample);
 			}
 		}
@@ -466,27 +449,25 @@ int FaceRecognitionModel::learn(const FaceRecognitionModelConfig& config)
 	const size_t labelsSize = labels.size();
 
 	if (0 != samplesSize && samplesSize == labelsSize) {
-		LOGD("Start to learn the model for %zu samples and %zu labels",
-				samplesSize, labelsSize);
+		LOGD("Start to learn the model for %zu samples and %zu labels", samplesSize, labelsSize);
 
 		if (m_learnAlgorithmConfig != config || m_recognizer.empty())
 			m_recognizer = CreateRecognitionAlgorithm(config);
 
 		if (m_recognizer.empty()) {
 			LOGE("Can't create recognition algorithm for recognition model. "
-					"Configuration is not supported by any of known algorithms.");
+				 "Configuration is not supported by any of known algorithms.");
 
 			return MEDIA_VISION_ERROR_NOT_SUPPORTED;
 		}
 
-		isIncremental ? m_recognizer->update(samples, labels) :
-						m_recognizer->train(samples, labels);
+		isIncremental ? m_recognizer->update(samples, labels) : m_recognizer->train(samples, labels);
 		m_canRecognize = true;
 		m_learnedLabels.clear();
 		m_learnedLabels = learnedLabels;
 	} else {
 		LOGE("Can't create recognition algorithm for no examples. Try to add "
-				"some face examples before learning");
+			 "some face examples before learning");
 
 		return MEDIA_VISION_ERROR_NO_DATA;
 	}
@@ -498,17 +479,15 @@ int FaceRecognitionModel::learn(const FaceRecognitionModelConfig& config)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int FaceRecognitionModel::recognize(const cv::Mat& image, FaceRecognitionResults& results)
+int FaceRecognitionModel::recognize(const cv::Mat &image, FaceRecognitionResults &results)
 {
 	if (!m_recognizer.empty() && m_canRecognize) {
 		double absConf = 0.0;
-		cv::Mat predictionImg(m_learnAlgorithmConfig.mImgWidth,
-				m_learnAlgorithmConfig.mImgHeight, CV_8UC1);
+		cv::Mat predictionImg(m_learnAlgorithmConfig.mImgWidth, m_learnAlgorithmConfig.mImgHeight, CV_8UC1);
 
 		if ((MEDIA_VISION_FACE_MODEL_TYPE_EIGENFACES == m_learnAlgorithmConfig.mModelType ||
-				MEDIA_VISION_FACE_MODEL_TYPE_FISHERFACES == m_learnAlgorithmConfig.mModelType) &&
-				(image.cols != m_learnAlgorithmConfig.mImgWidth ||
-				image.rows != m_learnAlgorithmConfig.mImgHeight))
+			 MEDIA_VISION_FACE_MODEL_TYPE_FISHERFACES == m_learnAlgorithmConfig.mModelType) &&
+			(image.cols != m_learnAlgorithmConfig.mImgWidth || image.rows != m_learnAlgorithmConfig.mImgHeight))
 			cv::resize(image, predictionImg, predictionImg.size());
 		else
 			predictionImg = image;
@@ -545,28 +524,20 @@ int FaceRecognitionModel::recognize(const cv::Mat& image, FaceRecognitionResults
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-cv::Ptr<cv::face::FaceRecognizer> FaceRecognitionModel::CreateRecognitionAlgorithm(
-		const FaceRecognitionModelConfig& config)
+cv::Ptr<cv::face::FaceRecognizer>
+FaceRecognitionModel::CreateRecognitionAlgorithm(const FaceRecognitionModelConfig &config)
 {
 	cv::Ptr<cv::face::FaceRecognizer> tempRecognizer;
 	switch (config.mModelType) {
 	case MEDIA_VISION_FACE_MODEL_TYPE_EIGENFACES:
-		tempRecognizer = cv::face::EigenFaceRecognizer::create(
-									config.mNumComponents,
-									config.mThreshold);
+		tempRecognizer = cv::face::EigenFaceRecognizer::create(config.mNumComponents, config.mThreshold);
 		break;
 	case MEDIA_VISION_FACE_MODEL_TYPE_FISHERFACES:
-		tempRecognizer = cv::face::FisherFaceRecognizer::create(
-									config.mNumComponents,
-									config.mThreshold);
+		tempRecognizer = cv::face::FisherFaceRecognizer::create(config.mNumComponents, config.mThreshold);
 		break;
 	case MEDIA_VISION_FACE_MODEL_TYPE_LBPH:
-		tempRecognizer = cv::face::LBPHFaceRecognizer::create(
-									config.mRadius,
-									config.mNeighbors,
-									config.mGridX,
-									config.mGridY,
-									config.mThreshold);
+		tempRecognizer = cv::face::LBPHFaceRecognizer::create(config.mRadius, config.mNeighbors, config.mGridX,
+															  config.mGridY, config.mThreshold);
 		break;
 	default:
 		LOGE("Unknown FaceRecognition model");
diff --git a/mv_face/face/src/FaceTracker.cpp b/mv_face/face/src/FaceTracker.cpp
index 9303b16..30cdf64 100644
--- a/mv_face/face/src/FaceTracker.cpp
+++ b/mv_face/face/src/FaceTracker.cpp
@@ -47,11 +47,13 @@
 #include <algorithm>
 #include <cmath>
 
-namespace {
-	float FloatEps = 10e-6f;
+namespace
+{
+float FloatEps = 10e-6f;
 } /* anonymous namespace */
 
-namespace cv {
+namespace cv
+{
 FaceTracker::Params::Params()
 {
 	mPointsInGrid = 10;
@@ -59,7 +61,7 @@ FaceTracker::Params::Params()
 	mPyrMaxLevel = 5;
 }
 
-void FaceTracker::Params::read(const cv::FileNode& fn)
+void FaceTracker::Params::read(const cv::FileNode &fn)
 {
 	mPointsInGrid = fn["pointsInGrid"];
 	int winSizeHeight = fn["windowSizeHeight"];
@@ -68,7 +70,7 @@ void FaceTracker::Params::read(const cv::FileNode& fn)
 	mPyrMaxLevel = fn["pyrMaxLevel"];
 }
 
-void FaceTracker::Params::write(cv::FileStorage& fs) const
+void FaceTracker::Params::write(cv::FileStorage &fs) const
 {
 	fs << "pointsInGrid" << mPointsInGrid;
 	fs << "windowSizeHeight" << mWindowSize.height;
@@ -76,15 +78,14 @@ void FaceTracker::Params::write(cv::FileStorage& fs) const
 	fs << "pyrMaxLevel" << mPyrMaxLevel;
 }
 
-FaceTracker::FaceTracker(Params paramsIn) :
-	m_termcrit(TermCriteria::COUNT | TermCriteria::EPS, 20, 0.3),
-	m_confidence(0.0)
+FaceTracker::FaceTracker(Params paramsIn)
+		: m_termcrit(TermCriteria::COUNT | TermCriteria::EPS, 20, 0.3), m_confidence(0.0)
 {
 	m_params = paramsIn;
 	m_isInit = false;
 }
 
-bool FaceTracker::copyTo(FaceTracker& copy) const
+bool FaceTracker::copyTo(FaceTracker &copy) const
 {
 	copy.m_isInit = m_isInit;
 	copy.m_params = m_params;
@@ -95,21 +96,20 @@ bool FaceTracker::copyTo(FaceTracker& copy) const
 	return true;
 }
 
-bool FaceTracker::initImpl(const Mat& image, const Rect2d& boundingBox)
+bool FaceTracker::initImpl(const Mat &image, const Rect2d &boundingBox)
 {
 	if (image.empty())
 		return false;
 
 	image.copyTo(m_image);
-	buildOpticalFlowPyramid(
-			m_image, m_pyramid, m_params.mWindowSize, m_params.mPyrMaxLevel);
+	buildOpticalFlowPyramid(m_image, m_pyramid, m_params.mWindowSize, m_params.mPyrMaxLevel);
 	m_boundingBox = boundingBox;
 
 	m_isInit = true;
 	return m_isInit;
 }
 
-bool FaceTracker::updateImpl(const Mat& image, Rect2d& boundingBox)
+bool FaceTracker::updateImpl(const Mat &image, Rect2d &boundingBox)
 {
 	if (!m_isInit || image.empty())
 		return false;
@@ -132,11 +132,11 @@ bool FaceTracker::updateImpl(const Mat& image, Rect2d& boundingBox)
 
 	Mat oldImage = m_image;
 
-	Rect2f oldBox = (Rect2f)m_boundingBox;
-	if(!medianFlowImpl(oldImage, image, oldBox))
+	Rect2f oldBox = (Rect2f) m_boundingBox;
+	if (!medianFlowImpl(oldImage, image, oldBox))
 		return false;
 
-	boundingBox = (Rect2d)oldBox;
+	boundingBox = (Rect2d) oldBox;
 	image.copyTo(m_image);
 	m_boundingBox = boundingBox;
 	return true;
@@ -157,8 +157,7 @@ Rect_<float> FaceTracker::getLastBoundingBox() const
 	return m_boundingBox;
 }
 
-bool FaceTracker::medianFlowImpl(
-		Mat oldGrayImage, Mat newGrayImage, Rect2f& oldBox)
+bool FaceTracker::medianFlowImpl(Mat oldGrayImage, Mat newGrayImage, Rect2f &oldBox)
 {
 	std::vector<Point2f> pointsToTrackOld, pointsToTrackNew;
 
@@ -166,29 +165,17 @@ bool FaceTracker::medianFlowImpl(
 	const float gridYStep = oldBox.height / m_params.mPointsInGrid;
 	for (int i = 0; i < m_params.mPointsInGrid; i++)
 		for (int j = 0; j < m_params.mPointsInGrid; j++)
-			pointsToTrackOld.push_back(
-						Point2f(oldBox.x + .5f*gridXStep + 1.f*gridXStep*j,
-								oldBox.y + .5f*gridYStep + 1.f*gridYStep*i));
+			pointsToTrackOld.push_back(Point2f(oldBox.x + .5f * gridXStep + 1.f * gridXStep * j,
+											   oldBox.y + .5f * gridYStep + 1.f * gridYStep * i));
 
 	std::vector<uchar> status(pointsToTrackOld.size());
 	std::vector<float> errors(pointsToTrackOld.size());
 
 	std::vector<Mat> tempPyramid;
-	buildOpticalFlowPyramid(
-							newGrayImage,
-							tempPyramid,
-							m_params.mWindowSize,
-							m_params.mPyrMaxLevel);
-
-	calcOpticalFlowPyrLK(m_pyramid,
-						tempPyramid,
-						pointsToTrackOld,
-						pointsToTrackNew,
-						status,
-						errors,
-						m_params.mWindowSize,
-						m_params.mPyrMaxLevel,
-						m_termcrit);
+	buildOpticalFlowPyramid(newGrayImage, tempPyramid, m_params.mWindowSize, m_params.mPyrMaxLevel);
+
+	calcOpticalFlowPyrLK(m_pyramid, tempPyramid, pointsToTrackOld, pointsToTrackNew, status, errors,
+						 m_params.mWindowSize, m_params.mPyrMaxLevel, m_termcrit);
 
 	std::vector<Point2f> di;
 	for (size_t idx = 0u; idx < pointsToTrackOld.size(); idx++)
@@ -196,16 +183,9 @@ bool FaceTracker::medianFlowImpl(
 			di.push_back(pointsToTrackNew[idx] - pointsToTrackOld[idx]);
 
 	std::vector<bool> filter_status;
-	check_FB(tempPyramid,
-				pointsToTrackOld,
-				pointsToTrackNew,
-				filter_status);
+	check_FB(tempPyramid, pointsToTrackOld, pointsToTrackNew, filter_status);
 
-	check_NCC(oldGrayImage,
-				newGrayImage,
-				pointsToTrackOld,
-				pointsToTrackNew,
-				filter_status);
+	check_NCC(oldGrayImage, newGrayImage, pointsToTrackOld, pointsToTrackNew, filter_status);
 
 	for (size_t idx = 0u; idx < pointsToTrackOld.size(); idx++) {
 		if (!filter_status[idx]) {
@@ -220,8 +200,7 @@ bool FaceTracker::medianFlowImpl(
 		return false;
 
 	Point2f mDisplacement;
-	Rect_<float> boxCandidate =
-			vote(pointsToTrackOld, pointsToTrackNew, oldBox, mDisplacement);
+	Rect_<float> boxCandidate = vote(pointsToTrackOld, pointsToTrackNew, oldBox, mDisplacement);
 
 	std::vector<float> displacements;
 	for (size_t idx = 0u; idx < di.size(); idx++) {
@@ -229,8 +208,7 @@ bool FaceTracker::medianFlowImpl(
 		displacements.push_back(sqrt(di[idx].ddot(di[idx])));
 	}
 
-	m_confidence =
-				(10.f - getMedian(displacements, (int)displacements.size())) / 10.f;
+	m_confidence = (10.f - getMedian(displacements, (int) displacements.size())) / 10.f;
 	if (m_confidence <= 0.f) {
 		m_confidence = 0.f;
 		return false;
@@ -241,22 +219,18 @@ bool FaceTracker::medianFlowImpl(
 	return true;
 }
 
-Rect_<float> FaceTracker::vote(
-		const std::vector<Point2f>& oldPoints,
-		const std::vector<Point2f>& newPoints,
-		const Rect_<float>& oldRect,
-		Point2f& mD)
+Rect_<float> FaceTracker::vote(const std::vector<Point2f> &oldPoints, const std::vector<Point2f> &newPoints,
+							   const Rect_<float> &oldRect, Point2f &mD)
 {
 	Rect_<float> newRect;
-	Point2d newCenter(oldRect.x + oldRect.width/2.0,
-						oldRect.y + oldRect.height/2.0);
+	Point2d newCenter(oldRect.x + oldRect.width / 2.0, oldRect.y + oldRect.height / 2.0);
 
-	int n = (int)oldPoints.size();
-	std::vector<float> buf(std::max(n*(n-1) / 2, 3), 0.f);
+	int n = (int) oldPoints.size();
+	std::vector<float> buf(std::max(n * (n - 1) / 2, 3), 0.f);
 
-	if(oldPoints.size() == 1) {
-		newRect.x = oldRect.x+newPoints[0].x-oldPoints[0].x;
-		newRect.y = oldRect.y+newPoints[0].y-oldPoints[0].y;
+	if (oldPoints.size() == 1) {
+		newRect.x = oldRect.x + newPoints[0].x - oldPoints[0].x;
+		newRect.y = oldRect.y + newPoints[0].y - oldPoints[0].y;
 		newRect.width = oldRect.width;
 		newRect.height = oldRect.height;
 		return newRect;
@@ -264,19 +238,19 @@ Rect_<float> FaceTracker::vote(
 
 	float xshift = 0.f;
 	float yshift = 0.f;
-	for(int i = 0; i < n; i++)
+	for (int i = 0; i < n; i++)
 		buf[i] = newPoints[i].x - oldPoints[i].x;
 
 	xshift = getMedian(buf, n);
 	newCenter.x += xshift;
-	for(int idx = 0; idx < n; idx++)
+	for (int idx = 0; idx < n; idx++)
 		buf[idx] = newPoints[idx].y - oldPoints[idx].y;
 
 	yshift = getMedian(buf, n);
 	newCenter.y += yshift;
 	mD = Point2f(xshift, yshift);
 
-	if(oldPoints.size() == 1) {
+	if (oldPoints.size() == 1) {
 		newRect.x = newCenter.x - oldRect.width / 2.0;
 		newRect.y = newCenter.y - oldRect.height / 2.0;
 		newRect.width = oldRect.width;
@@ -287,7 +261,7 @@ Rect_<float> FaceTracker::vote(
 	float nd = 0.f;
 	float od = 0.f;
 	for (int i = 0, ctr = 0; i < n; i++) {
-		for(int j = 0; j < i; j++) {
+		for (int j = 0; j < i; j++) {
 			nd = l2distance(newPoints[i], newPoints[j]);
 			od = l2distance(oldPoints[i], oldPoints[j]);
 			buf[ctr] = (od == 0.f ? 0.f : nd / od);
@@ -295,25 +269,24 @@ Rect_<float> FaceTracker::vote(
 		}
 	}
 
-	float scale = getMedian(buf, n*(n-1) / 2);
+	float scale = getMedian(buf, n * (n - 1) / 2);
 	newRect.x = newCenter.x - scale * oldRect.width / 2.f;
-	newRect.y = newCenter.y-scale * oldRect.height / 2.f;
+	newRect.y = newCenter.y - scale * oldRect.height / 2.f;
 	newRect.width = scale * oldRect.width;
 	newRect.height = scale * oldRect.height;
 
 	return newRect;
 }
 
-template<typename T>
-T FaceTracker::getMedian(std::vector<T>& values, int size)
+template<typename T> T FaceTracker::getMedian(std::vector<T> &values, int size)
 {
 	if (size == -1)
-		size = (int)values.size();
+		size = (int) values.size();
 
 	std::vector<T> copy(values.begin(), values.begin() + size);
 	std::sort(copy.begin(), copy.end());
-	if(size%2 == 0) {
-		return (copy[size/2-1]+copy[size/2])/((T)2.0);
+	if (size % 2 == 0) {
+		return (copy[size / 2 - 1] + copy[size / 2]) / ((T) 2.0);
 	} else {
 		return copy[(size - 1) / 2];
 	}
@@ -326,13 +299,10 @@ float FaceTracker::l2distance(Point2f p1, Point2f p2)
 	return sqrt(dx * dx + dy * dy);
 }
 
-void FaceTracker::check_FB(
-		std::vector<Mat> newPyramid,
-		const std::vector<Point2f>& oldPoints,
-		const std::vector<Point2f>& newPoints,
-		std::vector<bool>& status)
+void FaceTracker::check_FB(std::vector<Mat> newPyramid, const std::vector<Point2f> &oldPoints,
+						   const std::vector<Point2f> &newPoints, std::vector<bool> &status)
 {
-	if(status.size() == 0)
+	if (status.size() == 0)
 		status = std::vector<bool>(oldPoints.size(), true);
 
 	std::vector<uchar> LKstatus(oldPoints.size());
@@ -340,15 +310,8 @@ void FaceTracker::check_FB(
 	std::vector<float> FBerror(oldPoints.size());
 	std::vector<Point2f> pointsToTrackReprojection;
 
-	calcOpticalFlowPyrLK(newPyramid,
-						m_pyramid,
-						newPoints,
-						pointsToTrackReprojection,
-						LKstatus,
-						errors,
-						m_params.mWindowSize,
-						m_params.mPyrMaxLevel,
-						m_termcrit);
+	calcOpticalFlowPyrLK(newPyramid, m_pyramid, newPoints, pointsToTrackReprojection, LKstatus, errors,
+						 m_params.mWindowSize, m_params.mPyrMaxLevel, m_termcrit);
 
 	for (size_t idx = 0u; idx < oldPoints.size(); idx++)
 		FBerror[idx] = l2distance(oldPoints[idx], pointsToTrackReprojection[idx]);
@@ -358,12 +321,8 @@ void FaceTracker::check_FB(
 		status[idx] = (FBerror[idx] < FBerrorMedian);
 }
 
-void FaceTracker::check_NCC(
-		const Mat& oldImage,
-		const Mat& newImage,
-		const std::vector<Point2f>& oldPoints,
-		const std::vector<Point2f>& newPoints,
-		std::vector<bool>& status)
+void FaceTracker::check_NCC(const Mat &oldImage, const Mat &newImage, const std::vector<Point2f> &oldPoints,
+							const std::vector<Point2f> &newPoints, std::vector<bool> &status)
 {
 	std::vector<float> NCC(oldPoints.size(), 0.f);
 	Size patch(30, 30);
@@ -382,21 +341,20 @@ void FaceTracker::check_NCC(
 		const float prod = p1.dot(p2);
 		const float sq1 = sqrt(n1 * n1 - s1 * s1 / N);
 		const float sq2 = sqrt(n2 * n2 - s2 * s2 / N);
-		NCC[idx] = (sq2 == 0 ? sq1 / std::abs(sq1)
-					: (prod - s1 * s2 / N) / sq1 / sq2);
+		NCC[idx] = (sq2 == 0 ? sq1 / std::abs(sq1) : (prod - s1 * s2 / N) / sq1 / sq2);
 	}
 
 	float median = getMedian(NCC) - FloatEps;
-	for(size_t idx = 0u; idx < oldPoints.size(); idx++)
+	for (size_t idx = 0u; idx < oldPoints.size(); idx++)
 		status[idx] = status[idx] && (NCC[idx] > median);
 }
 
-void FaceTracker::read(const cv::FileNode& fn)
+void FaceTracker::read(const cv::FileNode &fn)
 {
 	m_params.read(fn);
 }
 
-void FaceTracker::read(cv::FileStorage& fs)
+void FaceTracker::read(cv::FileStorage &fs)
 {
 	read(fs.root());
 	float bbX = 0.f;
@@ -411,8 +369,7 @@ void FaceTracker::read(cv::FileStorage& fs)
 	fs["lastImage"] >> m_image;
 }
 
-
-void FaceTracker::write(cv::FileStorage& fs) const
+void FaceTracker::write(cv::FileStorage &fs) const
 {
 	m_params.write(fs);
 	fs << "lastLocationX" << m_boundingBox.x;
diff --git a/mv_face/face/src/FaceTrackingModel.cpp b/mv_face/face/src/FaceTrackingModel.cpp
index 778a82e..af20651 100644
--- a/mv_face/face/src/FaceTrackingModel.cpp
+++ b/mv_face/face/src/FaceTrackingModel.cpp
@@ -21,31 +21,28 @@
 
 #include <unistd.h>
 
-namespace MediaVision {
-namespace Face {
-FaceTrackingResults::FaceTrackingResults() :
-	mIsTracked(false),
-	mConfidence(0.f)
+namespace MediaVision
+{
+namespace Face
+{
+FaceTrackingResults::FaceTrackingResults() : mIsTracked(false), mConfidence(0.f)
 {
 	; /* NULL */
 }
 
-FaceTrackingModel::FaceTrackingModel() :
-	m_canTrack(false),
-	m_tracker(new cv::FaceTracker())
+FaceTrackingModel::FaceTrackingModel() : m_canTrack(false), m_tracker(new cv::FaceTracker())
 {
 	; /* NULL */
 }
 
-FaceTrackingModel::FaceTrackingModel(const FaceTrackingModel& origin) :
-	m_canTrack(origin.m_canTrack),
-	m_tracker(new cv::FaceTracker())
+FaceTrackingModel::FaceTrackingModel(const FaceTrackingModel &origin)
+		: m_canTrack(origin.m_canTrack), m_tracker(new cv::FaceTracker())
 {
 	if (!origin.m_tracker.empty())
 		origin.m_tracker->copyTo(*(m_tracker.get()));
 }
 
-FaceTrackingModel& FaceTrackingModel::operator=(const FaceTrackingModel& copy)
+FaceTrackingModel &FaceTrackingModel::operator=(const FaceTrackingModel &copy)
 {
 	if (this != &copy) {
 		m_canTrack = copy.m_canTrack;
@@ -62,7 +59,7 @@ FaceTrackingModel::~FaceTrackingModel()
 	; /* NULL */
 }
 
-int FaceTrackingModel::save(const std::string& fileName)
+int FaceTrackingModel::save(const std::string &fileName)
 {
 	if (m_tracker.empty()) {
 		LOGE("Can't save tracking model. No tracking algorithm is used");
@@ -82,7 +79,7 @@ int FaceTrackingModel::save(const std::string& fileName)
 
 			return MEDIA_VISION_ERROR_INVALID_PATH;
 		}
-	} catch (const std::out_of_range& e) {
+	} catch (const std::out_of_range &e) {
 		LOGE("Can't save tracking model. Path[%s] is invalid.", filePath.c_str());
 		return MEDIA_VISION_ERROR_INVALID_PATH;
 	}
@@ -105,7 +102,7 @@ int FaceTrackingModel::save(const std::string& fileName)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int FaceTrackingModel::load(const std::string& fileName)
+int FaceTrackingModel::load(const std::string &fileName)
 {
 	std::string filePath;
 
@@ -135,11 +132,11 @@ int FaceTrackingModel::load(const std::string& fileName)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int FaceTrackingModel::prepare(const cv::Mat& image)
+int FaceTrackingModel::prepare(const cv::Mat &image)
 {
 	if (m_tracker.empty()) {
 		LOGE("Failed to prepare tracking model. No tracking algorithm "
-				"is available.");
+			 "is available.");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
@@ -156,13 +153,11 @@ int FaceTrackingModel::prepare(const cv::Mat& image)
 	return prepare(image, lastBoundingBox);
 }
 
-int FaceTrackingModel::prepare(
-		const cv::Mat& image,
-		const cv::Rect_<float>& boundingBox)
+int FaceTrackingModel::prepare(const cv::Mat &image, const cv::Rect_<float> &boundingBox)
 {
 	if (m_tracker.empty()) {
 		LOGE("Failed to prepare tracking model. No tracking algorithm "
-				"is available.");
+			 "is available.");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
@@ -175,13 +170,13 @@ int FaceTrackingModel::prepare(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int FaceTrackingModel::track(const cv::Mat& image, FaceTrackingResults& results)
+int FaceTrackingModel::track(const cv::Mat &image, FaceTrackingResults &results)
 {
 	if (!m_tracker.empty() && m_canTrack) {
-		cv::Rect2d faceLocation = (cv::Rect2d)results.mFaceLocation;
+		cv::Rect2d faceLocation = (cv::Rect2d) results.mFaceLocation;
 		results.mIsTracked = m_tracker->updateImpl(image, faceLocation);
 		results.mConfidence = m_tracker->getLastConfidence();
-		results.mFaceLocation = (cv::Rect2f)faceLocation;
+		results.mFaceLocation = (cv::Rect2f) faceLocation;
 	} else {
 		LOGE("Attempt to track face with not prepared model");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
diff --git a/mv_face/face/src/FaceUtil.cpp b/mv_face/face/src/FaceUtil.cpp
index 1d89744..c1af063 100644
--- a/mv_face/face/src/FaceUtil.cpp
+++ b/mv_face/face/src/FaceUtil.cpp
@@ -21,16 +21,16 @@
 #include <opencv2/imgproc.hpp>
 #include <opencv2/imgproc/imgproc_c.h>
 
-namespace MediaVision {
-namespace Face {
-RecognitionParams::RecognitionParams(FaceRecognitionModelType algType) :
-	mRecognitionAlgType(algType)
+namespace MediaVision
+{
+namespace Face
+{
+RecognitionParams::RecognitionParams(FaceRecognitionModelType algType) : mRecognitionAlgType(algType)
 {
 	; /* NULL */
 }
 
-RecognitionParams::RecognitionParams() :
-	mRecognitionAlgType(MEDIA_VISION_FACE_MODEL_TYPE_LBPH)
+RecognitionParams::RecognitionParams() : mRecognitionAlgType(MEDIA_VISION_FACE_MODEL_TYPE_LBPH)
 {
 	; /* NULL */
 }
diff --git a/mv_face/face/src/mv_face.c b/mv_face/face/src/mv_face.c
index 7624622..782180d 100644
--- a/mv_face/face/src/mv_face.c
+++ b/mv_face/face/src/mv_face.c
@@ -42,8 +42,7 @@ static int check_source_roi_quadrangle(mv_quadrangle_s *roi, mv_source_h source)
 		return ret;
 	}
 	for (int idx = 0; idx < 4; idx++) {
-		if (roi->points[idx].x < 0 || roi->points[idx].y < 0 ||
-			(unsigned int) roi->points[idx].x > src_w ||
+		if (roi->points[idx].x < 0 || roi->points[idx].y < 0 || (unsigned int) roi->points[idx].x > src_w ||
 			(unsigned int) roi->points[idx].y > src_h) {
 			LOGE("roi is out of area on source");
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -74,8 +73,7 @@ static int check_source_roi(const mv_rectangle_s *roi, mv_source_h source)
 		LOGE("mv_source_get_height fail");
 		return ret;
 	}
-	if (roi->point.x < 0 || roi->point.y < 0 ||
-		(unsigned int) (roi->point.x + roi->width) > src_w ||
+	if (roi->point.x < 0 || roi->point.y < 0 || (unsigned int) (roi->point.x + roi->width) > src_w ||
 		(unsigned int) (roi->point.y + roi->height) > src_h) {
 		LOGE("roi is out of area on source");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -83,11 +81,7 @@ static int check_source_roi(const mv_rectangle_s *roi, mv_source_h source)
 	return ret;
 }
 
-int mv_face_detect(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_face_detected_cb detected_cb,
-		void *user_data)
+int mv_face_detect(mv_source_h source, mv_engine_config_h engine_cfg, mv_face_detected_cb detected_cb, void *user_data)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -103,13 +97,8 @@ int mv_face_detect(
 	return ret;
 }
 
-int mv_face_recognize(
-		mv_source_h source,
-		mv_face_recognition_model_h recognition_model,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s *face_location,
-		mv_face_recognized_cb recognized_cb,
-		void *user_data)
+int mv_face_recognize(mv_source_h source, mv_face_recognition_model_h recognition_model, mv_engine_config_h engine_cfg,
+					  mv_rectangle_s *face_location, mv_face_recognized_cb recognized_cb, void *user_data)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -124,25 +113,14 @@ int mv_face_recognize(
 		return ret;
 	}
 
-	ret = mv_face_recognize_open(
-					source,
-					recognition_model,
-					engine_cfg,
-					face_location,
-					recognized_cb,
-					user_data);
+	ret = mv_face_recognize_open(source, recognition_model, engine_cfg, face_location, recognized_cb, user_data);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_face_track(
-		mv_source_h source,
-		mv_face_tracking_model_h tracking_model,
-		mv_engine_config_h engine_cfg,
-		mv_face_tracked_cb tracked_cb,
-		bool do_learn,
-		void *user_data)
+int mv_face_track(mv_source_h source, mv_face_tracking_model_h tracking_model, mv_engine_config_h engine_cfg,
+				  mv_face_tracked_cb tracked_cb, bool do_learn, void *user_data)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -153,24 +131,14 @@ int mv_face_track(
 
 	int ret = MEDIA_VISION_ERROR_NONE;
 
-	ret = mv_face_track_open(
-			source,
-			tracking_model,
-			engine_cfg,
-			tracked_cb,
-			do_learn,
-			user_data);
+	ret = mv_face_track_open(source, tracking_model, engine_cfg, tracked_cb, do_learn, user_data);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_face_eye_condition_recognize(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s face_location,
-		mv_face_eye_condition_recognized_cb eye_condition_recognized_cb,
-		void *user_data)
+int mv_face_eye_condition_recognize(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s face_location,
+									mv_face_eye_condition_recognized_cb eye_condition_recognized_cb, void *user_data)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -180,23 +148,16 @@ int mv_face_eye_condition_recognize(
 
 	int ret = MEDIA_VISION_ERROR_NONE;
 
-	ret = mv_face_eye_condition_recognize_open(
-				source,
-				engine_cfg,
-				face_location,
-				eye_condition_recognized_cb,
-				user_data);
+	ret = mv_face_eye_condition_recognize_open(source, engine_cfg, face_location, eye_condition_recognized_cb,
+											   user_data);
 
-MEDIA_VISION_FUNCTION_LEAVE();
-return ret;
+	MEDIA_VISION_FUNCTION_LEAVE();
+	return ret;
 }
 
-int mv_face_facial_expression_recognize(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s face_location,
-		mv_face_facial_expression_recognized_cb expression_recognized_cb,
-		void *user_data)
+int mv_face_facial_expression_recognize(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s face_location,
+										mv_face_facial_expression_recognized_cb expression_recognized_cb,
+										void *user_data)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -210,19 +171,14 @@ int mv_face_facial_expression_recognize(
 		return ret;
 	}
 
-	ret = mv_face_facial_expression_recognize_open(
-					source,
-					engine_cfg,
-					face_location,
-					expression_recognized_cb,
-					user_data);
+	ret = mv_face_facial_expression_recognize_open(source, engine_cfg, face_location, expression_recognized_cb,
+												   user_data);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_face_recognition_model_create(
-		mv_face_recognition_model_h *recognition_model)
+int mv_face_recognition_model_create(mv_face_recognition_model_h *recognition_model)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(recognition_model);
@@ -237,8 +193,7 @@ int mv_face_recognition_model_create(
 	return ret;
 }
 
-int mv_face_recognition_model_destroy(
-		mv_face_recognition_model_h recognition_model)
+int mv_face_recognition_model_destroy(mv_face_recognition_model_h recognition_model)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(recognition_model);
@@ -253,9 +208,7 @@ int mv_face_recognition_model_destroy(
 	return ret;
 }
 
-int mv_face_recognition_model_clone(
-		mv_face_recognition_model_h src,
-		mv_face_recognition_model_h *dst)
+int mv_face_recognition_model_clone(mv_face_recognition_model_h src, mv_face_recognition_model_h *dst)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(src);
@@ -271,9 +224,7 @@ int mv_face_recognition_model_clone(
 	return ret;
 }
 
-int mv_face_recognition_model_save(
-		const char *file_name,
-		mv_face_recognition_model_h recognition_model)
+int mv_face_recognition_model_save(const char *file_name, mv_face_recognition_model_h recognition_model)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(recognition_model);
@@ -287,17 +238,13 @@ int mv_face_recognition_model_save(
 
 	int ret = MEDIA_VISION_ERROR_NONE;
 
-	ret = mv_face_recognition_model_save_open(
-					file_name,
-					recognition_model);
+	ret = mv_face_recognition_model_save_open(file_name, recognition_model);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_face_recognition_model_load(
-		const char *file_name,
-		mv_face_recognition_model_h *recognition_model)
+int mv_face_recognition_model_load(const char *file_name, mv_face_recognition_model_h *recognition_model)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(recognition_model);
@@ -311,19 +258,14 @@ int mv_face_recognition_model_load(
 
 	int ret = MEDIA_VISION_ERROR_NONE;
 
-	ret = mv_face_recognition_model_load_open(
-					file_name,
-					recognition_model);
+	ret = mv_face_recognition_model_load_open(file_name, recognition_model);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_face_recognition_model_add(
-		const mv_source_h source,
-		mv_face_recognition_model_h recognition_model,
-		const mv_rectangle_s *example_location,
-		int face_label)
+int mv_face_recognition_model_add(const mv_source_h source, mv_face_recognition_model_h recognition_model,
+								  const mv_rectangle_s *example_location, int face_label)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -337,19 +279,13 @@ int mv_face_recognition_model_add(
 		return ret;
 	}
 
-	ret = mv_face_recognition_model_add_open(
-					source,
-					recognition_model,
-					example_location,
-					face_label);
+	ret = mv_face_recognition_model_add_open(source, recognition_model, example_location, face_label);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_face_recognition_model_reset(
-		mv_face_recognition_model_h recognition_model,
-		int *face_label)
+int mv_face_recognition_model_reset(mv_face_recognition_model_h recognition_model, int *face_label)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(recognition_model);
@@ -358,17 +294,13 @@ int mv_face_recognition_model_reset(
 
 	int ret = MEDIA_VISION_ERROR_NONE;
 
-	ret = mv_face_recognition_model_reset_open(
-					recognition_model,
-					face_label);
+	ret = mv_face_recognition_model_reset_open(recognition_model, face_label);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_face_recognition_model_learn(
-		mv_engine_config_h engine_cfg,
-		mv_face_recognition_model_h recognition_model)
+int mv_face_recognition_model_learn(mv_engine_config_h engine_cfg, mv_face_recognition_model_h recognition_model)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(recognition_model);
@@ -383,10 +315,8 @@ int mv_face_recognition_model_learn(
 	return ret;
 }
 
-int mv_face_recognition_model_query_labels(
-		mv_face_recognition_model_h recognition_model,
-		int **labels,
-		unsigned int *number_of_labels)
+int mv_face_recognition_model_query_labels(mv_face_recognition_model_h recognition_model, int **labels,
+										   unsigned int *number_of_labels)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(recognition_model);
@@ -403,8 +333,7 @@ int mv_face_recognition_model_query_labels(
 	return ret;
 }
 
-int mv_face_tracking_model_create(
-		mv_face_tracking_model_h *tracking_model)
+int mv_face_tracking_model_create(mv_face_tracking_model_h *tracking_model)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(tracking_model);
@@ -419,8 +348,7 @@ int mv_face_tracking_model_create(
 	return ret;
 }
 
-int mv_face_tracking_model_destroy(
-		mv_face_tracking_model_h tracking_model)
+int mv_face_tracking_model_destroy(mv_face_tracking_model_h tracking_model)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(tracking_model);
@@ -435,11 +363,8 @@ int mv_face_tracking_model_destroy(
 	return ret;
 }
 
-int mv_face_tracking_model_prepare(
-		mv_face_tracking_model_h tracking_model,
-		mv_engine_config_h engine_cfg,
-		mv_source_h source,
-		mv_quadrangle_s *location)
+int mv_face_tracking_model_prepare(mv_face_tracking_model_h tracking_model, mv_engine_config_h engine_cfg,
+								   mv_source_h source, mv_quadrangle_s *location)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(tracking_model);
@@ -453,16 +378,13 @@ int mv_face_tracking_model_prepare(
 		return ret;
 	}
 
-	ret = mv_face_tracking_model_prepare_open(
-				tracking_model, engine_cfg, source, location);
+	ret = mv_face_tracking_model_prepare_open(tracking_model, engine_cfg, source, location);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_face_tracking_model_clone(
-		mv_face_tracking_model_h src,
-		mv_face_tracking_model_h *dst)
+int mv_face_tracking_model_clone(mv_face_tracking_model_h src, mv_face_tracking_model_h *dst)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(src);
@@ -478,9 +400,7 @@ int mv_face_tracking_model_clone(
 	return ret;
 }
 
-int mv_face_tracking_model_save(
-		const char *file_name,
-		mv_face_tracking_model_h tracking_model)
+int mv_face_tracking_model_save(const char *file_name, mv_face_tracking_model_h tracking_model)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(tracking_model);
@@ -494,17 +414,13 @@ int mv_face_tracking_model_save(
 
 	int ret = MEDIA_VISION_ERROR_NONE;
 
-	ret = mv_face_tracking_model_save_open(
-					file_name,
-					tracking_model);
+	ret = mv_face_tracking_model_save_open(file_name, tracking_model);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_face_tracking_model_load(
-		const char *file_name,
-		mv_face_tracking_model_h *tracking_model)
+int mv_face_tracking_model_load(const char *file_name, mv_face_tracking_model_h *tracking_model)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(tracking_model);
@@ -518,9 +434,7 @@ int mv_face_tracking_model_load(
 
 	int ret = MEDIA_VISION_ERROR_NONE;
 
-	ret = mv_face_tracking_model_load_open(
-					file_name,
-					tracking_model);
+	ret = mv_face_tracking_model_load_open(file_name, tracking_model);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
diff --git a/mv_face/face/src/mv_face_open.cpp b/mv_face/face/src/mv_face_open.cpp
index ce297d3..30dda5f 100644
--- a/mv_face/face/src/mv_face_open.cpp
+++ b/mv_face/face/src/mv_face_open.cpp
@@ -35,9 +35,7 @@ using namespace ::MediaVision::Face;
 
 static const RecognitionParams DEFAULT_RECOGNITION_PARAMS = RecognitionParams();
 
-static void extractRecognitionParams(
-		mv_engine_config_h engine_cfg,
-		RecognitionParams& recognitionParams)
+static void extractRecognitionParams(mv_engine_config_h engine_cfg, RecognitionParams &recognitionParams)
 {
 	mv_engine_config_h working_cfg = NULL;
 
@@ -50,23 +48,18 @@ static void extractRecognitionParams(
 	}
 
 	int algType = 0;
-	mv_engine_config_get_int_attribute_c(
-			working_cfg,
-			"MV_FACE_RECOGNITION_MODEL_TYPE",
-			&algType);
+	mv_engine_config_get_int_attribute_c(working_cfg, "MV_FACE_RECOGNITION_MODEL_TYPE", &algType);
 
 	if (0 < algType && 4 > algType)
-		recognitionParams.mRecognitionAlgType =
-				(FaceRecognitionModelType)algType;
+		recognitionParams.mRecognitionAlgType = (FaceRecognitionModelType) algType;
 	else
-		recognitionParams.mRecognitionAlgType =
-				DEFAULT_RECOGNITION_PARAMS.mRecognitionAlgType;
+		recognitionParams.mRecognitionAlgType = DEFAULT_RECOGNITION_PARAMS.mRecognitionAlgType;
 
 	if (NULL == engine_cfg)
 		mv_destroy_engine_config(working_cfg);
 }
 
-inline void convertRectCV2MV(const cv::Rect& src, mv_rectangle_s& dst)
+inline void convertRectCV2MV(const cv::Rect &src, mv_rectangle_s &dst)
 {
 	dst.point.x = src.x;
 	dst.point.y = src.y;
@@ -74,11 +67,8 @@ inline void convertRectCV2MV(const cv::Rect& src, mv_rectangle_s& dst)
 	dst.height = src.height;
 }
 
-int mv_face_detect_open(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_face_detected_cb detected_cb,
-		void *user_data)
+int mv_face_detect_open(mv_source_h source, mv_engine_config_h engine_cfg, mv_face_detected_cb detected_cb,
+						void *user_data)
 {
 	cv::Mat image;
 
@@ -91,17 +81,14 @@ int mv_face_detect_open(
 	/* default path */
 	cv::Size minSize(0, 0);
 	cv::Rect roi(-1, -1, -1, -1);
-	std::string haarcascadeFilePathStr =
-			"/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt2.xml";
+	std::string haarcascadeFilePathStr = "/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt2.xml";
 	if (engine_cfg) {
 		int minWidth, minHeight;
 
 		/* set face detection model */
 		char *haarcascadeFilepath;
-		error = mv_engine_config_get_string_attribute_c(
-				engine_cfg,
-				"MV_FACE_DETECTION_MODEL_FILE_PATH",
-				&haarcascadeFilepath);
+		error = mv_engine_config_get_string_attribute_c(engine_cfg, "MV_FACE_DETECTION_MODEL_FILE_PATH",
+														&haarcascadeFilepath);
 		if (error == MEDIA_VISION_ERROR_NONE) {
 			LOGI("Haarcascade file was set as default");
 			haarcascadeFilePathStr = std::string(haarcascadeFilepath);
@@ -110,61 +97,49 @@ int mv_face_detect_open(
 			haarcascadeFilepath = NULL;
 		} else {
 			LOGE("Error occurred during face detection haarcascade file receiving."
-				" (%i)", error);
+				 " (%i)",
+				 error);
 		}
 
 		/* Ser roi to be detected */
-		error = mv_engine_config_get_int_attribute_c(
-				engine_cfg,
-				MV_FACE_DETECTION_ROI_X,
-				&roi.x);
+		error = mv_engine_config_get_int_attribute_c(engine_cfg, MV_FACE_DETECTION_ROI_X, &roi.x);
 		if (error != MEDIA_VISION_ERROR_NONE)
 			LOGE("Error occurred during face detection roi (x) receiving."
-				" (%i)", error);
+				 " (%i)",
+				 error);
 
-		error = mv_engine_config_get_int_attribute_c(
-					engine_cfg,
-					MV_FACE_DETECTION_ROI_Y,
-					&roi.y);
+		error = mv_engine_config_get_int_attribute_c(engine_cfg, MV_FACE_DETECTION_ROI_Y, &roi.y);
 		if (error != MEDIA_VISION_ERROR_NONE)
 			LOGE("Error occurred during face detection roi (y) receiving."
-					" (%i)", error);
+				 " (%i)",
+				 error);
 
-		error = mv_engine_config_get_int_attribute_c(
-					engine_cfg,
-					MV_FACE_DETECTION_ROI_WIDTH,
-					&roi.width);
+		error = mv_engine_config_get_int_attribute_c(engine_cfg, MV_FACE_DETECTION_ROI_WIDTH, &roi.width);
 		if (error != MEDIA_VISION_ERROR_NONE)
 			LOGE("Error occurred during face detection roi (width) receiving."
-					" (%i)", error);
+				 " (%i)",
+				 error);
 
-		error = mv_engine_config_get_int_attribute_c(
-					engine_cfg,
-					MV_FACE_DETECTION_ROI_HEIGHT,
-					&roi.height);
+		error = mv_engine_config_get_int_attribute_c(engine_cfg, MV_FACE_DETECTION_ROI_HEIGHT, &roi.height);
 		if (error != MEDIA_VISION_ERROR_NONE)
 			LOGE("Error occurred during face detection roi (height) receiving."
-					" (%i)", error);
+				 " (%i)",
+				 error);
 
 		/* Set minimum size to be detected */
-		error = mv_engine_config_get_int_attribute_c(
-					engine_cfg,
-					MV_FACE_DETECTION_MIN_SIZE_WIDTH,
-					&minWidth);
+		error = mv_engine_config_get_int_attribute_c(engine_cfg, MV_FACE_DETECTION_MIN_SIZE_WIDTH, &minWidth);
 		if (error != MEDIA_VISION_ERROR_NONE)
 			LOGE("Error occurred during face detection minimum width receiving."
-					" (%i)", error);
+				 " (%i)",
+				 error);
 
-		error = mv_engine_config_get_int_attribute_c(
-					engine_cfg,
-					MV_FACE_DETECTION_MIN_SIZE_HEIGHT,
-					&minHeight);
+		error = mv_engine_config_get_int_attribute_c(engine_cfg, MV_FACE_DETECTION_MIN_SIZE_HEIGHT, &minHeight);
 		if (error != MEDIA_VISION_ERROR_NONE)
 			LOGE("Error occurred during face detection minimum height receiving."
-					" (%i)", error);
+				 " (%i)",
+				 error);
 
-		if (minWidth > 0 && minHeight > 0 &&
-			minWidth <= image.cols && minHeight <= image.rows) {
+		if (minWidth > 0 && minHeight > 0 && minWidth <= image.cols && minHeight <= image.rows) {
 			minSize.width = minWidth;
 			minSize.height = minHeight;
 		}
@@ -199,13 +174,9 @@ int mv_face_detect_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_face_recognize_open(
-		mv_source_h source,
-		mv_face_recognition_model_h recognition_model,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s *face_location,
-		mv_face_recognized_cb recognized_cb,
-		void *user_data)
+int mv_face_recognize_open(mv_source_h source, mv_face_recognition_model_h recognition_model,
+						   mv_engine_config_h engine_cfg, mv_rectangle_s *face_location,
+						   mv_face_recognized_cb recognized_cb, void *user_data)
 {
 	if (!source) {
 		LOGE("Can't recognize for the NULL Media Vision source handle");
@@ -214,7 +185,7 @@ int mv_face_recognize_open(
 
 	if (!recognized_cb) {
 		LOGE("Recognition failed. Can't output recognition results without "
-				"callback function");
+			 "callback function");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
@@ -223,7 +194,7 @@ int mv_face_recognize_open(
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	FaceRecognitionModel *pRecModel = static_cast<FaceRecognitionModel*>(recognition_model);
+	FaceRecognitionModel *pRecModel = static_cast<FaceRecognitionModel *>(recognition_model);
 
 	cv::Mat grayImage;
 	int ret = MediaVision::Common::convertSourceMV2GrayCV(source, grayImage);
@@ -257,14 +228,7 @@ int mv_face_recognize_open(
 	}
 
 	if (!results.mIsRecognized) {
-		recognized_cb(
-				source,
-				recognition_model,
-				engine_cfg,
-				NULL,
-				NULL,
-				0.0,
-				user_data);
+		recognized_cb(source, recognition_model, engine_cfg, NULL, NULL, 0.0, user_data);
 	} else {
 		mv_rectangle_s location;
 		location.point.x = results.mFaceLocation.x;
@@ -277,14 +241,8 @@ int mv_face_recognize_open(
 			location.point.y += face_location->point.y;
 		}
 
-		recognized_cb(
-				source,
-				recognition_model,
-				engine_cfg,
-				&location,
-				&(results.mFaceLabel),
-				results.mConfidence,
-				user_data);
+		recognized_cb(source, recognition_model, engine_cfg, &location, &(results.mFaceLabel), results.mConfidence,
+					  user_data);
 	}
 
 	LOGD("Face recognition is finished");
@@ -292,13 +250,8 @@ int mv_face_recognize_open(
 	return ret;
 }
 
-int mv_face_track_open(
-		mv_source_h source,
-		mv_face_tracking_model_h tracking_model,
-		mv_engine_config_h engine_cfg,
-		mv_face_tracked_cb tracked_cb,
-		bool /*do_learn*/,
-		void *user_data)
+int mv_face_track_open(mv_source_h source, mv_face_tracking_model_h tracking_model, mv_engine_config_h engine_cfg,
+					   mv_face_tracked_cb tracked_cb, bool /*do_learn*/, void *user_data)
 {
 	if (!source) {
 		LOGE("Can't track for the NULL Media Vision source handle");
@@ -307,7 +260,7 @@ int mv_face_track_open(
 
 	if (!tracked_cb) {
 		LOGE("Tracking failed. Can't output tracking results without "
-				"callback function");
+			 "callback function");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
@@ -316,8 +269,7 @@ int mv_face_track_open(
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	FaceTrackingModel *pTrackModel =
-			static_cast<FaceTrackingModel*>(tracking_model);
+	FaceTrackingModel *pTrackModel = static_cast<FaceTrackingModel *>(tracking_model);
 
 	cv::Mat grayImage;
 	int ret = MediaVision::Common::convertSourceMV2GrayCV(source, grayImage);
@@ -332,7 +284,7 @@ int mv_face_track_open(
 
 	if (MEDIA_VISION_ERROR_NONE != ret) {
 		LOGE("Tracking can't be performed. "
-				"Check that tracking model is prepared when tracking starts");
+			 "Check that tracking model is prepared when tracking starts");
 		return ret;
 	}
 
@@ -340,42 +292,24 @@ int mv_face_track_open(
 		mv_quadrangle_s predictedLocation;
 		predictedLocation.points[0].x = results.mFaceLocation.x;
 		predictedLocation.points[0].y = results.mFaceLocation.y;
-		predictedLocation.points[1].x =
-				results.mFaceLocation.x + results.mFaceLocation.width;
+		predictedLocation.points[1].x = results.mFaceLocation.x + results.mFaceLocation.width;
 		predictedLocation.points[1].y = results.mFaceLocation.y;
-		predictedLocation.points[2].x =
-				results.mFaceLocation.x + results.mFaceLocation.width;
-		predictedLocation.points[2].y =
-				results.mFaceLocation.y + results.mFaceLocation.height;
+		predictedLocation.points[2].x = results.mFaceLocation.x + results.mFaceLocation.width;
+		predictedLocation.points[2].y = results.mFaceLocation.y + results.mFaceLocation.height;
 		predictedLocation.points[3].x = results.mFaceLocation.x;
-		predictedLocation.points[3].y =
-				results.mFaceLocation.y + results.mFaceLocation.height;
-		tracked_cb(
-				source,
-				tracking_model,
-				engine_cfg,
-				&predictedLocation,
-				results.mConfidence,
-				user_data);
+		predictedLocation.points[3].y = results.mFaceLocation.y + results.mFaceLocation.height;
+		tracked_cb(source, tracking_model, engine_cfg, &predictedLocation, results.mConfidence, user_data);
 	} else {
-		tracked_cb(
-				source,
-				tracking_model,
-				engine_cfg,
-				NULL,
-				results.mConfidence,
-				user_data);
+		tracked_cb(source, tracking_model, engine_cfg, NULL, results.mConfidence, user_data);
 	}
 
 	return ret;
 }
 
-int mv_face_eye_condition_recognize_open(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s face_location,
-		mv_face_eye_condition_recognized_cb eye_condition_recognized_cb,
-		void *user_data)
+int mv_face_eye_condition_recognize_open(mv_source_h source, mv_engine_config_h engine_cfg,
+										 mv_rectangle_s face_location,
+										 mv_face_eye_condition_recognized_cb eye_condition_recognized_cb,
+										 void *user_data)
 {
 	cv::Mat image;
 
@@ -386,32 +320,22 @@ int mv_face_eye_condition_recognize_open(
 	}
 
 	mv_face_eye_condition_e eye_condition;
-	error = FaceEyeCondition::recognizeEyeCondition(
-									image,
-									face_location,
-									&eye_condition);
+	error = FaceEyeCondition::recognizeEyeCondition(image, face_location, &eye_condition);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		LOGE("eye contition recognition failed");
 		return error;
 	}
 
-	eye_condition_recognized_cb(
-				source,
-				engine_cfg,
-				face_location,
-				eye_condition,
-				user_data);
+	eye_condition_recognized_cb(source, engine_cfg, face_location, eye_condition, user_data);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_face_facial_expression_recognize_open(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s face_location,
-		mv_face_facial_expression_recognized_cb expression_recognized_cb,
-		void *user_data)
+int mv_face_facial_expression_recognize_open(mv_source_h source, mv_engine_config_h engine_cfg,
+											 mv_rectangle_s face_location,
+											 mv_face_facial_expression_recognized_cb expression_recognized_cb,
+											 void *user_data)
 {
 	cv::Mat image;
 
@@ -422,34 +346,26 @@ int mv_face_facial_expression_recognize_open(
 	}
 
 	mv_face_facial_expression_e expression;
-	error = FaceExpressionRecognizer::recognizeFaceExpression(
-					image, face_location, &expression);
+	error = FaceExpressionRecognizer::recognizeFaceExpression(image, face_location, &expression);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		LOGE("eye contition recognition failed");
 		return error;
 	}
 
-	expression_recognized_cb(
-				source,
-				engine_cfg,
-				face_location,
-				expression,
-				user_data);
+	expression_recognized_cb(source, engine_cfg, face_location, expression, user_data);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_face_recognition_model_create_open(
-		mv_face_recognition_model_h *recognition_model)
+int mv_face_recognition_model_create_open(mv_face_recognition_model_h *recognition_model)
 {
 	if (recognition_model == NULL) {
 		LOGE("Recognition model can't be created because handle pointer is NULL");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	(*recognition_model) =
-			static_cast<mv_face_recognition_model_h>(new (std::nothrow)FaceRecognitionModel());
+	(*recognition_model) = static_cast<mv_face_recognition_model_h>(new (std::nothrow) FaceRecognitionModel());
 
 	if (*recognition_model == NULL) {
 		LOGE("Failed to create media vision recognition model");
@@ -461,8 +377,7 @@ int mv_face_recognition_model_create_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_face_recognition_model_destroy_open(
-		mv_face_recognition_model_h recognition_model)
+int mv_face_recognition_model_destroy_open(mv_face_recognition_model_h recognition_model)
 {
 	if (!recognition_model) {
 		LOGE("Recognition model can't be destroyed because handle is NULL");
@@ -470,23 +385,21 @@ int mv_face_recognition_model_destroy_open(
 	}
 
 	LOGD("Destroying media vision recognition model [%p]", recognition_model);
-	delete static_cast<FaceRecognitionModel*>(recognition_model);
+	delete static_cast<FaceRecognitionModel *>(recognition_model);
 	LOGD("Media vision recognition model has been destroyed");
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_face_recognition_model_clone_open(
-		mv_face_recognition_model_h src,
-		mv_face_recognition_model_h *dst)
+int mv_face_recognition_model_clone_open(mv_face_recognition_model_h src, mv_face_recognition_model_h *dst)
 {
 	if (!src || !dst) {
 		LOGE("Can't clone recognition model. Both source and destination"
-				"recognition model handles has to be not NULL");
+			 "recognition model handles has to be not NULL");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	(*dst) = static_cast<mv_face_recognition_model_h>(new (std::nothrow)FaceRecognitionModel());
+	(*dst) = static_cast<mv_face_recognition_model_h>(new (std::nothrow) FaceRecognitionModel());
 
 	if (*dst == NULL) {
 		LOGE("Failed to create media vision recognition model");
@@ -495,8 +408,8 @@ int mv_face_recognition_model_clone_open(
 
 	LOGD("Recognition model [%p] has been created", *dst);
 
-	const FaceRecognitionModel *pSrcModel = static_cast<FaceRecognitionModel*>(src);
-	FaceRecognitionModel *pDstModel = static_cast<FaceRecognitionModel*>(*dst);
+	const FaceRecognitionModel *pSrcModel = static_cast<FaceRecognitionModel *>(src);
+	FaceRecognitionModel *pDstModel = static_cast<FaceRecognitionModel *>(*dst);
 
 	*pDstModel = *pSrcModel;
 
@@ -504,9 +417,7 @@ int mv_face_recognition_model_clone_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_face_recognition_model_save_open(
-		const char *file_name,
-		mv_face_recognition_model_h recognition_model)
+int mv_face_recognition_model_save_open(const char *file_name, mv_face_recognition_model_h recognition_model)
 {
 	if (!recognition_model) {
 		LOGE("Can't save recognition model to the file. Handle has to be not NULL");
@@ -518,7 +429,7 @@ int mv_face_recognition_model_save_open(
 		return MEDIA_VISION_ERROR_INVALID_PATH;
 	}
 
-	FaceRecognitionModel *pRecModel = static_cast<FaceRecognitionModel*>(recognition_model);
+	FaceRecognitionModel *pRecModel = static_cast<FaceRecognitionModel *>(recognition_model);
 	const int ret = pRecModel->save(std::string(file_name));
 
 	if (MEDIA_VISION_ERROR_NONE != ret) {
@@ -530,36 +441,32 @@ int mv_face_recognition_model_save_open(
 	return ret;
 }
 
-int mv_face_recognition_model_load_open(
-		const char *file_name,
-		mv_face_recognition_model_h *recognition_model)
+int mv_face_recognition_model_load_open(const char *file_name, mv_face_recognition_model_h *recognition_model)
 {
 	if (!recognition_model) {
 		LOGE("Can't load recognition model from the file. "
-				"Handle has to be not NULL");
+			 "Handle has to be not NULL");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
 	if (NULL == file_name) {
 		LOGE("Can't load recognition model from the file. "
-				"File name has to be specified");
+			 "File name has to be specified");
 		return MEDIA_VISION_ERROR_INVALID_PATH;
 	}
 
-	(*recognition_model) =
-		static_cast<mv_face_recognition_model_h>(new (std::nothrow)FaceRecognitionModel());
+	(*recognition_model) = static_cast<mv_face_recognition_model_h>(new (std::nothrow) FaceRecognitionModel());
 
 	if (*recognition_model == NULL) {
 		LOGE("Failed to create media vision recognition model");
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 	}
 
-	FaceRecognitionModel *pRecModel =
-			static_cast<FaceRecognitionModel*>(*recognition_model);
+	FaceRecognitionModel *pRecModel = static_cast<FaceRecognitionModel *>(*recognition_model);
 
 	if (!pRecModel) {
 		LOGE("Loading of the face recognition model from file failed. "
-				"Incorrect Media Vision Face recognition model handle is used");
+			 "Incorrect Media Vision Face recognition model handle is used");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
@@ -574,26 +481,22 @@ int mv_face_recognition_model_load_open(
 	return ret;
 }
 
-int mv_face_recognition_model_add_open(
-		const mv_source_h source,
-		mv_face_recognition_model_h recognition_model,
-		const mv_rectangle_s *example_location,
-		int face_label)
+int mv_face_recognition_model_add_open(const mv_source_h source, mv_face_recognition_model_h recognition_model,
+									   const mv_rectangle_s *example_location, int face_label)
 {
 	if (!source) {
 		LOGE("Can't add face image example for recognition model. "
-				"Media Vision source handle has to be not NULL");
+			 "Media Vision source handle has to be not NULL");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
 	if (!recognition_model) {
 		LOGE("Can't add face image example for recognition model. "
-				"Model handle has to be not NULL");
+			 "Model handle has to be not NULL");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	FaceRecognitionModel *pRecModel =
-			static_cast<FaceRecognitionModel*>(recognition_model);
+	FaceRecognitionModel *pRecModel = static_cast<FaceRecognitionModel *>(recognition_model);
 
 	cv::Mat image;
 	int ret = MediaVision::Common::convertSourceMV2GrayCV(source, image);
@@ -619,25 +522,21 @@ int mv_face_recognition_model_add_open(
 	}
 
 	LOGD("The face image example labeled %i has been added "
-			"to the Media Vision recognition model", face_label);
+		 "to the Media Vision recognition model",
+		 face_label);
 	return ret;
 }
 
-int mv_face_recognition_model_reset_open(
-		mv_face_recognition_model_h recognition_model,
-		const int *face_label)
+int mv_face_recognition_model_reset_open(mv_face_recognition_model_h recognition_model, const int *face_label)
 {
 	if (!recognition_model) {
 		LOGE("Can't reset positive examples for NULL recognition model");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	FaceRecognitionModel *pRecModel =
-			static_cast<FaceRecognitionModel*>(recognition_model);
+	FaceRecognitionModel *pRecModel = static_cast<FaceRecognitionModel *>(recognition_model);
 
-	int ret = (NULL != face_label ?
-				pRecModel->resetFaceExamples(*face_label) :
-				pRecModel->resetFaceExamples());
+	int ret = (NULL != face_label ? pRecModel->resetFaceExamples(*face_label) : pRecModel->resetFaceExamples());
 
 	if (MEDIA_VISION_ERROR_NONE != ret) {
 		LOGE("Error occurred when reset positive examples of the recognition model");
@@ -648,17 +547,14 @@ int mv_face_recognition_model_reset_open(
 	return ret;
 }
 
-int mv_face_recognition_model_learn_open(
-		mv_engine_config_h engine_cfg,
-		mv_face_recognition_model_h recognition_model)
+int mv_face_recognition_model_learn_open(mv_engine_config_h engine_cfg, mv_face_recognition_model_h recognition_model)
 {
 	if (!recognition_model) {
 		LOGE("Can't learn recognition model. Model handle has to be not NULL");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	FaceRecognitionModel *pRecModel =
-			static_cast<FaceRecognitionModel*>(recognition_model);
+	FaceRecognitionModel *pRecModel = static_cast<FaceRecognitionModel *>(recognition_model);
 
 	RecognitionParams recognitionParams;
 	extractRecognitionParams(engine_cfg, recognitionParams);
@@ -676,10 +572,8 @@ int mv_face_recognition_model_learn_open(
 	return ret;
 }
 
-int mv_face_recognition_model_query_labels_open(
-		mv_face_recognition_model_h recognition_model,
-		int **labels,
-		unsigned int *number_of_labels)
+int mv_face_recognition_model_query_labels_open(mv_face_recognition_model_h recognition_model, int **labels,
+												unsigned int *number_of_labels)
 {
 	if (!recognition_model) {
 		LOGE("Can't get list of labels for NULL recognition model");
@@ -688,19 +582,18 @@ int mv_face_recognition_model_query_labels_open(
 
 	if (NULL == labels || NULL == number_of_labels) {
 		LOGE("Can't get list of labels. labels and number_of_labels out "
-				"parameters both has to be not NULL.");
+			 "parameters both has to be not NULL.");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	FaceRecognitionModel *pRecModel =
-				static_cast<FaceRecognitionModel*>(recognition_model);
+	FaceRecognitionModel *pRecModel = static_cast<FaceRecognitionModel *>(recognition_model);
 
-	const std::set<int>& learnedLabels = pRecModel->getFaceLabels();
+	const std::set<int> &learnedLabels = pRecModel->getFaceLabels();
 	auto _number_of_labels = learnedLabels.size();
 	int *_pLabels = NULL;
 	if (_number_of_labels) {
-		_pLabels = (int*)malloc(sizeof(int) * (_number_of_labels));
-		if(_pLabels == NULL) {
+		_pLabels = (int *) malloc(sizeof(int) * (_number_of_labels));
+		if (_pLabels == NULL) {
 			LOGE("Fail to alloc memory for %zu labels", _number_of_labels);
 			return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 		}
@@ -715,16 +608,14 @@ int mv_face_recognition_model_query_labels_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_face_tracking_model_create_open(
-		mv_face_tracking_model_h *tracking_model)
+int mv_face_tracking_model_create_open(mv_face_tracking_model_h *tracking_model)
 {
 	if (tracking_model == NULL) {
 		LOGE("Tracking model can't be created because handle pointer is NULL");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	(*tracking_model) =
-			static_cast<mv_face_tracking_model_h>(new (std::nothrow)FaceTrackingModel());
+	(*tracking_model) = static_cast<mv_face_tracking_model_h>(new (std::nothrow) FaceTrackingModel());
 
 	if (*tracking_model == NULL) {
 		LOGE("Failed to create media vision tracking model");
@@ -736,8 +627,7 @@ int mv_face_tracking_model_create_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_face_tracking_model_destroy_open(
-		mv_face_tracking_model_h tracking_model)
+int mv_face_tracking_model_destroy_open(mv_face_tracking_model_h tracking_model)
 {
 	if (!tracking_model) {
 		LOGE("Tracking model can't be destroyed because handle is NULL");
@@ -745,17 +635,14 @@ int mv_face_tracking_model_destroy_open(
 	}
 
 	LOGD("Destroying media vision tracking model [%p]", tracking_model);
-	delete static_cast<FaceTrackingModel*>(tracking_model);
+	delete static_cast<FaceTrackingModel *>(tracking_model);
 	LOGD("Media vision tracking model has been destroyed");
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_face_tracking_model_prepare_open(
-		mv_face_tracking_model_h tracking_model,
-		mv_engine_config_h /*engine_cfg*/,
-		mv_source_h source,
-		mv_quadrangle_s *location)
+int mv_face_tracking_model_prepare_open(mv_face_tracking_model_h tracking_model, mv_engine_config_h /*engine_cfg*/,
+										mv_source_h source, mv_quadrangle_s *location)
 {
 	if (!tracking_model) {
 		LOGE("Can't prepare tracking model. Handle has to be not NULL");
@@ -764,12 +651,11 @@ int mv_face_tracking_model_prepare_open(
 
 	if (!source) {
 		LOGE("Can't prepare tracking model. "
-				"Media Vision source handle has to be not NULL");
+			 "Media Vision source handle has to be not NULL");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	FaceTrackingModel *pTrackModel =
-			static_cast<FaceTrackingModel*>(tracking_model);
+	FaceTrackingModel *pTrackModel = static_cast<FaceTrackingModel *>(tracking_model);
 
 	cv::Mat image;
 	int ret = MediaVision::Common::convertSourceMV2GrayCV(source, image);
@@ -810,17 +696,15 @@ int mv_face_tracking_model_prepare_open(
 	return ret;
 }
 
-int mv_face_tracking_model_clone_open(
-		mv_face_tracking_model_h src,
-		mv_face_tracking_model_h *dst)
+int mv_face_tracking_model_clone_open(mv_face_tracking_model_h src, mv_face_tracking_model_h *dst)
 {
 	if (!src || !dst) {
 		LOGE("Can't clone tracking model. Both source and destination"
-				"tracking model handles has to be not NULL");
+			 "tracking model handles has to be not NULL");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	(*dst) = static_cast<mv_face_tracking_model_h>(new (std::nothrow)FaceTrackingModel());
+	(*dst) = static_cast<mv_face_tracking_model_h>(new (std::nothrow) FaceTrackingModel());
 
 	if (*dst == NULL) {
 		LOGE("Failed to create media vision tracking model");
@@ -829,8 +713,8 @@ int mv_face_tracking_model_clone_open(
 
 	LOGD("Tracking model [%p] has been created", *dst);
 
-	const FaceTrackingModel *pSrcModel = static_cast<FaceTrackingModel*>(src);
-	FaceTrackingModel *pDstModel = static_cast<FaceTrackingModel*>(*dst);
+	const FaceTrackingModel *pSrcModel = static_cast<FaceTrackingModel *>(src);
+	FaceTrackingModel *pDstModel = static_cast<FaceTrackingModel *>(*dst);
 
 	*pDstModel = *pSrcModel;
 
@@ -839,23 +723,21 @@ int mv_face_tracking_model_clone_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_face_tracking_model_save_open(
-		const char *file_name,
-		mv_face_tracking_model_h tracking_model)
+int mv_face_tracking_model_save_open(const char *file_name, mv_face_tracking_model_h tracking_model)
 {
 	if (!tracking_model) {
 		LOGE("Can't save tracking model to the file. "
-				"Handle has to be not NULL");
+			 "Handle has to be not NULL");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
 	if (NULL == file_name) {
 		LOGE("Can't save tracking model to the file. "
-				"File name has to be specified");
+			 "File name has to be specified");
 		return MEDIA_VISION_ERROR_INVALID_PATH;
 	}
 
-	FaceTrackingModel *pTrackModel = static_cast<FaceTrackingModel*>(tracking_model);
+	FaceTrackingModel *pTrackModel = static_cast<FaceTrackingModel *>(tracking_model);
 
 	const int ret = pTrackModel->save(std::string(file_name));
 
@@ -869,36 +751,32 @@ int mv_face_tracking_model_save_open(
 	return ret;
 }
 
-int mv_face_tracking_model_load_open(
-		const char *file_name,
-		mv_face_tracking_model_h *tracking_model)
+int mv_face_tracking_model_load_open(const char *file_name, mv_face_tracking_model_h *tracking_model)
 {
 	if (!tracking_model) {
 		LOGE("Can't load tracking model from the file. "
-				"Handle has to be not NULL");
+			 "Handle has to be not NULL");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
 	if (NULL == file_name) {
 		LOGE("Can't load tracking model from the file. "
-				"File name has to be specified");
+			 "File name has to be specified");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	(*tracking_model) =
-		static_cast<mv_face_tracking_model_h>(new (std::nothrow)FaceTrackingModel());
+	(*tracking_model) = static_cast<mv_face_tracking_model_h>(new (std::nothrow) FaceTrackingModel());
 
 	if (*tracking_model == NULL) {
 		LOGE("Failed to create media vision tracking model");
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 	}
 
-	FaceTrackingModel *pTrackModel =
-			static_cast<FaceTrackingModel*>(*tracking_model);
+	FaceTrackingModel *pTrackModel = static_cast<FaceTrackingModel *>(*tracking_model);
 
 	if (!pTrackModel) {
 		LOGE("Loading of the face tracking model from file failed. "
-				"Incorrect Media Vision Face tracking model handle is used");
+			 "Incorrect Media Vision Face tracking model handle is used");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
@@ -906,7 +784,7 @@ int mv_face_tracking_model_load_open(
 
 	if (MEDIA_VISION_ERROR_NONE != ret) {
 		LOGE("Error occurred when load tracking model from the file");
-		delete static_cast<FaceTrackingModel*>(*tracking_model);
+		delete static_cast<FaceTrackingModel *>(*tracking_model);
 		*tracking_model = NULL;
 
 		return ret;
diff --git a/mv_image/image/include/Features/BasicExtractorFactory.h b/mv_image/image/include/Features/BasicExtractorFactory.h
index ca65f4f..8cfa99d 100644
--- a/mv_image/image/include/Features/BasicExtractorFactory.h
+++ b/mv_image/image/include/Features/BasicExtractorFactory.h
@@ -19,10 +19,12 @@
 
 #include "Features/FeatureExtractorFactory.h"
 
-namespace MediaVision {
-namespace Image {
-
-class BasicExtractorFactory : public FeatureExtractorFactory {
+namespace MediaVision
+{
+namespace Image
+{
+class BasicExtractorFactory : public FeatureExtractorFactory
+{
 public:
 	BasicExtractorFactory(KeypointType keypointsType, DescriptorType descType);
 
diff --git a/mv_image/image/include/Features/FeatureExtractor.h b/mv_image/image/include/Features/FeatureExtractor.h
index f2f6e5e..5642c3e 100644
--- a/mv_image/image/include/Features/FeatureExtractor.h
+++ b/mv_image/image/include/Features/FeatureExtractor.h
@@ -21,35 +21,29 @@
 
 #include "Features/FeaturePack.h"
 
-namespace MediaVision {
-namespace Image {
+namespace MediaVision
+{
+namespace Image
+{
 /**
  * @class FeatureExtractor
  * @brief Class contains functionality to extract features from an image
  *
  * @since_tizen 3.0
  */
-class FeatureExtractor {
+class FeatureExtractor
+{
 public:
 	FeatureExtractor();
 
-	void setFeatureDetector(
-			const cv::Ptr<cv::FeatureDetector> detector,
-			KeypointType keypointType);
+	void setFeatureDetector(const cv::Ptr<cv::FeatureDetector> detector, KeypointType keypointType);
 
-	void setDescriptorExtractor(
-			cv::Ptr<cv::DescriptorExtractor> extractor,
-			DescriptorType descriptorType);
+	void setDescriptorExtractor(cv::Ptr<cv::DescriptorExtractor> extractor, DescriptorType descriptorType);
 
-	void setRecognitionRateMetric(
-			float (*computeRecognitionRate)(
-					const cv::Mat&,
-					const std::vector<cv::KeyPoint>&));
+	void setRecognitionRateMetric(float (*computeRecognitionRate)(const cv::Mat &, const std::vector<cv::KeyPoint> &));
 
-	bool extract(
-			const cv::Mat& image,
-			FeaturePack& result,
-			const std::vector<cv::Point2f>& roi = std::vector<cv::Point2f>());
+	bool extract(const cv::Mat &image, FeaturePack &result,
+				 const std::vector<cv::Point2f> &roi = std::vector<cv::Point2f>());
 
 private:
 	static const cv::Size __MIN_SIZE;
@@ -63,9 +57,7 @@ private:
 
 	cv::Ptr<cv::DescriptorExtractor> __extractor;
 
-	float (*__computeRecognitionRate)(
-			const cv::Mat&,
-			const std::vector<cv::KeyPoint>&);
+	float (*__computeRecognitionRate)(const cv::Mat &, const std::vector<cv::KeyPoint> &);
 };
 
 } /* Image */
diff --git a/mv_image/image/include/Features/FeatureExtractorFactory.h b/mv_image/image/include/Features/FeatureExtractorFactory.h
index 1477292..fb21df5 100644
--- a/mv_image/image/include/Features/FeatureExtractorFactory.h
+++ b/mv_image/image/include/Features/FeatureExtractorFactory.h
@@ -21,10 +21,12 @@
 
 #include <opencv2/core.hpp>
 
-namespace MediaVision {
-namespace Image {
-
-class FeatureExtractorFactory {
+namespace MediaVision
+{
+namespace Image
+{
+class FeatureExtractorFactory
+{
 public:
 	virtual ~FeatureExtractorFactory();
 
diff --git a/mv_image/image/include/Features/FeatureMatcher.h b/mv_image/image/include/Features/FeatureMatcher.h
index 971e7f9..831938a 100644
--- a/mv_image/image/include/Features/FeatureMatcher.h
+++ b/mv_image/image/include/Features/FeatureMatcher.h
@@ -19,12 +19,15 @@
 
 #include "Features/FeaturePack.h"
 
-namespace MediaVision {
-namespace Image {
-
-class FeatureMatcher {
+namespace MediaVision
+{
+namespace Image
+{
+class FeatureMatcher
+{
 public:
-	enum MatchError {
+	enum MatchError
+	{
 		InvalidFeaturePackFrom,
 		InvalidFeaturePackTo,
 		DisparateTypes,
@@ -33,15 +36,9 @@ public:
 	};
 
 public:
-	FeatureMatcher(
-			float affectingPart = 1.f,
-			float tolerantError = 0.f,
-			size_t minimumMatchesNumber = 0u);
-
-	MatchError match(
-			const FeaturePack& from,
-			const FeaturePack& to,
-			cv::Mat& homophraphyMatrix) const;
+	FeatureMatcher(float affectingPart = 1.f, float tolerantError = 0.f, size_t minimumMatchesNumber = 0u);
+
+	MatchError match(const FeaturePack &from, const FeaturePack &to, cv::Mat &homophraphyMatrix) const;
 
 	float getAffectingPart() const;
 
diff --git a/mv_image/image/include/Features/FeaturePack.h b/mv_image/image/include/Features/FeaturePack.h
index 422de0b..746dac6 100644
--- a/mv_image/image/include/Features/FeaturePack.h
+++ b/mv_image/image/include/Features/FeaturePack.h
@@ -27,8 +27,10 @@
 #include <opencv2/xfeatures2d.hpp>
 #include <opencv2/calib3d.hpp>
 
-namespace MediaVision {
-namespace Image {
+namespace MediaVision
+{
+namespace Image
+{
 /**
  * @class    FeaturePack
  * @brief    This class contains information about features and can be used for
@@ -36,7 +38,8 @@ namespace Image {
  *
  * @since_tizen 3.0
  */
-class FeaturePack {
+class FeaturePack
+{
 public:
 	/**
 	 * @brief   @ref FeaturePack default constructor.
@@ -52,7 +55,7 @@ public:
 	 * @since_tizen 3.0
 	 * @param   [in] copy @ref FeaturePack which will be copied
 	 */
-	FeaturePack(const FeaturePack& copy);
+	FeaturePack(const FeaturePack &copy);
 
 	/**
 	 * @brief   @ref FeaturePack copy assignment operator.
@@ -61,7 +64,7 @@ public:
 	 * @since_tizen 3.0
 	 * @param   [in] copy @ref FeaturePack which will be copied
 	 */
-	FeaturePack& operator= (const FeaturePack& copy);
+	FeaturePack &operator=(const FeaturePack &copy);
 
 	KeypointType __keypointsType;
 
diff --git a/mv_image/image/include/Features/ORBExtractorFactory.h b/mv_image/image/include/Features/ORBExtractorFactory.h
index 335c04b..888619e 100644
--- a/mv_image/image/include/Features/ORBExtractorFactory.h
+++ b/mv_image/image/include/Features/ORBExtractorFactory.h
@@ -19,14 +19,14 @@
 
 #include "Features/FeatureExtractorFactory.h"
 
-namespace MediaVision {
-namespace Image {
-
-class ORBExtractorFactory : public FeatureExtractorFactory {
+namespace MediaVision
+{
+namespace Image
+{
+class ORBExtractorFactory : public FeatureExtractorFactory
+{
 public:
-	ORBExtractorFactory(
-			float scaleFactor = 1.2f,
-			size_t maximumFeaturesNumber = 800u);
+	ORBExtractorFactory(float scaleFactor = 1.2f, size_t maximumFeaturesNumber = 800u);
 
 	virtual cv::Ptr<FeatureExtractor> buildFeatureExtractor();
 
@@ -39,9 +39,7 @@ public:
 	void setMaximumFeaturesNumber(size_t maximumFeaturesNumber);
 
 private:
-	static float computeRecognitionRate(
-			const cv::Mat&,
-			const std::vector<cv::KeyPoint>&);
+	static float computeRecognitionRate(const cv::Mat &, const std::vector<cv::KeyPoint> &);
 
 	float __scaleFactor; /**< Recognition scale factor for the ORB detector. */
 
diff --git a/mv_image/image/include/ImageConfig.h b/mv_image/image/include/ImageConfig.h
index a29806b..0581a49 100644
--- a/mv_image/image/include/ImageConfig.h
+++ b/mv_image/image/include/ImageConfig.h
@@ -24,42 +24,40 @@
  * @brief This file contains Image Module configuration.
  */
 
-namespace MediaVision {
-namespace Image {
+namespace MediaVision
+{
+namespace Image
+{
 /**
  * @brief Keypoint's type enumeration.
  *
  * @since_tizen 3.0
  */
-enum KeypointType {
-	KT_INVALID = -1,  /**< Undefined keypoint's type */
-	KT_ORB,           /**< Oriented FAST keypoint's type */
-	KT_GFTT,          /**< Keypoint's type of good features to track */
-	KT_SIZE           /**< Number of keypoint's types */
+enum KeypointType
+{
+	KT_INVALID = -1, /**< Undefined keypoint's type */
+	KT_ORB, /**< Oriented FAST keypoint's type */
+	KT_GFTT, /**< Keypoint's type of good features to track */
+	KT_SIZE /**< Number of keypoint's types */
 };
 
-const std::string KeypointNames[KT_SIZE] = {
-	[KT_ORB] = "ORB",
-	[KT_GFTT] = "GFTT"
-};
+const std::string KeypointNames[KT_SIZE] = { [KT_ORB] = "ORB", [KT_GFTT] = "GFTT" };
 
 /*
  * @brief Descriptor's type enumeration.
  *
  * @since_tizen 3.0
  */
-enum DescriptorType {
-	DT_INVALID = -1,  /**< Undefined descriptor's type */
-	DT_ORB,           /**< Rotated BRIEF descriptor's type */
-	DT_BRIEF,         /**< Descriptor's type of binary robust independent
+enum DescriptorType
+{
+	DT_INVALID = -1, /**< Undefined descriptor's type */
+	DT_ORB, /**< Rotated BRIEF descriptor's type */
+	DT_BRIEF, /**< Descriptor's type of binary robust independent
 							elementary features */
-	DT_SIZE           /**< Number of descriptor's types */
+	DT_SIZE /**< Number of descriptor's types */
 };
 
-const std::string DescriptorNames[DT_SIZE] = {
-	[DT_ORB] = "ORB",
-	[DT_BRIEF] = "BRIEF"
-};
+const std::string DescriptorNames[DT_SIZE] = { [DT_ORB] = "ORB", [DT_BRIEF] = "BRIEF" };
 
 /**
  * @class FeaturesExtractingParams
@@ -67,15 +65,18 @@ const std::string DescriptorNames[DT_SIZE] = {
  *
  * @since_tizen 3.0
  */
-struct FeaturesExtractingParams {
+struct FeaturesExtractingParams
+{
 	FeaturesExtractingParams();
 
 	KeypointType mKeypointType; /**< Keypoint's type. */
 
 	DescriptorType mDescriptorType; /**< Descriptor's type. */
 
-	union { /**< Extracting parameters for concretes algorithms. */
-		struct { /**< Extracting parameters for ORB algorithm. */
+	union
+	{ /**< Extracting parameters for concretes algorithms. */
+		struct
+		{ /**< Extracting parameters for ORB algorithm. */
 			double mScaleFactor; /**< Recognition scale factor for the ORB detector. */
 			int mMaximumFeaturesNumber; /**< Maximum number of features,
 									which will be extracted from object image.*/
@@ -89,11 +90,9 @@ struct FeaturesExtractingParams {
  *
  * @since_tizen 3.0
  */
-struct RecognitionParams {
-	RecognitionParams(
-			int minMatchesNumber,
-			double requiredMatchesPart,
-			double tolerantMatchesPartError);
+struct RecognitionParams
+{
+	RecognitionParams(int minMatchesNumber, double requiredMatchesPart, double tolerantMatchesPartError);
 
 	RecognitionParams();
 
@@ -115,14 +114,10 @@ struct RecognitionParams {
  *
  * @since_tizen 3.0
  */
-struct StabilizationParams {
-	StabilizationParams(
-			bool isEnabled,
-			size_t historyAmount,
-			double tolerantShift,
-			double tolerantShiftExtra,
-			double stabilizationSpeed,
-			double stabilizationAcceleration);
+struct StabilizationParams
+{
+	StabilizationParams(bool isEnabled, size_t historyAmount, double tolerantShift, double tolerantShiftExtra,
+						double stabilizationSpeed, double stabilizationAcceleration);
 
 	StabilizationParams();
 
@@ -156,12 +151,10 @@ struct StabilizationParams {
  *
  * @since_tizen 3.0
  */
-struct TrackingParams {
-	TrackingParams(
-			FeaturesExtractingParams framesFeaturesExtractingParams,
-			RecognitionParams recognitionParams,
-			StabilizationParams stabilizationParams,
-			double expectedOffset);
+struct TrackingParams
+{
+	TrackingParams(FeaturesExtractingParams framesFeaturesExtractingParams, RecognitionParams recognitionParams,
+				   StabilizationParams stabilizationParams, double expectedOffset);
 
 	TrackingParams();
 
diff --git a/mv_image/image/include/ImageMathUtil.h b/mv_image/image/include/ImageMathUtil.h
index bd49674..ae75205 100644
--- a/mv_image/image/include/ImageMathUtil.h
+++ b/mv_image/image/include/ImageMathUtil.h
@@ -24,9 +24,10 @@
  * @brief This file contains math utility for Image Module.
  */
 
-namespace MediaVision {
-namespace Image {
-
+namespace MediaVision
+{
+namespace Image
+{
 const size_t MinimumNumberOfFeatures = 4u; /* Minimum number of features
 											when perspective transform
 											parameters calculation
@@ -42,9 +43,7 @@ const size_t NumberOfQuadrangleCorners = 4u; /* Number of quadrangle corneres */
  * @param [in] point2   The second point
  * @return distance between two points
  */
-float getDistance(
-		const cv::Point2f& point1,
-		const cv::Point2f& point2);
+float getDistance(const cv::Point2f &point1, const cv::Point2f &point2);
 
 /**
  * @brief   Calculates area of triangle.
@@ -55,10 +54,7 @@ float getDistance(
  * @param [in] point3   The third corner of triangle
  * @return area of triangle
  */
-float getTriangleArea(
-		const cv::Point2f& point1,
-		const cv::Point2f& point2,
-		const cv::Point2f& point3);
+float getTriangleArea(const cv::Point2f &point1, const cv::Point2f &point2, const cv::Point2f &point3);
 
 /**
  * @brief   Calculates area of quadrangle.
@@ -67,8 +63,7 @@ float getTriangleArea(
  * @param [in] points   Four corners of quadrangle
  * @return area of quadrangle
  */
-float getQuadrangleArea(
-		const cv::Point2f points[NumberOfQuadrangleCorners]);
+float getQuadrangleArea(const cv::Point2f points[NumberOfQuadrangleCorners]);
 
 /**
  * @brief   Checks point on the accessory region.
@@ -78,9 +73,7 @@ float getQuadrangleArea(
  * @param [in] region  Contour of region
  * @return true if point is inside the region, otherwise return false
  */
-bool checkAccessory(
-		const cv::Point2f& point,
-		const std::vector<cv::Point2f>& region);
+bool checkAccessory(const cv::Point2f &point, const std::vector<cv::Point2f> &region);
 
 /**
  * @brief   Cuts a rectangle according to the maximum size.
@@ -91,7 +84,7 @@ bool checkAccessory(
  * @param [in] rectange   Rectangle which will be cut
  * @param [in] maxSize    Maximum values of needed rectangle
  */
-void catRect(cv::Rect& rectange, const cv::Size& maxSize);
+void catRect(cv::Rect &rectange, const cv::Size &maxSize);
 
 /**
  * @brief   Resizes a region.
@@ -100,9 +93,7 @@ void catRect(cv::Rect& rectange, const cv::Size& maxSize);
  * @param [in] roi                  Contour of region which will be resized
  * @param [in] scalingCoefficient   Scaling coefficient
  */
-std::vector<cv::Point2f> contourResize(
-		const std::vector<cv::Point2f>& roi,
-		float scalingCoefficient);
+std::vector<cv::Point2f> contourResize(const std::vector<cv::Point2f> &roi, float scalingCoefficient);
 
 } /* Image */
 } /* MediaVision */
diff --git a/mv_image/image/include/Recognition/ImageObject.h b/mv_image/image/include/Recognition/ImageObject.h
index 35d33e2..bae3421 100644
--- a/mv_image/image/include/Recognition/ImageObject.h
+++ b/mv_image/image/include/Recognition/ImageObject.h
@@ -26,8 +26,10 @@
  * @brief This file contains the @ref ImageObject class.
  */
 
-namespace MediaVision {
-namespace Image {
+namespace MediaVision
+{
+namespace Image
+{
 /**
  * @class    ImageObject
  * @brief    This class contains the image information, which will
@@ -35,7 +37,8 @@ namespace Image {
  *
  * @since_tizen 3.0
  */
-class ImageObject {
+class ImageObject
+{
 public:
 	/**
 	 * @brief   @ref ImageObject default constructor.
@@ -54,7 +57,7 @@ public:
 	 *                      will be created
 	 * @param [in] params   Features extracting parameters
 	 */
-	ImageObject(const cv::Mat& image, const FeaturesExtractingParams& params);
+	ImageObject(const cv::Mat &image, const FeaturesExtractingParams &params);
 
 	/**
 	 * @brief   @ref ImageObject copy constructor.
@@ -63,7 +66,7 @@ public:
 	 * @since_tizen 3.0
 	 * @param   [in] copy @ref ImageObject which will be copied
 	 */
-	ImageObject(const ImageObject& copy);
+	ImageObject(const ImageObject &copy);
 
 	/**
 	 * @brief   @ref ImageObject copy assignment operator.
@@ -73,7 +76,7 @@ public:
 	 * @param   [in] copy @ref ImageObject which will be copied
 	 *
 	 */
-	ImageObject& operator=(const ImageObject& copy);
+	ImageObject &operator=(const ImageObject &copy);
 
 	/**
 	 * @brief   @ref ImageObject destructor.
@@ -93,10 +96,8 @@ public:
 	 * @param [in] params        Features extracting parameters
 	 * @param [in] roi           Region of interested object on the @a image
 	 */
-	void fill(
-			const cv::Mat& image,
-			const FeaturesExtractingParams& params,
-			const std::vector<cv::Point2f>& roi = std::vector<cv::Point2f>());
+	void fill(const cv::Mat &image, const FeaturesExtractingParams &params,
+			  const std::vector<cv::Point2f> &roi = std::vector<cv::Point2f>());
 
 	/**
 	 * @brief Gets a value that determines how well an @ref ImageObject can be recognized.
@@ -127,7 +128,7 @@ public:
 	 * @since_tizen 3.0
 	 * @param [in] contour  The contour which will be used with @ref ImageObject
 	 */
-	void setContour(const std::vector<cv::Point2f>& contour);
+	void setContour(const std::vector<cv::Point2f> &contour);
 
 	/**
 	 * @brief Sets a label for the image object.
@@ -144,7 +145,7 @@ public:
 	 * @param [out] label   The label of image object
 	 * @return @c true if object is labeled, otherwise return @c false
 	 */
-	bool getLabel(int& label) const;
+	bool getLabel(int &label) const;
 
 	/**
 	 * @brief  Stores the @ref ImageObject in a file.
@@ -165,10 +166,8 @@ public:
 	int load(const char *fileName);
 
 private:
-	void extractFeatures(
-			const cv::Mat& image,
-			const FeaturesExtractingParams& params,
-			const std::vector<cv::Point2f>& roi);
+	void extractFeatures(const cv::Mat &image, const FeaturesExtractingParams &params,
+						 const std::vector<cv::Point2f> &roi);
 
 private:
 	FeaturesExtractingParams __featureExtractingParams;
@@ -185,9 +184,9 @@ private:
 
 	friend class ImageRecognizer;
 
-	friend std::ostream& operator << (std::ostream& os, const ImageObject& obj);
+	friend std::ostream &operator<<(std::ostream &os, const ImageObject &obj);
 
-	friend std::istream& operator >> (std::istream& is, ImageObject& obj);
+	friend std::istream &operator>>(std::istream &is, ImageObject &obj);
 };
 
 } /* Image */
diff --git a/mv_image/image/include/Recognition/ImageRecognizer.h b/mv_image/image/include/Recognition/ImageRecognizer.h
index 5ac2f2e..a549e16 100644
--- a/mv_image/image/include/Recognition/ImageRecognizer.h
+++ b/mv_image/image/include/Recognition/ImageRecognizer.h
@@ -29,15 +29,18 @@
  * @brief This file contains functionality for image object recognition.
  */
 
-namespace MediaVision {
-namespace Image {
+namespace MediaVision
+{
+namespace Image
+{
 /**
  * @class    ImageRecognizer
  * @brief    This class contains functionality for image object recognition.
  *
  * @since_tizen 3.0
  */
-class ImageRecognizer {
+class ImageRecognizer
+{
 public:
 	/**
 	 * @brief   @ref ImageRecognizer constructor based on the scene @ref ImageObject.
@@ -46,7 +49,7 @@ public:
 	 * @param [in] scene   The scene for which the objects will be recognized by
 	 *                     calling method recognize()
 	 */
-	ImageRecognizer(const ImageObject& scene);
+	ImageRecognizer(const ImageObject &scene);
 
 	/**
 	 * @brief   @ref ImageRecognizer destructor.
@@ -67,31 +70,22 @@ public:
 	 *                             of object which will be ignored
 	 * @return true if object is found on the scene, otherwise return false
 	 */
-	bool recognize(
-			const ImageObject& target,
-			const RecognitionParams& params,
-			std::vector<cv::Point2f>& contour,
-			float ignoreFactor = 0.f) const;
+	bool recognize(const ImageObject &target, const RecognitionParams &params, std::vector<cv::Point2f> &contour,
+				   float ignoreFactor = 0.f) const;
 
 private:
 	ImageRecognizer();
 
-	bool findHomophraphyMatrix(
-			const ImageObject& target,
-			const RecognitionParams& params,
-			cv::Mat& homophraphyMatrix,
-			float ignoreFactor) const;
+	bool findHomophraphyMatrix(const ImageObject &target, const RecognitionParams &params, cv::Mat &homophraphyMatrix,
+							   float ignoreFactor) const;
 
-	size_t matchesSelection(
-			std::vector<cv::DMatch>& examples,
-			unsigned int filterAmount, unsigned int allowableError) const;
+	size_t matchesSelection(std::vector<cv::DMatch> &examples, unsigned int filterAmount,
+							unsigned int allowableError) const;
 
-	float computeLinearSupportElement(
-			const std::vector<cv::DMatch>& examples,
-			int requiredNumber, int leftLimit, int rightLimit) const;
+	float computeLinearSupportElement(const std::vector<cv::DMatch> &examples, int requiredNumber, int leftLimit,
+									  int rightLimit) const;
 
-	static bool isPossibleQuadrangleCorners(
-			const cv::Point2f corners[NumberOfQuadrangleCorners]);
+	static bool isPossibleQuadrangleCorners(const cv::Point2f corners[NumberOfQuadrangleCorners]);
 
 private:
 	/* TODO: Replace to cv::Ptr<ImageObject> */
diff --git a/mv_image/image/include/Tracking/AsyncTracker.h b/mv_image/image/include/Tracking/AsyncTracker.h
index a84fa57..174f28a 100644
--- a/mv_image/image/include/Tracking/AsyncTracker.h
+++ b/mv_image/image/include/Tracking/AsyncTracker.h
@@ -21,8 +21,10 @@
 
 #include <pthread.h>
 
-namespace MediaVision {
-namespace Image {
+namespace MediaVision
+{
+namespace Image
+{
 /**
  * @class    AsyncTracker
  * @brief    Tracker is based on the another tracker and extends the
@@ -30,7 +32,8 @@ namespace Image {
  *
  * @since_tizen 3.0
  */
-class AsyncTracker : public ObjectTracker {
+class AsyncTracker : public ObjectTracker
+{
 public:
 	/**
 	 * @brief @ref AsyncTracker copy constructor.
@@ -38,7 +41,7 @@ public:
 	 * @since_tizen 3.0
 	 * @param   [in] copy @ref AsyncTracker which will be copied
 	 */
-	AsyncTracker(const AsyncTracker& copy);
+	AsyncTracker(const AsyncTracker &copy);
 
 	/**
 	 * @brief @ref AsyncTracker constructor based on the another tracker.
@@ -68,7 +71,7 @@ public:
 	 * @param [out]  result   Result contour
 	 * @return true if object is tracked, otherwise return false
 	 */
-	virtual bool track(const cv::Mat& frame, std::vector<cv::Point>& result);
+	virtual bool track(const cv::Mat &frame, std::vector<cv::Point> &result);
 
 	/**
 	 * @brief Provides the current location of a target.
@@ -76,7 +79,7 @@ public:
 	 * @since_tizen 3.0
 	 * @param [in] location  Current location of a target
 	 */
-	virtual void reinforcement(const std::vector<cv::Point>& location);
+	virtual void reinforcement(const std::vector<cv::Point> &location);
 
 	/*
 	 * @brief Creates a copy of itself
@@ -90,14 +93,14 @@ public:
 
 	bool isRun();
 
-	bool isUpdated(std::vector<cv::Point>& result);
+	bool isUpdated(std::vector<cv::Point> &result);
 
-	bool getResult(std::vector<cv::Point>& location);
+	bool getResult(std::vector<cv::Point> &location);
 
 private:
-	AsyncTracker& operator= (const AsyncTracker& copy);
+	AsyncTracker &operator=(const AsyncTracker &copy);
 
-	bool baseTrack(std::vector<cv::Point>& result);
+	bool baseTrack(std::vector<cv::Point> &result);
 
 	static void *asyncTrack(void *data);
 
diff --git a/mv_image/image/include/Tracking/CascadeTracker.h b/mv_image/image/include/Tracking/CascadeTracker.h
index 09a9d08..d83dc6d 100644
--- a/mv_image/image/include/Tracking/CascadeTracker.h
+++ b/mv_image/image/include/Tracking/CascadeTracker.h
@@ -23,15 +23,18 @@
 
 #include <set>
 
-namespace MediaVision {
-namespace Image {
+namespace MediaVision
+{
+namespace Image
+{
 /**
  * @class    CascadeTracker
  * @brief    Tracker is based on the another trackers and combines the results.
  *
  * @since_tizen 3.0
  */
-class CascadeTracker : public ObjectTracker {
+class CascadeTracker : public ObjectTracker
+{
 public:
 	/**
 	 * @brief @ref CascadeTracker default constructor
@@ -47,7 +50,7 @@ public:
 	 * @since_tizen 3.0
 	 * @param   [in] copy @ref CascadeTracker which will be copied
 	 */
-	CascadeTracker(const CascadeTracker& copy);
+	CascadeTracker(const CascadeTracker &copy);
 
 	/**
 	 * @brief @ref CascadeTracker destructor
@@ -65,7 +68,7 @@ public:
 	 * @param [out]  result   Result contour
 	 * @return true if object is tracked, otherwise return false
 	 */
-	virtual bool track(const cv::Mat& frame, std::vector<cv::Point>& result);
+	virtual bool track(const cv::Mat &frame, std::vector<cv::Point> &result);
 
 	/**
 	 * @brief Provides the current location of a target.
@@ -73,7 +76,7 @@ public:
 	 * @since_tizen 3.0
 	 * @param [in] location  Current location of a target
 	 */
-	virtual void reinforcement(const std::vector<cv::Point>& location);
+	virtual void reinforcement(const std::vector<cv::Point> &location);
 
 	/*
 	 * @brief Creates a copy of itself
@@ -90,7 +93,7 @@ public:
 	 * @param [in] copy @ref CascadeTracker which will be copied
 	 * @return itself
 	 */
-	virtual CascadeTracker& operator=(const CascadeTracker& copy);
+	virtual CascadeTracker &operator=(const CascadeTracker &copy);
 
 	bool enableTracker(cv::Ptr<ObjectTracker> tracker, float priority);
 
@@ -99,17 +102,18 @@ public:
 private:
 	void internalReinforcement();
 
-	bool mergeResults(std::vector<cv::Point>& result) const;
+	bool mergeResults(std::vector<cv::Point> &result) const;
 
 private:
-	struct TrackerInfo {
+	struct TrackerInfo
+	{
 		TrackerInfo(cv::Ptr<ObjectTracker>, float);
 
-		bool operator<(const TrackerInfo&) const;
+		bool operator<(const TrackerInfo &) const;
 
-		bool operator==(const TrackerInfo&) const;
+		bool operator==(const TrackerInfo &) const;
 
-		bool operator!=(const TrackerInfo&) const;
+		bool operator!=(const TrackerInfo &) const;
 
 		cv::Ptr<ObjectTracker> mTracker;
 
diff --git a/mv_image/image/include/Tracking/FeatureSubstitutionTracker.h b/mv_image/image/include/Tracking/FeatureSubstitutionTracker.h
index 29ec6b1..222bc6a 100644
--- a/mv_image/image/include/Tracking/FeatureSubstitutionTracker.h
+++ b/mv_image/image/include/Tracking/FeatureSubstitutionTracker.h
@@ -21,15 +21,18 @@
 
 #include "Recognition/ImageObject.h"
 
-namespace MediaVision {
-namespace Image {
+namespace MediaVision
+{
+namespace Image
+{
 /**
  * @class    FeatureSubstitutionTracker
  * @brief    Tracker uses feature substitution.
  *
  * @since_tizen 3.0
  */
-class FeatureSubstitutionTracker : public ObjectTracker {
+class FeatureSubstitutionTracker : public ObjectTracker
+{
 public:
 	/**
 	 * @brief @ref FeatureSubstitutionTracker constructor.
@@ -47,12 +50,9 @@ public:
 	 *                                        recognition
 	 *                                        (recommended value is 0.5 - 1)
 	 */
-	FeatureSubstitutionTracker(
-			const FeaturesExtractingParams& featuresExtractingParams,
-			const RecognitionParams& recognitionParams,
-			float expectedOffset,
-			float sceneScalingFactor = 1.2f,
-			float objectScalingFactor = 0.85f);
+	FeatureSubstitutionTracker(const FeaturesExtractingParams &featuresExtractingParams,
+							   const RecognitionParams &recognitionParams, float expectedOffset,
+							   float sceneScalingFactor = 1.2f, float objectScalingFactor = 0.85f);
 
 	/**
 	 * @brief Tracks the target for the video stream consisting of frames.
@@ -63,7 +63,7 @@ public:
 	 * @param [out]  result   Result contour
 	 * @return true if object is tracked, otherwise return false
 	 */
-	virtual bool track(const cv::Mat& frame, std::vector<cv::Point>& result);
+	virtual bool track(const cv::Mat &frame, std::vector<cv::Point> &result);
 
 	/**
 	 * @brief Provides the current location of a target.
@@ -71,7 +71,7 @@ public:
 	 * @since_tizen 3.0
 	 * @param [in] location  Current location of a target
 	 */
-	virtual void reinforcement(const std::vector<cv::Point>& location);
+	virtual void reinforcement(const std::vector<cv::Point> &location);
 
 	/*
 	 * @brief Creates a copy of itself
diff --git a/mv_image/image/include/Tracking/ImageContourStabilizator.h b/mv_image/image/include/Tracking/ImageContourStabilizator.h
index 4b0b224..88306db 100644
--- a/mv_image/image/include/Tracking/ImageContourStabilizator.h
+++ b/mv_image/image/include/Tracking/ImageContourStabilizator.h
@@ -26,8 +26,10 @@
  *        during tracking.
  */
 
-namespace MediaVision {
-namespace Image {
+namespace MediaVision
+{
+namespace Image
+{
 /**
  * @class    ImageContourStabilizator
  * @brief    This class contains functionality for image contour stabilization
@@ -35,20 +37,22 @@ namespace Image {
  *
  * @since_tizen 3.0
  */
-class ImageContourStabilizator {
+class ImageContourStabilizator
+{
 public:
 	/**
 	 * @brief Enumeration for stabilization return value
 	 *
 	 * @since_tizen 3.0
 	 */
-	enum StabilizationError {
-		Successfully,           /**< Contour is stabilized. */
-		TooShortMovingHistory,  /**< Too short moving history, it's normal
+	enum StabilizationError
+	{
+		Successfully, /**< Contour is stabilized. */
+		TooShortMovingHistory, /**< Too short moving history, it's normal
 									behavior, you can continue to call
 									stabilization in order to accumulate it. */
-		InvalidSettings,        /**< Invalid settings. */
-		UnsupportedContourType  /**< Unsupported contour type. */
+		InvalidSettings, /**< Invalid settings. */
+		UnsupportedContourType /**< Unsupported contour type. */
 	};
 
 	/**
@@ -71,9 +75,7 @@ public:
 	 * @retval #InvalidSettings        Invalid settings
 	 * @retval #UnsupportedContourType Unsupported contour type
 	 */
-	StabilizationError stabilize(
-			std::vector<cv::Point2f>& contour,
-			const StabilizationParams& params);
+	StabilizationError stabilize(std::vector<cv::Point2f> &contour, const StabilizationParams &params);
 
 	/**
 	 * @brief Resets stabilization process.
@@ -84,7 +86,7 @@ public:
 	void reset(void);
 
 private:
-	bool updateSettings(const StabilizationParams& params);
+	bool updateSettings(const StabilizationParams &params);
 
 	std::vector<cv::Point2f> computeStabilizedQuadrangleContour(void);
 
diff --git a/mv_image/image/include/Tracking/ImageTrackingModel.h b/mv_image/image/include/Tracking/ImageTrackingModel.h
index 83664fd..f3a22b3 100644
--- a/mv_image/image/include/Tracking/ImageTrackingModel.h
+++ b/mv_image/image/include/Tracking/ImageTrackingModel.h
@@ -27,15 +27,18 @@
  * @brief This file contains the @ref ImageTrackingModel class.
  */
 
-namespace MediaVision {
-namespace Image {
+namespace MediaVision
+{
+namespace Image
+{
 /**
  * @class    ImageTrackingModel
  * @brief    This class contains the tracking functionality for image objects.
  *
  * @since_tizen 3.0
  */
-class ImageTrackingModel {
+class ImageTrackingModel
+{
 public:
 	/**
 	 * @brief   @ref ImageTrackingModel default constructor
@@ -51,7 +54,7 @@ public:
 	 * @since_tizen 3.0
 	 * @param   [in] copy @ref ImageTrackingModel which will be copied
 	 */
-	ImageTrackingModel(const ImageTrackingModel& copy);
+	ImageTrackingModel(const ImageTrackingModel &copy);
 
 	/**
 	 * @brief   Sets @ref ImageObject as target which will be tracked.
@@ -61,7 +64,7 @@ public:
 	 *
 	 * @return @a 0 on success, otherwise a negative error value
 	 */
-	int setTarget(const ImageObject& target);
+	int setTarget(const ImageObject &target);
 
 	/**
 	 * @brief Checks whether the tracking model is valid for tracking.
@@ -85,7 +88,7 @@ public:
 	 * @param [out]  result   Result contour
 	 * @return true if target is tracked, otherwise return false
 	 */
-	bool track(const cv::Mat& frame, std::vector<cv::Point>& result);
+	bool track(const cv::Mat &frame, std::vector<cv::Point> &result);
 
 	/**
 	 * @brief   Refreshes tracking model.
@@ -102,7 +105,7 @@ public:
 	 * @since_tizen 3.0
 	 * @param   [in] copy @ref ImageTrackingModel which will be copied
 	 */
-	ImageTrackingModel& operator=(const ImageTrackingModel& copy);
+	ImageTrackingModel &operator=(const ImageTrackingModel &copy);
 
 	/**
 	 * @brief  Stores the @ref ImageTrackingModel in a file.
@@ -122,13 +125,9 @@ public:
 	 */
 	int load(const char *filepath);
 
-	 friend std::ostream& operator << (
-			std::ostream& os,
-			const ImageTrackingModel& obj);
+	friend std::ostream &operator<<(std::ostream &os, const ImageTrackingModel &obj);
 
-	friend std::istream& operator >> (
-			std::istream& is,
-			ImageTrackingModel& obj);
+	friend std::istream &operator>>(std::istream &is, ImageTrackingModel &obj);
 
 private:
 	ImageObject __target;
diff --git a/mv_image/image/include/Tracking/MFTracker.h b/mv_image/image/include/Tracking/MFTracker.h
index 3fbd9ea..e051c17 100644
--- a/mv_image/image/include/Tracking/MFTracker.h
+++ b/mv_image/image/include/Tracking/MFTracker.h
@@ -19,17 +19,21 @@
 
 #include "Tracking/ObjectTracker.h"
 
-namespace MediaVision {
-namespace Image {
+namespace MediaVision
+{
+namespace Image
+{
 /**
  * @class    MFTracker
  * @brief    Median Flow tracker implementation.
  *
  * @since_tizen 3.0
  */
-class MFTracker : public ObjectTracker {
+class MFTracker : public ObjectTracker
+{
 public:
-	struct Params {
+	struct Params
+	{
 		/**
 		 * @brief TrackerMedianFlow algorithm parameters constructor
 		 */
@@ -47,7 +51,7 @@ public:
 									flow search used for tracking */
 
 		/* TODO: add lifetime*/
-		/*time_t mLifetime;*/  /**< Time of tracking without reinforcement. */
+		/*time_t mLifetime;*/ /**< Time of tracking without reinforcement. */
 	};
 
 	/**
@@ -67,7 +71,7 @@ public:
 	 * @param [out]  result   Result contour
 	 * @return true if object is tracked, otherwise return false
 	 */
-	virtual bool track(const cv::Mat& frame, std::vector<cv::Point>& result);
+	virtual bool track(const cv::Mat &frame, std::vector<cv::Point> &result);
 
 	/**
 	 * @brief Provides the current location of a target.
@@ -75,7 +79,7 @@ public:
 	 * @since_tizen 3.0
 	 * @param [in] location  Current location of a target
 	 */
-	virtual void reinforcement(const std::vector<cv::Point>& location);
+	virtual void reinforcement(const std::vector<cv::Point> &location);
 
 	/**
 	 * @brief Creates a copy of itself
@@ -88,43 +92,33 @@ public:
 private:
 	bool isInited() const;
 
-	bool init(const cv::Mat& image);
+	bool init(const cv::Mat &image);
 
-	bool update(const cv::Mat& image);
+	bool update(const cv::Mat &image);
 
 	float getLastConfidence() const;
 
 	cv::Rect_<float> getLastBoundingBox() const;
 
-	bool medianFlowImpl(cv::Mat oldImage, cv::Mat newImage, cv::Rect_<float>& oldBox);
+	bool medianFlowImpl(cv::Mat oldImage, cv::Mat newImage, cv::Rect_<float> &oldBox);
 
-	cv::Rect_<float> vote(
-			const std::vector<cv::Point2f>& oldPoints,
-			const std::vector<cv::Point2f>& newPoints,
-			const cv::Rect_<float>& oldRect,
-			cv::Point2f& mD);
+	cv::Rect_<float> vote(const std::vector<cv::Point2f> &oldPoints, const std::vector<cv::Point2f> &newPoints,
+						  const cv::Rect_<float> &oldRect, cv::Point2f &mD);
 
-	void check_FB(
-			std::vector<cv::Mat> newPyramid,
-			const std::vector<cv::Point2f>& oldPoints,
-			const std::vector<cv::Point2f>& newPoints,
-			std::vector<bool>& status);
+	void check_FB(std::vector<cv::Mat> newPyramid, const std::vector<cv::Point2f> &oldPoints,
+				  const std::vector<cv::Point2f> &newPoints, std::vector<bool> &status);
 
-	void check_NCC(
-			const cv::Mat& oldImage,
-			const cv::Mat& newImage,
-			const std::vector<cv::Point2f>& oldPoints,
-			const std::vector<cv::Point2f>& newPoints,
-			std::vector<bool>& status);
+	void check_NCC(const cv::Mat &oldImage, const cv::Mat &newImage, const std::vector<cv::Point2f> &oldPoints,
+				   const std::vector<cv::Point2f> &newPoints, std::vector<bool> &status);
 
 private:
-	bool __isInit;                /**< Flag is used to determine the model
+	bool __isInit; /**< Flag is used to determine the model
 										initialization */
 
-	Params __params;              /**< Parameters used during tracking, see
+	Params __params; /**< Parameters used during tracking, see
 										@ref TrackerMedianFlow::Params */
 
-	cv::TermCriteria __termcrit;  /**< Terminating criteria for OpenCV
+	cv::TermCriteria __termcrit; /**< Terminating criteria for OpenCV
 										Lucas–Kanade optical flow algorithm used
 										during tracking */
 
@@ -132,15 +126,15 @@ private:
 													location with relative values
 													to the bounding box */
 
-	cv::Rect_<float> __boundingBox;  /**< Tracking object bounding box */
+	cv::Rect_<float> __boundingBox; /**< Tracking object bounding box */
 
-	float __confidence;              /**< Confidence that object was tracked
+	float __confidence; /**< Confidence that object was tracked
 											correctly at the last tracking iteration */
 
-	cv::Mat __image;                 /**< Last image for which tracking was
+	cv::Mat __image; /**< Last image for which tracking was
 											performed */
 
-	std::vector<cv::Mat> __pyramid;  /**< The pyramid had been calculated for
+	std::vector<cv::Mat> __pyramid; /**< The pyramid had been calculated for
 											the previous frame(or when
 											initialize the model) */
 };
diff --git a/mv_image/image/include/Tracking/ObjectTracker.h b/mv_image/image/include/Tracking/ObjectTracker.h
index 9486b51..55cb051 100644
--- a/mv_image/image/include/Tracking/ObjectTracker.h
+++ b/mv_image/image/include/Tracking/ObjectTracker.h
@@ -20,15 +20,18 @@
 #include <opencv2/core.hpp>
 #include <opencv2/tracking.hpp>
 
-namespace MediaVision {
-namespace Image {
+namespace MediaVision
+{
+namespace Image
+{
 /**
  * @class    ObjectTracker
  * @brief    Basic object tracker.
  *
  * @since_tizen 3.0
  */
-class ObjectTracker {
+class ObjectTracker
+{
 public:
 	/**
 	 * @brief @ref ObjectTracker destructor
@@ -46,7 +49,7 @@ public:
 	 * @param [out]  result   Result contour
 	 * @return true if object is tracked, otherwise return false
 	 */
-	virtual bool track(const cv::Mat& frame, std::vector<cv::Point>& result) = 0;
+	virtual bool track(const cv::Mat &frame, std::vector<cv::Point> &result) = 0;
 
 	/**
 	 * @brief Provides the current location of a target.
@@ -54,7 +57,7 @@ public:
 	 * @since_tizen 3.0
 	 * @param [in] location  Current location of a target
 	 */
-	virtual void reinforcement(const std::vector<cv::Point>& location) = 0;
+	virtual void reinforcement(const std::vector<cv::Point> &location) = 0;
 
 	/*
 	 * @brief Creates a copy of itself
@@ -72,7 +75,7 @@ private:
 	 * @param [in] copy @ref ObjectTracker which will be copied
 	 * @return itself
 	 */
-	ObjectTracker& operator=(const ObjectTracker& copy) = default;
+	ObjectTracker &operator=(const ObjectTracker &copy) = default;
 };
 
 } /* Image */
diff --git a/mv_image/image/include/Tracking/RecognitionBasedTracker.h b/mv_image/image/include/Tracking/RecognitionBasedTracker.h
index 3f63b75..222060f 100644
--- a/mv_image/image/include/Tracking/RecognitionBasedTracker.h
+++ b/mv_image/image/include/Tracking/RecognitionBasedTracker.h
@@ -21,15 +21,18 @@
 
 #include "Recognition/ImageObject.h"
 
-namespace MediaVision {
-namespace Image {
+namespace MediaVision
+{
+namespace Image
+{
 /**
  * @class    FeatureSubstitutionTracker
  * @brief    Tracker uses recognition of target on the entire frame.
  *
  * @since_tizen 3.0
  */
-class RecognitionBasedTracker : public ObjectTracker {
+class RecognitionBasedTracker : public ObjectTracker
+{
 public:
 	/**
 	 * @brief @ref RecognitionBasedTracker constructor.
@@ -40,10 +43,8 @@ public:
 	 *                                             extracting from frames
 	 * @param [in] recognitionParams               Parameters of recognition
 	 */
-	RecognitionBasedTracker(
-			const ImageObject& target,
-			const FeaturesExtractingParams& sceneFeaturesExtractingParams,
-			const RecognitionParams& recognitionParams);
+	RecognitionBasedTracker(const ImageObject &target, const FeaturesExtractingParams &sceneFeaturesExtractingParams,
+							const RecognitionParams &recognitionParams);
 
 	/**
 	 * @brief @ref RecognitionBasedTracker destructor
@@ -61,7 +62,7 @@ public:
 	 * @param [out]  result   Result contour
 	 * @return true if object is tracked, otherwise return false
 	 */
-	virtual bool track(const cv::Mat& frame, std::vector<cv::Point>& result);
+	virtual bool track(const cv::Mat &frame, std::vector<cv::Point> &result);
 
 	/**
 	 * @brief Provides the current location of a target.
@@ -69,7 +70,7 @@ public:
 	 * @since_tizen 3.0
 	 * @param [in] location  Current location of a target
 	 */
-	virtual void reinforcement(const std::vector<cv::Point>& location);
+	virtual void reinforcement(const std::vector<cv::Point> &location);
 
 	/*
 	 * @brief Creates a copy of itself
diff --git a/mv_image/image/include/mv_image_open.h b/mv_image/image/include/mv_image_open.h
index 3089778..5ed4ee2 100644
--- a/mv_image/image/include/mv_image_open.h
+++ b/mv_image/image/include/mv_image_open.h
@@ -76,13 +76,8 @@ extern "C" {
  * @see mv_image_object_destroy_open()
  * @see mv_engine_config_h
  */
-int mv_image_recognize_open(
-		mv_source_h source,
-		const mv_image_object_h *image_objects,
-		int number_of_objects,
-		mv_engine_config_h engine_cfg,
-		mv_image_recognized_cb recognized_cb,
-		void *user_data);
+int mv_image_recognize_open(mv_source_h source, const mv_image_object_h *image_objects, int number_of_objects,
+							mv_engine_config_h engine_cfg, mv_image_recognized_cb recognized_cb, void *user_data);
 
 /*************************/
 /* Image object tracking */
@@ -139,12 +134,8 @@ int mv_image_recognize_open(
  * @see mv_image_tracking_model_set_target_open()
  * @see mv_image_tracking_model_destroy_open()
  */
-int mv_image_track_open(
-		mv_source_h source,
-		mv_image_tracking_model_h image_tracking_model,
-		mv_engine_config_h engine_cfg,
-		mv_image_tracked_cb tracked_cb,
-		void *user_data);
+int mv_image_track_open(mv_source_h source, mv_image_tracking_model_h image_tracking_model,
+						mv_engine_config_h engine_cfg, mv_image_tracked_cb tracked_cb, void *user_data);
 
 /**************************/
 /* Image object behaviour */
@@ -164,8 +155,7 @@ int mv_image_track_open(
  *
  * @see mv_image_object_destroy_open()
  */
-int mv_image_object_create_open(
-		mv_image_object_h *image_object);
+int mv_image_object_create_open(mv_image_object_h *image_object);
 
 /**
  * @brief Destroys the image object.
@@ -178,8 +168,7 @@ int mv_image_object_create_open(
  *
  * @see mv_image_object_create_open()
  */
-int mv_image_object_destroy_open(
-		mv_image_object_h image_object);
+int mv_image_object_destroy_open(mv_image_object_h image_object);
 
 /**
  * @brief Fills the image object.
@@ -218,11 +207,8 @@ int mv_image_object_destroy_open(
  * @see mv_image_object_destroy_open()
  * @see mv_engine_config_h
  */
-int mv_image_object_fill_open(
-		mv_image_object_h image_object,
-		mv_engine_config_h engine_cfg,
-		mv_source_h source,
-		mv_rectangle_s *location);
+int mv_image_object_fill_open(mv_image_object_h image_object, mv_engine_config_h engine_cfg, mv_source_h source,
+							  mv_rectangle_s *location);
 
 /**
  * @brief Gets a value that determines how well an image object can be recognized.
@@ -254,9 +240,7 @@ int mv_image_object_fill_open(
  * @see mv_image_object_destroy_open()
  * @see mv_engine_config_h
  */
-int mv_image_object_get_recognition_rate_open(
-		mv_image_object_h image_object,
-		double *recognition_rate);
+int mv_image_object_get_recognition_rate_open(mv_image_object_h image_object, double *recognition_rate);
 
 /**
  * @brief Sets a label for the image object.
@@ -280,9 +264,7 @@ int mv_image_object_get_recognition_rate_open(
  * @see mv_image_object_create_open()
  * @see mv_image_object_destroy_open()
  */
-int mv_image_object_set_label_open(
-		mv_image_object_h image_object,
-		int label);
+int mv_image_object_set_label_open(mv_image_object_h image_object, int label);
 
 /**
  * @brief Gets a label of image object.
@@ -308,9 +290,7 @@ int mv_image_object_set_label_open(
  * @see mv_image_object_create_open()
  * @see mv_image_object_destroy_open()
  */
-int mv_image_object_get_label_open(
-		mv_image_object_h image_object,
-		int *label);
+int mv_image_object_get_label_open(mv_image_object_h image_object, int *label);
 
 /**
  * @brief Clones the image object.
@@ -329,9 +309,7 @@ int mv_image_object_get_label_open(
  * @see mv_image_object_create_open()
  * @see mv_image_object_destroy_open()
  */
-int mv_image_object_clone_open(
-		mv_image_object_h src,
-		mv_image_object_h *dst);
+int mv_image_object_clone_open(mv_image_object_h src, mv_image_object_h *dst);
 
 /**
  * @brief Saves the image object.
@@ -350,9 +328,7 @@ int mv_image_object_clone_open(
  * @see mv_image_object_load_open()
  * @see mv_image_object_destroy_open()
  */
-int mv_image_object_save_open(
-		const char *file_name,
-		mv_image_object_h image_object);
+int mv_image_object_save_open(const char *file_name, mv_image_object_h image_object);
 
 /**
  * @brief Loads an image object from the file.
@@ -377,9 +353,7 @@ int mv_image_object_save_open(
  * @see mv_image_object_save_open()
  * @see mv_image_object_destroy_open()
  */
-int mv_image_object_load_open(
-		const char *file_name,
-		mv_image_object_h *image_object);
+int mv_image_object_load_open(const char *file_name, mv_image_object_h *image_object);
 
 /**********************************/
 /* Image tracking model behaviour */
@@ -399,8 +373,7 @@ int mv_image_object_load_open(
  *
  * @see mv_image_tracking_model_destroy_open()
  */
-int mv_image_tracking_model_create_open(
-		mv_image_tracking_model_h *image_tracking_model);
+int mv_image_tracking_model_create_open(mv_image_tracking_model_h *image_tracking_model);
 
 /**
  * @brief Sets target of image tracking model.
@@ -433,9 +406,8 @@ int mv_image_tracking_model_create_open(
  * @see mv_image_track_open()
  * @see mv_image_tracking_model_destroy_open()
  */
-int mv_image_tracking_model_set_target_open(
-		mv_image_object_h image_object,
-		mv_image_tracking_model_h image_tracking_model);
+int mv_image_tracking_model_set_target_open(mv_image_object_h image_object,
+											mv_image_tracking_model_h image_tracking_model);
 
 /**
  * @brief Destroys the image tracking model.
@@ -451,8 +423,7 @@ int mv_image_tracking_model_set_target_open(
  *
  * @see mv_image_tracking_model_create_open()
  */
-int mv_image_tracking_model_destroy_open(
-		mv_image_tracking_model_h image_tracking_model);
+int mv_image_tracking_model_destroy_open(mv_image_tracking_model_h image_tracking_model);
 
 /**
  * @brief Refreshes the state of image tracking model.
@@ -482,9 +453,7 @@ int mv_image_tracking_model_destroy_open(
  * @see mv_image_track_open()
  * @see mv_image_tracking_model_destroy_open()
  */
-int mv_image_tracking_model_refresh_open(
-		mv_image_tracking_model_h image_tracking_model,
-		mv_engine_config_h engine_cfg);
+int mv_image_tracking_model_refresh_open(mv_image_tracking_model_h image_tracking_model, mv_engine_config_h engine_cfg);
 
 /**
  * @brief Clones the image tracking model.
@@ -501,9 +470,7 @@ int mv_image_tracking_model_refresh_open(
  * @see mv_image_tracking_model_create_open()
  * @see mv_image_tracking_model_destroy_open()
  */
-int mv_image_tracking_model_clone_open(
-		mv_image_tracking_model_h src,
-		mv_image_tracking_model_h *dst);
+int mv_image_tracking_model_clone_open(mv_image_tracking_model_h src, mv_image_tracking_model_h *dst);
 
 /**
  * @brief Saves the image tracking model.
@@ -528,9 +495,7 @@ int mv_image_tracking_model_clone_open(
  * @see mv_image_tracking_model_load_open()
  * @see mv_image_tracking_model_destroy_open()
  */
-int mv_image_tracking_model_save_open(
-		const char *file_name,
-		mv_image_tracking_model_h image_tracking_model);
+int mv_image_tracking_model_save_open(const char *file_name, mv_image_tracking_model_h image_tracking_model);
 
 /**
  * @brief Loads an image tracking model from the file.
@@ -555,9 +520,7 @@ int mv_image_tracking_model_save_open(
  * @see mv_image_tracking_model_save_open()
  * @see mv_image_tracking_model_destroy_open()
  */
-int mv_image_tracking_model_load_open(
-		const char *file_name,
-		mv_image_tracking_model_h *image_tracking_model);
+int mv_image_tracking_model_load_open(const char *file_name, mv_image_tracking_model_h *image_tracking_model);
 
 #ifdef __cplusplus
 }
diff --git a/mv_image/image/src/Features/BasicExtractorFactory.cpp b/mv_image/image/src/Features/BasicExtractorFactory.cpp
index c788895..0c70c3a 100644
--- a/mv_image/image/src/Features/BasicExtractorFactory.cpp
+++ b/mv_image/image/src/Features/BasicExtractorFactory.cpp
@@ -18,20 +18,17 @@
 
 #include <opencv2/core.hpp>
 
-namespace MediaVision {
-namespace Image {
-
-BasicExtractorFactory::BasicExtractorFactory(
-		KeypointType keypointsType,
-		DescriptorType descType) :
-				__kpType(keypointsType),
-				__descType(descType)
+namespace MediaVision
 {
-}
+namespace Image
+{
+BasicExtractorFactory::BasicExtractorFactory(KeypointType keypointsType, DescriptorType descType)
+		: __kpType(keypointsType), __descType(descType)
+{}
 
 cv::Ptr<FeatureExtractor> BasicExtractorFactory::buildFeatureExtractor()
 {
-	cv::Ptr<FeatureExtractor> featureExtractor(new (std::nothrow)FeatureExtractor());
+	cv::Ptr<FeatureExtractor> featureExtractor(new (std::nothrow) FeatureExtractor());
 
 	if (featureExtractor != NULL) {
 		cv::Ptr<cv::FeatureDetector> detector;
diff --git a/mv_image/image/src/Features/FeatureExtractor.cpp b/mv_image/image/src/Features/FeatureExtractor.cpp
index 5b04f00..4e6d9a0 100644
--- a/mv_image/image/src/Features/FeatureExtractor.cpp
+++ b/mv_image/image/src/Features/FeatureExtractor.cpp
@@ -20,49 +20,35 @@
 
 #include <opencv2/core.hpp>
 
-
-namespace MediaVision {
-namespace Image {
-
+namespace MediaVision
+{
+namespace Image
+{
 const cv::Size FeatureExtractor::__MIN_SIZE = cv::Size(5, 5);
 
-FeatureExtractor::FeatureExtractor() :
-		__kpType(KT_INVALID),
-		__detector(),
-		__descType(DT_INVALID),
-		__extractor(),
-		__computeRecognitionRate(NULL)
-{
-}
+FeatureExtractor::FeatureExtractor()
+		: __kpType(KT_INVALID), __detector(), __descType(DT_INVALID), __extractor(), __computeRecognitionRate(NULL)
+{}
 
-void FeatureExtractor::setFeatureDetector(
-		const cv::Ptr<cv::FeatureDetector> detector,
-		KeypointType keypointType)
+void FeatureExtractor::setFeatureDetector(const cv::Ptr<cv::FeatureDetector> detector, KeypointType keypointType)
 {
 	__detector = detector;
 	__kpType = keypointType;
 }
 
-void FeatureExtractor::setDescriptorExtractor(
-		cv::Ptr<cv::DescriptorExtractor> extractor,
-		DescriptorType descriptorType)
+void FeatureExtractor::setDescriptorExtractor(cv::Ptr<cv::DescriptorExtractor> extractor, DescriptorType descriptorType)
 {
 	__extractor = extractor;
 	__descType = descriptorType;
 }
 
-void FeatureExtractor::setRecognitionRateMetric(
-		float (*computeRecognitionRate)(
-				const cv::Mat&,
-				const std::vector<cv::KeyPoint>&))
+void FeatureExtractor::setRecognitionRateMetric(float (*computeRecognitionRate)(const cv::Mat &,
+																				const std::vector<cv::KeyPoint> &))
 {
 	__computeRecognitionRate = computeRecognitionRate;
 }
 
-bool FeatureExtractor::extract(
-		const cv::Mat& image,
-		FeaturePack& result,
-		const std::vector<cv::Point2f>& roi)
+bool FeatureExtractor::extract(const cv::Mat &image, FeaturePack &result, const std::vector<cv::Point2f> &roi)
 {
 	if (__detector.empty() || __extractor.empty())
 		return false;
@@ -89,9 +75,7 @@ bool FeatureExtractor::extract(
 
 	std::vector<cv::KeyPoint> keypoints;
 
-	__detector->detect(
-			image(boundingBox),
-			keypoints);
+	__detector->detect(image(boundingBox), keypoints);
 
 	result.__objectKeypoints = keypoints;
 
@@ -116,15 +100,10 @@ bool FeatureExtractor::extract(
 		}
 	}
 
-	 __extractor->compute(
-			image,
-			result.__objectKeypoints,
-			result.__objectDescriptors);
+	__extractor->compute(image, result.__objectKeypoints, result.__objectDescriptors);
 
 	if (NULL != __computeRecognitionRate) {
-		result.__recognitionRate = __computeRecognitionRate(
-				image(boundingBox),
-				keypoints);
+		result.__recognitionRate = __computeRecognitionRate(image(boundingBox), keypoints);
 	} else {
 		/* Default recognition rate metric */
 		if (result.__objectKeypoints.size() < MinimumNumberOfFeatures)
diff --git a/mv_image/image/src/Features/FeatureExtractorFactory.cpp b/mv_image/image/src/Features/FeatureExtractorFactory.cpp
index 3cda88e..463a754 100644
--- a/mv_image/image/src/Features/FeatureExtractorFactory.cpp
+++ b/mv_image/image/src/Features/FeatureExtractorFactory.cpp
@@ -16,9 +16,10 @@
 
 #include "Features/FeatureExtractorFactory.h"
 
-namespace MediaVision {
-namespace Image {
-
+namespace MediaVision
+{
+namespace Image
+{
 FeatureExtractorFactory::~FeatureExtractorFactory()
 {
 	; /* NULL */
diff --git a/mv_image/image/src/Features/FeatureMatcher.cpp b/mv_image/image/src/Features/FeatureMatcher.cpp
index c32d49d..31e3e0e 100644
--- a/mv_image/image/src/Features/FeatureMatcher.cpp
+++ b/mv_image/image/src/Features/FeatureMatcher.cpp
@@ -21,17 +21,15 @@
 #include <opencv2/core.hpp>
 #include <opencv2/calib3d/calib3d_c.h>
 
-namespace MediaVision {
-namespace Image {
-
+namespace MediaVision
+{
+namespace Image
+{
 // LCOV_EXCL_START
-namespace {
-
-float computeLinearSupportElement(
-		const std::vector<cv::DMatch>& examples,
-		int requiredNumber,
-		int leftLimit,
-		int rightLimit)
+namespace
+{
+float computeLinearSupportElement(const std::vector<cv::DMatch> &examples, int requiredNumber, int leftLimit,
+								  int rightLimit)
 {
 	int sizeOfExamples = rightLimit - leftLimit + 1;
 
@@ -58,10 +56,7 @@ float computeLinearSupportElement(
 	return k * requiredNumber + b;
 }
 
-size_t matchesSelection(
-		std::vector<cv::DMatch>& examples,
-		size_t filterAmount,
-		size_t allowableError)
+size_t matchesSelection(std::vector<cv::DMatch> &examples, size_t filterAmount, size_t allowableError)
 {
 	size_t sizeOfExamples = examples.size();
 
@@ -86,21 +81,18 @@ size_t matchesSelection(
 			break;
 		}
 
-		supportElement = computeLinearSupportElement(examples, requiredNumber,
-				leftLimit, rightLimit);
+		supportElement = computeLinearSupportElement(examples, requiredNumber, leftLimit, rightLimit);
 
 		/* Iteration similar quicksort */
 		while (true) {
 			/* Search the leftmost element which have
 			 * bigger confidence than support element */
-			while (examples[leftLimit].distance <= supportElement &&
-					leftLimit < startRightLimit)
+			while (examples[leftLimit].distance <= supportElement && leftLimit < startRightLimit)
 				++leftLimit;
 
 			/* Search the rightmost element which have smaller
 			 * confidence than support element */
-			while (examples[rightLimit].distance >= supportElement &&
-					rightLimit >= startLeftLimit)
+			while (examples[rightLimit].distance >= supportElement && rightLimit >= startLeftLimit)
 				--rightLimit;
 
 			if (leftLimit >= rightLimit)
@@ -122,25 +114,20 @@ size_t matchesSelection(
 		}
 	}
 
-	return (size_t)leftLimit;
+	return (size_t) leftLimit;
 }
 
 } /* anonymous namespace */
 
-FeatureMatcher::FeatureMatcher(
-		float affectingPart,
-		float tolerantError,
-		size_t minimumMatchesNumber)
+FeatureMatcher::FeatureMatcher(float affectingPart, float tolerantError, size_t minimumMatchesNumber)
 {
 	setAffectingPart(affectingPart);
 	setTolerantError(tolerantError);
 	setMinimumMatchesNumber(minimumMatchesNumber);
 }
 
-FeatureMatcher::MatchError FeatureMatcher::match(
-		const FeaturePack& from,
-		const FeaturePack& to,
-		cv::Mat& homophraphyMatrix) const
+FeatureMatcher::MatchError FeatureMatcher::match(const FeaturePack &from, const FeaturePack &to,
+												 cv::Mat &homophraphyMatrix) const
 {
 	if (MinimumNumberOfFeatures > from.__objectKeypoints.size())
 		return InvalidFeaturePackFrom;
@@ -164,30 +151,24 @@ FeatureMatcher::MatchError FeatureMatcher::match(
 	size_t allowableMatchesNumberError = __tolerantError * requiredMatchesNumber;
 
 	if (matchesNumber - allowableMatchesNumberError > MinimumNumberOfFeatures &&
-			requiredMatchesNumber + allowableMatchesNumberError < matchesNumber) {
-		if (requiredMatchesNumber - allowableMatchesNumberError <
-				__minimumMatchesNumber) {
-			if (requiredMatchesNumber + allowableMatchesNumberError >
-					__minimumMatchesNumber) {
-				requiredMatchesNumber = (requiredMatchesNumber +
-						__minimumMatchesNumber + allowableMatchesNumberError) / 2;
-
-				allowableMatchesNumberError = requiredMatchesNumber -
-						__minimumMatchesNumber + allowableMatchesNumberError;
+		requiredMatchesNumber + allowableMatchesNumberError < matchesNumber) {
+		if (requiredMatchesNumber - allowableMatchesNumberError < __minimumMatchesNumber) {
+			if (requiredMatchesNumber + allowableMatchesNumberError > __minimumMatchesNumber) {
+				requiredMatchesNumber =
+						(requiredMatchesNumber + __minimumMatchesNumber + allowableMatchesNumberError) / 2;
+
+				allowableMatchesNumberError =
+						requiredMatchesNumber - __minimumMatchesNumber + allowableMatchesNumberError;
 			} else {
 				const size_t minimalAllowableMatchesNumberError = 2u;
 
-				requiredMatchesNumber = minimalAllowableMatchesNumberError +
-										__minimumMatchesNumber;
+				requiredMatchesNumber = minimalAllowableMatchesNumberError + __minimumMatchesNumber;
 
 				allowableMatchesNumberError = minimalAllowableMatchesNumberError;
 			}
 		}
 
-		const size_t filterAmount = matchesSelection(
-													matches,
-													requiredMatchesNumber,
-													allowableMatchesNumberError);
+		const size_t filterAmount = matchesSelection(matches, requiredMatchesNumber, allowableMatchesNumberError);
 
 		if (filterAmount >= MinimumNumberOfFeatures)
 			matches.resize(filterAmount);
@@ -199,11 +180,9 @@ FeatureMatcher::MatchError FeatureMatcher::match(
 	std::vector<cv::Point2f> scenePoints(matchesNumber);
 
 	for (size_t matchIdx = 0; matchIdx < matchesNumber; ++matchIdx) {
-		objectPoints[matchIdx] =
-				from.__objectKeypoints[matches[matchIdx].queryIdx].pt;
+		objectPoints[matchIdx] = from.__objectKeypoints[matches[matchIdx].queryIdx].pt;
 
-		scenePoints[matchIdx] =
-				to.__objectKeypoints[matches[matchIdx].trainIdx].pt;
+		scenePoints[matchIdx] = to.__objectKeypoints[matches[matchIdx].trainIdx].pt;
 	}
 
 	homophraphyMatrix = cv::findHomography(objectPoints, scenePoints, CV_RANSAC);
diff --git a/mv_image/image/src/Features/FeaturePack.cpp b/mv_image/image/src/Features/FeaturePack.cpp
index d2ce616..0d8e9dd 100644
--- a/mv_image/image/src/Features/FeaturePack.cpp
+++ b/mv_image/image/src/Features/FeaturePack.cpp
@@ -18,30 +18,31 @@
 
 #include <opencv2/core.hpp>
 
-namespace MediaVision {
-namespace Image {
-
-FeaturePack::FeaturePack() :
-		__keypointsType(KT_INVALID),
-		__objectKeypoints(),
-		__descriptorsType(DT_INVALID),
-		__objectDescriptors(),
-		__recognitionRate(0.f)
+namespace MediaVision
+{
+namespace Image
+{
+FeaturePack::FeaturePack()
+		: __keypointsType(KT_INVALID)
+		, __objectKeypoints()
+		, __descriptorsType(DT_INVALID)
+		, __objectDescriptors()
+		, __recognitionRate(0.f)
 {
 	; /* NULL */
 }
 
-FeaturePack::FeaturePack(const FeaturePack& copy) :
-		__keypointsType(copy.__keypointsType),
-		__objectKeypoints(copy.__objectKeypoints),
-		__descriptorsType(copy.__descriptorsType),
-		__objectDescriptors(copy.__objectDescriptors.clone()),
-		__recognitionRate(copy.__recognitionRate)
+FeaturePack::FeaturePack(const FeaturePack &copy)
+		: __keypointsType(copy.__keypointsType)
+		, __objectKeypoints(copy.__objectKeypoints)
+		, __descriptorsType(copy.__descriptorsType)
+		, __objectDescriptors(copy.__objectDescriptors.clone())
+		, __recognitionRate(copy.__recognitionRate)
 {
 	; /* NULL */
 }
 
-FeaturePack& FeaturePack::operator= (const FeaturePack& copy)
+FeaturePack &FeaturePack::operator=(const FeaturePack &copy)
 {
 	if (this != &copy) {
 		__keypointsType = copy.__keypointsType;
diff --git a/mv_image/image/src/Features/ORBExtractorFactory.cpp b/mv_image/image/src/Features/ORBExtractorFactory.cpp
index 1dcded8..1a12237 100644
--- a/mv_image/image/src/Features/ORBExtractorFactory.cpp
+++ b/mv_image/image/src/Features/ORBExtractorFactory.cpp
@@ -20,11 +20,11 @@
 
 #include <opencv2/core.hpp>
 
-namespace MediaVision {
-namespace Image {
-ORBExtractorFactory::ORBExtractorFactory(
-		float scaleFactor,
-		size_t maximumFeaturesNumber)
+namespace MediaVision
+{
+namespace Image
+{
+ORBExtractorFactory::ORBExtractorFactory(float scaleFactor, size_t maximumFeaturesNumber)
 {
 	setScaleFactor(scaleFactor);
 	setMaximumFeaturesNumber(maximumFeaturesNumber);
@@ -32,7 +32,7 @@ ORBExtractorFactory::ORBExtractorFactory(
 
 cv::Ptr<FeatureExtractor> ORBExtractorFactory::buildFeatureExtractor()
 {
-	cv::Ptr<FeatureExtractor> featureExtractor(new (std::nothrow)FeatureExtractor());
+	cv::Ptr<FeatureExtractor> featureExtractor(new (std::nothrow) FeatureExtractor());
 
 	cv::Ptr<cv::ORB> detector = cv::ORB::create(__maximumFeaturesNumber, __scaleFactor);
 	cv::Ptr<cv::ORB> extractor = detector;
@@ -64,9 +64,7 @@ void ORBExtractorFactory::setMaximumFeaturesNumber(size_t maximumFeaturesNumber)
 	__maximumFeaturesNumber = maximumFeaturesNumber;
 }
 
-float ORBExtractorFactory::computeRecognitionRate(
-		const cv::Mat& image,
-		const std::vector<cv::KeyPoint>& keypoints)
+float ORBExtractorFactory::computeRecognitionRate(const cv::Mat &image, const std::vector<cv::KeyPoint> &keypoints)
 {
 	const size_t numberOfKeypoints = keypoints.size();
 
@@ -86,11 +84,7 @@ float ORBExtractorFactory::computeRecognitionRate(
 
 	for (size_t x = 0u; x < X_CELLS_NUMBER; ++x) {
 		for (size_t y = 0u; y < Y_CELLS_NUMBER; ++y) {
-			cells[x][y] = image(cv::Rect(
-					x * cellWidth,
-					y * cellHeight,
-					cellWidth,
-					cellHeight));
+			cells[x][y] = image(cv::Rect(x * cellWidth, y * cellHeight, cellWidth, cellHeight));
 
 			accumulationCounter[x][y] = 0;
 		}
@@ -106,26 +100,23 @@ float ORBExtractorFactory::computeRecognitionRate(
 		++(accumulationCounter[xCellIdx][yCellIdx]);
 	}
 
-	const float exceptedNumber = numberOfKeypoints /
-			(float)(X_CELLS_NUMBER * Y_CELLS_NUMBER);
+	const float exceptedNumber = numberOfKeypoints / (float) (X_CELLS_NUMBER * Y_CELLS_NUMBER);
 
 	float distributedEvaluation = 0.f;
 
 	for (size_t x = 0u; x < X_CELLS_NUMBER; ++x) {
 		for (size_t y = 0u; y < Y_CELLS_NUMBER; ++y) {
 			distributedEvaluation += (accumulationCounter[x][y] - exceptedNumber) *
-					(accumulationCounter[x][y] - exceptedNumber) / exceptedNumber;
+									 (accumulationCounter[x][y] - exceptedNumber) / exceptedNumber;
 		}
 	}
 
-	float maximumDistributedEvaluation = (X_CELLS_NUMBER * Y_CELLS_NUMBER - 1) *
-			exceptedNumber;
+	float maximumDistributedEvaluation = (X_CELLS_NUMBER * Y_CELLS_NUMBER - 1) * exceptedNumber;
 
-	maximumDistributedEvaluation += (numberOfKeypoints - exceptedNumber) *
-			(numberOfKeypoints - exceptedNumber) / exceptedNumber;
+	maximumDistributedEvaluation +=
+			(numberOfKeypoints - exceptedNumber) * (numberOfKeypoints - exceptedNumber) / exceptedNumber;
 
-	distributedEvaluation = 1 -
-			(distributedEvaluation / maximumDistributedEvaluation);
+	distributedEvaluation = 1 - (distributedEvaluation / maximumDistributedEvaluation);
 
 	/* Exponentiation to find an approximate confidence value based on the
 	 * number of key points on the image. */
diff --git a/mv_image/image/src/ImageConfig.cpp b/mv_image/image/src/ImageConfig.cpp
index de887d5..86cec12 100644
--- a/mv_image/image/src/ImageConfig.cpp
+++ b/mv_image/image/src/ImageConfig.cpp
@@ -16,80 +16,65 @@
 
 #include "ImageConfig.h"
 
-namespace MediaVision {
-namespace Image {
-FeaturesExtractingParams::FeaturesExtractingParams() :
-	mKeypointType(KT_INVALID),
-	mDescriptorType(DT_INVALID)
+namespace MediaVision
+{
+namespace Image
+{
+FeaturesExtractingParams::FeaturesExtractingParams() : mKeypointType(KT_INVALID), mDescriptorType(DT_INVALID)
 {
 	; /* NULL */
 }
 
-RecognitionParams::RecognitionParams(
-					int minMatchesNumber,
-					double requiredMatchesPart,
-					double tolerantMatchesPartError) :
-	mMinMatchesNumber(minMatchesNumber),
-	mRequiredMatchesPart(requiredMatchesPart),
-	mTolerantMatchesPartError(tolerantMatchesPartError)
+RecognitionParams::RecognitionParams(int minMatchesNumber, double requiredMatchesPart, double tolerantMatchesPartError)
+		: mMinMatchesNumber(minMatchesNumber)
+		, mRequiredMatchesPart(requiredMatchesPart)
+		, mTolerantMatchesPartError(tolerantMatchesPartError)
 {
 	; /* NULL */
 }
 
-RecognitionParams::RecognitionParams() :
-	mMinMatchesNumber(0),
-	mRequiredMatchesPart(1.0),
-	mTolerantMatchesPartError(0.0)
+RecognitionParams::RecognitionParams() : mMinMatchesNumber(0), mRequiredMatchesPart(1.0), mTolerantMatchesPartError(0.0)
 {
 	; /* NULL */
 }
 
-StabilizationParams::StabilizationParams(
-					bool isEnabled,
-					size_t historyAmount,
-					double tolerantShift,
-					double tolerantShiftExtra,
-					double stabilizationSpeed,
-					double stabilizationAcceleration) :
-	mIsEnabled(isEnabled),
-	mHistoryAmount(historyAmount),
-	mTolerantShift(tolerantShift),
-	mTolerantShiftExtra(tolerantShiftExtra),
-	mStabilizationSpeed(stabilizationSpeed),
-	mStabilizationAcceleration(stabilizationAcceleration)
+StabilizationParams::StabilizationParams(bool isEnabled, size_t historyAmount, double tolerantShift,
+										 double tolerantShiftExtra, double stabilizationSpeed,
+										 double stabilizationAcceleration)
+		: mIsEnabled(isEnabled)
+		, mHistoryAmount(historyAmount)
+		, mTolerantShift(tolerantShift)
+		, mTolerantShiftExtra(tolerantShiftExtra)
+		, mStabilizationSpeed(stabilizationSpeed)
+		, mStabilizationAcceleration(stabilizationAcceleration)
 {
 	; /* NULL */
 }
 
-StabilizationParams::StabilizationParams() :
-	mIsEnabled(false),
-	mHistoryAmount(1),
-	mTolerantShift(0.0),
-	mTolerantShiftExtra(0.0),
-	mStabilizationSpeed(0.0),
-	mStabilizationAcceleration(1.0)
+StabilizationParams::StabilizationParams()
+		: mIsEnabled(false)
+		, mHistoryAmount(1)
+		, mTolerantShift(0.0)
+		, mTolerantShiftExtra(0.0)
+		, mStabilizationSpeed(0.0)
+		, mStabilizationAcceleration(1.0)
 {
 	; /* NULL */
 }
 
-TrackingParams::TrackingParams(
-					FeaturesExtractingParams framesFeaturesExtractingParams,
-					RecognitionParams recognitionParams,
-					StabilizationParams stabilizationParams,
-					double expectedOffset) :
-	mFramesFeaturesExtractingParams(framesFeaturesExtractingParams),
-	mRecognitionParams(recognitionParams),
-	mStabilizationParams(stabilizationParams),
-	mExpectedOffset(expectedOffset)
+TrackingParams::TrackingParams(FeaturesExtractingParams framesFeaturesExtractingParams,
+							   RecognitionParams recognitionParams, StabilizationParams stabilizationParams,
+							   double expectedOffset)
+		: mFramesFeaturesExtractingParams(framesFeaturesExtractingParams)
+		, mRecognitionParams(recognitionParams)
+		, mStabilizationParams(stabilizationParams)
+		, mExpectedOffset(expectedOffset)
 {
 	; /* NULL */
 }
 
-TrackingParams::TrackingParams() :
-	mFramesFeaturesExtractingParams(),
-	mRecognitionParams(),
-	mStabilizationParams(),
-	mExpectedOffset(0.0)
+TrackingParams::TrackingParams()
+		: mFramesFeaturesExtractingParams(), mRecognitionParams(), mStabilizationParams(), mExpectedOffset(0.0)
 {
 	; /* NULL */
 }
diff --git a/mv_image/image/src/ImageMathUtil.cpp b/mv_image/image/src/ImageMathUtil.cpp
index 8b53f9f..b6e08ce 100644
--- a/mv_image/image/src/ImageMathUtil.cpp
+++ b/mv_image/image/src/ImageMathUtil.cpp
@@ -16,21 +16,16 @@
 
 #include "ImageMathUtil.h"
 
-namespace MediaVision {
-namespace Image {
-float getDistance(
-		const cv::Point2f& point1,
-		const cv::Point2f& point2)
+namespace MediaVision
 {
-	return sqrt(
-			(point1.x - point2.x) * (point1.x - point2.x) +
-			(point1.y - point2.y) * (point1.y - point2.y));
+namespace Image
+{
+float getDistance(const cv::Point2f &point1, const cv::Point2f &point2)
+{
+	return sqrt((point1.x - point2.x) * (point1.x - point2.x) + (point1.y - point2.y) * (point1.y - point2.y));
 }
 
-float getTriangleArea(
-		const cv::Point2f& point1,
-		const cv::Point2f& point2,
-		const cv::Point2f& point3)
+float getTriangleArea(const cv::Point2f &point1, const cv::Point2f &point2, const cv::Point2f &point3)
 {
 	float distances[3];
 
@@ -40,10 +35,8 @@ float getTriangleArea(
 
 	const float semiperimeter = (distances[0] + distances[1] + distances[2]) / 2.0f;
 
-	const float res2x = semiperimeter *
-			(semiperimeter - distances[0]) *
-			(semiperimeter - distances[1]) *
-			(semiperimeter - distances[2]);
+	const float res2x = semiperimeter * (semiperimeter - distances[0]) * (semiperimeter - distances[1]) *
+						(semiperimeter - distances[2]);
 
 	if (res2x < 0.f)
 		return 0.f;
@@ -53,13 +46,10 @@ float getTriangleArea(
 
 float getQuadrangleArea(const cv::Point2f points[NumberOfQuadrangleCorners])
 {
-	return getTriangleArea(points[0], points[1], points[2]) +
-			getTriangleArea(points[0], points[3], points[2]);
+	return getTriangleArea(points[0], points[1], points[2]) + getTriangleArea(points[0], points[3], points[2]);
 }
 
-bool checkAccessory(
-		const cv::Point2f& point,
-		const std::vector<cv::Point2f>& region)
+bool checkAccessory(const cv::Point2f &point, const std::vector<cv::Point2f> &region)
 {
 	if (region.size() < 3)
 		return false;
@@ -69,16 +59,15 @@ bool checkAccessory(
 
 	for (size_t i = 0u, j = numberOfContourPoints - 1; i < numberOfContourPoints; j = i++) {
 		if (((region[i].y > point.y) != (region[j].y > point.y)) &&
-				((float) point.x < (float)
-				(region[j].x - region[i].x) * (point.y - region[i].y) /
-				(region[j].y - region[i].y) + region[i].x))
+			((float) point.x <
+			 (float) (region[j].x - region[i].x) * (point.y - region[i].y) / (region[j].y - region[i].y) + region[i].x))
 			insideFlag = !insideFlag;
 	}
 
 	return insideFlag;
 }
 
-void catRect(cv::Rect& rectange, const cv::Size& maxSize)
+void catRect(cv::Rect &rectange, const cv::Size &maxSize)
 {
 	if (rectange.width < 0) {
 		rectange.x += rectange.width;
@@ -115,9 +104,7 @@ void catRect(cv::Rect& rectange, const cv::Size& maxSize)
 		rectange.height = maxSize.height - rectange.y;
 }
 
-std::vector<cv::Point2f> contourResize(
-		const std::vector<cv::Point2f>& roi,
-		float scalingCoefficient)
+std::vector<cv::Point2f> contourResize(const std::vector<cv::Point2f> &roi, float scalingCoefficient)
 {
 	const size_t numberOfContourPoints = roi.size();
 	cv::Point2f centre(0, 0);
diff --git a/mv_image/image/src/Recognition/ImageObject.cpp b/mv_image/image/src/Recognition/ImageObject.cpp
index 79f99c9..a13d599 100644
--- a/mv_image/image/src/Recognition/ImageObject.cpp
+++ b/mv_image/image/src/Recognition/ImageObject.cpp
@@ -31,39 +31,33 @@
 #include <unistd.h>
 #include <iomanip>
 
-namespace MediaVision {
-namespace Image {
-ImageObject::ImageObject() :
-		__features(),
-		__isEmpty(true),
-		__isLabeled(false),
-		__label(0)
+namespace MediaVision
+{
+namespace Image
+{
+ImageObject::ImageObject() : __features(), __isEmpty(true), __isLabeled(false), __label(0)
 {
 	; /* NULL */
 }
 
-ImageObject::ImageObject(const cv::Mat& image, const FeaturesExtractingParams& params) :
-		__featureExtractingParams(),
-		__features(),
-		__isEmpty(true),
-		__isLabeled(false),
-		__label(0)
+ImageObject::ImageObject(const cv::Mat &image, const FeaturesExtractingParams &params)
+		: __featureExtractingParams(), __features(), __isEmpty(true), __isLabeled(false), __label(0)
 {
 	fill(image, params);
 }
 
-ImageObject::ImageObject(const ImageObject& copy) :
-		__featureExtractingParams(copy.__featureExtractingParams),
-		__features(copy.__features),
-		__isEmpty(copy.__isEmpty),
-		__isLabeled(copy.__isLabeled),
-		__label(copy.__label),
-		__boundingContour(copy.__boundingContour)
+ImageObject::ImageObject(const ImageObject &copy)
+		: __featureExtractingParams(copy.__featureExtractingParams)
+		, __features(copy.__features)
+		, __isEmpty(copy.__isEmpty)
+		, __isLabeled(copy.__isLabeled)
+		, __label(copy.__label)
+		, __boundingContour(copy.__boundingContour)
 {
 	; /* NULL */
 }
 
-ImageObject& ImageObject::operator=(const ImageObject& copy)
+ImageObject &ImageObject::operator=(const ImageObject &copy)
 {
 	if (this != &copy) {
 		__isEmpty = copy.__isEmpty;
@@ -82,10 +76,8 @@ ImageObject::~ImageObject()
 	; /* NULL */
 }
 
-void ImageObject::fill(
-		const cv::Mat& image,
-		const FeaturesExtractingParams& params,
-		const std::vector<cv::Point2f>& roi)
+void ImageObject::fill(const cv::Mat &image, const FeaturesExtractingParams &params,
+					   const std::vector<cv::Point2f> &roi)
 {
 	__isEmpty = false;
 
@@ -119,27 +111,22 @@ float ImageObject::getRecognitionRate(void) const
 	return __features.__recognitionRate;
 }
 
-void ImageObject::extractFeatures(
-		const cv::Mat& image,
-		const FeaturesExtractingParams& params,
-		const std::vector<cv::Point2f>& roi)
+void ImageObject::extractFeatures(const cv::Mat &image, const FeaturesExtractingParams &params,
+								  const std::vector<cv::Point2f> &roi)
 {
 	/* TODO: It is advisable to consider the distribution of functional */
 
 	cv::Ptr<FeatureExtractor> extractor;
 
-	if (params.mKeypointType == KT_ORB &&
-			params.mDescriptorType == DT_ORB) {
+	if (params.mKeypointType == KT_ORB && params.mDescriptorType == DT_ORB) {
 		ORBExtractorFactory extractorFactory;
 
-		extractorFactory.setScaleFactor((float)params.ORB.mScaleFactor);
+		extractorFactory.setScaleFactor((float) params.ORB.mScaleFactor);
 		extractorFactory.setMaximumFeaturesNumber(params.ORB.mMaximumFeaturesNumber);
 
 		extractor = extractorFactory.buildFeatureExtractor();
 	} else {
-		BasicExtractorFactory extractorFactory(
-				params.mKeypointType,
-				params.mDescriptorType);
+		BasicExtractorFactory extractorFactory(params.mKeypointType, params.mDescriptorType);
 
 		extractor = extractorFactory.buildFeatureExtractor();
 	}
@@ -150,11 +137,10 @@ void ImageObject::extractFeatures(
 
 bool ImageObject::isEmpty() const
 {
-	return (__features.__objectKeypoints.empty() ||
-				__features.__objectDescriptors.empty());
+	return (__features.__objectKeypoints.empty() || __features.__objectDescriptors.empty());
 }
 
-void ImageObject::setContour(const std::vector<cv::Point2f>& contour)
+void ImageObject::setContour(const std::vector<cv::Point2f> &contour)
 {
 	__boundingContour = contour;
 }
@@ -165,7 +151,7 @@ void ImageObject::setLabel(int label)
 	__label = label;
 }
 
-bool ImageObject::getLabel(int& label) const
+bool ImageObject::getLabel(int &label) const
 {
 	if (!__isLabeled) {
 		LOGW("[%s] Image hasn't label.", __FUNCTION__);
@@ -228,7 +214,7 @@ int ImageObject::load(const char *fileName)
 		return MEDIA_VISION_ERROR_PERMISSION_DENIED;
 	}
 
-	in>>(*this);
+	in >> (*this);
 
 	if (!in.good()) {
 		/* TODO: Provide another error code */
@@ -242,7 +228,7 @@ int ImageObject::load(const char *fileName)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-std::ostream& operator << (std::ostream& os, const ImageObject& obj)
+std::ostream &operator<<(std::ostream &os, const ImageObject &obj)
 {
 	os << std::setprecision(7);
 
@@ -275,20 +261,16 @@ std::ostream& operator << (std::ostream& os, const ImageObject& obj)
 	os << sizeOfDescriptor << ' ';
 	os << obj.__features.__objectDescriptors.type() << '\n';
 
-	for (int descriptorNum = 0; descriptorNum < numberOfDescriptors;
-				++descriptorNum, os << '\n') {
-		for (int featureNum = 0; featureNum < sizeOfDescriptor;
-					++featureNum) {
-				os << (int)obj.__features.__objectDescriptors.at<uchar>(
-				descriptorNum,
-				featureNum) << ' ';
+	for (int descriptorNum = 0; descriptorNum < numberOfDescriptors; ++descriptorNum, os << '\n') {
+		for (int featureNum = 0; featureNum < sizeOfDescriptor; ++featureNum) {
+			os << (int) obj.__features.__objectDescriptors.at<uchar>(descriptorNum, featureNum) << ' ';
 		}
 	}
 
 	return os;
 }
 
-std::istream& operator >> (std::istream& is, ImageObject& obj)
+std::istream &operator>>(std::istream &is, ImageObject &obj)
 {
 	size_t numberOfContourPoints = 0u;
 	size_t numberOfKeypoints = 0u;
@@ -298,8 +280,8 @@ std::istream& operator >> (std::istream& is, ImageObject& obj)
 	ImageObject temporal;
 
 #define MEDIA_VISION_CHECK_IFSTREAM \
-	if (!is.good()) { \
-		return is; \
+	if (!is.good()) {               \
+		return is;                  \
 	}
 
 	is >> temporal.__isEmpty;
@@ -352,8 +334,7 @@ std::istream& operator >> (std::istream& is, ImageObject& obj)
 			is >> value;
 			MEDIA_VISION_CHECK_IFSTREAM
 
-			temporal.__features.__objectDescriptors.at<uchar>(descriptorNum, featureNum) =
-					(uchar)value;
+			temporal.__features.__objectDescriptors.at<uchar>(descriptorNum, featureNum) = (uchar) value;
 		}
 	}
 
diff --git a/mv_image/image/src/Recognition/ImageRecognizer.cpp b/mv_image/image/src/Recognition/ImageRecognizer.cpp
index a119009..603ebbe 100644
--- a/mv_image/image/src/Recognition/ImageRecognizer.cpp
+++ b/mv_image/image/src/Recognition/ImageRecognizer.cpp
@@ -20,10 +20,11 @@
 
 #include "mv_private.h"
 
-namespace MediaVision {
-namespace Image {
-ImageRecognizer::ImageRecognizer(const ImageObject& scene) :
-		__scene(scene)
+namespace MediaVision
+{
+namespace Image
+{
+ImageRecognizer::ImageRecognizer(const ImageObject &scene) : __scene(scene)
 {
 	; /* NULL */
 }
@@ -33,11 +34,8 @@ ImageRecognizer::~ImageRecognizer()
 	; /* NULL */
 }
 
-bool ImageRecognizer::recognize(
-		const ImageObject& target,
-		const RecognitionParams& params,
-		std::vector<cv::Point2f>& contour,
-		float ignoreFactor) const
+bool ImageRecognizer::recognize(const ImageObject &target, const RecognitionParams &params,
+								std::vector<cv::Point2f> &contour, float ignoreFactor) const
 {
 	cv::Mat homophraphyMatrix;
 
@@ -53,7 +51,7 @@ bool ImageRecognizer::recognize(
 		return false;
 	}
 
-	if(!findHomophraphyMatrix(target, params, homophraphyMatrix, ignoreFactor)) {
+	if (!findHomophraphyMatrix(target, params, homophraphyMatrix, ignoreFactor)) {
 		LOGE("[%s] Can't match the features.", __FUNCTION__);
 		return false;
 	}
@@ -72,18 +70,12 @@ bool ImageRecognizer::recognize(
 	return true;
 }
 
-bool ImageRecognizer::findHomophraphyMatrix(
-		const ImageObject& target,
-		const RecognitionParams& params,
-		cv::Mat& homophraphyMatrix,
-		float ignoreFactor) const
+bool ImageRecognizer::findHomophraphyMatrix(const ImageObject &target, const RecognitionParams &params,
+											cv::Mat &homophraphyMatrix, float ignoreFactor) const
 {
 	std::vector<cv::DMatch> matches;
 
-	__matcher.match(
-			target.__features.__objectDescriptors,
-			__scene.__features.__objectDescriptors,
-			matches);
+	__matcher.match(target.__features.__objectDescriptors, __scene.__features.__objectDescriptors, matches);
 
 	size_t matchesNumber = matches.size();
 
@@ -92,39 +84,29 @@ bool ImageRecognizer::findHomophraphyMatrix(
 		return false;
 	}
 
-	size_t requiredMatchesNumber =
-			params.mRequiredMatchesPart * matchesNumber;
-
-	size_t allowableMatchesNumberError =
-			params.mTolerantMatchesPartError * requiredMatchesNumber;
-
-	if (matchesNumber - allowableMatchesNumberError >
-			(size_t)params.mMinMatchesNumber &&
-			requiredMatchesNumber + allowableMatchesNumberError <
-			matchesNumber) {
-		if (requiredMatchesNumber - allowableMatchesNumberError <
-				(size_t)params.mMinMatchesNumber) {
-			if (requiredMatchesNumber + allowableMatchesNumberError >
-					(size_t)params.mMinMatchesNumber) {
-				requiredMatchesNumber = ((size_t)params.mMinMatchesNumber +
-						requiredMatchesNumber + allowableMatchesNumberError) / 2;
-
-				allowableMatchesNumberError = requiredMatchesNumber-
-						(size_t)params.mMinMatchesNumber +
-						allowableMatchesNumberError;
+	size_t requiredMatchesNumber = params.mRequiredMatchesPart * matchesNumber;
+
+	size_t allowableMatchesNumberError = params.mTolerantMatchesPartError * requiredMatchesNumber;
+
+	if (matchesNumber - allowableMatchesNumberError > (size_t) params.mMinMatchesNumber &&
+		requiredMatchesNumber + allowableMatchesNumberError < matchesNumber) {
+		if (requiredMatchesNumber - allowableMatchesNumberError < (size_t) params.mMinMatchesNumber) {
+			if (requiredMatchesNumber + allowableMatchesNumberError > (size_t) params.mMinMatchesNumber) {
+				requiredMatchesNumber =
+						((size_t) params.mMinMatchesNumber + requiredMatchesNumber + allowableMatchesNumberError) / 2;
+
+				allowableMatchesNumberError =
+						requiredMatchesNumber - (size_t) params.mMinMatchesNumber + allowableMatchesNumberError;
 			} else {
 				const size_t minimalAllowableMatchesNumberError = 2u;
 
-				requiredMatchesNumber = params.mMinMatchesNumber +
-						minimalAllowableMatchesNumberError;
+				requiredMatchesNumber = params.mMinMatchesNumber + minimalAllowableMatchesNumberError;
 
 				allowableMatchesNumberError = minimalAllowableMatchesNumberError;
 			}
 		}
 
-		const size_t filterAmount = matchesSelection(matches,
-													requiredMatchesNumber,
-													allowableMatchesNumberError);
+		const size_t filterAmount = matchesSelection(matches, requiredMatchesNumber, allowableMatchesNumberError);
 
 		if (filterAmount >= MinimumNumberOfFeatures)
 			matches.resize(filterAmount);
@@ -138,17 +120,13 @@ bool ImageRecognizer::findHomophraphyMatrix(
 	std::vector<cv::Point2f> scenePoints(matchesNumber);
 
 	for (size_t matchIdx = 0; matchIdx < matchesNumber; ++matchIdx) {
-		objectPoints[matchIdx] =
-				target.__features.__objectKeypoints[matches[matchIdx].queryIdx].pt;
+		objectPoints[matchIdx] = target.__features.__objectKeypoints[matches[matchIdx].queryIdx].pt;
 
-		scenePoints[matchIdx] =
-				__scene.__features.__objectKeypoints[matches[matchIdx].trainIdx].pt;
+		scenePoints[matchIdx] = __scene.__features.__objectKeypoints[matches[matchIdx].trainIdx].pt;
 	}
 
 	if (ignoreFactor > FLT_EPSILON) {
-		const std::vector<cv::Point2f> significantArea = contourResize(
-				target.__boundingContour,
-				ignoreFactor);
+		const std::vector<cv::Point2f> significantArea = contourResize(target.__boundingContour, ignoreFactor);
 
 		for (size_t matchIdx = 0; matchIdx < objectPoints.size(); ++matchIdx) {
 			if (!checkAccessory(objectPoints[matchIdx], significantArea)) {
@@ -167,9 +145,8 @@ bool ImageRecognizer::findHomophraphyMatrix(
 	return true;
 }
 
-size_t ImageRecognizer::matchesSelection(
-		std::vector<cv::DMatch>& examples,
-		unsigned int filterAmount, unsigned int allowableError) const
+size_t ImageRecognizer::matchesSelection(std::vector<cv::DMatch> &examples, unsigned int filterAmount,
+										 unsigned int allowableError) const
 {
 	size_t sizeOfExamples = examples.size();
 
@@ -188,25 +165,22 @@ size_t ImageRecognizer::matchesSelection(
 
 	while (true) {
 		if (leftLimit >= rightLimit) {
-			if (leftLimit < (requiredNumber - (int)allowableError))
-				leftLimit = requiredNumber + (int)allowableError;
+			if (leftLimit < (requiredNumber - (int) allowableError))
+				leftLimit = requiredNumber + (int) allowableError;
 
 			break;
 		}
 
-		supportElement = computeLinearSupportElement(examples, requiredNumber,
-					leftLimit, rightLimit);
+		supportElement = computeLinearSupportElement(examples, requiredNumber, leftLimit, rightLimit);
 
 		/* Iteration similar quicksort */
 		while (true) {
 			/* Search the leftmost element which have bigger confidence than support element */
-			while (examples[leftLimit].distance <= supportElement &&
-					leftLimit < startRightLimit)
+			while (examples[leftLimit].distance <= supportElement && leftLimit < startRightLimit)
 				++leftLimit;
 
 			/* Search the rightmost element which have smaller confidence than support element */
-			while (examples[rightLimit].distance >= supportElement &&
-					rightLimit >= startLeftLimit)
+			while (examples[rightLimit].distance >= supportElement && rightLimit >= startLeftLimit)
 				--rightLimit;
 
 			if (leftLimit >= rightLimit)
@@ -219,7 +193,7 @@ size_t ImageRecognizer::matchesSelection(
 		if (std::abs(static_cast<int>(filterAmount - leftLimit)) <= static_cast<int>(allowableError))
 			break;
 
-		if ((int)filterAmount > leftLimit) {
+		if ((int) filterAmount > leftLimit) {
 			requiredNumber -= leftLimit - startLeftLimit;
 
 			rightLimit = startRightLimit;
@@ -230,11 +204,11 @@ size_t ImageRecognizer::matchesSelection(
 		}
 	}
 
-	return (size_t)leftLimit;
+	return (size_t) leftLimit;
 }
 
-float ImageRecognizer::computeLinearSupportElement(const std::vector<cv::DMatch>& examples,
-		int requiredNumber, int leftLimit, int rightLimit) const
+float ImageRecognizer::computeLinearSupportElement(const std::vector<cv::DMatch> &examples, int requiredNumber,
+												   int leftLimit, int rightLimit) const
 {
 	int sizeOfExamples = rightLimit - leftLimit + 1;
 
@@ -263,22 +237,21 @@ float ImageRecognizer::computeLinearSupportElement(const std::vector<cv::DMatch>
 	return k * requiredNumber + b;
 }
 
-bool ImageRecognizer::isPossibleQuadrangleCorners(
-		const cv::Point2f corners[NumberOfQuadrangleCorners])
+bool ImageRecognizer::isPossibleQuadrangleCorners(const cv::Point2f corners[NumberOfQuadrangleCorners])
 {
 	static const float __EPSILON = 0.1f;
 
 	/* TODO: move the __MIN_SIZE_OF_DETECTED_AREA out of the ImageRecognizer */
 	static const float __MIN_SIZE_OF_DETECTED_AREA = 64.f;
 
-	const float firstSemiArea = getTriangleArea(corners[0], corners[2], corners[1]) +
-			getTriangleArea(corners[0], corners[2], corners[3]);
+	const float firstSemiArea =
+			getTriangleArea(corners[0], corners[2], corners[1]) + getTriangleArea(corners[0], corners[2], corners[3]);
 
-	const float secondSemiArea = getTriangleArea(corners[1], corners[3], corners[2]) +
-			getTriangleArea(corners[1], corners[3], corners[0]);
+	const float secondSemiArea =
+			getTriangleArea(corners[1], corners[3], corners[2]) + getTriangleArea(corners[1], corners[3], corners[0]);
 
 	if (__EPSILON < fabs(firstSemiArea - secondSemiArea) ||
-			__MIN_SIZE_OF_DETECTED_AREA > (firstSemiArea + secondSemiArea))
+		__MIN_SIZE_OF_DETECTED_AREA > (firstSemiArea + secondSemiArea))
 		return false;
 
 	return true;
diff --git a/mv_image/image/src/Tracking/AsyncTracker.cpp b/mv_image/image/src/Tracking/AsyncTracker.cpp
index 427814d..c4522b7 100644
--- a/mv_image/image/src/Tracking/AsyncTracker.cpp
+++ b/mv_image/image/src/Tracking/AsyncTracker.cpp
@@ -18,16 +18,17 @@
 
 #include <new>
 
-namespace MediaVision {
-namespace Image {
-
-AsyncTracker::AsyncTracker(const AsyncTracker& copy) :
-		__baseTracker(copy.__baseTracker.get()->clone()),
-		__result(copy.__result),
-		__isRun(false),
-		__isUpdated(copy.__isUpdated),
-		__copyingPolicy(copy.__copyingPolicy),
-		__mvThread(0)
+namespace MediaVision
+{
+namespace Image
+{
+AsyncTracker::AsyncTracker(const AsyncTracker &copy)
+		: __baseTracker(copy.__baseTracker.get()->clone())
+		, __result(copy.__result)
+		, __isRun(false)
+		, __isUpdated(copy.__isUpdated)
+		, __copyingPolicy(copy.__copyingPolicy)
+		, __mvThread(0)
 {
 	pthread_mutex_init(&__globalGuard, NULL);
 	pthread_spin_init(&__resultGuard, PTHREAD_PROCESS_SHARED);
@@ -35,15 +36,13 @@ AsyncTracker::AsyncTracker(const AsyncTracker& copy) :
 	pthread_spin_init(&__isUpdatedGuard, PTHREAD_PROCESS_SHARED);
 }
 
-AsyncTracker::AsyncTracker(
-		cv::Ptr<ObjectTracker> baseTracker,
-		bool copyingPolicy) :
-		__baseTracker(baseTracker),
-		__result(),
-		__isRun(false),
-		__isUpdated(false),
-		__copyingPolicy(copyingPolicy),
-		__mvThread(0)
+AsyncTracker::AsyncTracker(cv::Ptr<ObjectTracker> baseTracker, bool copyingPolicy)
+		: __baseTracker(baseTracker)
+		, __result()
+		, __isRun(false)
+		, __isUpdated(false)
+		, __copyingPolicy(copyingPolicy)
+		, __mvThread(0)
 {
 	pthread_mutex_init(&__globalGuard, NULL);
 	pthread_spin_init(&__resultGuard, PTHREAD_PROCESS_SHARED);
@@ -53,7 +52,7 @@ AsyncTracker::AsyncTracker(
 
 AsyncTracker::~AsyncTracker()
 {
-	if(isRun()) {
+	if (isRun()) {
 		pthread_mutex_lock(&__globalGuard);
 		pthread_mutex_unlock(&__globalGuard);
 	}
@@ -64,9 +63,7 @@ AsyncTracker::~AsyncTracker()
 	pthread_spin_destroy(&__isUpdatedGuard);
 }
 
-bool AsyncTracker::track(
-		const cv::Mat& frame,
-		std::vector<cv::Point>& result)
+bool AsyncTracker::track(const cv::Mat &frame, std::vector<cv::Point> &result)
 {
 	while (pthread_mutex_trylock(&__globalGuard) != 0)
 		return getResult(result);
@@ -96,7 +93,7 @@ bool AsyncTracker::track(
 	return getResult(result);
 }
 
-void AsyncTracker::reinforcement(const std::vector<cv::Point>& location)
+void AsyncTracker::reinforcement(const std::vector<cv::Point> &location)
 {
 	/* TODO: Unsafe. Need to redesign. */
 	__baseTracker->reinforcement(location);
@@ -108,17 +105,17 @@ void AsyncTracker::reinforcement(const std::vector<cv::Point>& location)
 
 cv::Ptr<ObjectTracker> AsyncTracker::clone() const
 {
-	return cv::Ptr<ObjectTracker>(new (std::nothrow)AsyncTracker(*this));
+	return cv::Ptr<ObjectTracker>(new (std::nothrow) AsyncTracker(*this));
 }
 
-bool AsyncTracker::baseTrack(std::vector<cv::Point>& result)
+bool AsyncTracker::baseTrack(std::vector<cv::Point> &result)
 {
 	return __baseTracker->track(__frame, result);
 }
 
 void *AsyncTracker::asyncTrack(void *data)
 {
-	AsyncTracker *tracker = reinterpret_cast<AsyncTracker*>(data);
+	AsyncTracker *tracker = reinterpret_cast<AsyncTracker *>(data);
 
 	std::vector<cv::Point> result;
 	tracker->baseTrack(result);
@@ -142,7 +139,7 @@ void *AsyncTracker::asyncTrack(void *data)
 
 bool AsyncTracker::wait()
 {
-	if(isRun()) {
+	if (isRun()) {
 		pthread_mutex_lock(&__globalGuard);
 		pthread_mutex_unlock(&__globalGuard);
 		return true;
@@ -161,7 +158,7 @@ bool AsyncTracker::isRun()
 	return result;
 }
 
-bool AsyncTracker::isUpdated(std::vector<cv::Point>& result)
+bool AsyncTracker::isUpdated(std::vector<cv::Point> &result)
 {
 	bool isUpdated = false;
 
@@ -175,7 +172,7 @@ bool AsyncTracker::isUpdated(std::vector<cv::Point>& result)
 	return isUpdated;
 }
 
-bool AsyncTracker::getResult(std::vector<cv::Point>& result)
+bool AsyncTracker::getResult(std::vector<cv::Point> &result)
 {
 	bool isTracked = false;
 
diff --git a/mv_image/image/src/Tracking/CascadeTracker.cpp b/mv_image/image/src/Tracking/CascadeTracker.cpp
index a60bbb2..2db13af 100644
--- a/mv_image/image/src/Tracking/CascadeTracker.cpp
+++ b/mv_image/image/src/Tracking/CascadeTracker.cpp
@@ -20,19 +20,16 @@
 #include "ImageMathUtil.h"
 #include <new>
 
-namespace MediaVision {
-namespace Image {
-
-CascadeTracker::CascadeTracker(float minimumArea) :
-		__trackers(),
-		__minimumArea(minimumArea)
+namespace MediaVision
+{
+namespace Image
+{
+CascadeTracker::CascadeTracker(float minimumArea) : __trackers(), __minimumArea(minimumArea)
 {
 	; /* NULL */
 }
 
-CascadeTracker::CascadeTracker(const CascadeTracker& copy) :
-		__trackers(),
-		__minimumArea(copy.__minimumArea)
+CascadeTracker::CascadeTracker(const CascadeTracker &copy) : __trackers(), __minimumArea(copy.__minimumArea)
 {
 	*this = copy;
 }
@@ -42,7 +39,7 @@ CascadeTracker::~CascadeTracker()
 	; /* NULL */
 }
 
-bool CascadeTracker::track(const cv::Mat& frame, std::vector<cv::Point>& result)
+bool CascadeTracker::track(const cv::Mat &frame, std::vector<cv::Point> &result)
 {
 	internalReinforcement();
 
@@ -55,7 +52,7 @@ bool CascadeTracker::track(const cv::Mat& frame, std::vector<cv::Point>& result)
 	return mergeResults(result);
 }
 
-void CascadeTracker::reinforcement(const std::vector<cv::Point>& location)
+void CascadeTracker::reinforcement(const std::vector<cv::Point> &location)
 {
 	std::set<TrackerInfo>::iterator it = __trackers.begin();
 
@@ -65,10 +62,10 @@ void CascadeTracker::reinforcement(const std::vector<cv::Point>& location)
 
 cv::Ptr<ObjectTracker> CascadeTracker::clone() const
 {
-	return cv::Ptr<ObjectTracker>(new (std::nothrow)CascadeTracker(*this));
+	return cv::Ptr<ObjectTracker>(new (std::nothrow) CascadeTracker(*this));
 }
 
-CascadeTracker& CascadeTracker::operator=(const CascadeTracker& copy)
+CascadeTracker &CascadeTracker::operator=(const CascadeTracker &copy)
 {
 	if (this != &copy) {
 		this->__minimumArea = copy.__minimumArea;
@@ -90,8 +87,7 @@ bool CascadeTracker::enableTracker(cv::Ptr<ObjectTracker> tracker, float priorit
 {
 	TrackerInfo temp(tracker, priority);
 
-	std::set<TrackerInfo>::iterator it =
-			std::find(__trackers.begin(), __trackers.end(), temp);
+	std::set<TrackerInfo>::iterator it = std::find(__trackers.begin(), __trackers.end(), temp);
 
 	if (it != __trackers.end())
 		__trackers.erase(it);
@@ -103,8 +99,7 @@ bool CascadeTracker::disableTracker(cv::Ptr<ObjectTracker> tracker)
 {
 	TrackerInfo target(tracker, 0);
 
-	std::set<TrackerInfo>::iterator it =
-			std::find(__trackers.begin(), __trackers.end(), target);
+	std::set<TrackerInfo>::iterator it = std::find(__trackers.begin(), __trackers.end(), target);
 
 	if (it == __trackers.end())
 		return false;
@@ -121,7 +116,7 @@ void CascadeTracker::internalReinforcement()
 		bool isUpdated = true;
 
 		/* TODO: Redesign without dynamic_cast */
-		AsyncTracker *asyncView = dynamic_cast<AsyncTracker*>(it1->mTracker.get());
+		AsyncTracker *asyncView = dynamic_cast<AsyncTracker *>(it1->mTracker.get());
 		if (NULL != asyncView)
 			isUpdated = asyncView->isUpdated(it1->mResult);
 
@@ -143,12 +138,12 @@ void CascadeTracker::internalReinforcement()
 
 			for (; it2 != __trackers.end(); ++it2)
 				if (it1 != it2 && priority > it2->mPriority)
-					 it2->mTracker.get()->reinforcement(it1->mResult);
+					it2->mTracker.get()->reinforcement(it1->mResult);
 		}
 	}
 }
 
-bool CascadeTracker::mergeResults(std::vector<cv::Point>& result) const
+bool CascadeTracker::mergeResults(std::vector<cv::Point> &result) const
 {
 	result.clear();
 
@@ -165,25 +160,23 @@ bool CascadeTracker::mergeResults(std::vector<cv::Point>& result) const
 	return !(result.empty());
 }
 
-CascadeTracker::TrackerInfo::TrackerInfo(cv::Ptr<ObjectTracker> tracker, float priority) :
-		mTracker(tracker),
-		mPriority(priority),
-		mResult()
+CascadeTracker::TrackerInfo::TrackerInfo(cv::Ptr<ObjectTracker> tracker, float priority)
+		: mTracker(tracker), mPriority(priority), mResult()
 {
 	; /* NULL */
 }
 
-bool CascadeTracker::TrackerInfo::operator<(const TrackerInfo& second) const
+bool CascadeTracker::TrackerInfo::operator<(const TrackerInfo &second) const
 {
 	return (this->mPriority < second.mPriority);
 }
 
-bool CascadeTracker::TrackerInfo::operator==(const TrackerInfo& second) const
+bool CascadeTracker::TrackerInfo::operator==(const TrackerInfo &second) const
 {
 	return (this->mTracker == second.mTracker);
 }
 
-bool CascadeTracker::TrackerInfo::operator!=(const TrackerInfo& second) const
+bool CascadeTracker::TrackerInfo::operator!=(const TrackerInfo &second) const
 {
 	return !(*this == second);
 }
diff --git a/mv_image/image/src/Tracking/FeatureSubstitutionTracker.cpp b/mv_image/image/src/Tracking/FeatureSubstitutionTracker.cpp
index b6e10fc..6b8e39c 100644
--- a/mv_image/image/src/Tracking/FeatureSubstitutionTracker.cpp
+++ b/mv_image/image/src/Tracking/FeatureSubstitutionTracker.cpp
@@ -20,30 +20,26 @@
 
 #include <new>
 
-namespace MediaVision {
-namespace Image {
-
-FeatureSubstitutionTracker::FeatureSubstitutionTracker(
-		const FeaturesExtractingParams& featuresExtractingParams,
-		const RecognitionParams& recognitionParams,
-		float expectedOffset,
-		float sceneScalingFactor,
-		float objectScalingFactor) :
-				__isInit(false),
-				__target(),
-				__location(),
-				__featureExtractingParams(featuresExtractingParams),
-				__recogParams(recognitionParams),
-				__expectedOffset(expectedOffset),
-				__sceneScalingFactor(sceneScalingFactor),
-				__objectScalingFactor(objectScalingFactor)
+namespace MediaVision
+{
+namespace Image
+{
+FeatureSubstitutionTracker::FeatureSubstitutionTracker(const FeaturesExtractingParams &featuresExtractingParams,
+													   const RecognitionParams &recognitionParams, float expectedOffset,
+													   float sceneScalingFactor, float objectScalingFactor)
+		: __isInit(false)
+		, __target()
+		, __location()
+		, __featureExtractingParams(featuresExtractingParams)
+		, __recogParams(recognitionParams)
+		, __expectedOffset(expectedOffset)
+		, __sceneScalingFactor(sceneScalingFactor)
+		, __objectScalingFactor(objectScalingFactor)
 {
 	; /* NULL */
 }
 
-bool FeatureSubstitutionTracker::track(
-		const cv::Mat& frame,
-		std::vector<cv::Point>& result)
+bool FeatureSubstitutionTracker::track(const cv::Mat &frame, std::vector<cv::Point> &result)
 {
 	std::vector<cv::Point2f> contour;
 	size_t numberOfContourPoints = __location.size();
@@ -57,14 +53,11 @@ bool FeatureSubstitutionTracker::track(
 		if (__location.empty()) {
 			return false;
 		} else {
-			__target = new (std::nothrow)ImageObject;
+			__target = new (std::nothrow) ImageObject;
 			if (__target == NULL)
 				return false;
 
-			__target->fill(
-					frame,
-					__featureExtractingParams,
-					contourResize(contour, __objectScalingFactor));
+			__target->fill(frame, __featureExtractingParams, contourResize(contour, __objectScalingFactor));
 			__target->setContour(contour);
 			__isInit = true;
 			result = __location;
@@ -72,7 +65,7 @@ bool FeatureSubstitutionTracker::track(
 		}
 	}
 
-	cv::Ptr<ImageObject> sceneImageObject = new (std::nothrow)ImageObject;
+	cv::Ptr<ImageObject> sceneImageObject = new (std::nothrow) ImageObject;
 	if (sceneImageObject == NULL)
 		return false;
 
@@ -80,19 +73,14 @@ bool FeatureSubstitutionTracker::track(
 
 	ImageRecognizer recognizer(*sceneImageObject.get());
 
-	const bool isTracked =
-			recognizer.recognize(
-					*(__target.get()),
-					__recogParams,
-					contour,
-					__objectScalingFactor);
+	const bool isTracked = recognizer.recognize(*(__target.get()), __recogParams, contour, __objectScalingFactor);
 
 	if (isTracked) {
 		numberOfContourPoints = contour.size();
 		__location.resize(numberOfContourPoints);
 		for (size_t i = 0u; i < numberOfContourPoints; ++i) {
-			__location[i].x = (int)contour[i].x;
-			__location[i].y = (int)contour[i].y;
+			__location[i].x = (int) contour[i].x;
+			__location[i].y = (int) contour[i].y;
 		}
 
 		result = __location;
@@ -106,7 +94,7 @@ bool FeatureSubstitutionTracker::track(
 	return isTracked;
 }
 
-void FeatureSubstitutionTracker::reinforcement(const std::vector<cv::Point>& location)
+void FeatureSubstitutionTracker::reinforcement(const std::vector<cv::Point> &location)
 {
 	__isInit = false;
 
@@ -120,7 +108,7 @@ void FeatureSubstitutionTracker::reinforcement(const std::vector<cv::Point>& loc
 
 cv::Ptr<ObjectTracker> FeatureSubstitutionTracker::clone() const
 {
-	return cv::Ptr<ObjectTracker>(new (std::nothrow)FeatureSubstitutionTracker(*this));
+	return cv::Ptr<ObjectTracker>(new (std::nothrow) FeatureSubstitutionTracker(*this));
 }
 
 std::vector<cv::Point2f> FeatureSubstitutionTracker::computeExpectedArea()
diff --git a/mv_image/image/src/Tracking/ImageContourStabilizator.cpp b/mv_image/image/src/Tracking/ImageContourStabilizator.cpp
index 87a6c20..4651eb3 100644
--- a/mv_image/image/src/Tracking/ImageContourStabilizator.cpp
+++ b/mv_image/image/src/Tracking/ImageContourStabilizator.cpp
@@ -20,12 +20,11 @@
 
 #include "mv_private.h"
 
-namespace MediaVision {
-namespace Image {
-
-ImageContourStabilizator::ImageContourStabilizator() :
-		__movingHistory(),
-		__priorities()
+namespace MediaVision
+{
+namespace Image
+{
+ImageContourStabilizator::ImageContourStabilizator() : __movingHistory(), __priorities()
 {
 	reset();
 }
@@ -41,9 +40,8 @@ void ImageContourStabilizator::reset(void)
 	__movingHistory.clear();
 }
 
-ImageContourStabilizator::StabilizationError ImageContourStabilizator::stabilize(
-		std::vector<cv::Point2f>& contour,
-		const StabilizationParams& params)
+ImageContourStabilizator::StabilizationError ImageContourStabilizator::stabilize(std::vector<cv::Point2f> &contour,
+																				 const StabilizationParams &params)
 {
 	if (!updateSettings(params)) {
 		LOGW("Not stabilized. Invalid settings.");
@@ -112,8 +110,7 @@ ImageContourStabilizator::StabilizationError ImageContourStabilizator::stabilize
 		stabilizedState = __lastStabilizedContour;
 	}
 
-	const float tolerantShift = getQuadrangleArea(contour.data()) *
-				__tolerantShift + __tolerantShiftExtra;
+	const float tolerantShift = getQuadrangleArea(contour.data()) * __tolerantShift + __tolerantShiftExtra;
 
 	const size_t contourSize = stabilizedState.size();
 	for (size_t i = 0u; i < contourSize; ++i) {
@@ -143,13 +140,13 @@ ImageContourStabilizator::StabilizationError ImageContourStabilizator::stabilize
 	return Successfully;
 }
 
-bool ImageContourStabilizator::updateSettings(const StabilizationParams& params)
+bool ImageContourStabilizator::updateSettings(const StabilizationParams &params)
 {
 	if (params.mHistoryAmount < 1)
 		return false;
 
-	__tolerantShift = (float)params.mTolerantShift;
-	__tolerantShiftExtra = (float)params.mTolerantShiftExtra;
+	__tolerantShift = (float) params.mTolerantShift;
+	__tolerantShiftExtra = (float) params.mTolerantShiftExtra;
 
 	if (__historyAmount != params.mHistoryAmount) {
 		__historyAmount = params.mHistoryAmount;
@@ -159,8 +156,7 @@ bool ImageContourStabilizator::updateSettings(const StabilizationParams& params)
 		/* calculation of priorities for positions in the moving history */
 		for (size_t i = 0u; i < __historyAmount; ++i) {
 			/* linear dependence on the elapsed time */
-			__priorities[i] = ((i + 1) * 2.0f) /
-						((__historyAmount + 1) * __historyAmount);
+			__priorities[i] = ((i + 1) * 2.0f) / ((__historyAmount + 1) * __historyAmount);
 		}
 	}
 
@@ -181,8 +177,7 @@ bool ImageContourStabilizator::updateSettings(const StabilizationParams& params)
 	if (__speeds.size() > 1) {
 		const static float __EPSILON = 0.0001f;
 		if (fabs(__speeds[0] - params.mStabilizationSpeed) < __EPSILON &&
-				fabs((__speeds[1] - __speeds[0]) -
-				params.mStabilizationAcceleration) < __EPSILON) {
+			fabs((__speeds[1] - __speeds[0]) - params.mStabilizationAcceleration) < __EPSILON) {
 			speedIsValid = true;
 		}
 	}
@@ -190,8 +185,7 @@ bool ImageContourStabilizator::updateSettings(const StabilizationParams& params)
 	if (!speedIsValid) {
 		__speeds.clear();
 
-		int speedsSize = (int)((1 - params.mStabilizationSpeed) /
-					params.mStabilizationAcceleration) + 1;
+		int speedsSize = (int) ((1 - params.mStabilizationSpeed) / params.mStabilizationAcceleration) + 1;
 
 		if (speedsSize < 1) {
 			__speeds.push_back(1.0f);
@@ -201,8 +195,7 @@ bool ImageContourStabilizator::updateSettings(const StabilizationParams& params)
 			if (speedsSize > MAX_SPEED_SIZE)
 				speedsSize = MAX_SPEED_SIZE;
 
-			float speed = std::max(0.f,
-					std::min((float)params.mStabilizationSpeed, 1.0f));
+			float speed = std::max(0.f, std::min((float) params.mStabilizationSpeed, 1.0f));
 
 			for (int i = 0; i < speedsSize; ++i) {
 				__speeds.push_back(speed);
@@ -217,12 +210,10 @@ bool ImageContourStabilizator::updateSettings(const StabilizationParams& params)
 std::vector<cv::Point2f> ImageContourStabilizator::computeStabilizedQuadrangleContour(void)
 {
 	/* final contour */
-	std::vector<cv::Point2f> stabilizedState(
-				NumberOfQuadrangleCorners, cv::Point2f(0.f, 0.f));
+	std::vector<cv::Point2f> stabilizedState(NumberOfQuadrangleCorners, cv::Point2f(0.f, 0.f));
 
 	/* calculation the direction of contour corners to a new location */
-	std::vector<cv::Point2f> directions(
-				NumberOfQuadrangleCorners, cv::Point2f(0.f, 0.f));
+	std::vector<cv::Point2f> directions(NumberOfQuadrangleCorners, cv::Point2f(0.f, 0.f));
 
 	/* computing expected directions and outliers searching */
 	bool expressiveTime = false;
@@ -235,13 +226,11 @@ std::vector<cv::Point2f> ImageContourStabilizator::computeStabilizedQuadrangleCo
 		cv::Point2f averageDirections(0.f, 0.f);
 
 		for (size_t i = 0u; i < __historyAmount - 1; ++i) {
-			averageDirections.x += (trackDirections[i].x =
-					__movingHistory[i+1][j].x - __movingHistory[i][j].x) /
-					(__historyAmount - 1);
+			averageDirections.x += (trackDirections[i].x = __movingHistory[i + 1][j].x - __movingHistory[i][j].x) /
+								   (__historyAmount - 1);
 
-			averageDirections.y += (trackDirections[i].y =
-					__movingHistory[i+1][j].y - __movingHistory[i][j].y) /
-					(__historyAmount - 1);
+			averageDirections.y += (trackDirections[i].y = __movingHistory[i + 1][j].y - __movingHistory[i][j].y) /
+								   (__historyAmount - 1);
 		}
 
 		/* calculation a deviations and select outlier */
@@ -250,9 +239,7 @@ std::vector<cv::Point2f> ImageContourStabilizator::computeStabilizedQuadrangleCo
 		int idxWithMaxDistance = 0;
 		int numExpressiveDirection = -1;
 		for (size_t i = 0u; i < __historyAmount - 1; ++i) {
-			directionDistances[i] = getDistance(
-					trackDirections[i],
-					averageDirections);
+			directionDistances[i] = getDistance(trackDirections[i], averageDirections);
 
 			if (directionDistances[i] > prevMaxDistance) {
 				if (directionDistances[i] > maxDistance) {
@@ -275,28 +262,24 @@ std::vector<cv::Point2f> ImageContourStabilizator::computeStabilizedQuadrangleCo
 		/* final direction computing */
 		float summPriority = 0.f;
 		for (size_t i = 0u; i < __historyAmount - 1; ++i) {
-			if ((int)i != numExpressiveDirection) {
+			if ((int) i != numExpressiveDirection) {
 				directions[j].x += trackDirections[i].x * __priorities[i];
 				directions[j].y += trackDirections[i].y * __priorities[i];
 				summPriority += __priorities[i];
 			}
 		}
 
-		if (numExpressiveDirection == (int)(__historyAmount - 1))
+		if (numExpressiveDirection == (int) (__historyAmount - 1))
 			expressiveTime = true;
 
 		summPriorityWithoutToLastPos[j] = summPriority;
 		priorityToLastPos[j] = __priorities[__historyAmount - 1];
 
 		directions[j].x -= directionsToLastPos[j].x =
-					(__lastStabilizedContour[j].x -
-					__movingHistory[__historyAmount - 1][j].x) *
-					priorityToLastPos[j];
+				(__lastStabilizedContour[j].x - __movingHistory[__historyAmount - 1][j].x) * priorityToLastPos[j];
 
 		directions[j].y -= directionsToLastPos[j].y =
-					(__lastStabilizedContour[j].y -
-					__movingHistory[__historyAmount - 1][j].y) *
-					priorityToLastPos[j];
+				(__lastStabilizedContour[j].y - __movingHistory[__historyAmount - 1][j].y) * priorityToLastPos[j];
 
 		summPriority += priorityToLastPos[j];
 
@@ -307,13 +290,11 @@ std::vector<cv::Point2f> ImageContourStabilizator::computeStabilizedQuadrangleCo
 	/* final corners computing */
 	for (size_t j = 0u; j < NumberOfQuadrangleCorners; ++j) {
 		if (expressiveTime) {
-			directions[j].x *= (summPriorityWithoutToLastPos[j] +
-						priorityToLastPos[j]);
+			directions[j].x *= (summPriorityWithoutToLastPos[j] + priorityToLastPos[j]);
 			directions[j].x -= directionsToLastPos[j].x;
 			directions[j].x /= summPriorityWithoutToLastPos[j];
 
-			directions[j].y *= (summPriorityWithoutToLastPos[j] +
-						priorityToLastPos[j]);
+			directions[j].y *= (summPriorityWithoutToLastPos[j] + priorityToLastPos[j]);
 			directions[j].y -= directionsToLastPos[j].y;
 			directions[j].y /= summPriorityWithoutToLastPos[j];
 		}
diff --git a/mv_image/image/src/Tracking/ImageTrackingModel.cpp b/mv_image/image/src/Tracking/ImageTrackingModel.cpp
index ba83581..bae97dd 100644
--- a/mv_image/image/src/Tracking/ImageTrackingModel.cpp
+++ b/mv_image/image/src/Tracking/ImageTrackingModel.cpp
@@ -30,31 +30,28 @@
 #include <new>
 #include <iomanip>
 
-namespace MediaVision {
-namespace Image {
-
-ImageTrackingModel::ImageTrackingModel() :
-		__target(),
-		__tracker(),
-		__stabilizator(),
-		__location(),
-		__stabilizationParams()
+namespace MediaVision
+{
+namespace Image
+{
+ImageTrackingModel::ImageTrackingModel()
+		: __target(), __tracker(), __stabilizator(), __location(), __stabilizationParams()
 {
 	; /* NULL */
 }
 
-ImageTrackingModel::ImageTrackingModel(const ImageTrackingModel& copy) :
-		__target(copy.__target),
-		__stabilizator(copy.__stabilizator),
-		__location(copy.__location),
-		__stabilizationParams(copy.__stabilizationParams)
+ImageTrackingModel::ImageTrackingModel(const ImageTrackingModel &copy)
+		: __target(copy.__target)
+		, __stabilizator(copy.__stabilizator)
+		, __location(copy.__location)
+		, __stabilizationParams(copy.__stabilizationParams)
 {
 	if (!copy.__tracker.empty())
 		__tracker = copy.__tracker->clone();
 	/* NULL */
 }
 
-int ImageTrackingModel::setTarget(const ImageObject& target)
+int ImageTrackingModel::setTarget(const ImageObject &target)
 {
 	/* TODO: Here are all the settings.
 	 *        This can be transferred to configuration file.
@@ -117,7 +114,7 @@ int ImageTrackingModel::setTarget(const ImageObject& target)
 
 	/* Creating a basic tracker which will have other trackers */
 
-	cv::Ptr<CascadeTracker> mainTracker = new (std::nothrow)CascadeTracker;
+	cv::Ptr<CascadeTracker> mainTracker = new (std::nothrow) CascadeTracker;
 	if (mainTracker == NULL) {
 		LOGE("Failed to create mainTracker");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
@@ -125,56 +122,37 @@ int ImageTrackingModel::setTarget(const ImageObject& target)
 
 	/* Adding asynchronous recognition based tracker */
 
-	cv::Ptr<RecognitionBasedTracker> recogTracker =
-			new (std::nothrow)RecognitionBasedTracker(
-					target,
-					orbFeatureExtractingParams,
-					orbRecogParams);
+	cv::Ptr<RecognitionBasedTracker> recogTracker = new (std::nothrow)
+			RecognitionBasedTracker(target, orbFeatureExtractingParams, orbRecogParams);
 	if (recogTracker == NULL)
 		LOGE("Failed to create Recognition Tracker");
 
-	cv::Ptr<AsyncTracker> asyncRecogTracker =
-			new (std::nothrow)AsyncTracker(
-					recogTracker,
-					true);
+	cv::Ptr<AsyncTracker> asyncRecogTracker = new (std::nothrow) AsyncTracker(recogTracker, true);
 	if (asyncRecogTracker == NULL)
 		LOGE("Failed to create Async Recognition Tracker");
 
-	mainTracker->enableTracker(
-			asyncRecogTracker,
-			recognitionBasedTrackerPriotity);
+	mainTracker->enableTracker(asyncRecogTracker, recognitionBasedTrackerPriotity);
 
 	/* Adding asynchronous feature substitution based tracker */
 
-	cv::Ptr<FeatureSubstitutionTracker> substitutionTracker =
-			new (std::nothrow)FeatureSubstitutionTracker(
-					gfttWbriefFeatureExtractingParams,
-					gfttWbriefRecogParams,
-					expectedOffset);
+	cv::Ptr<FeatureSubstitutionTracker> substitutionTracker = new (std::nothrow)
+			FeatureSubstitutionTracker(gfttWbriefFeatureExtractingParams, gfttWbriefRecogParams, expectedOffset);
 	if (substitutionTracker == NULL)
 		LOGE("Failed to create Substitution Tracker");
 
-	cv::Ptr<AsyncTracker> asyncSubstitutionTracker =
-			new (std::nothrow)AsyncTracker(
-					substitutionTracker,
-					true);
+	cv::Ptr<AsyncTracker> asyncSubstitutionTracker = new (std::nothrow) AsyncTracker(substitutionTracker, true);
 	if (asyncSubstitutionTracker == NULL)
 		LOGE("Failed to create Async Substitution Tracker");
 
-	mainTracker->enableTracker(
-			asyncSubstitutionTracker,
-			featureSubstitutionTrackerPriotity);
+	mainTracker->enableTracker(asyncSubstitutionTracker, featureSubstitutionTrackerPriotity);
 
 	/* Adding median flow tracker */
 
-	cv::Ptr<MFTracker> mfTracker = new (std::nothrow)MFTracker(
-			medianflowTrackingParams);
+	cv::Ptr<MFTracker> mfTracker = new (std::nothrow) MFTracker(medianflowTrackingParams);
 	if (mfTracker == NULL)
 		LOGE("Failed to create MFTracker");
 
-	mainTracker->enableTracker(
-			mfTracker,
-			medianFlowTrackerPriotity);
+	mainTracker->enableTracker(mfTracker, medianFlowTrackerPriotity);
 
 	__tracker = mainTracker;
 	__target = target;
@@ -187,7 +165,7 @@ bool ImageTrackingModel::isValid() const
 	return !(__target.isEmpty());
 }
 
-bool ImageTrackingModel::track(const cv::Mat& frame, std::vector<cv::Point>& result)
+bool ImageTrackingModel::track(const cv::Mat &frame, std::vector<cv::Point> &result)
 {
 	result.clear();
 
@@ -202,14 +180,14 @@ bool ImageTrackingModel::track(const cv::Mat& frame, std::vector<cv::Point>& res
 	const size_t numberOfContourPoints = __location.size();
 	std::vector<cv::Point2f> stabilizedContour(numberOfContourPoints);
 	for (size_t i = 0; i < numberOfContourPoints; ++i) {
-		stabilizedContour[i].x = (float)__location[i].x;
-		stabilizedContour[i].y = (float)__location[i].y;
+		stabilizedContour[i].x = (float) __location[i].x;
+		stabilizedContour[i].y = (float) __location[i].y;
 	}
 
 	__stabilizator.stabilize(stabilizedContour, __stabilizationParams);
 	for (size_t i = 0; i < numberOfContourPoints; ++i) {
-		__location[i].x = (int)stabilizedContour[i].x;
-		__location[i].y = (int)stabilizedContour[i].y;
+		__location[i].x = (int) stabilizedContour[i].x;
+		__location[i].y = (int) stabilizedContour[i].y;
 	}
 
 	result = __location;
@@ -222,7 +200,7 @@ void ImageTrackingModel::refresh(void)
 	__location.clear();
 }
 
-ImageTrackingModel& ImageTrackingModel::operator=(const ImageTrackingModel& copy)
+ImageTrackingModel &ImageTrackingModel::operator=(const ImageTrackingModel &copy)
 {
 	if (this != &copy) {
 		__target = copy.__target;
@@ -291,7 +269,7 @@ int ImageTrackingModel::load(const char *filepath)
 		return MEDIA_VISION_ERROR_PERMISSION_DENIED;
 	}
 
-	in>>(*this);
+	in >> (*this);
 
 	if (!in.good()) {
 		LOGE("[%s] Unexpected end of file.", __FUNCTION__);
@@ -304,7 +282,7 @@ int ImageTrackingModel::load(const char *filepath)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-std::ostream& operator << (std::ostream& os, const ImageTrackingModel& obj)
+std::ostream &operator<<(std::ostream &os, const ImageTrackingModel &obj)
 {
 	os << std::setprecision(7);
 
@@ -326,10 +304,10 @@ std::ostream& operator << (std::ostream& os, const ImageTrackingModel& obj)
 	return os;
 }
 
-std::istream& operator >> (std::istream& is, ImageTrackingModel& obj)
+std::istream &operator>>(std::istream &is, ImageTrackingModel &obj)
 {
 #define MEDIA_VISION_CHECK_IFSTREAM \
-	if (!is.good()) \
+	if (!is.good())                 \
 		return is;
 
 	ImageObject target;
diff --git a/mv_image/image/src/Tracking/MFTracker.cpp b/mv_image/image/src/Tracking/MFTracker.cpp
index 72695b2..969f00d 100644
--- a/mv_image/image/src/Tracking/MFTracker.cpp
+++ b/mv_image/image/src/Tracking/MFTracker.cpp
@@ -19,22 +19,23 @@
 #include "opencv2/video/tracking.hpp"
 #include "opencv2/imgproc.hpp"
 
-namespace MediaVision {
-namespace Image {
-
-namespace {
+namespace MediaVision
+{
+namespace Image
+{
+namespace
+{
 const float FLOATEPS = 10e-6f;
 
-template<typename T>
-T getMedian(std::vector<T>& values, int size = -1)
+template<typename T> T getMedian(std::vector<T> &values, int size = -1)
 {
 	if (size == -1)
-		size = (int)values.size();
+		size = (int) values.size();
 
 	std::vector<T> copy(values.begin(), values.begin() + size);
 	std::sort(copy.begin(), copy.end());
-	if (size%2 == 0) {
-		return (copy[size / 2 - 1] + copy[size/2]) / ((T)2.0);
+	if (size % 2 == 0) {
+		return (copy[size / 2 - 1] + copy[size / 2]) / ((T) 2.0);
 	} else {
 		return copy[(size - 1) / 2];
 	}
@@ -55,15 +56,14 @@ MFTracker::Params::Params()
 	mPyrMaxLevel = 5;
 }
 
-MFTracker::MFTracker(Params params) :
-		__isInit(false),
-		__params(params),
-		__termcrit(cv::TermCriteria::COUNT | cv::TermCriteria::EPS, 20, 0.3),
-		__confidence(0.0f)
-{
-}
+MFTracker::MFTracker(Params params)
+		: __isInit(false)
+		, __params(params)
+		, __termcrit(cv::TermCriteria::COUNT | cv::TermCriteria::EPS, 20, 0.3)
+		, __confidence(0.0f)
+{}
 
-bool MFTracker::track(const cv::Mat& frame, std::vector<cv::Point>& result)
+bool MFTracker::track(const cv::Mat &frame, std::vector<cv::Point> &result)
 {
 	result.clear();
 
@@ -85,16 +85,14 @@ bool MFTracker::track(const cv::Mat& frame, std::vector<cv::Point>& result)
 	result.resize(numberOfContourPoints);
 
 	for (size_t i = 0; i < numberOfContourPoints; ++i) {
-		result[i].x = static_cast<int>(__boundingBox.x +
-							__startLocation[i].x * __boundingBox.width);
-		result[i].y = static_cast<int>(__boundingBox.y +
-							__startLocation[i].y * __boundingBox.height);
+		result[i].x = static_cast<int>(__boundingBox.x + __startLocation[i].x * __boundingBox.width);
+		result[i].y = static_cast<int>(__boundingBox.y + __startLocation[i].y * __boundingBox.height);
 	}
 
 	return true;
 }
 
-void MFTracker::reinforcement(const std::vector<cv::Point>& location)
+void MFTracker::reinforcement(const std::vector<cv::Point> &location)
 {
 	__isInit = false;
 
@@ -108,7 +106,7 @@ void MFTracker::reinforcement(const std::vector<cv::Point>& location)
 		return;
 	}
 
-	const cv::Rect_<float>& boundingBox = cv::boundingRect(location);
+	const cv::Rect_<float> &boundingBox = cv::boundingRect(location);
 	__boundingBox = boundingBox;
 
 	const size_t numberOfContourPoints = location.size();
@@ -121,26 +119,22 @@ void MFTracker::reinforcement(const std::vector<cv::Point>& location)
 
 cv::Ptr<ObjectTracker> MFTracker::clone() const
 {
-	return cv::Ptr<ObjectTracker>(new (std::nothrow)MFTracker(*this));
+	return cv::Ptr<ObjectTracker>(new (std::nothrow) MFTracker(*this));
 }
 
-bool MFTracker::init(const cv::Mat& image)
+bool MFTracker::init(const cv::Mat &image)
 {
 	if (image.empty())
 		return false;
 
 	image.copyTo(__image);
-	buildOpticalFlowPyramid(
-			__image,
-			__pyramid,
-			__params.mWindowSize,
-			__params.mPyrMaxLevel);
+	buildOpticalFlowPyramid(__image, __pyramid, __params.mWindowSize, __params.mPyrMaxLevel);
 
 	__isInit = true;
 	return __isInit;
 }
 
-bool MFTracker::update(const cv::Mat& image)
+bool MFTracker::update(const cv::Mat &image)
 {
 	if (!__isInit || image.empty())
 		return false;
@@ -188,8 +182,7 @@ cv::Rect_<float> MFTracker::getLastBoundingBox() const
 	return __boundingBox;
 }
 
-bool MFTracker::medianFlowImpl(
-		cv::Mat oldImage_gray, cv::Mat newImage_gray, cv::Rect_<float>& oldBox)
+bool MFTracker::medianFlowImpl(cv::Mat oldImage_gray, cv::Mat newImage_gray, cv::Rect_<float> &oldBox)
 {
 	std::vector<cv::Point2f> pointsToTrackOld, pointsToTrackNew;
 
@@ -197,30 +190,18 @@ bool MFTracker::medianFlowImpl(
 	const float gridYStep = oldBox.height / __params.mPointsInGrid;
 	for (int i = 0; i < __params.mPointsInGrid; i++)
 		for (int j = 0; j < __params.mPointsInGrid; j++)
-			pointsToTrackOld.push_back(
-					cv::Point2f(oldBox.x + .5f*gridXStep + 1.f*gridXStep*j,
-							oldBox.y + .5f*gridYStep + 1.f*gridYStep*i));
+			pointsToTrackOld.push_back(cv::Point2f(oldBox.x + .5f * gridXStep + 1.f * gridXStep * j,
+												   oldBox.y + .5f * gridYStep + 1.f * gridYStep * i));
 
 	const size_t numberOfPointsToTrackOld = pointsToTrackOld.size();
 	std::vector<uchar> status(numberOfPointsToTrackOld);
 	std::vector<float> errors(numberOfPointsToTrackOld);
 
 	std::vector<cv::Mat> tempPyramid;
-	buildOpticalFlowPyramid(
-							newImage_gray,
-							tempPyramid,
-							__params.mWindowSize,
-							__params.mPyrMaxLevel);
-
-	calcOpticalFlowPyrLK(__pyramid,
-							tempPyramid,
-							pointsToTrackOld,
-							pointsToTrackNew,
-							status,
-							errors,
-							__params.mWindowSize,
-							__params.mPyrMaxLevel,
-							__termcrit);
+	buildOpticalFlowPyramid(newImage_gray, tempPyramid, __params.mWindowSize, __params.mPyrMaxLevel);
+
+	calcOpticalFlowPyrLK(__pyramid, tempPyramid, pointsToTrackOld, pointsToTrackNew, status, errors,
+						 __params.mWindowSize, __params.mPyrMaxLevel, __termcrit);
 
 	std::vector<cv::Point2f> di;
 	for (size_t idx = 0u; idx < numberOfPointsToTrackOld; idx++)
@@ -228,16 +209,9 @@ bool MFTracker::medianFlowImpl(
 			di.push_back(pointsToTrackNew[idx] - pointsToTrackOld[idx]);
 
 	std::vector<bool> filter_status;
-	check_FB(tempPyramid,
-			pointsToTrackOld,
-			pointsToTrackNew,
-			filter_status);
+	check_FB(tempPyramid, pointsToTrackOld, pointsToTrackNew, filter_status);
 
-	check_NCC(oldImage_gray,
-			newImage_gray,
-			pointsToTrackOld,
-			pointsToTrackNew,
-			filter_status);
+	check_NCC(oldImage_gray, newImage_gray, pointsToTrackOld, pointsToTrackNew, filter_status);
 
 	for (size_t idx = 0u; idx < pointsToTrackOld.size(); idx++) {
 		if (!filter_status[idx]) {
@@ -252,8 +226,7 @@ bool MFTracker::medianFlowImpl(
 		return false;
 
 	cv::Point2f mDisplacement;
-	cv::Rect_<float> boxCandidate =
-				vote(pointsToTrackOld, pointsToTrackNew, oldBox, mDisplacement);
+	cv::Rect_<float> boxCandidate = vote(pointsToTrackOld, pointsToTrackNew, oldBox, mDisplacement);
 
 	std::vector<float> displacements;
 	for (size_t idx = 0u; idx < di.size(); idx++) {
@@ -261,8 +234,7 @@ bool MFTracker::medianFlowImpl(
 		displacements.push_back(sqrt(di[idx].ddot(di[idx])));
 	}
 
-	__confidence =
-			(10.f - getMedian(displacements, static_cast<int>(displacements.size()))) / 10.f;
+	__confidence = (10.f - getMedian(displacements, static_cast<int>(displacements.size()))) / 10.f;
 
 	if (__confidence < 0.f) {
 		__confidence = 0.f;
@@ -274,23 +246,18 @@ bool MFTracker::medianFlowImpl(
 	return true;
 }
 
-cv::Rect_<float> MFTracker::vote(
-		const std::vector<cv::Point2f>& oldPoints,
-		const std::vector<cv::Point2f>& newPoints,
-		const cv::Rect_<float>& oldRect,
-		cv::Point2f& mD)
+cv::Rect_<float> MFTracker::vote(const std::vector<cv::Point2f> &oldPoints, const std::vector<cv::Point2f> &newPoints,
+								 const cv::Rect_<float> &oldRect, cv::Point2f &mD)
 {
 	cv::Rect_<float> newRect;
-	cv::Point2f newCenter(
-			oldRect.x + oldRect.width / 2.f,
-			oldRect.y + oldRect.height / 2.f);
+	cv::Point2f newCenter(oldRect.x + oldRect.width / 2.f, oldRect.y + oldRect.height / 2.f);
 
-	const int n = (int)oldPoints.size();
-	std::vector<float> buf(std::max(n*(n-1) / 2, 3), 0.f);
+	const int n = (int) oldPoints.size();
+	std::vector<float> buf(std::max(n * (n - 1) / 2, 3), 0.f);
 
 	if (oldPoints.size() == 1) {
-		newRect.x = oldRect.x+newPoints[0].x-oldPoints[0].x;
-		newRect.y = oldRect.y+newPoints[0].y-oldPoints[0].y;
+		newRect.x = oldRect.x + newPoints[0].x - oldPoints[0].x;
+		newRect.y = oldRect.y + newPoints[0].y - oldPoints[0].y;
 		newRect.width = oldRect.width;
 		newRect.height = oldRect.height;
 
@@ -331,20 +298,17 @@ cv::Rect_<float> MFTracker::vote(
 		}
 	}
 
-	float scale = getMedian(buf, n*(n-1) / 2);
+	float scale = getMedian(buf, n * (n - 1) / 2);
 	newRect.x = newCenter.x - scale * oldRect.width / 2.f;
-	newRect.y = newCenter.y-scale * oldRect.height / 2.f;
+	newRect.y = newCenter.y - scale * oldRect.height / 2.f;
 	newRect.width = scale * oldRect.width;
 	newRect.height = scale * oldRect.height;
 
 	return newRect;
 }
 
-void MFTracker::check_FB(
-		std::vector<cv::Mat> newPyramid,
-		const std::vector<cv::Point2f>& oldPoints,
-		const std::vector<cv::Point2f>& newPoints,
-		std::vector<bool>& status)
+void MFTracker::check_FB(std::vector<cv::Mat> newPyramid, const std::vector<cv::Point2f> &oldPoints,
+						 const std::vector<cv::Point2f> &newPoints, std::vector<bool> &status)
 {
 	const size_t numberOfOldPoints = oldPoints.size();
 
@@ -356,15 +320,8 @@ void MFTracker::check_FB(
 	std::vector<float> FBerror(numberOfOldPoints);
 	std::vector<cv::Point2f> pointsToTrackReprojection;
 
-	calcOpticalFlowPyrLK(newPyramid,
-						__pyramid,
-						newPoints,
-						pointsToTrackReprojection,
-						LKstatus,
-						errors,
-						__params.mWindowSize,
-						__params.mPyrMaxLevel,
-						__termcrit);
+	calcOpticalFlowPyrLK(newPyramid, __pyramid, newPoints, pointsToTrackReprojection, LKstatus, errors,
+						 __params.mWindowSize, __params.mPyrMaxLevel, __termcrit);
 
 	for (size_t idx = 0u; idx < numberOfOldPoints; idx++)
 		FBerror[idx] = l2distance(oldPoints[idx], pointsToTrackReprojection[idx]);
@@ -374,12 +331,8 @@ void MFTracker::check_FB(
 		status[idx] = (FBerror[idx] < FBerrorMedian);
 }
 
-void MFTracker::check_NCC(
-		const cv::Mat& oldImage,
-		const cv::Mat& newImage,
-		const std::vector<cv::Point2f>& oldPoints,
-		const std::vector<cv::Point2f>& newPoints,
-		std::vector<bool>& status)
+void MFTracker::check_NCC(const cv::Mat &oldImage, const cv::Mat &newImage, const std::vector<cv::Point2f> &oldPoints,
+						  const std::vector<cv::Point2f> &newPoints, std::vector<bool> &status)
 {
 	std::vector<float> NCC(oldPoints.size(), 0.f);
 	cv::Size patch(30, 30);
diff --git a/mv_image/image/src/Tracking/ObjectTracker.cpp b/mv_image/image/src/Tracking/ObjectTracker.cpp
index 4e73730..7e69a58 100644
--- a/mv_image/image/src/Tracking/ObjectTracker.cpp
+++ b/mv_image/image/src/Tracking/ObjectTracker.cpp
@@ -16,8 +16,10 @@
 
 #include "Tracking/ObjectTracker.h"
 
-namespace MediaVision {
-namespace Image {
+namespace MediaVision
+{
+namespace Image
+{
 ObjectTracker::~ObjectTracker()
 {
 	; /* NULL */
diff --git a/mv_image/image/src/Tracking/RecognitionBasedTracker.cpp b/mv_image/image/src/Tracking/RecognitionBasedTracker.cpp
index d3cbfbc..beb6bfa 100644
--- a/mv_image/image/src/Tracking/RecognitionBasedTracker.cpp
+++ b/mv_image/image/src/Tracking/RecognitionBasedTracker.cpp
@@ -20,16 +20,16 @@
 
 #include <new>
 
-namespace MediaVision {
-namespace Image {
-
-RecognitionBasedTracker::RecognitionBasedTracker(
-		const ImageObject& target,
-		const FeaturesExtractingParams& sceneFeaturesExtractingParams,
-		const RecognitionParams& recognitionParams) :
-				__target(target),
-				__sceneFeatureExtractingParams(sceneFeaturesExtractingParams),
-				__recogParams(recognitionParams)
+namespace MediaVision
+{
+namespace Image
+{
+RecognitionBasedTracker::RecognitionBasedTracker(const ImageObject &target,
+												 const FeaturesExtractingParams &sceneFeaturesExtractingParams,
+												 const RecognitionParams &recognitionParams)
+		: __target(target)
+		, __sceneFeatureExtractingParams(sceneFeaturesExtractingParams)
+		, __recogParams(recognitionParams)
 {
 	; /* NULL */
 }
@@ -39,9 +39,7 @@ RecognitionBasedTracker::~RecognitionBasedTracker()
 	; /* NULL */
 }
 
-bool RecognitionBasedTracker::track(
-		const cv::Mat& frame,
-		std::vector<cv::Point>& result)
+bool RecognitionBasedTracker::track(const cv::Mat &frame, std::vector<cv::Point> &result)
 {
 	result.clear();
 
@@ -57,15 +55,15 @@ bool RecognitionBasedTracker::track(
 		size_t numberOfContourPoints = contour.size();
 		result.resize(numberOfContourPoints);
 		for (size_t i = 0u; i < numberOfContourPoints; ++i) {
-			result[i].x = (int)contour[i].x;
-			result[i].y = (int)contour[i].y;
+			result[i].x = (int) contour[i].x;
+			result[i].y = (int) contour[i].y;
 		}
 	}
 
 	return isRecognized;
 }
 
-void RecognitionBasedTracker::reinforcement(const std::vector<cv::Point>& /*location*/)
+void RecognitionBasedTracker::reinforcement(const std::vector<cv::Point> & /*location*/)
 {
 	; /* The tracker is based on the recognition on the entire image.
 	   * The reinforcement does not make a sense.*/
@@ -73,7 +71,7 @@ void RecognitionBasedTracker::reinforcement(const std::vector<cv::Point>& /*loca
 
 cv::Ptr<ObjectTracker> RecognitionBasedTracker::clone() const
 {
-	return cv::Ptr<ObjectTracker>(new (std::nothrow)RecognitionBasedTracker(*this));
+	return cv::Ptr<ObjectTracker>(new (std::nothrow) RecognitionBasedTracker(*this));
 }
 
 } /* Image */
diff --git a/mv_image/image/src/mv_image.c b/mv_image/image/src/mv_image.c
index 7b4ab29..0a8bd83 100644
--- a/mv_image/image/src/mv_image.c
+++ b/mv_image/image/src/mv_image.c
@@ -23,13 +23,8 @@
  * @brief This file contains the porting layer for Media Vision image module.
  */
 
-int mv_image_recognize(
-		mv_source_h source,
-		const mv_image_object_h *image_objects,
-		int number_of_objects,
-		mv_engine_config_h engine_cfg,
-		mv_image_recognized_cb recognized_cb,
-		void *user_data)
+int mv_image_recognize(mv_source_h source, const mv_image_object_h *image_objects, int number_of_objects,
+					   mv_engine_config_h engine_cfg, mv_image_recognized_cb recognized_cb, void *user_data)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -43,19 +38,14 @@ int mv_image_recognize(
 
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	int ret = mv_image_recognize_open(source, image_objects,
-			number_of_objects, engine_cfg, recognized_cb, user_data);
+	int ret = mv_image_recognize_open(source, image_objects, number_of_objects, engine_cfg, recognized_cb, user_data);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_image_track(
-		mv_source_h source,
-		mv_image_tracking_model_h image_tracking_model,
-		mv_engine_config_h engine_cfg,
-		mv_image_tracked_cb tracked_cb,
-		void *user_data)
+int mv_image_track(mv_source_h source, mv_image_tracking_model_h image_tracking_model, mv_engine_config_h engine_cfg,
+				   mv_image_tracked_cb tracked_cb, void *user_data)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -70,8 +60,7 @@ int mv_image_track(
 	return ret;
 }
 
-int mv_image_object_create(
-		mv_image_object_h *image_object)
+int mv_image_object_create(mv_image_object_h *image_object)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(image_object);
@@ -83,8 +72,7 @@ int mv_image_object_create(
 	return ret;
 }
 
-int mv_image_object_destroy(
-		mv_image_object_h image_object)
+int mv_image_object_destroy(mv_image_object_h image_object)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(image_object);
@@ -96,11 +84,8 @@ int mv_image_object_destroy(
 	return ret;
 }
 
-int mv_image_object_fill(
-		mv_image_object_h image_object,
-		mv_engine_config_h engine_cfg,
-		mv_source_h source,
-		mv_rectangle_s *location)
+int mv_image_object_fill(mv_image_object_h image_object, mv_engine_config_h engine_cfg, mv_source_h source,
+						 mv_rectangle_s *location)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(image_object);
@@ -114,9 +99,7 @@ int mv_image_object_fill(
 	return ret;
 }
 
-int mv_image_object_get_recognition_rate(
-		mv_image_object_h image_object,
-		double *recognition_rate)
+int mv_image_object_get_recognition_rate(mv_image_object_h image_object, double *recognition_rate)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(image_object);
@@ -130,9 +113,7 @@ int mv_image_object_get_recognition_rate(
 	return ret;
 }
 
-int mv_image_object_set_label(
-		mv_image_object_h image_object,
-		int label)
+int mv_image_object_set_label(mv_image_object_h image_object, int label)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(image_object);
@@ -145,9 +126,7 @@ int mv_image_object_set_label(
 	return ret;
 }
 
-int mv_image_object_get_label(
-		mv_image_object_h image_object,
-		int *label)
+int mv_image_object_get_label(mv_image_object_h image_object, int *label)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(image_object);
@@ -161,9 +140,7 @@ int mv_image_object_get_label(
 	return ret;
 }
 
-int mv_image_object_clone(
-		mv_image_object_h src,
-		mv_image_object_h *dst)
+int mv_image_object_clone(mv_image_object_h src, mv_image_object_h *dst)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(src);
@@ -176,8 +153,7 @@ int mv_image_object_clone(
 	return ret;
 }
 
-int mv_image_object_save(
-		const char *file_name, mv_image_object_h image_object)
+int mv_image_object_save(const char *file_name, mv_image_object_h image_object)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(image_object);
@@ -195,8 +171,7 @@ int mv_image_object_save(
 	return ret;
 }
 
-int mv_image_object_load(
-		const char *file_name, mv_image_object_h *image_object)
+int mv_image_object_load(const char *file_name, mv_image_object_h *image_object)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(image_object);
@@ -214,8 +189,7 @@ int mv_image_object_load(
 	return ret;
 }
 
-int mv_image_tracking_model_create(
-		mv_image_tracking_model_h *image_tracking_model)
+int mv_image_tracking_model_create(mv_image_tracking_model_h *image_tracking_model)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(image_tracking_model);
@@ -228,9 +202,7 @@ int mv_image_tracking_model_create(
 	return ret;
 }
 
-int mv_image_tracking_model_set_target(
-		mv_image_object_h image_object,
-		mv_image_tracking_model_h image_tracking_model)
+int mv_image_tracking_model_set_target(mv_image_object_h image_object, mv_image_tracking_model_h image_tracking_model)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(image_tracking_model);
@@ -244,8 +216,7 @@ int mv_image_tracking_model_set_target(
 	return ret;
 }
 
-int mv_image_tracking_model_destroy(
-		mv_image_tracking_model_h image_tracking_model)
+int mv_image_tracking_model_destroy(mv_image_tracking_model_h image_tracking_model)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(image_tracking_model);
@@ -258,26 +229,20 @@ int mv_image_tracking_model_destroy(
 	return ret;
 }
 
-int mv_image_tracking_model_refresh(
-		mv_image_tracking_model_h image_tracking_model,
-		mv_engine_config_h engine_cfg)
+int mv_image_tracking_model_refresh(mv_image_tracking_model_h image_tracking_model, mv_engine_config_h engine_cfg)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(image_tracking_model);
 
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	int ret = mv_image_tracking_model_refresh_open(
-					image_tracking_model,
-					engine_cfg);
+	int ret = mv_image_tracking_model_refresh_open(image_tracking_model, engine_cfg);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_image_tracking_model_clone(
-		mv_image_tracking_model_h src,
-		mv_image_tracking_model_h *dst)
+int mv_image_tracking_model_clone(mv_image_tracking_model_h src, mv_image_tracking_model_h *dst)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(src);
@@ -291,8 +256,7 @@ int mv_image_tracking_model_clone(
 	return ret;
 }
 
-int mv_image_tracking_model_save(
-		const char *file_name, mv_image_tracking_model_h image_tracking_model)
+int mv_image_tracking_model_save(const char *file_name, mv_image_tracking_model_h image_tracking_model)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(image_tracking_model);
@@ -310,8 +274,7 @@ int mv_image_tracking_model_save(
 	return ret;
 }
 
-int mv_image_tracking_model_load(
-		const char *file_name, mv_image_tracking_model_h *image_tracking_model)
+int mv_image_tracking_model_load(const char *file_name, mv_image_tracking_model_h *image_tracking_model)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(image_tracking_model);
diff --git a/mv_image/image/src/mv_image_open.cpp b/mv_image/image/src/mv_image_open.cpp
index 3ba7dd4..8599892 100644
--- a/mv_image/image/src/mv_image_open.cpp
+++ b/mv_image/image/src/mv_image_open.cpp
@@ -29,11 +29,12 @@
 #include <opencv2/core.hpp>
 #include <opencv2/imgproc/imgproc_c.h>
 
-namespace {
-
-class DefaultConfiguration {
+namespace
+{
+class DefaultConfiguration
+{
 public:
-	static const DefaultConfiguration& getInstance();
+	static const DefaultConfiguration &getInstance();
 
 	MediaVision::Image::FeaturesExtractingParams getObjectFeaturesExtractingParams() const;
 
@@ -64,12 +65,12 @@ private:
 
 DefaultConfiguration DefaultConfiguration::instance;
 
-DefaultConfiguration::DefaultConfiguration() :
-		__objectFeaturesExtractingParams(),
-		__sceneFeaturesExtractingParams(),
-		__recognitionParams(15, 0.33, 0.1),
-		__stabilizationParams(true, 3, 0.00006, 1.3, 2, 0.001),
-		__trackingParams()
+DefaultConfiguration::DefaultConfiguration()
+		: __objectFeaturesExtractingParams()
+		, __sceneFeaturesExtractingParams()
+		, __recognitionParams(15, 0.33, 0.1)
+		, __stabilizationParams(true, 3, 0.00006, 1.3, 2, 0.001)
+		, __trackingParams()
 {
 	__objectFeaturesExtractingParams.mKeypointType = MediaVision::Image::KT_ORB;
 	__objectFeaturesExtractingParams.mDescriptorType = MediaVision::Image::DT_ORB;
@@ -87,44 +88,38 @@ DefaultConfiguration::DefaultConfiguration() :
 	__trackingParams.mExpectedOffset = 0.0;
 }
 
-const DefaultConfiguration& DefaultConfiguration::getInstance()
+const DefaultConfiguration &DefaultConfiguration::getInstance()
 {
 	return instance;
 }
 
-MediaVision::Image::FeaturesExtractingParams
-DefaultConfiguration::getObjectFeaturesExtractingParams() const
+MediaVision::Image::FeaturesExtractingParams DefaultConfiguration::getObjectFeaturesExtractingParams() const
 {
 	return __objectFeaturesExtractingParams;
 }
 
-MediaVision::Image::FeaturesExtractingParams
-DefaultConfiguration::getSceneFeaturesExtractingParams() const
+MediaVision::Image::FeaturesExtractingParams DefaultConfiguration::getSceneFeaturesExtractingParams() const
 {
 	return __sceneFeaturesExtractingParams;
 }
 
-MediaVision::Image::RecognitionParams
-DefaultConfiguration::getRecognitionParams() const
+MediaVision::Image::RecognitionParams DefaultConfiguration::getRecognitionParams() const
 {
 	return __recognitionParams;
 }
 
-MediaVision::Image::StabilizationParams
-DefaultConfiguration::getStabilizationParams() const
+MediaVision::Image::StabilizationParams DefaultConfiguration::getStabilizationParams() const
 {
 	return __stabilizationParams;
 }
 
-MediaVision::Image::TrackingParams
-DefaultConfiguration::getTrackingParams() const
+MediaVision::Image::TrackingParams DefaultConfiguration::getTrackingParams() const
 {
 	return __trackingParams;
 }
 
-void extractTargetFeaturesExtractingParams(
-		mv_engine_config_h engine_cfg,
-		MediaVision::Image::FeaturesExtractingParams& featuresExtractingParams)
+void extractTargetFeaturesExtractingParams(mv_engine_config_h engine_cfg,
+										   MediaVision::Image::FeaturesExtractingParams &featuresExtractingParams)
 {
 	mv_engine_config_h working_cfg = NULL;
 
@@ -134,26 +129,20 @@ void extractTargetFeaturesExtractingParams(
 		working_cfg = engine_cfg;
 	}
 
-	featuresExtractingParams =
-			DefaultConfiguration::getInstance().getObjectFeaturesExtractingParams();
+	featuresExtractingParams = DefaultConfiguration::getInstance().getObjectFeaturesExtractingParams();
 
-	mv_engine_config_get_double_attribute_c(
-			working_cfg,
-			MV_IMAGE_RECOGNITION_OBJECT_SCALE_FACTOR,
-			&featuresExtractingParams.ORB.mScaleFactor);
+	mv_engine_config_get_double_attribute_c(working_cfg, MV_IMAGE_RECOGNITION_OBJECT_SCALE_FACTOR,
+											&featuresExtractingParams.ORB.mScaleFactor);
 
-	mv_engine_config_get_int_attribute_c(
-			working_cfg,
-			MV_IMAGE_RECOGNITION_OBJECT_MAX_KEYPOINTS_NUM,
-			&featuresExtractingParams.ORB.mMaximumFeaturesNumber);
+	mv_engine_config_get_int_attribute_c(working_cfg, MV_IMAGE_RECOGNITION_OBJECT_MAX_KEYPOINTS_NUM,
+										 &featuresExtractingParams.ORB.mMaximumFeaturesNumber);
 
 	if (NULL == engine_cfg)
 		mv_destroy_engine_config(working_cfg);
 }
 
-void extractSceneFeaturesExtractingParams(
-		mv_engine_config_h engine_cfg,
-		MediaVision::Image::FeaturesExtractingParams& featuresExtractingParams)
+void extractSceneFeaturesExtractingParams(mv_engine_config_h engine_cfg,
+										  MediaVision::Image::FeaturesExtractingParams &featuresExtractingParams)
 {
 	mv_engine_config_h working_cfg = NULL;
 
@@ -163,26 +152,19 @@ void extractSceneFeaturesExtractingParams(
 		working_cfg = engine_cfg;
 	}
 
-	featuresExtractingParams =
-			DefaultConfiguration::getInstance().getSceneFeaturesExtractingParams();
+	featuresExtractingParams = DefaultConfiguration::getInstance().getSceneFeaturesExtractingParams();
 
-	mv_engine_config_get_double_attribute_c(
-			working_cfg,
-			MV_IMAGE_RECOGNITION_SCENE_SCALE_FACTOR,
-			&featuresExtractingParams.ORB.mScaleFactor);
+	mv_engine_config_get_double_attribute_c(working_cfg, MV_IMAGE_RECOGNITION_SCENE_SCALE_FACTOR,
+											&featuresExtractingParams.ORB.mScaleFactor);
 
-	mv_engine_config_get_int_attribute_c(
-			working_cfg,
-			MV_IMAGE_RECOGNITION_SCENE_MAX_KEYPOINTS_NUM,
-			&featuresExtractingParams.ORB.mMaximumFeaturesNumber);
+	mv_engine_config_get_int_attribute_c(working_cfg, MV_IMAGE_RECOGNITION_SCENE_MAX_KEYPOINTS_NUM,
+										 &featuresExtractingParams.ORB.mMaximumFeaturesNumber);
 
 	if (NULL == engine_cfg)
 		mv_destroy_engine_config(working_cfg);
 }
 
-void extractRecognitionParams(
-		mv_engine_config_h engine_cfg,
-		MediaVision::Image::RecognitionParams& recognitionParams)
+void extractRecognitionParams(mv_engine_config_h engine_cfg, MediaVision::Image::RecognitionParams &recognitionParams)
 {
 	mv_engine_config_h working_cfg = NULL;
 
@@ -192,31 +174,23 @@ void extractRecognitionParams(
 		working_cfg = engine_cfg;
 	}
 
-	recognitionParams =
-			DefaultConfiguration::getInstance().getRecognitionParams();
+	recognitionParams = DefaultConfiguration::getInstance().getRecognitionParams();
 
-	mv_engine_config_get_int_attribute_c(
-			working_cfg,
-			MV_IMAGE_RECOGNITION_MIN_MATCH_NUM,
-			&recognitionParams.mMinMatchesNumber);
+	mv_engine_config_get_int_attribute_c(working_cfg, MV_IMAGE_RECOGNITION_MIN_MATCH_NUM,
+										 &recognitionParams.mMinMatchesNumber);
 
-	mv_engine_config_get_double_attribute_c(
-			working_cfg,
-			MV_IMAGE_RECOGNITION_REQ_MATCH_PART,
-			&recognitionParams.mRequiredMatchesPart);
+	mv_engine_config_get_double_attribute_c(working_cfg, MV_IMAGE_RECOGNITION_REQ_MATCH_PART,
+											&recognitionParams.mRequiredMatchesPart);
 
-	mv_engine_config_get_double_attribute_c(
-			working_cfg,
-			MV_IMAGE_RECOGNITION_TOLERANT_MATCH_PART_ERR,
-			&recognitionParams.mTolerantMatchesPartError);
+	mv_engine_config_get_double_attribute_c(working_cfg, MV_IMAGE_RECOGNITION_TOLERANT_MATCH_PART_ERR,
+											&recognitionParams.mTolerantMatchesPartError);
 
 	if (NULL == engine_cfg)
 		mv_destroy_engine_config(working_cfg);
 }
 
-void extractStabilizationParams(
-		mv_engine_config_h engine_cfg,
-		MediaVision::Image::StabilizationParams& stabilizationParams)
+void extractStabilizationParams(mv_engine_config_h engine_cfg,
+								MediaVision::Image::StabilizationParams &stabilizationParams)
 {
 	mv_engine_config_h working_cfg = NULL;
 	int _history_amount = 0;
@@ -227,45 +201,28 @@ void extractStabilizationParams(
 		working_cfg = engine_cfg;
 	}
 
-	stabilizationParams =
-			DefaultConfiguration::getInstance().getStabilizationParams();
-
-	mv_engine_config_get_bool_attribute_c(
-			working_cfg,
-			MV_IMAGE_TRACKING_USE_STABLIZATION,
-			&stabilizationParams.mIsEnabled);
-
-	mv_engine_config_get_int_attribute_c(
-			working_cfg,
-			MV_IMAGE_TRACKING_HISTORY_AMOUNT,
-			&_history_amount);
-	stabilizationParams.mHistoryAmount =
-		static_cast<size_t>(
-			static_cast<unsigned int>(_history_amount)
-		);
-
-	mv_engine_config_get_double_attribute_c(
-			working_cfg,
-			MV_IMAGE_TRACKING_STABLIZATION_TOLERANT_SHIFT,
-			&stabilizationParams.mTolerantShift);
-
-	mv_engine_config_get_double_attribute_c(
-			working_cfg,
-			MV_IMAGE_TRACKING_STABLIZATION_SPEED,
-			&stabilizationParams.mStabilizationSpeed);
-
-	mv_engine_config_get_double_attribute_c(
-			working_cfg,
-			MV_IMAGE_TRACKING_STABLIZATION_ACCELERATION,
-			&stabilizationParams.mStabilizationAcceleration);
+	stabilizationParams = DefaultConfiguration::getInstance().getStabilizationParams();
+
+	mv_engine_config_get_bool_attribute_c(working_cfg, MV_IMAGE_TRACKING_USE_STABLIZATION,
+										  &stabilizationParams.mIsEnabled);
+
+	mv_engine_config_get_int_attribute_c(working_cfg, MV_IMAGE_TRACKING_HISTORY_AMOUNT, &_history_amount);
+	stabilizationParams.mHistoryAmount = static_cast<size_t>(static_cast<unsigned int>(_history_amount));
+
+	mv_engine_config_get_double_attribute_c(working_cfg, MV_IMAGE_TRACKING_STABLIZATION_TOLERANT_SHIFT,
+											&stabilizationParams.mTolerantShift);
+
+	mv_engine_config_get_double_attribute_c(working_cfg, MV_IMAGE_TRACKING_STABLIZATION_SPEED,
+											&stabilizationParams.mStabilizationSpeed);
+
+	mv_engine_config_get_double_attribute_c(working_cfg, MV_IMAGE_TRACKING_STABLIZATION_ACCELERATION,
+											&stabilizationParams.mStabilizationAcceleration);
 
 	if (NULL == engine_cfg)
 		mv_destroy_engine_config(working_cfg);
 }
 
-void extractTrackingParams(
-		mv_engine_config_h engine_cfg,
-		MediaVision::Image::TrackingParams& trackingParams)
+void extractTrackingParams(mv_engine_config_h engine_cfg, MediaVision::Image::TrackingParams &trackingParams)
 {
 	mv_engine_config_h working_cfg = NULL;
 
@@ -275,25 +232,16 @@ void extractTrackingParams(
 		working_cfg = engine_cfg;
 	}
 
-	trackingParams =
-			DefaultConfiguration::getInstance().getTrackingParams();
+	trackingParams = DefaultConfiguration::getInstance().getTrackingParams();
 
-	extractSceneFeaturesExtractingParams(
-			working_cfg,
-			trackingParams.mFramesFeaturesExtractingParams);
+	extractSceneFeaturesExtractingParams(working_cfg, trackingParams.mFramesFeaturesExtractingParams);
 
-	extractRecognitionParams(
-			working_cfg,
-			trackingParams.mRecognitionParams);
+	extractRecognitionParams(working_cfg, trackingParams.mRecognitionParams);
 
-	extractStabilizationParams(
-			working_cfg,
-			trackingParams.mStabilizationParams);
+	extractStabilizationParams(working_cfg, trackingParams.mStabilizationParams);
 
-	mv_engine_config_get_double_attribute_c(
-			working_cfg,
-			MV_IMAGE_TRACKING_EXPECTED_OFFSET,
-			&trackingParams.mExpectedOffset);
+	mv_engine_config_get_double_attribute_c(working_cfg, MV_IMAGE_TRACKING_EXPECTED_OFFSET,
+											&trackingParams.mExpectedOffset);
 
 	if (NULL == engine_cfg)
 		mv_destroy_engine_config(working_cfg);
@@ -301,13 +249,8 @@ void extractTrackingParams(
 
 } /* anonymous namespace */
 
-int mv_image_recognize_open(
-		mv_source_h source,
-		const mv_image_object_h *image_objects,
-		int number_of_objects,
-		mv_engine_config_h engine_cfg,
-		mv_image_recognized_cb recognized_cb,
-		void *user_data)
+int mv_image_recognize_open(mv_source_h source, const mv_image_object_h *image_objects, int number_of_objects,
+							mv_engine_config_h engine_cfg, mv_image_recognized_cb recognized_cb, void *user_data)
 {
 	MEDIA_VISION_INSTANCE_CHECK(source);
 	MEDIA_VISION_NULL_ARG_CHECK(image_objects);
@@ -316,9 +259,7 @@ int mv_image_recognize_open(
 	MEDIA_VISION_NULL_ARG_CHECK(recognized_cb);
 
 	cv::Mat scene;
-	MEDIA_VISION_ASSERT(
-			MediaVision::Common::convertSourceMV2GrayCV(source, scene),
-			"Failed to convert mv_source.");
+	MEDIA_VISION_ASSERT(MediaVision::Common::convertSourceMV2GrayCV(source, scene), "Failed to convert mv_source.");
 
 	int ret = MEDIA_VISION_ERROR_NONE;
 
@@ -336,37 +277,25 @@ int mv_image_recognize_open(
 
 	for (int objectNum = 0; objectNum < number_of_objects; ++objectNum) {
 		std::vector<cv::Point2f> resultContour;
-		bool isRecognized = recognizer.recognize(
-						*((MediaVision::Image::ImageObject*)image_objects[objectNum]),
-						recognitionParams, resultContour);
-		if (isRecognized && (resultContour.size() ==
-			MediaVision::Image::NumberOfQuadrangleCorners)) {
+		bool isRecognized = recognizer.recognize(*((MediaVision::Image::ImageObject *) image_objects[objectNum]),
+												 recognitionParams, resultContour);
+		if (isRecognized && (resultContour.size() == MediaVision::Image::NumberOfQuadrangleCorners)) {
 			resultLocations[objectNum] = new mv_quadrangle_s;
 			if (resultLocations[objectNum] == NULL) {
 				ret = MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 				goto ErrorExit;
 			}
 
-			for (size_t pointNum = 0u;
-				pointNum < MediaVision::Image::NumberOfQuadrangleCorners;
-				++pointNum) {
-				resultLocations[objectNum]->points[pointNum].x =
-							resultContour[pointNum].x;
-				resultLocations[objectNum]->points[pointNum].y =
-							resultContour[pointNum].y;
+			for (size_t pointNum = 0u; pointNum < MediaVision::Image::NumberOfQuadrangleCorners; ++pointNum) {
+				resultLocations[objectNum]->points[pointNum].x = resultContour[pointNum].x;
+				resultLocations[objectNum]->points[pointNum].y = resultContour[pointNum].y;
 			}
 		} else {
 			resultLocations[objectNum] = NULL;
 		}
 	}
 
-	recognized_cb(
-			source,
-			engine_cfg,
-			image_objects,
-			resultLocations,
-			number_of_objects,
-			user_data);
+	recognized_cb(source, engine_cfg, image_objects, resultLocations, number_of_objects, user_data);
 
 ErrorExit:
 
@@ -380,18 +309,14 @@ ErrorExit:
 	return ret;
 }
 
-int mv_image_track_open(
-		mv_source_h source,
-		mv_image_tracking_model_h image_tracking_model,
-		mv_engine_config_h engine_cfg,
-		mv_image_tracked_cb tracked_cb,
-		void *user_data)
+int mv_image_track_open(mv_source_h source, mv_image_tracking_model_h image_tracking_model,
+						mv_engine_config_h engine_cfg, mv_image_tracked_cb tracked_cb, void *user_data)
 {
 	MEDIA_VISION_INSTANCE_CHECK(source);
 	MEDIA_VISION_INSTANCE_CHECK(image_tracking_model);
 	MEDIA_VISION_NULL_ARG_CHECK(tracked_cb);
 
-	if (!((MediaVision::Image::ImageTrackingModel*)image_tracking_model)->isValid()) {
+	if (!((MediaVision::Image::ImageTrackingModel *) image_tracking_model)->isValid()) {
 		LOGE("[%s] Image tracking model is invalid.", __FUNCTION__);
 		return MEDIA_VISION_ERROR_INVALID_DATA;
 	}
@@ -400,22 +325,17 @@ int mv_image_track_open(
 	extractTrackingParams(engine_cfg, trackingParams);
 
 	cv::Mat frame;
-	MEDIA_VISION_ASSERT(
-			MediaVision::Common::convertSourceMV2GrayCV(source, frame),
-			"Failed to convert mv_source.");
+	MEDIA_VISION_ASSERT(MediaVision::Common::convertSourceMV2GrayCV(source, frame), "Failed to convert mv_source.");
 
 	MediaVision::Image::ImageTrackingModel *trackingModel =
-			(MediaVision::Image::ImageTrackingModel*)image_tracking_model;
+			(MediaVision::Image::ImageTrackingModel *) image_tracking_model;
 
 	std::vector<cv::Point> resultContour;
 	const bool isTracked = trackingModel->track(frame, resultContour);
 
-	if (isTracked &&
-		MediaVision::Image::NumberOfQuadrangleCorners == resultContour.size()) {
+	if (isTracked && MediaVision::Image::NumberOfQuadrangleCorners == resultContour.size()) {
 		mv_quadrangle_s result;
-		for (size_t pointNum = 0u;
-			pointNum < MediaVision::Image::NumberOfQuadrangleCorners;
-			++pointNum) {
+		for (size_t pointNum = 0u; pointNum < MediaVision::Image::NumberOfQuadrangleCorners; ++pointNum) {
 			result.points[pointNum].x = resultContour[pointNum].x;
 			result.points[pointNum].y = resultContour[pointNum].y;
 		}
@@ -427,41 +347,34 @@ int mv_image_track_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_object_create_open(
-		mv_image_object_h *image_object)
+int mv_image_object_create_open(mv_image_object_h *image_object)
 {
 	MEDIA_VISION_NULL_ARG_CHECK(image_object);
 
-	(*image_object) = (mv_image_object_h)new (std::nothrow)MediaVision::Image::ImageObject();
+	(*image_object) = (mv_image_object_h) new (std::nothrow) MediaVision::Image::ImageObject();
 	if (*image_object == NULL)
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_object_destroy_open(
-		mv_image_object_h image_object)
+int mv_image_object_destroy_open(mv_image_object_h image_object)
 {
 	MEDIA_VISION_INSTANCE_CHECK(image_object);
 
-	delete (MediaVision::Image::ImageObject*)image_object;
+	delete (MediaVision::Image::ImageObject *) image_object;
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_object_fill_open(
-		mv_image_object_h image_object,
-		mv_engine_config_h engine_cfg,
-		mv_source_h source,
-		mv_rectangle_s *location)
+int mv_image_object_fill_open(mv_image_object_h image_object, mv_engine_config_h engine_cfg, mv_source_h source,
+							  mv_rectangle_s *location)
 {
 	MEDIA_VISION_INSTANCE_CHECK(image_object);
 	MEDIA_VISION_INSTANCE_CHECK(source);
 
 	cv::Mat image;
-	MEDIA_VISION_ASSERT(
-			MediaVision::Common::convertSourceMV2GrayCV(source, image),
-			"Failed to convert mv_source.");
+	MEDIA_VISION_ASSERT(MediaVision::Common::convertSourceMV2GrayCV(source, image), "Failed to convert mv_source.");
 
 	std::vector<cv::Point2f> roi;
 	if (NULL != location) {
@@ -483,45 +396,35 @@ int mv_image_object_fill_open(
 	MediaVision::Image::FeaturesExtractingParams featuresExtractingParams;
 	extractTargetFeaturesExtractingParams(engine_cfg, featuresExtractingParams);
 
-	static_cast<MediaVision::Image::ImageObject*>(image_object)->fill(
-			image,
-			featuresExtractingParams,
-			roi);
+	static_cast<MediaVision::Image::ImageObject *>(image_object)->fill(image, featuresExtractingParams, roi);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_object_get_recognition_rate_open(
-		mv_image_object_h image_object,
-		double *recognition_rate)
+int mv_image_object_get_recognition_rate_open(mv_image_object_h image_object, double *recognition_rate)
 {
 	MEDIA_VISION_INSTANCE_CHECK(image_object);
 	MEDIA_VISION_NULL_ARG_CHECK(recognition_rate);
 
-	(*recognition_rate) =
-		((MediaVision::Image::ImageObject*)image_object)->getRecognitionRate();
+	(*recognition_rate) = ((MediaVision::Image::ImageObject *) image_object)->getRecognitionRate();
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_object_set_label_open(
-		mv_image_object_h image_object,
-		int label)
+int mv_image_object_set_label_open(mv_image_object_h image_object, int label)
 {
 	MEDIA_VISION_INSTANCE_CHECK(image_object);
 
-	((MediaVision::Image::ImageObject*)image_object)->setLabel(label);
+	((MediaVision::Image::ImageObject *) image_object)->setLabel(label);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
-int mv_image_object_get_label_open(
-		mv_image_object_h image_object,
-		int *label)
+int mv_image_object_get_label_open(mv_image_object_h image_object, int *label)
 {
 	MEDIA_VISION_INSTANCE_CHECK(image_object);
 	MEDIA_VISION_NULL_ARG_CHECK(label);
 
-	if (!((MediaVision::Image::ImageObject*)image_object)->getLabel(*label)) {
+	if (!((MediaVision::Image::ImageObject *) image_object)->getLabel(*label)) {
 		LOGW("[%s] Image object haven't a label.", __FUNCTION__);
 		return MEDIA_VISION_ERROR_NO_DATA;
 	}
@@ -529,25 +432,21 @@ int mv_image_object_get_label_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_object_clone_open(
-		mv_image_object_h src,
-		mv_image_object_h *dst)
+int mv_image_object_clone_open(mv_image_object_h src, mv_image_object_h *dst)
 {
 	MEDIA_VISION_INSTANCE_CHECK(src);
 	MEDIA_VISION_NULL_ARG_CHECK(dst);
 
-	(*dst) = (mv_image_object_h)new (std::nothrow)MediaVision::Image::ImageObject();
+	(*dst) = (mv_image_object_h) new (std::nothrow) MediaVision::Image::ImageObject();
 	if (*dst == NULL)
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 
-	*(MediaVision::Image::ImageObject*)(*dst) =
-			*(MediaVision::Image::ImageObject*)src;
+	*(MediaVision::Image::ImageObject *) (*dst) = *(MediaVision::Image::ImageObject *) src;
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_object_save_open(
-		const char *file_name, mv_image_object_h image_object)
+int mv_image_object_save_open(const char *file_name, mv_image_object_h image_object)
 {
 	MEDIA_VISION_INSTANCE_CHECK(image_object);
 
@@ -556,7 +455,7 @@ int mv_image_object_save_open(
 		return MEDIA_VISION_ERROR_INVALID_PATH;
 	}
 
-	int ret = ((MediaVision::Image::ImageObject*)image_object)->save(file_name);
+	int ret = ((MediaVision::Image::ImageObject *) image_object)->save(file_name);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to save image object.");
 		return ret;
@@ -565,8 +464,7 @@ int mv_image_object_save_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_object_load_open(
-		const char *file_name, mv_image_object_h *image_object)
+int mv_image_object_load_open(const char *file_name, mv_image_object_h *image_object)
 {
 	MEDIA_VISION_NULL_ARG_CHECK(image_object);
 
@@ -575,11 +473,11 @@ int mv_image_object_load_open(
 		return MEDIA_VISION_ERROR_INVALID_PATH;
 	}
 
-	(*image_object) = (mv_image_object_h)new (std::nothrow)MediaVision::Image::ImageObject();
+	(*image_object) = (mv_image_object_h) new (std::nothrow) MediaVision::Image::ImageObject();
 	if (*image_object == NULL)
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 
-	int ret = ((MediaVision::Image::ImageObject*)(*image_object))->load(file_name);
+	int ret = ((MediaVision::Image::ImageObject *) (*image_object))->load(file_name);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to save image object.");
 		return ret;
@@ -588,34 +486,32 @@ int mv_image_object_load_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_tracking_model_create_open(
-		mv_image_tracking_model_h *image_tracking_model)
+int mv_image_tracking_model_create_open(mv_image_tracking_model_h *image_tracking_model)
 {
 	MEDIA_VISION_NULL_ARG_CHECK(image_tracking_model);
 
-	(*image_tracking_model) = (mv_image_tracking_model_h)
-			new (std::nothrow)MediaVision::Image::ImageTrackingModel();
+	(*image_tracking_model) = (mv_image_tracking_model_h) new (std::nothrow) MediaVision::Image::ImageTrackingModel();
 	if (*image_tracking_model == NULL)
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_tracking_model_set_target_open(
-		mv_image_object_h image_object,
-		mv_image_tracking_model_h image_tracking_model)
+int mv_image_tracking_model_set_target_open(mv_image_object_h image_object,
+											mv_image_tracking_model_h image_tracking_model)
 {
 	MEDIA_VISION_INSTANCE_CHECK(image_tracking_model);
 	MEDIA_VISION_INSTANCE_CHECK(image_object);
 
-	if (((MediaVision::Image::ImageObject*)image_object)->isEmpty()) {
+	if (((MediaVision::Image::ImageObject *) image_object)->isEmpty()) {
 		LOGE("[%s] Target is empty and can't be set as target of tracking"
-				"model.", __FUNCTION__);
+			 "model.",
+			 __FUNCTION__);
 		return MEDIA_VISION_ERROR_INVALID_DATA;
 	}
 
-	int ret = ((MediaVision::Image::ImageTrackingModel*)image_tracking_model)->setTarget(
-			*(MediaVision::Image::ImageObject*)image_object);
+	int ret = ((MediaVision::Image::ImageTrackingModel *) image_tracking_model)
+					  ->setTarget(*(MediaVision::Image::ImageObject *) image_object);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to set target.");
 		return ret;
@@ -624,52 +520,47 @@ int mv_image_tracking_model_set_target_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_tracking_model_destroy_open(
-		mv_image_tracking_model_h image_tracking_model)
+int mv_image_tracking_model_destroy_open(mv_image_tracking_model_h image_tracking_model)
 {
 	MEDIA_VISION_INSTANCE_CHECK(image_tracking_model);
 
-	delete (MediaVision::Image::ImageTrackingModel*)image_tracking_model;
+	delete (MediaVision::Image::ImageTrackingModel *) image_tracking_model;
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_tracking_model_refresh_open(
-		mv_image_tracking_model_h image_tracking_model,
-		mv_engine_config_h /*engine_cfg*/)
+int mv_image_tracking_model_refresh_open(mv_image_tracking_model_h image_tracking_model,
+										 mv_engine_config_h /*engine_cfg*/)
 {
 	MEDIA_VISION_INSTANCE_CHECK(image_tracking_model);
 
-	if (!((MediaVision::Image::ImageTrackingModel*)image_tracking_model)->isValid()) {
+	if (!((MediaVision::Image::ImageTrackingModel *) image_tracking_model)->isValid()) {
 		LOGE("[%s] Image tracking model is invalid.", __FUNCTION__);
 		return MEDIA_VISION_ERROR_INVALID_DATA;
 	}
 
-	((MediaVision::Image::ImageTrackingModel*)image_tracking_model)->refresh();
+	((MediaVision::Image::ImageTrackingModel *) image_tracking_model)->refresh();
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_tracking_model_clone_open(
-		mv_image_tracking_model_h src,
-		mv_image_tracking_model_h *dst)
+int mv_image_tracking_model_clone_open(mv_image_tracking_model_h src, mv_image_tracking_model_h *dst)
 {
 	MEDIA_VISION_INSTANCE_CHECK(src);
 	MEDIA_VISION_NULL_ARG_CHECK(dst);
 
-	(*dst) = (mv_image_tracking_model_h)new (std::nothrow)MediaVision::Image::ImageTrackingModel();
+	(*dst) = (mv_image_tracking_model_h) new (std::nothrow) MediaVision::Image::ImageTrackingModel();
 	if (*dst == NULL) {
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 	}
 
-	*(MediaVision::Image::ImageTrackingModel*)(*dst) = *(MediaVision::Image::ImageTrackingModel*)src;
+	*(MediaVision::Image::ImageTrackingModel *) (*dst) = *(MediaVision::Image::ImageTrackingModel *) src;
 
 	LOGD("Image tracking model has been successfully cloned");
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_tracking_model_save_open(
-		const char *file_name, mv_image_tracking_model_h image_tracking_model)
+int mv_image_tracking_model_save_open(const char *file_name, mv_image_tracking_model_h image_tracking_model)
 {
 	MEDIA_VISION_INSTANCE_CHECK(image_tracking_model);
 
@@ -678,7 +569,7 @@ int mv_image_tracking_model_save_open(
 		return MEDIA_VISION_ERROR_INVALID_PATH;
 	}
 
-	int ret = ((MediaVision::Image::ImageTrackingModel*)image_tracking_model)->save(file_name);
+	int ret = ((MediaVision::Image::ImageTrackingModel *) image_tracking_model)->save(file_name);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Failed to save image tracking model");
 		return ret;
@@ -688,8 +579,7 @@ int mv_image_tracking_model_save_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_image_tracking_model_load_open(
-		const char *file_name, mv_image_tracking_model_h *image_tracking_model)
+int mv_image_tracking_model_load_open(const char *file_name, mv_image_tracking_model_h *image_tracking_model)
 {
 	MEDIA_VISION_NULL_ARG_CHECK(image_tracking_model);
 
@@ -698,13 +588,12 @@ int mv_image_tracking_model_load_open(
 		return MEDIA_VISION_ERROR_INVALID_PATH;
 	}
 
-	(*image_tracking_model) = (mv_image_tracking_model_h)
-			new (std::nothrow)MediaVision::Image::ImageTrackingModel();
+	(*image_tracking_model) = (mv_image_tracking_model_h) new (std::nothrow) MediaVision::Image::ImageTrackingModel();
 
 	if (*image_tracking_model == NULL)
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 
-	int ret = ((MediaVision::Image::ImageTrackingModel*)(*image_tracking_model))->load(file_name);
+	int ret = ((MediaVision::Image::ImageTrackingModel *) (*image_tracking_model))->load(file_name);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Failed to load image tracking model");
 		return ret;
diff --git a/mv_machine_learning/common/include/context.h b/mv_machine_learning/common/include/context.h
index 77932ec..847bbdf 100644
--- a/mv_machine_learning/common/include/context.h
+++ b/mv_machine_learning/common/include/context.h
@@ -24,10 +24,13 @@ namespace mediavision
 {
 namespace common
 {
-class Context {
+class Context
+{
 public:
-	Context() { }
-	~Context() { }
+	Context()
+	{}
+	~Context()
+	{}
 
 	std::map<std::string, void *> __tasks;
 };
diff --git a/mv_machine_learning/common/include/itask.h b/mv_machine_learning/common/include/itask.h
index cacf827..1216ccf 100644
--- a/mv_machine_learning/common/include/itask.h
+++ b/mv_machine_learning/common/include/itask.h
@@ -22,15 +22,15 @@ namespace mediavision
 namespace common
 {
 // T : parameter type, V : return type
-template <typename T, typename V>
-class ITask {
+template<typename T, typename V> class ITask
+{
 public:
-	virtual ~ITask() { };
+	virtual ~ITask() {};
 	virtual void configure() = 0;
 	virtual void prepare() = 0;
-	virtual void setInput(T& t) = 0;
+	virtual void setInput(T &t) = 0;
 	virtual void perform() = 0;
-	virtual V& getOutput() = 0;
+	virtual V &getOutput() = 0;
 };
 } // namespace
 } // namespace
diff --git a/mv_machine_learning/common/include/machine_learning_exception.h b/mv_machine_learning/common/include/machine_learning_exception.h
index 1038c93..6bb857b 100644
--- a/mv_machine_learning/common/include/machine_learning_exception.h
+++ b/mv_machine_learning/common/include/machine_learning_exception.h
@@ -22,54 +22,66 @@
 
 #include <mv_common.h>
 
-namespace mediavision {
-namespace machine_learning {
-namespace exception {
-
-class BaseException : public std::exception {
+namespace mediavision
+{
+namespace machine_learning
+{
+namespace exception
+{
+class BaseException : public std::exception
+{
 private:
 	std::string _msg;
 	int _errorType;
 
 public:
-	BaseException(std::string msg, int errorType) :
-		_msg(msg), _errorType(errorType) {}
+	BaseException(std::string msg, int errorType) : _msg(msg), _errorType(errorType)
+	{}
 	~BaseException() override = default;
 
-	const char* what() const noexcept override { return _msg.c_str(); }
-	int getError() const { return _errorType; }
+	const char *what() const noexcept override
+	{
+		return _msg.c_str();
+	}
+	int getError() const
+	{
+		return _errorType;
+	}
 };
 
-
-class InvalidParameter : public BaseException {
+class InvalidParameter : public BaseException
+{
 public:
-	InvalidParameter(std::string msg) :
-		BaseException("Invalid parameter: " + msg, MEDIA_VISION_ERROR_INVALID_PARAMETER) {}
+	InvalidParameter(std::string msg) : BaseException("Invalid parameter: " + msg, MEDIA_VISION_ERROR_INVALID_PARAMETER)
+	{}
 	~InvalidParameter() override = default;
 };
 
-class InvalidOperation : public BaseException {
+class InvalidOperation : public BaseException
+{
 public:
-	InvalidOperation(std::string msg, int errorType = MEDIA_VISION_ERROR_INVALID_OPERATION) :
-		BaseException("Invalid operation: " + msg, errorType) {}
-	~InvalidOperation() final  = default;
+	InvalidOperation(std::string msg, int errorType = MEDIA_VISION_ERROR_INVALID_OPERATION)
+			: BaseException("Invalid operation: " + msg, errorType)
+	{}
+	~InvalidOperation() final = default;
 };
 
-class OutOfMemory : public BaseException {
+class OutOfMemory : public BaseException
+{
 public:
-	OutOfMemory(std::string msg) :
-		BaseException("Out of memory: " + msg, MEDIA_VISION_ERROR_OUT_OF_MEMORY) {}
+	OutOfMemory(std::string msg) : BaseException("Out of memory: " + msg, MEDIA_VISION_ERROR_OUT_OF_MEMORY)
+	{}
 	~OutOfMemory() final = default;
 };
 
-class NoData : public BaseException {
+class NoData : public BaseException
+{
 public:
-	NoData(std::string msg) :
-		BaseException("No Data: " + msg, MEDIA_VISION_ERROR_NO_DATA) {}
+	NoData(std::string msg) : BaseException("No Data: " + msg, MEDIA_VISION_ERROR_NO_DATA)
+	{}
 	~NoData() final = default;
 };
 
-
 }; // Exception
 }; // MachineLearning
 }; // Mediavision
diff --git a/mv_machine_learning/face_recognition/include/backbone_model_info.h b/mv_machine_learning/face_recognition/include/backbone_model_info.h
index b2164ff..8862d3a 100644
--- a/mv_machine_learning/face_recognition/include/backbone_model_info.h
+++ b/mv_machine_learning/face_recognition/include/backbone_model_info.h
@@ -19,17 +19,20 @@
 
 #include "inference_engine_common_impl.h"
 
-typedef struct {
+typedef struct
+{
 	std::string layer_name;
 	inference_engine_tensor_info tensor_info;
 } model_layer_info;
 
-class IBackboneModelInfo {
+class IBackboneModelInfo
+{
 public:
-	virtual ~IBackboneModelInfo() { }
+	virtual ~IBackboneModelInfo()
+	{}
 
-	virtual std::vector<model_layer_info>& GetInputLayerInfo() = 0;
-	virtual std::vector<model_layer_info>& GetOutputLayerInfo() = 0;
+	virtual std::vector<model_layer_info> &GetInputLayerInfo() = 0;
+	virtual std::vector<model_layer_info> &GetOutputLayerInfo() = 0;
 	virtual std::string GetModelFilePath() = 0;
 };
 
diff --git a/mv_machine_learning/face_recognition/include/face_net_info.h b/mv_machine_learning/face_recognition/include/face_net_info.h
index e2cf317..8e54704 100644
--- a/mv_machine_learning/face_recognition/include/face_net_info.h
+++ b/mv_machine_learning/face_recognition/include/face_net_info.h
@@ -19,7 +19,8 @@
 
 #include "backbone_model_info.h"
 
-class FaceNetInfo : public IBackboneModelInfo {
+class FaceNetInfo : public IBackboneModelInfo
+{
 private:
 	std::vector<model_layer_info> _input_layer_info;
 	std::vector<model_layer_info> _output_layer_info;
@@ -29,8 +30,8 @@ public:
 	FaceNetInfo(std::string model_file_path);
 	~FaceNetInfo();
 
-	std::vector<model_layer_info>& GetInputLayerInfo() override;
-	std::vector<model_layer_info>& GetOutputLayerInfo() override;
+	std::vector<model_layer_info> &GetInputLayerInfo() override;
+	std::vector<model_layer_info> &GetOutputLayerInfo() override;
 	std::string GetModelFilePath() override;
 };
 
diff --git a/mv_machine_learning/face_recognition/include/face_recognition.h b/mv_machine_learning/face_recognition/include/face_recognition.h
index 47e7530..6dcfb3b 100644
--- a/mv_machine_learning/face_recognition/include/face_recognition.h
+++ b/mv_machine_learning/face_recognition/include/face_recognition.h
@@ -38,10 +38,10 @@ namespace machine_learning
 {
 namespace face_recognition
 {
-
 namespace status
 {
-enum {
+enum
+{
 	NONE = 0,
 	INITIALIZED,
 	REGISTERED,
@@ -52,7 +52,8 @@ enum {
 
 namespace mode
 {
-enum {
+enum
+{
 	REGISTER = 0,
 	INFERENCE,
 	DELETE
@@ -61,7 +62,8 @@ enum {
 
 } // face_recognition
 
-typedef struct {
+typedef struct
+{
 	unsigned int mode;
 	std::unordered_map<mv_source_h, std::string> register_src;
 	mv_source_h inference_src;
@@ -73,13 +75,15 @@ typedef struct {
  * @details Contains face recognition result such as label, label index, raw data,
  *          and raw data count.
  */
-typedef struct {
+typedef struct
+{
 	unsigned int label_idx; /**< label index of label file. */
 	std::vector<float> raw_data; /**< raw data to each label. */
 	std::string label; /**< label string. */
 } mv_face_recognition_result_s;
 
-typedef struct {
+typedef struct
+{
 	mv_inference_target_device_e training_target_device_type;
 	mv_inference_backend_type_e training_engine_backend_type;
 	mv_inference_target_device_e inference_target_device_type;
@@ -93,7 +97,8 @@ typedef struct {
 	double decision_threshold;
 } FaceRecognitionConfig;
 
-class FaceRecognition {
+class FaceRecognition
+{
 private:
 	unsigned int _status;
 	std::unique_ptr<mediavision::inference::Inference> _internal;
@@ -103,32 +108,33 @@ private:
 	std::unique_ptr<LabelManager> _label_manager;
 	FaceRecognitionConfig _config;
 	mv_face_recognition_result_s _result;
-	std::vector<std::unique_ptr<DataAugment>> _data_augments;
-
+	std::vector<std::unique_ptr<DataAugment> > _data_augments;
 
 	// FYI. This function should be called every time a new face is registered.
 	void ImportLabel();
-	void CheckFeatureVectorFile(std::unique_ptr<FeatureVectorManager>& old_fvm, std::unique_ptr<FeatureVectorManager>& new_fvm);
+	void CheckFeatureVectorFile(std::unique_ptr<FeatureVectorManager> &old_fvm,
+								std::unique_ptr<FeatureVectorManager> &new_fvm);
 	std::unique_ptr<DataSetManager> CreateDSM(const mv_inference_backend_type_e backend_type);
-	std::unique_ptr<FeatureVectorManager> CreateFVM(const mv_inference_backend_type_e backend_type, std::string file_name);
-	void UpdateDataSet(std::unique_ptr<DataSetManager>& data_set, std::vector<float>& feature_vec, const int label_idx, const int label_cnt);
-	void UpdateDataSet(std::unique_ptr<DataSetManager>& data_set);
+	std::unique_ptr<FeatureVectorManager> CreateFVM(const mv_inference_backend_type_e backend_type,
+													std::string file_name);
+	void UpdateDataSet(std::unique_ptr<DataSetManager> &data_set, std::vector<float> &feature_vec, const int label_idx,
+					   const int label_cnt);
+	void UpdateDataSet(std::unique_ptr<DataSetManager> &data_set);
 	int GetAnswer();
-	std::vector<model_layer_info>& GetBackboneInputLayerInfo();
-	int GetVecFromMvSource(mv_source_h img_src, std::vector<float>& out_vec);
+	std::vector<model_layer_info> &GetBackboneInputLayerInfo();
+	int GetVecFromMvSource(mv_source_h img_src, std::vector<float> &out_vec);
 
 public:
 	FaceRecognition();
-	~ FaceRecognition();
+	~FaceRecognition();
 
 	int Initialize();
-	void SetConfig(FaceRecognitionConfig& config);
+	void SetConfig(FaceRecognitionConfig &config);
 	int RegisterNewFace(mv_source_h img_src, std::string label_name);
 	int RecognizeFace(mv_source_h img_src);
 	int DeleteLabel(std::string label_name);
 	int GetLabel(const char **out_label);
-	mv_face_recognition_result_s& GetResult();
-
+	mv_face_recognition_result_s &GetResult();
 };
 
 } // machine_learning
diff --git a/mv_machine_learning/face_recognition/include/face_recognition_adapter.h b/mv_machine_learning/face_recognition/include/face_recognition_adapter.h
index 97cebbf..0839b80 100644
--- a/mv_machine_learning/face_recognition/include/face_recognition_adapter.h
+++ b/mv_machine_learning/face_recognition/include/face_recognition_adapter.h
@@ -60,9 +60,8 @@ namespace mediavision
 {
 namespace machine_learning
 {
-
-template <typename T, typename V>
-class FaceRecognitionAdapter : public mediavision::common::ITask<T, V> {
+template<typename T, typename V> class FaceRecognitionAdapter : public mediavision::common::ITask<T, V>
+{
 private:
 	std::unique_ptr<FaceRecognition> _face_recognition;
 	mv_face_recognition_input_s _source;
@@ -72,16 +71,16 @@ public:
 	FaceRecognitionAdapter();
 	~FaceRecognitionAdapter();
 
-	std::unique_ptr<MediaVision::Common::EngineConfig>& getConfig()
+	std::unique_ptr<MediaVision::Common::EngineConfig> &getConfig()
 	{
 		return _config;
 	}
 
 	void configure() override;
 	void prepare() override;
-	void setInput(T& t) override;
+	void setInput(T &t) override;
 	void perform() override;
-	V& getOutput() override;
+	V &getOutput() override;
 };
 
 } // machine_learning
diff --git a/mv_machine_learning/face_recognition/include/mv_face_recognition_open.h b/mv_machine_learning/face_recognition/include/mv_face_recognition_open.h
index 5055ec5..b698d27 100644
--- a/mv_machine_learning/face_recognition/include/mv_face_recognition_open.h
+++ b/mv_machine_learning/face_recognition/include/mv_face_recognition_open.h
@@ -22,11 +22,10 @@
 #include <mv_face_recognition_type.h>
 
 #ifdef __cplusplus
-extern "C"
-{
+extern "C" {
 #endif /* __cplusplus */
 
-	/**
+/**
 	 * @brief Create face recognition object handle.
 	 * @details Use this function to create an face recognition object handle.
 	 *          After creation the handle has to be prepared with
@@ -48,9 +47,9 @@ extern "C"
 	 *
 	 * @see mv_face_recognition_destroy_open()
 	 */
-	int mv_face_recognition_create_open(mv_face_recognition_h *out_handle);
+int mv_face_recognition_create_open(mv_face_recognition_h *out_handle);
 
-	/**
+/**
 	 * @brief Destroy face recognition handle and releases all its resources.
 	 *
 	 * @since_tizen 7.0
@@ -65,9 +64,9 @@ extern "C"
 	 *
 	 * @see mv_face_recognition_create_open()
 	 */
-	int mv_face_recognition_destroy_open(mv_face_recognition_h handle);
+int mv_face_recognition_destroy_open(mv_face_recognition_h handle);
 
-	/**
+/**
 	 * @brief Prepare face recognition.
 	 *
 	 * @since_tizen 7.0
@@ -82,9 +81,9 @@ extern "C"
 	 *
 	 * @see mv_face_recognition_create_open()
 	 */
-	int mv_face_recognition_prepare_open(mv_face_recognition_h handle);
+int mv_face_recognition_prepare_open(mv_face_recognition_h handle);
 
-	/**
+/**
 	 * @brief Register a new face on the @a source
 	 * @details Use this function to register a new face.
 	 *          Each time when this function is called, a new face on the media source
@@ -107,9 +106,9 @@ extern "C"
 	 * @pre Create an face recognition handle by calling @ref mv_face_recognition_create_open()
 	 * @pre Prepare an face recognition by calling @ref mv_face_recognition_prepare_open()
 	 */
-	int mv_face_recognition_register_open(mv_face_recognition_h handle, mv_source_h source, const char *label);
+int mv_face_recognition_register_open(mv_face_recognition_h handle, mv_source_h source, const char *label);
 
-	/**
+/**
 	 * @brief Unregister a new face on the @a source
 	 * @details Use this function to unregister a given label.
 	 *          Each time when this function is called, all data related to the label
@@ -130,9 +129,9 @@ extern "C"
 	 * @pre Create an face recognition handle by calling @ref mv_face_recognition_create_open()
 	 * @pre Prepare an face recognition by calling @ref mv_face_recognition_prepare_open()
 	 */
-	int mv_face_recognition_unregister_open(mv_face_recognition_h handle, const char *label);
+int mv_face_recognition_unregister_open(mv_face_recognition_h handle, const char *label);
 
-	/**
+/**
 	 * @brief Inference with a given face on the @a source
 	 * @details Use this function to inference with a given source.
 	 *
@@ -154,9 +153,9 @@ extern "C"
 	 * @pre Prepare an face recognition by calling @ref mv_face_recognition_prepare_open()
 	 * @pre Register a new face by calling @ref mv_face_recognition_register_open()
 	 */
-	int mv_face_recognition_inference_open(mv_face_recognition_h handle, mv_source_h source);
+int mv_face_recognition_inference_open(mv_face_recognition_h handle, mv_source_h source);
 
-	/**
+/**
 	 * @brief Get a label name and store it to @a out_label.
 	 * @details Use this function to get a label name after calling mv_face_recognition_inference_open function.
 	 *
@@ -172,7 +171,7 @@ extern "C"
 	 *
 	 * @pre Request a inference by calling @ref mv_face_recognition_inference_open()
 	 */
-	int mv_face_recognition_get_label_open(mv_face_recognition_h handle, const char **out_label);
+int mv_face_recognition_get_label_open(mv_face_recognition_h handle, const char **out_label);
 
 #ifdef __cplusplus
 }
diff --git a/mv_machine_learning/face_recognition/include/nntrainer_dsm.h b/mv_machine_learning/face_recognition/include/nntrainer_dsm.h
index fda9cc2..a2ece91 100644
--- a/mv_machine_learning/face_recognition/include/nntrainer_dsm.h
+++ b/mv_machine_learning/face_recognition/include/nntrainer_dsm.h
@@ -17,15 +17,15 @@
 #ifndef __NNTRAINER_DSM_H__
 #define __NNTRAINER_DSM_H__
 
-
 #include <string>
 
 #include "feature_vector_manager.h"
 #include "data_set_manager.h"
 
-class NNTrainerDSM : public DataSetManager {
+class NNTrainerDSM : public DataSetManager
+{
 private:
-	void PrintHeader(FeaVecHeader& fvh);
+	void PrintHeader(FeaVecHeader &fvh);
 
 public:
 	NNTrainerDSM();
diff --git a/mv_machine_learning/face_recognition/include/nntrainer_fvm.h b/mv_machine_learning/face_recognition/include/nntrainer_fvm.h
index f2647ec..c410fa3 100644
--- a/mv_machine_learning/face_recognition/include/nntrainer_fvm.h
+++ b/mv_machine_learning/face_recognition/include/nntrainer_fvm.h
@@ -23,14 +23,15 @@
 #include "feature_vector_manager.h"
 #include "file_util.h"
 
-class NNTrainerFVM : public FeatureVectorManager {
+class NNTrainerFVM : public FeatureVectorManager
+{
 public:
 	NNTrainerFVM(const std::string feature_vector_file = "feature_vector_file.dat");
 	~NNTrainerFVM() = default;
 
-	void WriteHeader(size_t feature_size, size_t one_hot_table_size, unsigned int  data_set_cnt) override;
-	void ReadHeader(FeaVecHeader& header) override;
-	void WriteFeatureVec(std::vector<float>& feature_vec, const int max_label, const int label_index) override;
+	void WriteHeader(size_t feature_size, size_t one_hot_table_size, unsigned int data_set_cnt) override;
+	void ReadHeader(FeaVecHeader &header) override;
+	void WriteFeatureVec(std::vector<float> &feature_vec, const int max_label, const int label_index) override;
 	void Remove() override;
 };
 
diff --git a/mv_machine_learning/face_recognition/include/simple_shot.h b/mv_machine_learning/face_recognition/include/simple_shot.h
index d2e025d..dc5d63b 100644
--- a/mv_machine_learning/face_recognition/include/simple_shot.h
+++ b/mv_machine_learning/face_recognition/include/simple_shot.h
@@ -20,12 +20,15 @@
 #include <mv_inference_type.h>
 #include "training_model.h"
 
-class SimpleShot : public TrainingModel {
+class SimpleShot : public TrainingModel
+{
 private:
 	TrainingEngineBackendInfo _engine_info;
+
 private:
 	void SaveModel(const std::string file_path) override;
 	void RemoveModel(const std::string file_path) override;
+
 public:
 	SimpleShot(const mv_inference_backend_type_e backend_type = MV_INFERENCE_BACKEND_NNTRAINER,
 			   const mv_inference_target_device_e target_type = MV_INFERENCE_TARGET_DEVICE_CPU,
@@ -34,7 +37,7 @@ public:
 
 	// Configure layers for SimpleShot learning.
 	void ConfigureModel(int num_of_class) override;
-	TrainingEngineBackendInfo& GetTrainingEngineInfo() override;
+	TrainingEngineBackendInfo &GetTrainingEngineInfo() override;
 };
 
 #endif
\ No newline at end of file
diff --git a/mv_machine_learning/face_recognition/src/face_net_info.cpp b/mv_machine_learning/face_recognition/src/face_net_info.cpp
index 8224787..888e51b 100644
--- a/mv_machine_learning/face_recognition/src/face_net_info.cpp
+++ b/mv_machine_learning/face_recognition/src/face_net_info.cpp
@@ -22,12 +22,9 @@ FaceNetInfo::FaceNetInfo(string model_file_path)
 {
 	_model_file_path = model_file_path;
 
-	const string input_layer_name = {  "input_1" };
+	const string input_layer_name = { "input_1" };
 	const inference_engine_tensor_info input_tensor_info = {
-		{ 160, 160, 3, 1 },
-		INFERENCE_TENSOR_SHAPE_NCHW,
-		INFERENCE_TENSOR_DATA_TYPE_FLOAT32,
-		(size_t)(1 * 3 * 160 * 160)
+		{ 160, 160, 3, 1 }, INFERENCE_TENSOR_SHAPE_NCHW, INFERENCE_TENSOR_DATA_TYPE_FLOAT32, (size_t)(1 * 3 * 160 * 160)
 	};
 
 	model_layer_info input_info = { input_layer_name, input_tensor_info };
@@ -35,10 +32,7 @@ FaceNetInfo::FaceNetInfo(string model_file_path)
 
 	const string output_layer_name = { "normalize/l2_normalize" };
 	const inference_engine_tensor_info output_tensor_info = {
-		{ 512, 1, 1, 1 },
-		INFERENCE_TENSOR_SHAPE_NCHW,
-		INFERENCE_TENSOR_DATA_TYPE_FLOAT32,
-		(size_t)(1 * 512)
+		{ 512, 1, 1, 1 }, INFERENCE_TENSOR_SHAPE_NCHW, INFERENCE_TENSOR_DATA_TYPE_FLOAT32, (size_t)(1 * 512)
 	};
 
 	model_layer_info output_info = { output_layer_name, output_tensor_info };
@@ -56,12 +50,12 @@ string FaceNetInfo::GetModelFilePath()
 	return _model_file_path;
 }
 
-vector<model_layer_info>& FaceNetInfo::GetInputLayerInfo()
+vector<model_layer_info> &FaceNetInfo::GetInputLayerInfo()
 {
 	return _input_layer_info;
 }
 
-vector<model_layer_info>& FaceNetInfo::GetOutputLayerInfo()
+vector<model_layer_info> &FaceNetInfo::GetOutputLayerInfo()
 {
 	return _output_layer_info;
 }
\ No newline at end of file
diff --git a/mv_machine_learning/face_recognition/src/face_recognition.cpp b/mv_machine_learning/face_recognition/src/face_recognition.cpp
index 41a71ed..678ecd3 100644
--- a/mv_machine_learning/face_recognition/src/face_recognition.cpp
+++ b/mv_machine_learning/face_recognition/src/face_recognition.cpp
@@ -45,9 +45,15 @@ namespace mediavision
 {
 namespace machine_learning
 {
-
-FaceRecognition::FaceRecognition() :
-		_status(NONE), _internal(), _backbone(), _backbone_model_info(), _training_model(), _label_manager(), _config(), _result()
+FaceRecognition::FaceRecognition()
+		: _status(NONE)
+		, _internal()
+		, _backbone()
+		, _backbone_model_info()
+		, _training_model()
+		, _label_manager()
+		, _config()
+		, _result()
 {
 	_data_augments.push_back(std::make_unique<DataAugmentDefault>());
 	/* Add other data argument classes. */
@@ -59,7 +65,8 @@ FaceRecognition::~FaceRecognition()
 		_label_manager->Clear();
 }
 
-void FaceRecognition::CheckFeatureVectorFile(unique_ptr<FeatureVectorManager>& old_fvm, unique_ptr<FeatureVectorManager>& new_fvm)
+void FaceRecognition::CheckFeatureVectorFile(unique_ptr<FeatureVectorManager> &old_fvm,
+											 unique_ptr<FeatureVectorManager> &new_fvm)
 {
 	// Change new feature vector file to existing one in case that current process is terminated just after removing existing feature vector file but
 	// new feature vector file isn't changed to existing one yet.
@@ -82,7 +89,7 @@ void FaceRecognition::CheckFeatureVectorFile(unique_ptr<FeatureVectorManager>& o
 
 unique_ptr<DataSetManager> FaceRecognition::CreateDSM(const mv_inference_backend_type_e backend_type)
 {
-	switch(backend_type) {
+	switch (backend_type) {
 	case MV_INFERENCE_BACKEND_NNTRAINER:
 		return make_unique<NNTrainerDSM>();
 	default:
@@ -92,9 +99,10 @@ unique_ptr<DataSetManager> FaceRecognition::CreateDSM(const mv_inference_backend
 	throw InvalidParameter("Invalid training engine backend type.");
 }
 
-unique_ptr<FeatureVectorManager> FaceRecognition::CreateFVM(const mv_inference_backend_type_e backend_type, string file_name)
+unique_ptr<FeatureVectorManager> FaceRecognition::CreateFVM(const mv_inference_backend_type_e backend_type,
+															string file_name)
 {
-	switch(backend_type) {
+	switch (backend_type) {
 	case MV_INFERENCE_BACKEND_NNTRAINER:
 		return make_unique<NNTrainerFVM>(file_name);
 	default:
@@ -104,7 +112,8 @@ unique_ptr<FeatureVectorManager> FaceRecognition::CreateFVM(const mv_inference_b
 	throw InvalidParameter("Invalid training engine backend type.");
 }
 
-void FaceRecognition::UpdateDataSet(unique_ptr<DataSetManager>& data_set, vector<float>& feature_vec, const int label_idx, const int label_cnt)
+void FaceRecognition::UpdateDataSet(unique_ptr<DataSetManager> &data_set, vector<float> &feature_vec,
+									const int label_idx, const int label_cnt)
 {
 	size_t data_set_cnt = 0;
 
@@ -124,7 +133,7 @@ void FaceRecognition::UpdateDataSet(unique_ptr<DataSetManager>& data_set, vector
 		if (FaceRecogUtil::IsFileExist(fvm->GetFileName())) {
 			data_set->LoadDataSet(fvm->GetFileName());
 
-			vector<vector<float>> feature_vectors = data_set->GetData();
+			vector<vector<float> > feature_vectors = data_set->GetData();
 			vector<unsigned int> label_idx_vectors = data_set->GetLabelIdx();
 
 			// 1) Write existing feature vectors and its one-hot encoding table considered
@@ -165,13 +174,13 @@ void FaceRecognition::UpdateDataSet(unique_ptr<DataSetManager>& data_set, vector
 
 		data_set->Clear();
 		data_set->LoadDataSet(fvm->GetFileName());
-	} catch (const BaseException& e) {
+	} catch (const BaseException &e) {
 		LOGE("%s", e.what());
 		throw e;
 	}
 }
 
-void FaceRecognition::UpdateDataSet(unique_ptr<DataSetManager>& data_set)
+void FaceRecognition::UpdateDataSet(unique_ptr<DataSetManager> &data_set)
 {
 	try {
 		data_set = CreateDSM(_config.training_engine_backend_type);
@@ -182,23 +191,23 @@ void FaceRecognition::UpdateDataSet(unique_ptr<DataSetManager>& data_set)
 			throw InvalidOperation("Feature vector file not found.");
 
 		data_set->LoadDataSet(fvm->GetFileName());
-	} catch (const BaseException& e) {
+	} catch (const BaseException &e) {
 		LOGE("%s", e.what());
 		throw e;
 	}
 }
 
-void FaceRecognition::SetConfig(FaceRecognitionConfig& config)
+void FaceRecognition::SetConfig(FaceRecognitionConfig &config)
 {
 	_config = config;
 }
 
-std::vector<model_layer_info>& FaceRecognition::GetBackboneInputLayerInfo()
+std::vector<model_layer_info> &FaceRecognition::GetBackboneInputLayerInfo()
 {
 	return _backbone_model_info->GetInputLayerInfo();
 }
 
-int FaceRecognition::GetVecFromMvSource(mv_source_h img_src, std::vector<float>& out_vec)
+int FaceRecognition::GetVecFromMvSource(mv_source_h img_src, std::vector<float> &out_vec)
 {
 	mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
 	unsigned int width = 0, height = 0, bufferSize = 0;
@@ -208,7 +217,7 @@ int FaceRecognition::GetVecFromMvSource(mv_source_h img_src, std::vector<float>&
 		mv_source_get_height(img_src, &height) != MEDIA_VISION_ERROR_NONE ||
 		mv_source_get_colorspace(img_src, &colorspace) != MEDIA_VISION_ERROR_NONE ||
 		mv_source_get_buffer(img_src, &buffer, &bufferSize))
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 
 	// TODO. Let's support various color spaces.
 
@@ -217,7 +226,7 @@ int FaceRecognition::GetVecFromMvSource(mv_source_h img_src, std::vector<float>&
 		return MEDIA_VISION_ERROR_NOT_SUPPORTED_FORMAT;
 	}
 
-	vector<model_layer_info>& input_layer_info = GetBackboneInputLayerInfo();
+	vector<model_layer_info> &input_layer_info = GetBackboneInputLayerInfo();
 	// TODO. consider multiple tensor info.
 	size_t re_width = input_layer_info[0].tensor_info.shape[0];
 	size_t re_height = input_layer_info[0].tensor_info.shape[1];
@@ -246,12 +255,12 @@ int FaceRecognition::Initialize()
 	vector<string> input_layer_names, output_layer_names;
 	vector<inference_engine_tensor_info> input_tensor_info, output_tensor_info;
 
-	for (auto& input : _backbone_model_info->GetInputLayerInfo()) {
+	for (auto &input : _backbone_model_info->GetInputLayerInfo()) {
 		input_layer_names.push_back(input.layer_name);
 		input_tensor_info.push_back(input.tensor_info);
 	}
 
-	for (auto& output : _backbone_model_info->GetOutputLayerInfo()) {
+	for (auto &output : _backbone_model_info->GetOutputLayerInfo()) {
 		output_layer_names.push_back(output.layer_name);
 		output_tensor_info.push_back(output.tensor_info);
 	}
@@ -264,7 +273,7 @@ int FaceRecognition::Initialize()
 		return ret;
 
 	// Tensor order is NCHW.
-	vector<model_layer_info>& input_layer_info = GetBackboneInputLayerInfo();
+	vector<model_layer_info> &input_layer_info = GetBackboneInputLayerInfo();
 	size_t width = input_layer_info[0].tensor_info.shape[0];
 	size_t height = input_layer_info[0].tensor_info.shape[1];
 	size_t ch = input_layer_info[0].tensor_info.shape[2];
@@ -277,9 +286,8 @@ int FaceRecognition::Initialize()
 	if (ret != MEDIA_VISION_ERROR_NONE)
 		return ret;
 
-	_training_model = make_unique<SimpleShot>(_config.training_engine_backend_type,
-												_config.training_target_device_type,
-												_config.internal_model_file_path);
+	_training_model = make_unique<SimpleShot>(_config.training_engine_backend_type, _config.training_target_device_type,
+											  _config.internal_model_file_path);
 
 	_internal = make_unique<Inference>();
 
@@ -287,7 +295,6 @@ int FaceRecognition::Initialize()
 	if (ret != MEDIA_VISION_ERROR_NONE)
 		return ret;
 
-
 	_status = INITIALIZED;
 
 	return MEDIA_VISION_ERROR_NONE;
@@ -304,7 +311,7 @@ void FaceRecognition::ImportLabel()
 		int cnt = _label_manager->ImportLabel();
 
 		LOGD("%d labels have been imported", cnt);
-	} catch (const BaseException& e) {
+	} catch (const BaseException &e) {
 		LOGE("%s", e.what());
 		throw e;
 	}
@@ -312,7 +319,7 @@ void FaceRecognition::ImportLabel()
 
 int FaceRecognition::RegisterNewFace(mv_source_h img_src, string label_name)
 {
-	vector<model_layer_info>& output_layer_info = _backbone_model_info->GetOutputLayerInfo();
+	vector<model_layer_info> &output_layer_info = _backbone_model_info->GetOutputLayerInfo();
 
 	if (_status < INITIALIZED) {
 		LOGE("Initialization not ready yet. (%u)", _status);
@@ -325,7 +332,7 @@ int FaceRecognition::RegisterNewFace(mv_source_h img_src, string label_name)
 		ImportLabel();
 
 		// 1. Store only label names to label file, which aren't duplicated.
-		bool duplicated  = _label_manager->AddLabelToMap(label_name, label_name);
+		bool duplicated = _label_manager->AddLabelToMap(label_name, label_name);
 		if (!duplicated) {
 			int ret = _label_manager->AddLabelToFile(label_name);
 			if (ret == 0)
@@ -344,7 +351,8 @@ int FaceRecognition::RegisterNewFace(mv_source_h img_src, string label_name)
 		// 2. Get feature vector from a given vec through inference engine.
 		// Ps. output layer size should be 1.
 		TensorBuffer tensorBuffer = _backbone->GetOutputTensorBuffer();
-		inference_engine_tensor_buffer *backbone_output_buffer = tensorBuffer.getTensorBuffer(output_layer_info[0].layer_name);
+		inference_engine_tensor_buffer *backbone_output_buffer =
+				tensorBuffer.getTensorBuffer(output_layer_info[0].layer_name);
 		if (!backbone_output_buffer) {
 			LOGE("fail to get output tensor buffer.");
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -372,7 +380,7 @@ int FaceRecognition::RegisterNewFace(mv_source_h img_src, string label_name)
 		// again in this case. So make sure to clear previous data set before next training.
 		_training_model->ClearDataSet(data_set);
 		_status = REGISTERED;
-	} catch (const BaseException& e) {
+	} catch (const BaseException &e) {
 		LOGE("%s", e.what());
 		return e.getError();
 	}
@@ -387,7 +395,7 @@ int FaceRecognition::GetAnswer()
 	string result_str;
 
 	try {
-		for (auto& r : _result.raw_data)
+		for (auto &r : _result.raw_data)
 			result_str += to_string(r) + " ";
 
 		LOGD("raw data = %s", result_str.c_str());
@@ -402,7 +410,7 @@ int FaceRecognition::GetAnswer()
 		float weighted = _result.raw_data[answer_idx] * _label_manager->GetDecisionWeight();
 
 		// Check decision weight threshold.
-		for (auto& r : _result.raw_data) {
+		for (auto &r : _result.raw_data) {
 			if (_result.raw_data[answer_idx] == r)
 				continue;
 
@@ -411,7 +419,7 @@ int FaceRecognition::GetAnswer()
 		}
 
 		_result.label_idx = answer_idx;
-	} catch (const BaseException& e) {
+	} catch (const BaseException &e) {
 		LOGE("%s", e.what());
 		return e.getError();
 	}
@@ -432,10 +440,10 @@ int FaceRecognition::RecognizeFace(mv_source_h img_src)
 	}
 
 	TrainingEngineBackendInfo engine_info = _training_model->GetTrainingEngineInfo();
-	vector<string>& input_layers = engine_info.input_layer_names;
-	vector<inference_engine_tensor_info>& input_tensor_info = engine_info.input_tensor_info;
-	vector<string>& output_layers = engine_info.output_layer_names;
-	vector<inference_engine_tensor_info>& output_tensor_info = engine_info.output_tensor_info;
+	vector<string> &input_layers = engine_info.input_layer_names;
+	vector<inference_engine_tensor_info> &input_tensor_info = engine_info.input_tensor_info;
+	vector<string> &output_layers = engine_info.output_layer_names;
+	vector<inference_engine_tensor_info> &output_tensor_info = engine_info.output_tensor_info;
 
 	// Face Recognition has following steps
 	// ------------------------------------
@@ -453,7 +461,8 @@ int FaceRecognition::RecognizeFace(mv_source_h img_src)
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 		}
 
-		if (_backbone_model_info->GetOutputLayerInfo().empty() || _backbone_model_info->GetOutputLayerInfo().size() > 1) {
+		if (_backbone_model_info->GetOutputLayerInfo().empty() ||
+			_backbone_model_info->GetOutputLayerInfo().size() > 1) {
 			LOGE("Invalid output layer size - output layer size should be 1.");
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 		}
@@ -469,10 +478,11 @@ int FaceRecognition::RecognizeFace(mv_source_h img_src)
 		}
 
 		// Get output layer info for facenet model.
-		vector<model_layer_info>& output_layer_info = _backbone_model_info->GetOutputLayerInfo();
+		vector<model_layer_info> &output_layer_info = _backbone_model_info->GetOutputLayerInfo();
 		// Get output tensor buffer to the output layer.
 		TensorBuffer tensorBuffer = _backbone->GetOutputTensorBuffer();
-		inference_engine_tensor_buffer *backbone_output_buffer = tensorBuffer.getTensorBuffer(output_layer_info[0].layer_name);
+		inference_engine_tensor_buffer *backbone_output_buffer =
+				tensorBuffer.getTensorBuffer(output_layer_info[0].layer_name);
 		if (!backbone_output_buffer) {
 			LOGE("fail to get backbone output tensor buffer.");
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -522,7 +532,7 @@ int FaceRecognition::RecognizeFace(mv_source_h img_src)
 		_status = INFERENCED;
 
 		return GetAnswer();
-	} catch (const BaseException& e) {
+	} catch (const BaseException &e) {
 		LOGE("%s", e.what());
 		return e.getError();
 	}
@@ -564,7 +574,7 @@ int FaceRecognition::DeleteLabel(string label_name)
 
 		data_set->LoadDataSet(fvm->GetFileName());
 
-		vector<vector<float>> feature_vectors = data_set->GetData();
+		vector<vector<float> > feature_vectors = data_set->GetData();
 		vector<unsigned int> label_idx_vectors = data_set->GetLabelIdx();
 
 		size_t data_set_cnt = 0;
@@ -630,7 +640,7 @@ int FaceRecognition::DeleteLabel(string label_name)
 		}
 
 		_status = DELETED;
-	} catch (const BaseException& e) {
+	} catch (const BaseException &e) {
 		LOGE("%s", e.what());
 		return e.getError();
 	}
@@ -647,7 +657,7 @@ int FaceRecognition::GetLabel(const char **out_label)
 
 	try {
 		_label_manager->GetLabelString(_result.label, _result.label_idx);
-	} catch (const BaseException& e) {
+	} catch (const BaseException &e) {
 		LOGE("%s", e.what());
 		return e.getError();
 	}
@@ -657,20 +667,20 @@ int FaceRecognition::GetLabel(const char **out_label)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
- mv_face_recognition_result_s& FaceRecognition::GetResult()
- {
+mv_face_recognition_result_s &FaceRecognition::GetResult()
+{
 	if (!_label_manager)
 		throw NoData("Label file doesn't exist.");
 
 	try {
 		_label_manager->GetLabelString(_result.label, _result.label_idx);
-	} catch (const BaseException& e) {
+	} catch (const BaseException &e) {
 		LOGE("%s", e.what());
 		throw e;
 	}
 
 	return _result;
- }
+}
 
 } // machine_learning
 } // mediavision
\ No newline at end of file
diff --git a/mv_machine_learning/face_recognition/src/face_recognition_adapter.cpp b/mv_machine_learning/face_recognition/src/face_recognition_adapter.cpp
index dba1829..2fcca3a 100644
--- a/mv_machine_learning/face_recognition/src/face_recognition_adapter.cpp
+++ b/mv_machine_learning/face_recognition/src/face_recognition_adapter.cpp
@@ -17,7 +17,7 @@
 #include "machine_learning_exception.h"
 #include "face_recognition_adapter.h"
 
-#define FACE_RECOGNITION_META_FILE_NAME	"face_recognition.json"
+#define FACE_RECOGNITION_META_FILE_NAME "face_recognition.json"
 
 using namespace std;
 using namespace MediaVision::Common;
@@ -28,27 +28,19 @@ namespace mediavision
 {
 namespace machine_learning
 {
-
-template <typename T, typename V>
-FaceRecognitionAdapter<T, V>::FaceRecognitionAdapter()
+template<typename T, typename V> FaceRecognitionAdapter<T, V>::FaceRecognitionAdapter()
 {
 	_face_recognition = make_unique<FaceRecognition>();
 }
 
-template <typename T, typename V>
-FaceRecognitionAdapter<T, V>::~FaceRecognitionAdapter()
-{
-
-}
+template<typename T, typename V> FaceRecognitionAdapter<T, V>::~FaceRecognitionAdapter()
+{}
 
-template <typename T, typename V>
-void FaceRecognitionAdapter<T, V>::configure()
+template<typename T, typename V> void FaceRecognitionAdapter<T, V>::configure()
 {
-	_config = make_unique<EngineConfig>(string(MV_CONFIG_PATH) +
-										string(FACE_RECOGNITION_META_FILE_NAME));
+	_config = make_unique<EngineConfig>(string(MV_CONFIG_PATH) + string(FACE_RECOGNITION_META_FILE_NAME));
 	string backboneModelFilePath;
-	int ret = _config->getStringAttribute(string(MV_FACE_RECOGNITION_BACKBONE_MODEL_FILE_PATH),
-											&backboneModelFilePath);
+	int ret = _config->getStringAttribute(string(MV_FACE_RECOGNITION_BACKBONE_MODEL_FILE_PATH), &backboneModelFilePath);
 	if (ret != MEDIA_VISION_ERROR_NONE)
 		throw InvalidParameter("Failed to get an attribute");
 
@@ -56,16 +48,14 @@ void FaceRecognitionAdapter<T, V>::configure()
 
 	string defaultPath;
 
-	ret = _config->getStringAttribute(string(MV_FACE_RECOGNITION_DEFAULT_PATH),
-										&defaultPath);
+	ret = _config->getStringAttribute(string(MV_FACE_RECOGNITION_DEFAULT_PATH), &defaultPath);
 	if (ret != MEDIA_VISION_ERROR_NONE)
 		throw InvalidOperation("Fail to get default path.");
 
 	LOGD("Default path : %s", defaultPath.c_str());
 
 	double decisionThreshold = 0.0f;
-	ret = _config->getDoubleAttribute(string(MV_FACE_RECOGNITION_DECISION_THRESHOLD),
-										&decisionThreshold);
+	ret = _config->getDoubleAttribute(string(MV_FACE_RECOGNITION_DECISION_THRESHOLD), &decisionThreshold);
 	if (ret != MEDIA_VISION_ERROR_NONE)
 		throw InvalidOperation("Fail to get default decision threshold value.");
 
@@ -86,25 +76,22 @@ void FaceRecognitionAdapter<T, V>::configure()
 	_face_recognition->SetConfig(config);
 }
 
-template <typename T, typename V>
-void FaceRecognitionAdapter<T, V>::prepare()
+template<typename T, typename V> void FaceRecognitionAdapter<T, V>::prepare()
 {
 	int ret = _face_recognition->Initialize();
 	if (ret != MEDIA_VISION_ERROR_NONE)
 		throw InvalidOperation("Fail to initialize face recognition.");
 }
 
-template <typename T, typename V>
-void FaceRecognitionAdapter<T, V>::setInput(T& t)
+template<typename T, typename V> void FaceRecognitionAdapter<T, V>::setInput(T &t)
 {
 	_source = t;
 }
 
-template <typename T, typename V>
-void FaceRecognitionAdapter<T, V>::perform()
+template<typename T, typename V> void FaceRecognitionAdapter<T, V>::perform()
 {
 	if (_source.mode == mode::REGISTER) {
-		for (auto& s : _source.register_src) {
+		for (auto &s : _source.register_src) {
 			int ret = _face_recognition->RegisterNewFace(s.first, s.second);
 			if (ret != MEDIA_VISION_ERROR_NONE)
 				throw InvalidOperation("Fail to register new face.");
@@ -118,14 +105,14 @@ void FaceRecognitionAdapter<T, V>::perform()
 		if (ret == MEDIA_VISION_ERROR_NO_DATA)
 			throw NoData("Label not found.");
 
-		if  (ret != MEDIA_VISION_ERROR_NONE)
+		if (ret != MEDIA_VISION_ERROR_NONE)
 			throw InvalidOperation("Fail to request a recognition.");
 
 		return;
 	}
 
 	if (_source.mode == mode::DELETE) {
-		for (auto& l : _source.labels) {
+		for (auto &l : _source.labels) {
 			int ret = _face_recognition->DeleteLabel(l);
 			if (ret != MEDIA_VISION_ERROR_NONE)
 				throw InvalidOperation("Fail to unregister a given label.");
@@ -135,8 +122,7 @@ void FaceRecognitionAdapter<T, V>::perform()
 	}
 }
 
-template <typename T, typename V>
-V& FaceRecognitionAdapter<T, V>::getOutput()
+template<typename T, typename V> V &FaceRecognitionAdapter<T, V>::getOutput()
 {
 	return _face_recognition->GetResult();
 }
diff --git a/mv_machine_learning/face_recognition/src/mv_face_recognition.c b/mv_machine_learning/face_recognition/src/mv_face_recognition.c
index 49ca8b4..1a7cd6a 100644
--- a/mv_machine_learning/face_recognition/src/mv_face_recognition.c
+++ b/mv_machine_learning/face_recognition/src/mv_face_recognition.c
@@ -20,8 +20,7 @@
 
 int mv_face_recognition_create(mv_face_recognition_h *out_handle)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-		_mv_inference_face_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_face_check_system_info_feature_supported());
 
 	MEDIA_VISION_NULL_ARG_CHECK(out_handle);
 
@@ -38,8 +37,7 @@ int mv_face_recognition_create(mv_face_recognition_h *out_handle)
 
 int mv_face_recognition_destroy(mv_face_recognition_h handle)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-		_mv_inference_face_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_face_check_system_info_feature_supported());
 
 	MEDIA_VISION_INSTANCE_CHECK(handle);
 
@@ -56,8 +54,7 @@ int mv_face_recognition_destroy(mv_face_recognition_h handle)
 
 int mv_face_recognition_prepare(mv_face_recognition_h handle)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-		_mv_inference_face_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_face_check_system_info_feature_supported());
 
 	MEDIA_VISION_INSTANCE_CHECK(handle);
 
@@ -74,8 +71,7 @@ int mv_face_recognition_prepare(mv_face_recognition_h handle)
 
 int mv_face_recognition_register(mv_face_recognition_h handle, mv_source_h source, const char *label)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-		_mv_inference_face_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_face_check_system_info_feature_supported());
 
 	MEDIA_VISION_INSTANCE_CHECK(handle);
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -94,8 +90,7 @@ int mv_face_recognition_register(mv_face_recognition_h handle, mv_source_h sourc
 
 int mv_face_recognition_unregister(mv_face_recognition_h handle, const char *label)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-		_mv_inference_face_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_face_check_system_info_feature_supported());
 
 	MEDIA_VISION_INSTANCE_CHECK(handle);
 	MEDIA_VISION_INSTANCE_CHECK(label);
@@ -113,8 +108,7 @@ int mv_face_recognition_unregister(mv_face_recognition_h handle, const char *lab
 
 int mv_face_recognition_inference(mv_face_recognition_h handle, mv_source_h source)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-		_mv_inference_face_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_face_check_system_info_feature_supported());
 
 	MEDIA_VISION_INSTANCE_CHECK(handle);
 	MEDIA_VISION_INSTANCE_CHECK(source);
@@ -132,8 +126,7 @@ int mv_face_recognition_inference(mv_face_recognition_h handle, mv_source_h sour
 
 int mv_face_recognition_get_label(mv_face_recognition_h handle, const char **out_label)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-		_mv_inference_face_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_face_check_system_info_feature_supported());
 
 	MEDIA_VISION_INSTANCE_CHECK(handle);
 	MEDIA_VISION_INSTANCE_CHECK(out_label);
diff --git a/mv_machine_learning/face_recognition/src/mv_face_recognition_open.cpp b/mv_machine_learning/face_recognition/src/mv_face_recognition_open.cpp
index 9ac8351..5d305f3 100644
--- a/mv_machine_learning/face_recognition/src/mv_face_recognition_open.cpp
+++ b/mv_machine_learning/face_recognition/src/mv_face_recognition_open.cpp
@@ -37,14 +37,14 @@ int mv_face_recognition_create_open(mv_face_recognition_h *handle)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	Context *context = new (nothrow)Context();
+	Context *context = new (nothrow) Context();
 	if (!context) {
 		LOGE("Fail to allocate a context.");
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 	}
 
-	FaceRecognitionTask *task =
-		new (nothrow)FaceRecognitionAdapter<mv_face_recognition_input_s, mv_face_recognition_result_s>();
+	FaceRecognitionTask *task = new (nothrow)
+			FaceRecognitionAdapter<mv_face_recognition_input_s, mv_face_recognition_result_s>();
 	if (!task) {
 		delete context;
 		LOGE("Fail to allocate a task.");
@@ -104,7 +104,7 @@ int mv_face_recognition_prepare_open(mv_face_recognition_h handle)
 
 		task->configure();
 		task->prepare();
-	} catch (const BaseException& e) {
+	} catch (const BaseException &e) {
 		LOGE("%s", e.what());
 		return e.getError();
 	}
@@ -133,7 +133,7 @@ int mv_face_recognition_register_open(mv_face_recognition_h handle, mv_source_h
 		input.register_src.insert(make_pair(source, string(label)));
 		task->setInput(input);
 		task->perform();
-	} catch (const BaseException& e) {
+	} catch (const BaseException &e) {
 		LOGE("%s", e.what());
 		return e.getError();
 	}
@@ -162,7 +162,7 @@ int mv_face_recognition_unregister_open(mv_face_recognition_h handle, const char
 		input.labels.push_back(string(label));
 		task->setInput(input);
 		task->perform();
-	} catch (const BaseException& e) {
+	} catch (const BaseException &e) {
 		LOGE("%s", e.what());
 		return e.getError();
 	}
@@ -190,7 +190,7 @@ int mv_face_recognition_inference_open(mv_face_recognition_h handle, mv_source_h
 		input.inference_src = source;
 		task->setInput(input);
 		task->perform();
-	} catch (const BaseException& e) {
+	} catch (const BaseException &e) {
 		LOGE("%s", e.what());
 		return e.getError();
 	}
@@ -214,7 +214,7 @@ int mv_face_recognition_get_label_open(mv_face_recognition_h handle, const char
 		auto task = static_cast<FaceRecognitionTask *>(context->__tasks["face_recognition"]);
 
 		*out_label = task->getOutput().label.c_str();
-	} catch (const BaseException& e) {
+	} catch (const BaseException &e) {
 		LOGE("%s", e.what());
 		return e.getError();
 	}
diff --git a/mv_machine_learning/face_recognition/src/nntrainer_dsm.cpp b/mv_machine_learning/face_recognition/src/nntrainer_dsm.cpp
index 2eedaa4..b732f68 100644
--- a/mv_machine_learning/face_recognition/src/nntrainer_dsm.cpp
+++ b/mv_machine_learning/face_recognition/src/nntrainer_dsm.cpp
@@ -24,7 +24,7 @@
 using namespace std;
 using namespace mediavision::machine_learning::exception;
 
-void NNTrainerDSM::PrintHeader(FeaVecHeader& fvh)
+void NNTrainerDSM::PrintHeader(FeaVecHeader &fvh)
 {
 	LOGD("signature = %u", fvh.signature);
 	LOGD("feature vector size = %zu", fvh.feature_size);
@@ -32,11 +32,8 @@ void NNTrainerDSM::PrintHeader(FeaVecHeader& fvh)
 	LOGD("data set count = %u", fvh.data_set_cnt);
 }
 
-NNTrainerDSM::NNTrainerDSM()
-	: DataSetManager()
-{
-
-}
+NNTrainerDSM::NNTrainerDSM() : DataSetManager()
+{}
 
 void NNTrainerDSM::LoadDataSet(const string file_name)
 {
@@ -51,7 +48,7 @@ void NNTrainerDSM::LoadDataSet(const string file_name)
 
 	FeaVecHeader fvh;
 
-	inFile.read((char *)&fvh, sizeof(FeaVecHeader));
+	inFile.read((char *) &fvh, sizeof(FeaVecHeader));
 	if (inFile.gcount() != sizeof(FeaVecHeader))
 		throw InvalidOperation("Invalid feature vector file.");
 
@@ -62,8 +59,7 @@ void NNTrainerDSM::LoadDataSet(const string file_name)
 	if (FeatureVectorManager::feature_vector_signature != fvh.signature)
 		throw InvalidOperation("Wrong feature vector header.");
 
-	size_t line_size_in_bytes = fvh.feature_size * sizeof(float) +
-								fvh.one_hot_table_size * sizeof(float);
+	size_t line_size_in_bytes = fvh.feature_size * sizeof(float) + fvh.one_hot_table_size * sizeof(float);
 
 	_feature_vector_size = fvh.feature_size;
 	_label_size = fvh.one_hot_table_size;
@@ -72,7 +68,7 @@ void NNTrainerDSM::LoadDataSet(const string file_name)
 	vector<float> line_data(fvh.feature_size + fvh.one_hot_table_size);
 
 	for (size_t idx = 0; idx < fvh.data_set_cnt; ++idx) {
-		inFile.read((char *)line_data.data(), line_size_in_bytes);
+		inFile.read((char *) line_data.data(), line_size_in_bytes);
 
 		vector<float> data;
 		copy_n(line_data.begin(), _feature_vector_size, back_inserter(data));
@@ -85,7 +81,7 @@ void NNTrainerDSM::LoadDataSet(const string file_name)
 			if (line_data[fvh.feature_size + num] == 1.0f)
 				label_idx = num;
 
-			label.push_back((float)line_data[fvh.feature_size + num]);
+			label.push_back((float) line_data[fvh.feature_size + num]);
 		}
 
 		_labels.push_back(label);
diff --git a/mv_machine_learning/face_recognition/src/nntrainer_fvm.cpp b/mv_machine_learning/face_recognition/src/nntrainer_fvm.cpp
index b999e84..24f4ad2 100644
--- a/mv_machine_learning/face_recognition/src/nntrainer_fvm.cpp
+++ b/mv_machine_learning/face_recognition/src/nntrainer_fvm.cpp
@@ -22,45 +22,32 @@
 using namespace std;
 using namespace mediavision::machine_learning::exception;
 
-NNTrainerFVM::NNTrainerFVM(const string feature_vector_file)
-	: FeatureVectorManager(feature_vector_file)
-{
-
-}
+NNTrainerFVM::NNTrainerFVM(const string feature_vector_file) : FeatureVectorManager(feature_vector_file)
+{}
 
-void NNTrainerFVM::WriteHeader(size_t feature_size, size_t one_hot_table_size, unsigned int  data_set_cnt)
+void NNTrainerFVM::WriteHeader(size_t feature_size, size_t one_hot_table_size, unsigned int data_set_cnt)
 {
-	ofstream outFile {
-		_feature_vector_file,
-		ios::out | ios::binary | ios::app
-	};
+	ofstream outFile { _feature_vector_file, ios::out | ios::binary | ios::app };
 
 	if (!outFile.is_open())
 		throw InvalidOperation("fail to open a file");
 
-	FeaVecHeader fvHeader {
-		FeatureVectorManager::feature_vector_signature,
-		feature_size,
-		one_hot_table_size,
-		data_set_cnt
-	};
+	FeaVecHeader fvHeader { FeatureVectorManager::feature_vector_signature, feature_size, one_hot_table_size,
+							data_set_cnt };
 
-	outFile.write((char *)&fvHeader, sizeof(FeaVecHeader));
+	outFile.write((char *) &fvHeader, sizeof(FeaVecHeader));
 }
 
-void NNTrainerFVM::ReadHeader(FeaVecHeader& header)
+void NNTrainerFVM::ReadHeader(FeaVecHeader &header)
 {
-	ifstream inFile {
-		_feature_vector_file,
-		ios::in | ios::binary
-	};
+	ifstream inFile { _feature_vector_file, ios::in | ios::binary };
 
 	if (!inFile.is_open())
 		throw InvalidOperation("fail to open a file.");
 
 	inFile.seekg(static_cast<int>(sizeof(FeaVecHeader) * -1), ios::end);
 
-	inFile.read((char *)&header, sizeof(FeaVecHeader));
+	inFile.read((char *) &header, sizeof(FeaVecHeader));
 	if (inFile.gcount() != sizeof(FeaVecHeader))
 		throw InvalidOperation("Invalid feature vector file.");
 
@@ -68,12 +55,9 @@ void NNTrainerFVM::ReadHeader(FeaVecHeader& header)
 		throw InvalidParameter("wrong feature vector file header.");
 }
 
-void NNTrainerFVM::WriteFeatureVec(vector<float>& feature_vec, const int max_label, const int label_index)
+void NNTrainerFVM::WriteFeatureVec(vector<float> &feature_vec, const int max_label, const int label_index)
 {
-	ofstream outFile {
-		_feature_vector_file,
-		ios::out | ios::binary | ios::app
-	};
+	ofstream outFile { _feature_vector_file, ios::out | ios::binary | ios::app };
 
 	if (!outFile.is_open())
 		throw InvalidOperation("fail to open a file.");
@@ -82,7 +66,7 @@ void NNTrainerFVM::WriteFeatureVec(vector<float>& feature_vec, const int max_lab
 
 	for (int idx = 0; idx < max_label; ++idx) {
 		float oneHotTable = (label_index == idx) ? 1.0f : 0.0f;
-		outFile.write((char *)&oneHotTable, sizeof(float));
+		outFile.write((char *) &oneHotTable, sizeof(float));
 	}
 }
 
diff --git a/mv_machine_learning/face_recognition/src/simple_shot.cpp b/mv_machine_learning/face_recognition/src/simple_shot.cpp
index d460364..233bdbe 100644
--- a/mv_machine_learning/face_recognition/src/simple_shot.cpp
+++ b/mv_machine_learning/face_recognition/src/simple_shot.cpp
@@ -33,10 +33,9 @@ using namespace std;
 using namespace TrainingEngineInterface::Common;
 using namespace mediavision::machine_learning::exception;
 
-SimpleShot::SimpleShot(const mv_inference_backend_type_e backend_type,
-					   const mv_inference_target_device_e target_type,
-					   const string internal_model_file) :
-						TrainingModel(backend_type, target_type, internal_model_file)
+SimpleShot::SimpleShot(const mv_inference_backend_type_e backend_type, const mv_inference_target_device_e target_type,
+					   const string internal_model_file)
+		: TrainingModel(backend_type, target_type, internal_model_file)
 {
 	_engine_info.backend_type = backend_type;
 	// TODO. training engine interface has no target type attribute yet.
@@ -45,10 +44,7 @@ SimpleShot::SimpleShot(const mv_inference_backend_type_e backend_type,
 	_engine_info.target_device = target_type;
 
 	const inference_engine_tensor_info nntrainer_input_tensor_info = {
-		{ 512, 1, 1, 1 },
-		INFERENCE_TENSOR_SHAPE_NCHW,
-		INFERENCE_TENSOR_DATA_TYPE_FLOAT32,
-		(size_t)(512 * 1 * 1 * 1)
+		{ 512, 1, 1, 1 }, INFERENCE_TENSOR_SHAPE_NCHW, INFERENCE_TENSOR_DATA_TYPE_FLOAT32, (size_t)(512 * 1 * 1 * 1)
 	};
 
 	_engine_info.input_layer_names.push_back("preprocess_l2norm0");
@@ -57,12 +53,9 @@ SimpleShot::SimpleShot(const mv_inference_backend_type_e backend_type,
 	// size of output tensor will be updated by RecognizeFace function
 	// because the size should be changed according to maximum label count
 	// so it has 1 in default.
-	inference_engine_tensor_info nntrainer_output_tensor_info = {
-		vector<size_t>{ 1, 1, 1, 1 },
-		INFERENCE_TENSOR_SHAPE_NCHW,
-		INFERENCE_TENSOR_DATA_TYPE_FLOAT32,
-		1
-	};
+	inference_engine_tensor_info nntrainer_output_tensor_info = { vector<size_t> { 1, 1, 1, 1 },
+																  INFERENCE_TENSOR_SHAPE_NCHW,
+																  INFERENCE_TENSOR_DATA_TYPE_FLOAT32, 1 };
 
 	_engine_info.output_layer_names.push_back("centroid_knn1");
 	_engine_info.output_tensor_info.push_back(nntrainer_output_tensor_info);
@@ -118,7 +111,7 @@ void SimpleShot::ConfigureModel(int num_of_class)
 		throw InvalidOperation("Fail to add knn layer.");
 }
 
-TrainingEngineBackendInfo& SimpleShot::GetTrainingEngineInfo()
+TrainingEngineBackendInfo &SimpleShot::GetTrainingEngineInfo()
 {
 	return _engine_info;
 }
diff --git a/mv_machine_learning/inference/include/BoxInfo.h b/mv_machine_learning/inference/include/BoxInfo.h
index d4d6c6a..b3eb829 100644
--- a/mv_machine_learning/inference/include/BoxInfo.h
+++ b/mv_machine_learning/inference/include/BoxInfo.h
@@ -62,10 +62,8 @@ private:
 	Number number;
 
 	std::map<std::string, inference_box_type_e> supportedBoxTypes;
-	std::map<std::string, inference_box_coordinate_type_e>
-			supportedBoxCoordinateTypes;
-	std::map<std::string, inference_box_decoding_type_e>
-			supportedBoxDecodingTypes;
+	std::map<std::string, inference_box_coordinate_type_e> supportedBoxCoordinateTypes;
+	std::map<std::string, inference_box_decoding_type_e> supportedBoxDecodingTypes;
 
 public:
 	BoxInfo()
@@ -78,22 +76,15 @@ public:
 			, decodingInfo()
 
 	{
-		supportedBoxTypes.insert(
-				{ "ORIGIN_LEFTTOP", INFERENCE_BOX_TYPE_ORIGIN_LEFTTOP });
-		supportedBoxTypes.insert(
-				{ "ORIGIN_CENTER", INFERENCE_BOX_TYPE_ORIGIN_CENTER });
-
-		supportedBoxCoordinateTypes.insert(
-				{ "RATIO", INFERENCE_BOX_COORDINATE_TYPE_RATIO });
-		supportedBoxCoordinateTypes.insert(
-				{ "PIXEL", INFERENCE_BOX_COORDINATE_TYPE_PIXEL });
-
-		supportedBoxDecodingTypes.insert(
-				{ "BYPASS", INFERENCE_BOX_DECODING_TYPE_BYPASS });
-		supportedBoxDecodingTypes.insert(
-				{ "SSD_ANCHOR", INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR });
-		supportedBoxDecodingTypes.insert(
-				{ "YOLO_ANCHOR", INFERENCE_BOX_DECODING_TYPE_YOLO_ANCHOR });
+		supportedBoxTypes.insert({ "ORIGIN_LEFTTOP", INFERENCE_BOX_TYPE_ORIGIN_LEFTTOP });
+		supportedBoxTypes.insert({ "ORIGIN_CENTER", INFERENCE_BOX_TYPE_ORIGIN_CENTER });
+
+		supportedBoxCoordinateTypes.insert({ "RATIO", INFERENCE_BOX_COORDINATE_TYPE_RATIO });
+		supportedBoxCoordinateTypes.insert({ "PIXEL", INFERENCE_BOX_COORDINATE_TYPE_PIXEL });
+
+		supportedBoxDecodingTypes.insert({ "BYPASS", INFERENCE_BOX_DECODING_TYPE_BYPASS });
+		supportedBoxDecodingTypes.insert({ "SSD_ANCHOR", INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR });
+		supportedBoxDecodingTypes.insert({ "YOLO_ANCHOR", INFERENCE_BOX_DECODING_TYPE_YOLO_ANCHOR });
 	}
 
 	~BoxInfo() = default;
diff --git a/mv_machine_learning/inference/include/Bvh.h b/mv_machine_learning/inference/include/Bvh.h
index 6b9b853..150671e 100644
--- a/mv_machine_learning/inference/include/Bvh.h
+++ b/mv_machine_learning/inference/include/Bvh.h
@@ -11,16 +11,17 @@ namespace mediavision
 {
 namespace inference
 {
-
-  /** Class created for storing motion data from bvh file */
-  class Bvh {
-  public:
-    /** Constructor of Bvh object
+/** Class created for storing motion data from bvh file */
+class Bvh
+{
+public:
+	/** Constructor of Bvh object
      *  @details  Initializes local variables
      */
-    Bvh() : num_frames_(0), frame_time_(0), num_channels_(0) {}
+	Bvh() : num_frames_(0), frame_time_(0), num_channels_(0)
+	{}
 
-    /**
+	/**
      * Recalculation of local transformation matrix for each frame in each joint
      *
      * Should be called to set local_transformation_matrix vectors in joints
@@ -30,79 +31,103 @@ namespace inference
      * matrix will be recalculated, as default it is NULL which will be resolved
      * to root_joint in method body
      */
-    void recalculate_joints_ltm(std::shared_ptr<Joint> start_joint = NULL);
+	void recalculate_joints_ltm(std::shared_ptr<Joint> start_joint = NULL);
 
-    /** Adds joint to Bvh object
+	/** Adds joint to Bvh object
      *  @details  Adds joint and increases number of data channels
      *  @param  joint  The joint that will be added
      */
-    void add_joint(const std::shared_ptr<Joint> joint) {
-      joints_.push_back(joint);
-      num_channels_ += joint->num_channels();
-    }
+	void add_joint(const std::shared_ptr<Joint> joint)
+	{
+		joints_.push_back(joint);
+		num_channels_ += joint->num_channels();
+	}
 
-    /** Gets the root joint
+	/** Gets the root joint
      *  @return  The root joint
      */
-    const std::shared_ptr<Joint> root_joint() const { return root_joint_; }
+	const std::shared_ptr<Joint> root_joint() const
+	{
+		return root_joint_;
+	}
 
-    /** Gets all joints
+	/** Gets all joints
      *  @return  The all joints
      */
-    const std::vector <std::shared_ptr <Joint>> joints() const {
-      return joints_;
-    }
+	const std::vector<std::shared_ptr<Joint> > joints() const
+	{
+		return joints_;
+	}
 
-    /** Gets the number of data frames
+	/** Gets the number of data frames
      *  @return  The number of frames
      */
-    unsigned num_frames() const { return num_frames_; }
+	unsigned num_frames() const
+	{
+		return num_frames_;
+	}
 
-    /** Gets the frame time
+	/** Gets the frame time
      *  @return  The single frame time (in second)
      */
-    double frame_time() const { return frame_time_; }
+	double frame_time() const
+	{
+		return frame_time_;
+	}
 
-    /** Gets the total number of channels
+	/** Gets the total number of channels
      *  @return  The number of data channels
      */
-    unsigned num_channels() const { return num_channels_; }
+	unsigned num_channels() const
+	{
+		return num_channels_;
+	}
 
-    /** Sets the root joint
+	/** Sets the root joint
      *  @param  arg  The root joint to be set
      */
-    void set_root_joint(const std::shared_ptr<Joint> arg) { root_joint_ = arg; }
+	void set_root_joint(const std::shared_ptr<Joint> arg)
+	{
+		root_joint_ = arg;
+	}
 
-    /** Sets the all joint at once
+	/** Sets the all joint at once
      *  @param  arg  The all joints to be set
      */
-    void set_joints(const std::vector <std::shared_ptr <Joint>> arg) {
-      joints_ = arg;
-    }
+	void set_joints(const std::vector<std::shared_ptr<Joint> > arg)
+	{
+		joints_ = arg;
+	}
 
-    /** Sets the number of data frames
+	/** Sets the number of data frames
      *  @param  arg  The number of frames to be set
      */
-    void set_num_frames(const unsigned arg) { num_frames_ = arg; }
+	void set_num_frames(const unsigned arg)
+	{
+		num_frames_ = arg;
+	}
 
-    /** Sets the single data frame time
+	/** Sets the single data frame time
      *  @param  arg  The time of frame to be set
      */
-    void set_frame_time(const double arg) { frame_time_ = arg; }
-
-  private:
-    /** A root joint in this bvh file */
-    std::shared_ptr<Joint> root_joint_;
-    /** All joints in file in order of parse */
-    std::vector <std::shared_ptr <Joint>> joints_;
-    /** A number of motion frames in this bvh file */
-    unsigned num_frames_;
-    /** A time of single frame */
-    double frame_time_;
-    /** Number of channels of all joints */
-    unsigned num_channels_;
-  };
+	void set_frame_time(const double arg)
+	{
+		frame_time_ = arg;
+	}
+
+private:
+	/** A root joint in this bvh file */
+	std::shared_ptr<Joint> root_joint_;
+	/** All joints in file in order of parse */
+	std::vector<std::shared_ptr<Joint> > joints_;
+	/** A number of motion frames in this bvh file */
+	unsigned num_frames_;
+	/** A time of single frame */
+	double frame_time_;
+	/** Number of channels of all joints */
+	unsigned num_channels_;
+};
 
 } // namespace
 }
-#endif  // __MEDIA_VISION_BVH_H__
+#endif // __MEDIA_VISION_BVH_H__
diff --git a/mv_machine_learning/inference/include/BvhParser.h b/mv_machine_learning/inference/include/BvhParser.h
index c96bedb..5a89fec 100644
--- a/mv_machine_learning/inference/include/BvhParser.h
+++ b/mv_machine_learning/inference/include/BvhParser.h
@@ -13,66 +13,65 @@ namespace mediavision
 {
 namespace inference
 {
+/** Bvh Parser class that is responsible for parsing .bvh file */
+class BvhParser
+{
+public:
+	BvhParser() : bvh_(NULL) {};
+	~BvhParser() = default;
 
-    /** Bvh Parser class that is responsible for parsing .bvh file */
-    class BvhParser {
-    public:
-    BvhParser() : bvh_(NULL) {};
-    ~BvhParser() = default;
-
-    /** Parses single bvh file and stored data into bvh structure
+	/** Parses single bvh file and stored data into bvh structure
      *  @param  path  The path to file to be parsed
      *  @param  bvh   The pointer to bvh object where parsed data will be stored
      *  @return  0 if success, -1 otherwise
      */
-    int parse(const std::string& path, Bvh* bvh);
+	int parse(const std::string &path, Bvh *bvh);
 
-    private:
-    /** Parses single hierarchy in bvh file
+private:
+	/** Parses single hierarchy in bvh file
      *  @param  file  The input stream that is needed for reading file content
      *  @return  0 if success, -1 otherwise
      */
-    int parse_hierarchy(std::ifstream& file);
+	int parse_hierarchy(std::ifstream &file);
 
-    /** Parses joint and its children in bvh file
+	/** Parses joint and its children in bvh file
      *  @param  file    The input stream that is needed for reading file content
      *  @param  parent  The pointer to parent joint
      *  @param  parsed  The output parameter, here will be stored parsed joint
      *  @return  0 if success, -1 otherwise
      */
-    int parse_joint(std::ifstream& file, std::shared_ptr <Joint> parent,
-        std::shared_ptr <Joint>& parsed);
+	int parse_joint(std::ifstream &file, std::shared_ptr<Joint> parent, std::shared_ptr<Joint> &parsed);
 
-    /** Parses order of channel for single joint
+	/** Parses order of channel for single joint
      *  @param  file    The input stream that is needed for reading file content
      *  @param  joint   The pointer to joint that channels order will be parsed
      *  @return  0 if success, -1 otherwise
      */
-    int parse_channel_order(std::ifstream& file, std::shared_ptr <Joint> joint);
+	int parse_channel_order(std::ifstream &file, std::shared_ptr<Joint> joint);
 
-    /** Parses motion part data
+	/** Parses motion part data
      *  @param  file    The input stream that is needed for reading file content
      *  @return  0 if success, -1 otherwise
      */
-    int parse_motion(std::ifstream& file);
+	int parse_motion(std::ifstream &file);
 
-    /** Trims the string, removes leading and trailing whitespace from it
+	/** Trims the string, removes leading and trailing whitespace from it
      *  @param  s   The string, which leading and trailing whitespace will be
      *              trimmed
      */
-    inline void trim(std::string &s) {
-        s.erase( std::remove_if( s.begin(), s.end(),
-            std::bind( std::isspace<char>, std::placeholders::_1,
-            std::locale::classic() ) ), s.end() );
-    }
-
+	inline void trim(std::string &s)
+	{
+		s.erase(std::remove_if(s.begin(), s.end(),
+							   std::bind(std::isspace<char>, std::placeholders::_1, std::locale::classic())),
+				s.end());
+	}
 
-    /** The path to file that was parsed previously */
-    std::string path_;
+	/** The path to file that was parsed previously */
+	std::string path_;
 
-    /** The bvh object to store parsed data */
-    Bvh* bvh_;
-    };
+	/** The bvh object to store parsed data */
+	Bvh *bvh_;
+};
 }
 } // namespace
-#endif  // __MEDIA_VISION_BVH_PARSER_H__
+#endif // __MEDIA_VISION_BVH_PARSER_H__
diff --git a/mv_machine_learning/inference/include/BvhUtils.h b/mv_machine_learning/inference/include/BvhUtils.h
index 9d1a131..ce07273 100644
--- a/mv_machine_learning/inference/include/BvhUtils.h
+++ b/mv_machine_learning/inference/include/BvhUtils.h
@@ -12,12 +12,12 @@ namespace mediavision
 {
 namespace inference
 {
-
 /** Enumeration class for axis */
-enum class Axis {
-  X,
-  Y,
-  Z
+enum class Axis
+{
+	X,
+	Y,
+	Z
 };
 
 /** Creates rotation matrix
diff --git a/mv_machine_learning/inference/include/DecodeInfo.h b/mv_machine_learning/inference/include/DecodeInfo.h
index dba3647..83c53db 100644
--- a/mv_machine_learning/inference/include/DecodeInfo.h
+++ b/mv_machine_learning/inference/include/DecodeInfo.h
@@ -33,144 +33,151 @@ namespace inference
 {
 namespace box
 {
-	struct AnchorParam {
-		int mode; /**< 0: generate anchor, 1:load pre-anchor*/
-		int numLayers;
-		float minScale;
-		float maxScale;
-		int inputSizeHeight;
-		int inputSizeWidth;
-		float anchorOffsetX;
-		float anchorOffsetY;
-		std::vector<int> strides;
-		std::vector<float> aspectRatios;
-		bool isReduceBoxedInLowestLayer;
-		float interpolatedScaleAspectRatio;
-		bool isFixedAnchorSize;
-		bool isExponentialBoxScale;
-		float xScale;
-		float yScale;
-		float wScale;
-		float hScale;
-	};
-
-	struct CellParam {
-		int numScales;
-		std::vector<int> scales;
-		int offsetScales;
-		inference_score_type_e type;
-		std::map<std::string, inference_score_type_e> supportedCellType;
-	};
-
-	struct NMSParam {
-		inference_box_nms_type_e mode; /**< 0: standard */
-		float iouThreshold;
-		std::map<std::string, inference_box_nms_type_e> supportedBoxNmsTypes;
-	};
-
-	struct RotateParam {
-		int startPointIndex;
-		int endPointIndex;
-		cv::Point2f startPoint;
-		cv::Point2f endPoint;
-		float baseAngle;
-	};
-
-	struct RoiOptionParam {
-		int startPointIndex;
-		int endPointIndex;
-		int centerPointIndex;
-		cv::Point2f centerPoint;
-		float shiftX;
-		float shiftY;
-		float scaleX;
-		float scaleY;
-		int mode;
-	};
-
-	class DecodeInfo {
-	private:
-		AnchorParam anchorParam;
-		std::vector<cv::Rect2f> anchorBoxes;
-		CellParam cellParam;
-		NMSParam nmsParam;
-		RotateParam rotParam;
-		RoiOptionParam roiOptParam;
-
-	public:
-		DecodeInfo() {
-			cellParam.type = INFERENCE_SCORE_TYPE_NORMAL;
-			cellParam.supportedCellType.insert({"NORMAL", INFERENCE_SCORE_TYPE_NORMAL});
-			cellParam.supportedCellType.insert({"SIGMOID", INFERENCE_SCORE_TYPE_SIGMOID});
-
-			nmsParam.mode = INFERENCE_BOX_NMS_TYPE_NONE;
-			nmsParam.iouThreshold = 0.2f;
-			nmsParam.supportedBoxNmsTypes.insert({"STANDARD", INFERENCE_BOX_NMS_TYPE_STANDARD});
-
-			rotParam.startPointIndex = -1;
-			rotParam.endPointIndex = -1;
-			rotParam.startPoint = cv::Point2f(0.f,0.f);
-			rotParam.endPoint = cv::Point2f(0.f,0.f);
-			rotParam.baseAngle = 0.f;
-
-			roiOptParam.startPointIndex = -1;
-			roiOptParam.endPointIndex = -1;
-			roiOptParam.centerPointIndex = -1;
-			roiOptParam.centerPoint = cv::Point2f(0.f, 0.f);
-			roiOptParam.shiftX = 0.f;
-			roiOptParam.shiftY = 0.f;
-			roiOptParam.scaleX = 1.f;
-			roiOptParam.scaleY = 1.f;
-			roiOptParam.mode = -1;
-		}
-
-		~DecodeInfo() = default;
-
-		std::vector<cv::Rect2f>& GetAnchorBoxAll();
-		bool IsAnchorBoxEmpty();
-		void AddAnchorBox(cv::Rect2f& ahcnor);
-		void ClearAnchorBox();
-
-		// Anchor param
-		int ParseAnchorParam(JsonObject *root);
-		int GenerateAnchor();
-		bool IsFixedAnchorSize();
-		bool IsExponentialBoxScale();
-		float GetAnchorXscale();
-		float GetAnchorYscale();
-		float GetAnchorWscale();
-		float GetAnchorHscale();
-		float CalculateScale(float min, float max, int index, int maxStride);
-
-		// Cell param
-		int ParseCellParam(JsonObject *root);
-		std::vector<int>& GetCellScalesAll();
-		int GetCellNumScales();
-		int GetCellOffsetScales();
-		inference_score_type_e GetCellType();
-
-		// Nms param
-		int ParseNms(JsonObject *root);
-		int GetNmsMode();
-		float GetNmsIouThreshold();
-
-		// Rotate param
-		int ParseRotate(JsonObject *root);
-		int GetRotStartPointIndex();
-		int GetRotEndPointIndex();
-		float GetBaseAngle();
-
-		// Roi option param
-		int ParseRoiOption(JsonObject *root);
-		int GetRoiMode();
-		int GetRoiCenterPointIndex();
-		int GetRoiStartPointIndex();
-		int GetRoiEndPointIndex();
-		float GetShiftX();
-		float GetShiftY();
-		float GetScaleX();
-		float GetScaleY();
-	};
+struct AnchorParam
+{
+	int mode; /**< 0: generate anchor, 1:load pre-anchor*/
+	int numLayers;
+	float minScale;
+	float maxScale;
+	int inputSizeHeight;
+	int inputSizeWidth;
+	float anchorOffsetX;
+	float anchorOffsetY;
+	std::vector<int> strides;
+	std::vector<float> aspectRatios;
+	bool isReduceBoxedInLowestLayer;
+	float interpolatedScaleAspectRatio;
+	bool isFixedAnchorSize;
+	bool isExponentialBoxScale;
+	float xScale;
+	float yScale;
+	float wScale;
+	float hScale;
+};
+
+struct CellParam
+{
+	int numScales;
+	std::vector<int> scales;
+	int offsetScales;
+	inference_score_type_e type;
+	std::map<std::string, inference_score_type_e> supportedCellType;
+};
+
+struct NMSParam
+{
+	inference_box_nms_type_e mode; /**< 0: standard */
+	float iouThreshold;
+	std::map<std::string, inference_box_nms_type_e> supportedBoxNmsTypes;
+};
+
+struct RotateParam
+{
+	int startPointIndex;
+	int endPointIndex;
+	cv::Point2f startPoint;
+	cv::Point2f endPoint;
+	float baseAngle;
+};
+
+struct RoiOptionParam
+{
+	int startPointIndex;
+	int endPointIndex;
+	int centerPointIndex;
+	cv::Point2f centerPoint;
+	float shiftX;
+	float shiftY;
+	float scaleX;
+	float scaleY;
+	int mode;
+};
+
+class DecodeInfo
+{
+private:
+	AnchorParam anchorParam;
+	std::vector<cv::Rect2f> anchorBoxes;
+	CellParam cellParam;
+	NMSParam nmsParam;
+	RotateParam rotParam;
+	RoiOptionParam roiOptParam;
+
+public:
+	DecodeInfo()
+	{
+		cellParam.type = INFERENCE_SCORE_TYPE_NORMAL;
+		cellParam.supportedCellType.insert({ "NORMAL", INFERENCE_SCORE_TYPE_NORMAL });
+		cellParam.supportedCellType.insert({ "SIGMOID", INFERENCE_SCORE_TYPE_SIGMOID });
+
+		nmsParam.mode = INFERENCE_BOX_NMS_TYPE_NONE;
+		nmsParam.iouThreshold = 0.2f;
+		nmsParam.supportedBoxNmsTypes.insert({ "STANDARD", INFERENCE_BOX_NMS_TYPE_STANDARD });
+
+		rotParam.startPointIndex = -1;
+		rotParam.endPointIndex = -1;
+		rotParam.startPoint = cv::Point2f(0.f, 0.f);
+		rotParam.endPoint = cv::Point2f(0.f, 0.f);
+		rotParam.baseAngle = 0.f;
+
+		roiOptParam.startPointIndex = -1;
+		roiOptParam.endPointIndex = -1;
+		roiOptParam.centerPointIndex = -1;
+		roiOptParam.centerPoint = cv::Point2f(0.f, 0.f);
+		roiOptParam.shiftX = 0.f;
+		roiOptParam.shiftY = 0.f;
+		roiOptParam.scaleX = 1.f;
+		roiOptParam.scaleY = 1.f;
+		roiOptParam.mode = -1;
+	}
+
+	~DecodeInfo() = default;
+
+	std::vector<cv::Rect2f> &GetAnchorBoxAll();
+	bool IsAnchorBoxEmpty();
+	void AddAnchorBox(cv::Rect2f &ahcnor);
+	void ClearAnchorBox();
+
+	// Anchor param
+	int ParseAnchorParam(JsonObject *root);
+	int GenerateAnchor();
+	bool IsFixedAnchorSize();
+	bool IsExponentialBoxScale();
+	float GetAnchorXscale();
+	float GetAnchorYscale();
+	float GetAnchorWscale();
+	float GetAnchorHscale();
+	float CalculateScale(float min, float max, int index, int maxStride);
+
+	// Cell param
+	int ParseCellParam(JsonObject *root);
+	std::vector<int> &GetCellScalesAll();
+	int GetCellNumScales();
+	int GetCellOffsetScales();
+	inference_score_type_e GetCellType();
+
+	// Nms param
+	int ParseNms(JsonObject *root);
+	int GetNmsMode();
+	float GetNmsIouThreshold();
+
+	// Rotate param
+	int ParseRotate(JsonObject *root);
+	int GetRotStartPointIndex();
+	int GetRotEndPointIndex();
+	float GetBaseAngle();
+
+	// Roi option param
+	int ParseRoiOption(JsonObject *root);
+	int GetRoiMode();
+	int GetRoiCenterPointIndex();
+	int GetRoiStartPointIndex();
+	int GetRoiEndPointIndex();
+	float GetShiftX();
+	float GetShiftY();
+	float GetScaleX();
+	float GetScaleY();
+};
 } /* box */
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/include/DimInfo.h b/mv_machine_learning/inference/include/DimInfo.h
index 64e0f05..3c0782a 100644
--- a/mv_machine_learning/inference/include/DimInfo.h
+++ b/mv_machine_learning/inference/include/DimInfo.h
@@ -24,29 +24,29 @@ namespace mediavision
 {
 namespace inference
 {
-	class DimInfo
-	{
-	private:
-		std::vector<int> dims;
+class DimInfo
+{
+private:
+	std::vector<int> dims;
 
-	public:
-		std::vector<int> GetValidIndexAll() const
-		{
-			LOGI("ENTER");
+public:
+	std::vector<int> GetValidIndexAll() const
+	{
+		LOGI("ENTER");
 
-			LOGI("LEAVE");
-			return dims;
-		}
+		LOGI("LEAVE");
+		return dims;
+	}
 
-		void SetValidIndex(int index)
-		{
-			LOGI("ENTER");
+	void SetValidIndex(int index)
+	{
+		LOGI("ENTER");
 
-			dims.push_back(index);
+		dims.push_back(index);
 
-			LOGI("LEAVE");
-		}
-	};
+		LOGI("LEAVE");
+	}
+};
 } /* Inference */
 } /* MediaVision */
 
diff --git a/mv_machine_learning/inference/include/DispVec.h b/mv_machine_learning/inference/include/DispVec.h
index f43dcf5..b9685bd 100644
--- a/mv_machine_learning/inference/include/DispVec.h
+++ b/mv_machine_learning/inference/include/DispVec.h
@@ -30,63 +30,71 @@ namespace mediavision
 {
 namespace inference
 {
-	class DispVec
+class DispVec
+{
+private:
+	std::string name;
+	DimInfo dimInfo;
+	inference_displacement_type_e type;
+	int shapeType;
+	std::map<std::string, inference_displacement_type_e> supportedDispTypes;
+
+public:
+	DispVec() : name(), dimInfo(), type(INFERENCE_DISPLACEMENT_TYPE_FORWARD), shapeType(INFERENCE_TENSOR_SHAPE_NCHW)
 	{
-	private:
-		std::string name;
-		DimInfo dimInfo;
-		inference_displacement_type_e type;
-		int shapeType;
-		std::map<std::string, inference_displacement_type_e> supportedDispTypes;
-
-	public:
-		DispVec() :
-			name(),
-			dimInfo(),
-			type(INFERENCE_DISPLACEMENT_TYPE_FORWARD),
-			shapeType(INFERENCE_TENSOR_SHAPE_NCHW)
-		{
-			supportedDispTypes.insert({"FORWARD", INFERENCE_DISPLACEMENT_TYPE_FORWARD});
-			supportedDispTypes.insert({"BACKWARD", INFERENCE_DISPLACEMENT_TYPE_BACKWARD});
-		}
+		supportedDispTypes.insert({ "FORWARD", INFERENCE_DISPLACEMENT_TYPE_FORWARD });
+		supportedDispTypes.insert({ "BACKWARD", INFERENCE_DISPLACEMENT_TYPE_BACKWARD });
+	}
 
-		~DispVec() = default;
+	~DispVec() = default;
 
-		std::string GetName() { return name; }
-		DimInfo GetDimInfo() { return dimInfo; }
-		inference_displacement_type_e GetType() { return type; }
-		int GetShapeType() { return shapeType; }
-
-		int ParseDisplacement(JsonObject *root, const std::map<std::string, inference_tensor_shape_type_e>& supportedShapeType)
-		{
-			LOGI("ENTER");
+	std::string GetName()
+	{
+		return name;
+	}
+	DimInfo GetDimInfo()
+	{
+		return dimInfo;
+	}
+	inference_displacement_type_e GetType()
+	{
+		return type;
+	}
+	int GetShapeType()
+	{
+		return shapeType;
+	}
 
-			name = static_cast<const char*>(json_object_get_string_member(root,"name"));
-			LOGI("layer: %s", name.c_str());
+	int ParseDisplacement(JsonObject *root,
+						  const std::map<std::string, inference_tensor_shape_type_e> &supportedShapeType)
+	{
+		LOGI("ENTER");
 
-			JsonArray * array = json_object_get_array_member(root, "index");
-			unsigned int elements2 = json_array_get_length(array);
+		name = static_cast<const char *>(json_object_get_string_member(root, "name"));
+		LOGI("layer: %s", name.c_str());
 
-			LOGI("range dim: size[%u]", elements2);
+		JsonArray *array = json_object_get_array_member(root, "index");
+		unsigned int elements2 = json_array_get_length(array);
 
-			for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
-				if(static_cast<int>(json_array_get_int_element(array, elem2)) == 1)
-					dimInfo.SetValidIndex(elem2);
-			}
+		LOGI("range dim: size[%u]", elements2);
 
-			try {
-				shapeType = GetSupportedType(root, "shape_type", supportedShapeType);
-				type = GetSupportedType(root, "type", supportedDispTypes);
-			} catch (const std::exception& e) {
-				LOGE("Invalid %s", e.what());
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
+		for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
+			if (static_cast<int>(json_array_get_int_element(array, elem2)) == 1)
+				dimInfo.SetValidIndex(elem2);
+		}
 
-			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
+		try {
+			shapeType = GetSupportedType(root, "shape_type", supportedShapeType);
+			type = GetSupportedType(root, "type", supportedDispTypes);
+		} catch (const std::exception &e) {
+			LOGE("Invalid %s", e.what());
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
 		}
 
-	};
+		LOGI("LEAVE");
+		return MEDIA_VISION_ERROR_NONE;
+	}
+};
 } /* Inference */
 } /* MediaVision */
 
diff --git a/mv_machine_learning/inference/include/Edge.h b/mv_machine_learning/inference/include/Edge.h
index 80c0216..338bee1 100644
--- a/mv_machine_learning/inference/include/Edge.h
+++ b/mv_machine_learning/inference/include/Edge.h
@@ -25,43 +25,46 @@ namespace mediavision
 {
 namespace inference
 {
-	class Edge
-	{
-	private:
-		std::vector<std::pair<int, int>> edges;
-
-	public:
-		Edge() = default;
+class Edge
+{
+private:
+	std::vector<std::pair<int, int> > edges;
 
-		~Edge() = default;
+public:
+	Edge() = default;
 
-		int ParseEdge(JsonObject *root)
-		{
-			LOGI("ENTER");
+	~Edge() = default;
 
-			JsonArray * rootArray = json_object_get_array_member(root, "edgemap");
-			unsigned int elements = json_array_get_length(rootArray);
+	int ParseEdge(JsonObject *root)
+	{
+		LOGI("ENTER");
 
-			// TODO: handling error
-			int pEdgeNode, cEdgeNode;
+		JsonArray *rootArray = json_object_get_array_member(root, "edgemap");
+		unsigned int elements = json_array_get_length(rootArray);
 
-			for (unsigned int elem = 0; elem < elements; ++elem) {
-				JsonNode *pNode = json_array_get_element(rootArray, elem);
-				JsonObject *pObject = json_node_get_object(pNode);
+		// TODO: handling error
+		int pEdgeNode, cEdgeNode;
 
-				pEdgeNode = json_object_get_int_member(pObject, "parent");
-				cEdgeNode = json_object_get_int_member(pObject, "child");
+		for (unsigned int elem = 0; elem < elements; ++elem) {
+			JsonNode *pNode = json_array_get_element(rootArray, elem);
+			JsonObject *pObject = json_node_get_object(pNode);
 
-				edges.push_back(std::make_pair(pEdgeNode, cEdgeNode));
-				LOGI("%ud: parent - child: %d - %d", elem, pEdgeNode, cEdgeNode);
-			}
+			pEdgeNode = json_object_get_int_member(pObject, "parent");
+			cEdgeNode = json_object_get_int_member(pObject, "child");
 
-			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
+			edges.push_back(std::make_pair(pEdgeNode, cEdgeNode));
+			LOGI("%ud: parent - child: %d - %d", elem, pEdgeNode, cEdgeNode);
 		}
 
-		std::vector<std::pair<int, int>>& GetEdgesAll() { return edges; }
-	};
+		LOGI("LEAVE");
+		return MEDIA_VISION_ERROR_NONE;
+	}
+
+	std::vector<std::pair<int, int> > &GetEdgesAll()
+	{
+		return edges;
+	}
+};
 } /* Inference */
 } /* MediaVision */
 
diff --git a/mv_machine_learning/inference/include/Inference.h b/mv_machine_learning/inference/include/Inference.h
index 84a63d2..76c7cb9 100644
--- a/mv_machine_learning/inference/include/Inference.h
+++ b/mv_machine_learning/inference/include/Inference.h
@@ -44,14 +44,16 @@
  */
 using namespace InferenceEngineInterface::Common;
 
-typedef struct _ImageClassficationResults {
+typedef struct _ImageClassficationResults
+{
 	int number_of_classes;
 	std::vector<int> indices;
 	std::vector<std::string> names;
 	std::vector<float> confidences;
 } ImageClassificationResults; /**< structure ImageClassificationResults */
 
-typedef struct _ObjectDetectionResults {
+typedef struct _ObjectDetectionResults
+{
 	int number_of_objects;
 	std::vector<int> indices;
 	std::vector<std::string> names;
@@ -59,18 +61,21 @@ typedef struct _ObjectDetectionResults {
 	std::vector<cv::Rect> locations;
 } ObjectDetectionResults; /**< structure ObjectDetectionResults */
 
-typedef struct _FaceDetectionResults {
+typedef struct _FaceDetectionResults
+{
 	int number_of_faces;
 	std::vector<float> confidences;
 	std::vector<cv::Rect> locations;
 } FaceDetectionResults; /**< structure FaceDetectionResults */
 
-typedef struct _FacialLandMarkDetectionResults {
+typedef struct _FacialLandMarkDetectionResults
+{
 	int number_of_landmarks;
 	std::vector<cv::Point> locations;
 } FacialLandMarkDetectionResults; /**< structure FacialLandMarkDetectionResults */
 
-typedef struct _PoseLandmarkDetectionResults {
+typedef struct _PoseLandmarkDetectionResults
+{
 	int number_of_landmarks;
 	std::vector<cv::Point2f> locations;
 	std::vector<float> score;
@@ -80,122 +85,121 @@ namespace mediavision
 {
 namespace inference
 {
-	struct TensorInfo {
-		int width;
-		int height;
-		int dim;
-		int ch;
-	};
-
-	struct InferenceConfig {
-		/**
+struct TensorInfo
+{
+	int width;
+	int height;
+	int dim;
+	int ch;
+};
+
+struct InferenceConfig
+{
+	/**
 		 * @brief Default constructor for the @ref InferenceConfig
 		 *
 		 * @since_tizen 5.0
 		 */
-		InferenceConfig();
+	InferenceConfig();
 
-		std::string mConfigFilePath; /**< Path of a model configuration file */
+	std::string mConfigFilePath; /**< Path of a model configuration file */
 
-		std::string mWeightFilePath; /**< Path of a model weight file */
+	std::string mWeightFilePath; /**< Path of a model weight file */
 
-		std::string mUserFilePath; /**< Path of model user file */
+	std::string mUserFilePath; /**< Path of model user file */
 
-		TensorInfo mTensorInfo; /**< Tensor information */
+	TensorInfo mTensorInfo; /**< Tensor information */
 
-		mv_inference_data_type_e mDataType; /**< Data type of a input tensor */
+	mv_inference_data_type_e mDataType; /**< Data type of a input tensor */
 
-		int mTargetTypes; /**< Target type to run inference */
+	int mTargetTypes; /**< Target type to run inference */
 
-		double mConfidenceThresHold; /**< Confidence threshold value */
+	double mConfidenceThresHold; /**< Confidence threshold value */
 
-		double mMeanValue; /**< The mean value for normalization */
+	double mMeanValue; /**< The mean value for normalization */
 
-		double mStdValue; /**< The scale factor value for normalization */
+	double mStdValue; /**< The scale factor value for normalization */
 
-		int mMaxOutputNumbers;
+	int mMaxOutputNumbers;
 
-		std::vector<std::string> mInputLayerNames; /**< The input layer names */
-		std::vector<std::string> mOutputLayerNames; /**< The output layer names */
-	};
+	std::vector<std::string> mInputLayerNames; /**< The input layer names */
+	std::vector<std::string> mOutputLayerNames; /**< The output layer names */
+};
 
-	class Inference
-	{
-	public:
-		/**
+class Inference
+{
+public:
+	/**
 		 * @brief   Creates an Inference class instance.
 		 *
 		 * @since_tizen 5.5
 		 */
-		Inference();
+	Inference();
 
-		/**
+	/**
 		 * @brief   Destroys an Inference class instance including
 		 *           its all resources.
 		 *
 		 * @since_tizen 5.5
 		 */
-		~Inference();
+	~Inference();
 
-		/**
+	/**
 		 * @brief   Configure modelfiles
 		 *
 		 * @since_tizen 5.5
 		 */
-		void ConfigureModelFiles(const std::string modelConfigFilePath,
-								 const std::string modelWeightFilePath,
-								 const std::string modelUserFilePath);
+	void ConfigureModelFiles(const std::string modelConfigFilePath, const std::string modelWeightFilePath,
+							 const std::string modelUserFilePath);
 
-		/**
+	/**
 		 * @brief Configure input information
 		 *
 		 * @since_tizen 6.0
 		 */
-		void ConfigureInputInfo(int width, int height, int dim, int ch,
-								double stdValue, double meanValue, int dataType,
-								const std::vector<std::string> names);
+	void ConfigureInputInfo(int width, int height, int dim, int ch, double stdValue, double meanValue, int dataType,
+							const std::vector<std::string> names);
 
-		void ConfigureOutputInfo(std::vector<std::string> names,
-								 std::vector<inference_engine_tensor_info>& tensors_info);
+	void ConfigureOutputInfo(std::vector<std::string> names, std::vector<inference_engine_tensor_info> &tensors_info);
 
-		/**
+	/**
 		 * @brief   Configure a inference target device type such as CPU, GPU or NPU. (only one type can be set)
 		 * @details Internally, a given device type will be converted to new type.
 		 * 			This API is just used for backward compatibility.
 		 *
 		 * @since_tizen 6.0 (Deprecated)
 		 */
-		int ConfigureTargetTypes(int targetType, bool isNewVersion);
+	int ConfigureTargetTypes(int targetType, bool isNewVersion);
 
-		/**
+	/**
 		 * @brief   Configure inference target devices such as CPU, GPU or NPU. (one more types can be combined)
 		 *
 		 * @since_tizen 6.0
 		 */
-		int ConfigureTargetDevices(const int targetDevices);
+	int ConfigureTargetDevices(const int targetDevices);
 
-		/**
+	/**
 		 * @brief   Configure the maximum number of inference results
 		 *
 		 * @since_tizen 5.5
 		 */
-		void ConfigureOutput(const int maxOutputNumbers);
+	void ConfigureOutput(const int maxOutputNumbers);
 
-		/**
+	/**
 		 * @brief   Configure the confidence threshold
 		 *
 		 * @since_tizen 5.5
 		 */
-		void ConfigureThreshold(const double threshold);
+	void ConfigureThreshold(const double threshold);
 
-		/**
+	/**
 		 * @brief   Parses the metadata file path
 		 *
 		 * @since_tizen 6.5
 		 */
-		int ParseMetadata(const std::string filePath);
+	int ParseMetadata(const std::string filePath);
 
-		/**
+	/**
 		 * @brief   Bind a backend engine
 		 * @details Use this function to bind a backend engine for the inference.
 		 * 			This creates a inference engine common class object, and loads a backend
@@ -212,9 +216,9 @@ namespace inference
 		 * @retval #MEDIA_VISION_ERROR_NONE Successful
 		 * @retval #MEDIA_VISION_ERROR_INVALID_PARAMETER Invalid parameter
 		 */
-		int Bind(int backend_type, int device_type);
+	int Bind(int backend_type, int device_type);
 
-		/**
+	/**
 		 * @brief   Load model files
 		 * @details Use this function to load given model files for the inference.
 		 *
@@ -226,9 +230,9 @@ namespace inference
 		 * @retval #MEDIA_VISION_ERROR_NONE Successful
 		 * @retval #MEDIA_VISION_ERROR_INVALID_PARAMETER Invalid parameter
 		 */
-		int Load();
+	int Load();
 
-		/**
+	/**
 		 * @brief	Runs inference with a region of a given image
 		 * @details Use this function to run forward pass with the given image.
 		 *          The given image is preprocessed and the region of the image is
@@ -238,10 +242,9 @@ namespace inference
 		 * @since_tizen 5.5
 		 * @return @c true on success, otherwise a negative error value
 		 */
-		int Run(std::vector<mv_source_h> &mvSources,
-				std::vector<mv_rectangle_s> &rects);
+	int Run(std::vector<mv_source_h> &mvSources, std::vector<mv_rectangle_s> &rects);
 
-		/**
+	/**
 		 * @brief	Runs inference with a region of a given image
 		 * @details Use this function to run forward pass with the given image.
 		 *          The given image is preprocessed and the region of the image is
@@ -251,113 +254,111 @@ namespace inference
 		 * @since_tizen 7.0
 		 * @return @c true on success, otherwise a negative error value
 		 */
-		int Run(std::vector<void *>& buffer_objs);
+	int Run(std::vector<void *> &buffer_objs);
 
-		/**
+	/**
 		 * @brief	Gets that given engine is supported or not
 		 *
 		 * @since_tizen 5.5
 		 * @return @c true on success, otherwise a negative error value
 		 */
-		std::pair<std::string, bool> GetSupportedInferenceBackend(int backend);
+	std::pair<std::string, bool> GetSupportedInferenceBackend(int backend);
 
-		/**
+	/**
 		 * @brief	Gets the ImageClassificationResults
 		 *
 		 * @since_tizen 5.5
 		 * @return @c true on success, otherwise a negative error value
 		 */
-		int GetClassficationResults(ImageClassificationResults *results);
+	int GetClassficationResults(ImageClassificationResults *results);
 
-		/**
+	/**
 		 * @brief	Gets the ObjectDetectioResults
 		 *
 		 * @since_tizen 5.5
 		 * @return @c true on success, otherwise a negative error value
 		 */
-		int GetObjectDetectionResults(ObjectDetectionResults *results);
+	int GetObjectDetectionResults(ObjectDetectionResults *results);
 
-		/**
+	/**
 		 * @brief	Gets the FaceDetectioResults
 		 *
 		 * @since_tizen 5.5
 		 * @return @c true on success, otherwise a negative error value
 		 */
-		int GetFaceDetectionResults(FaceDetectionResults *results);
+	int GetFaceDetectionResults(FaceDetectionResults *results);
 
-		/**
+	/**
 		 * @brief	Gets the FacialLandmarkDetectionResults
 		 *
 		 * @since_tizen 5.5
 		 * @return @c true on success, otherwise a negative error value
 		 */
-		int GetFacialLandMarkDetectionResults(FacialLandMarkDetectionResults *results);
+	int GetFacialLandMarkDetectionResults(FacialLandMarkDetectionResults *results);
 
-		/**
+	/**
 		 * @brief	Gets the PoseLandmarkDetectionResults
 		 *
 		 * @since_tizen 6.0
 		 * @return @c true on success, otherwise a negative error value
 		 */
-		int GetPoseLandmarkDetectionResults(std::unique_ptr<mv_inference_pose_s> &detectionResults,
-										int width, int height);
-
-		mv_engine_config_h GetEngineConfig(void)
-		{
-			return engine_config;
-		}
-
-		void SetEngineConfig(mv_engine_config_h config)
-		{
-			engine_config = config;
-		}
-
-		int GetTargetType()
-		{
-			return mConfig.mTargetTypes;
-		}
-
-		TensorBuffer& GetOutputTensorBuffer()
-		{
-			return mOutputTensorBuffers;
-		}
-
-	private:
-		bool mCanRun; /**< The flag indicating ready to run Inference */
-		InferenceConfig mConfig;
-		inference_engine_capacity mBackendCapacity;
-		std::map<int, std::pair<std::string, bool> > mSupportedInferenceBackend;
-		cv::Size mInputSize;
-		cv::Size mSourceSize;
-		mv_engine_config_h engine_config;
-		InferenceEngineCommon *mBackend;
-		std::map<std::string, int> mModelFormats;
-		std::vector<std::string> mUserListName;
-		//std::map<std::string, inference_engine_tensor_buffer> mInputTensorBuffers;
-		TensorBuffer mInputTensorBuffers;
-		inference_engine_layer_property mInputLayerProperty;
-		//std::map<std::string, inference_engine_tensor_buffer> mOutputTensorBuffers;
-		TensorBuffer mOutputTensorBuffers;
-		inference_engine_layer_property mOutputLayerProperty;
-
-		Metadata mMetadata;
-		PreProcess mPreProc;
-
-	private:
-		void CheckSupportedInferenceBackend();
-		int CheckBackendType(const mv_inference_backend_type_e backendType);
-		bool IsTargetDeviceSupported(const int targetDevices);
-		int ConvertEngineErrorToVisionError(int error);
-		int ConvertTargetTypes(int given_types);
-		int ConvertToCv(int given_type);
-		int ConvertOutputDataTypeToFloat();
-		int Preprocess(std::vector<mv_source_h>& mv_sources, std::vector<cv::Mat>& cv_sources);
-		inference_tensor_data_type_e ConvertToIE(int given_type);
-		int PrepareTenosrBuffers(void);
-		void CleanupTensorBuffers(void);
-		int SetUserFile(std::string filename);
-
-	};
+	int GetPoseLandmarkDetectionResults(std::unique_ptr<mv_inference_pose_s> &detectionResults, int width, int height);
+
+	mv_engine_config_h GetEngineConfig(void)
+	{
+		return engine_config;
+	}
+
+	void SetEngineConfig(mv_engine_config_h config)
+	{
+		engine_config = config;
+	}
+
+	int GetTargetType()
+	{
+		return mConfig.mTargetTypes;
+	}
+
+	TensorBuffer &GetOutputTensorBuffer()
+	{
+		return mOutputTensorBuffers;
+	}
+
+private:
+	bool mCanRun; /**< The flag indicating ready to run Inference */
+	InferenceConfig mConfig;
+	inference_engine_capacity mBackendCapacity;
+	std::map<int, std::pair<std::string, bool> > mSupportedInferenceBackend;
+	cv::Size mInputSize;
+	cv::Size mSourceSize;
+	mv_engine_config_h engine_config;
+	InferenceEngineCommon *mBackend;
+	std::map<std::string, int> mModelFormats;
+	std::vector<std::string> mUserListName;
+	//std::map<std::string, inference_engine_tensor_buffer> mInputTensorBuffers;
+	TensorBuffer mInputTensorBuffers;
+	inference_engine_layer_property mInputLayerProperty;
+	//std::map<std::string, inference_engine_tensor_buffer> mOutputTensorBuffers;
+	TensorBuffer mOutputTensorBuffers;
+	inference_engine_layer_property mOutputLayerProperty;
+
+	Metadata mMetadata;
+	PreProcess mPreProc;
+
+private:
+	void CheckSupportedInferenceBackend();
+	int CheckBackendType(const mv_inference_backend_type_e backendType);
+	bool IsTargetDeviceSupported(const int targetDevices);
+	int ConvertEngineErrorToVisionError(int error);
+	int ConvertTargetTypes(int given_types);
+	int ConvertToCv(int given_type);
+	int ConvertOutputDataTypeToFloat();
+	int Preprocess(std::vector<mv_source_h> &mv_sources, std::vector<cv::Mat> &cv_sources);
+	inference_tensor_data_type_e ConvertToIE(int given_type);
+	int PrepareTenosrBuffers(void);
+	void CleanupTensorBuffers(void);
+	int SetUserFile(std::string filename);
+};
 
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/include/InferenceIni.h b/mv_machine_learning/inference/include/InferenceIni.h
index 7a58614..3a06a61 100644
--- a/mv_machine_learning/inference/include/InferenceIni.h
+++ b/mv_machine_learning/inference/include/InferenceIni.h
@@ -25,46 +25,46 @@ namespace mediavision
 {
 namespace inference
 {
-	class InferenceInI
-	{
-	public:
-		/**
+class InferenceInI
+{
+public:
+	/**
 		 * @brief   Creates an Inference class instance.
 		 *
 		 * @since_tizen 5.5
 		 */
-		InferenceInI();
+	InferenceInI();
 
-		/**
+	/**
 		 * @brief   Destroys an Inference class instance including
 		 *           its all resources.
 		 *
 		 * @since_tizen 5.5
 		 */
-		~InferenceInI();
+	~InferenceInI();
 
-		/**
+	/**
 		 * @brief   Load()
 		 *
 		 * @since_tizen 5.5
 		 */
-		int LoadInI();
+	int LoadInI();
 
-		/**
+	/**
 		 * @brief   Unload()
 		 *
 		 * @since_tizen 5.5
 		 */
-		void UnLoadInI();
+	void UnLoadInI();
 
-		std::vector<int> GetSupportedInferenceEngines();
+	std::vector<int> GetSupportedInferenceEngines();
 
-	private:
-		std::vector<int> mSupportedInferenceBackend;
-		std::string mIniDefaultPath;
-		std::string mDefaultBackend;
-		std::string mDelimeter;
-	};
+private:
+	std::vector<int> mSupportedInferenceBackend;
+	std::string mIniDefaultPath;
+	std::string mDefaultBackend;
+	std::string mDelimeter;
+};
 
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/include/InputMetadata.h b/mv_machine_learning/inference/include/InputMetadata.h
index 77a5c71..f1c762c 100644
--- a/mv_machine_learning/inference/include/InputMetadata.h
+++ b/mv_machine_learning/inference/include/InputMetadata.h
@@ -35,97 +35,110 @@ namespace mediavision
 {
 namespace inference
 {
+struct Normalization
+{
+	bool use { false };
+	std::vector<double> mean;
+	std::vector<double> std;
+};
 
-	struct Normalization {
-		bool use { false };
-		std::vector<double> mean;
-		std::vector<double> std;
-	};
+struct Quantization
+{
+	bool use { false };
+	std::vector<double> scale;
+	std::vector<double> zeropoint;
+};
 
-	struct Quantization {
-		bool use { false };
-		std::vector<double> scale;
-		std::vector<double> zeropoint;
-	};
+struct Options
+{
+	Normalization normalization;
+	Quantization quantization;
+};
 
-	struct Options {
-		Normalization normalization;
-		Quantization  quantization;
-	};
+struct LayerInfo
+{
+	std::string name;
+	std::vector<int> dims;
+	mv_colorspace_e colorSpace {};
+	mv_inference_data_type_e dataType {};
+	inference_tensor_shape_type_e shapeType {}; // TODO: define mv_inference_shape_type_e
 
-	struct LayerInfo
+	int getWidth() const
 	{
-		std::string name;
-		std::vector<int> dims;
-		mv_colorspace_e colorSpace {};
-		mv_inference_data_type_e dataType {};
-		inference_tensor_shape_type_e shapeType {}; // TODO: define mv_inference_shape_type_e
-
-		int getWidth() const {
-			if (shapeType == INFERENCE_TENSOR_SHAPE_NCHW) {
-				return dims[3];
-			} else { // INFERENCE_TENSOR_SHAPE_NHWC
-				return dims[2];
-			}
+		if (shapeType == INFERENCE_TENSOR_SHAPE_NCHW) {
+			return dims[3];
+		} else { // INFERENCE_TENSOR_SHAPE_NHWC
+			return dims[2];
 		}
+	}
 
-		int getHeight() const {
-			if (shapeType == INFERENCE_TENSOR_SHAPE_NCHW) {
-				return dims[2];
-			} else { // INFERENCE_TENSOR_SHAPE_NHWC
-				return dims[1];
-			}
+	int getHeight() const
+	{
+		if (shapeType == INFERENCE_TENSOR_SHAPE_NCHW) {
+			return dims[2];
+		} else { // INFERENCE_TENSOR_SHAPE_NHWC
+			return dims[1];
 		}
+	}
 
-		int getChannel() const {
-			if (shapeType == INFERENCE_TENSOR_SHAPE_NCHW) {
-				return dims[1];
-			} else { // INFERENCE_TENSOR_SHAPE_NHWC
-				return dims[3];
-			}
+	int getChannel() const
+	{
+		if (shapeType == INFERENCE_TENSOR_SHAPE_NCHW) {
+			return dims[1];
+		} else { // INFERENCE_TENSOR_SHAPE_NHWC
+			return dims[3];
 		}
-	};
+	}
+};
 
-	class InputMetadata
-	{
-	public:
-		/**
+class InputMetadata
+{
+public:
+	/**
 		 * @brief   Creates an InputMetadata class instance.
 		 *
 		 * @since_tizen 6.5
 		 */
-		InputMetadata();
+	InputMetadata();
 
-		/**
+	/**
 		 * @brief   Destroys an InputMetadata class instance including
 		 *          its all resources.
 		 *
 		 * @since_tizen 6.5
 		 */
-		~InputMetadata() = default;
+	~InputMetadata() = default;
 
-		/**
+	/**
 		 * @brief Parses an InputMetadata
 		 *
 		 * @since_tizen 6.5
 		 */
-		int Parse(JsonObject *root);
-		bool IsParsed(void) { return parsed; }
-		std::map<std::string, LayerInfo>& GetLayer() { return layer; }
-		std::map<std::string, Options>& GetOption() { return option; }
-
-	private:
-		bool parsed;
-		std::map<std::string, inference_tensor_shape_type_e> mSupportedShapeType;
-		std::map<std::string, mv_inference_data_type_e> mSupportedDataType;
-		std::map<std::string, mv_colorspace_e> mSupportedColorSpace;
-		std::map<std::string, LayerInfo> layer;
-		std::map<std::string, Options> option;
-
-		int GetTensorInfo(JsonObject* root);
-		int GetPreProcess(JsonObject* root);
-
-	};
+	int Parse(JsonObject *root);
+	bool IsParsed(void)
+	{
+		return parsed;
+	}
+	std::map<std::string, LayerInfo> &GetLayer()
+	{
+		return layer;
+	}
+	std::map<std::string, Options> &GetOption()
+	{
+		return option;
+	}
+
+private:
+	bool parsed;
+	std::map<std::string, inference_tensor_shape_type_e> mSupportedShapeType;
+	std::map<std::string, mv_inference_data_type_e> mSupportedDataType;
+	std::map<std::string, mv_colorspace_e> mSupportedColorSpace;
+	std::map<std::string, LayerInfo> layer;
+	std::map<std::string, Options> option;
+
+	int GetTensorInfo(JsonObject *root);
+	int GetPreProcess(JsonObject *root);
+};
 
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/include/Joint.h b/mv_machine_learning/inference/include/Joint.h
index 6f4512b..7d052c8 100644
--- a/mv_machine_learning/inference/include/Joint.h
+++ b/mv_machine_learning/inference/include/Joint.h
@@ -10,222 +10,255 @@ namespace mediavision
 {
 namespace inference
 {
+/** Class created for storing single joint data from bvh file */
+class Joint
+{
+public:
+	/** A struct that keep offset of joint in relation to parent */
+	struct Offset
+	{
+		float x;
+		float y;
+		float z;
+	};
+
+	/** A enumeration type useful for set order of channels for every joint */
+	enum class Channel
+	{
+		XPOSITION,
+		YPOSITION,
+		ZPOSITION,
+		ZROTATION,
+		XROTATION,
+		YROTATION
+	};
+
+	/** A string names for each channel */
+	const std::vector<std::string> channel_name_str = { "XPOSITION", "YPOSITION", "ZPOSITION",
+														"ZROTATION", "XROTATION", "YROTATION" };
 
-  /** Class created for storing single joint data from bvh file */
-  class Joint {
-  public:
-    /** A struct that keep offset of joint in relation to parent */
-    struct Offset {
-      float x;
-      float y;
-      float z;
-    };
-
-    /** A enumeration type useful for set order of channels for every joint */
-    enum class Channel {
-      XPOSITION,
-      YPOSITION,
-      ZPOSITION,
-      ZROTATION,
-      XROTATION,
-      YROTATION
-    };
-
-    /** A string names for each channel */
-    const std::vector<std::string> channel_name_str = {
-      "XPOSITION",
-      "YPOSITION",
-      "ZPOSITION",
-      "ZROTATION",
-      "XROTATION",
-      "YROTATION"
-    };
-
-    /** Adds single frame motion data
+	/** Adds single frame motion data
      *  @param  data    The motion data to be added
      */
-    void add_frame_motion_data(const std::vector <float>& data) {
-      channel_data_.push_back(data);
-    }
+	void add_frame_motion_data(const std::vector<float> &data)
+	{
+		channel_data_.push_back(data);
+	}
 
-    /** Gets the parent joint of this joint
+	/** Gets the parent joint of this joint
      *  @return  The parent joint
      */
-    std::shared_ptr <Joint> parent() const { return parent_; }
+	std::shared_ptr<Joint> parent() const
+	{
+		return parent_;
+	}
 
-    /** Gets the name of this joint
+	/** Gets the name of this joint
      *  @return  The joint's name
      */
-    std::string name() const { return name_; }
+	std::string name() const
+	{
+		return name_;
+	}
 
-    /** Gets the offset of this joint
+	/** Gets the offset of this joint
      *  @return  The joint's offset
      */
-    Offset offset() const { return offset_; }
+	Offset offset() const
+	{
+		return offset_;
+	}
 
-    /** Gets the channels order of this joint
+	/** Gets the channels order of this joint
      *  @return  The joint's channels order
      */
-    std::vector <Channel> channels_order() const {
-      return channels_order_;
-    }
+	std::vector<Channel> channels_order() const
+	{
+		return channels_order_;
+	}
 
-    /** Gets the all children joints of this joint
+	/** Gets the all children joints of this joint
      *  @return  The joint's children
      */
-    std::vector <std::shared_ptr <Joint>> children() const {
-      return children_;
-    }
+	std::vector<std::shared_ptr<Joint> > children() const
+	{
+		return children_;
+	}
 
-    /** Gets the channels data of this joint for all frames
+	/** Gets the channels data of this joint for all frames
      *  @return  The joint's channel data
      */
-    const std::vector <std::vector <float>>& channel_data() const {
-      return channel_data_;
-    }
+	const std::vector<std::vector<float> > &channel_data() const
+	{
+		return channel_data_;
+	}
 
-    /** Gets the channel data of this joint for selected frame
+	/** Gets the channel data of this joint for selected frame
      *  @param   frame   The frame for which channel data will be returned
      *  @return  The joint's channel data for selected frame
      */
-    const std::vector <float>& channel_data(unsigned frame) const {
-      return channel_data_[frame];
-    }
+	const std::vector<float> &channel_data(unsigned frame) const
+	{
+		return channel_data_[frame];
+	}
 
-    /** Gets the channel data of this joint for selected frame and channel
+	/** Gets the channel data of this joint for selected frame and channel
      *  @param   frame        The frame for which channel data will be returned
      *  @param   channel_num  The number of channel which data will be returned
      *  @return  The joint's channel data for selected frame and channel
      */
-    float channel_data(unsigned frame, unsigned channel_num) const {
-      return channel_data_[frame][channel_num];
-    }
+	float channel_data(unsigned frame, unsigned channel_num) const
+	{
+		return channel_data_[frame][channel_num];
+	}
 
-    /** Gets the local transformation matrix for this joint for all frames
+	/** Gets the local transformation matrix for this joint for all frames
      *  @return  The joint's local transformation matrix
      */
-    std::vector <cv::Mat> ltm() const {
-      return ltm_;
-    }
+	std::vector<cv::Mat> ltm() const
+	{
+		return ltm_;
+	}
 
-    /** Gets the local transformation matrix for this joint for selected frame
+	/** Gets the local transformation matrix for this joint for selected frame
      *  @param   frame    The frame for which ltm will be returned
      *  @return  The joint's local transformation matrix for selected frame
      */
-    cv::Mat ltm(unsigned frame) const {
-      return ltm_[frame];
-    }
+	cv::Mat ltm(unsigned frame) const
+	{
+		return ltm_[frame];
+	}
 
-    /** Gets the position for this joint for all frames
+	/** Gets the position for this joint for all frames
      *  @return  The joint's position
      */
-    std::vector <cv::Vec3f> pos() const {
-      return pos_;
-    }
+	std::vector<cv::Vec3f> pos() const
+	{
+		return pos_;
+	}
 
-    /** Gets the position for this joint for selected frame
+	/** Gets the position for this joint for selected frame
      *  @param   frame    The frame for which ltm will be returned
      *  @return  The joint's position for selected frame
      */
-    cv::Vec3f pos(unsigned frame) const {
-      return pos_[frame];
-    }
+	cv::Vec3f pos(unsigned frame) const
+	{
+		return pos_[frame];
+	}
 
-    /** Gets the number of channels of this joint
+	/** Gets the number of channels of this joint
      *  @return  The joint's channels number
      */
-    unsigned num_channels() const { return channels_order_.size(); }
+	unsigned num_channels() const
+	{
+		return channels_order_.size();
+	}
 
-    /** Sets the this joint parent joint
+	/** Sets the this joint parent joint
      *  @param   arg    The parent joint of this joint
      */
-    void set_parent(const std::shared_ptr <Joint> arg) { parent_ = arg; }
+	void set_parent(const std::shared_ptr<Joint> arg)
+	{
+		parent_ = arg;
+	}
 
-    /** Sets the this joint name
+	/** Sets the this joint name
      *  @param   arg    The name of this joint
      */
-    void set_name(const std::string arg) { name_ = arg; }
+	void set_name(const std::string arg)
+	{
+		name_ = arg;
+	}
 
-    /** Sets the this joint offset
+	/** Sets the this joint offset
      *  @param   arg    The offset of this joint
      */
-    void set_offset(const Offset arg) { offset_ = arg; }
+	void set_offset(const Offset arg)
+	{
+		offset_ = arg;
+	}
 
-    /** Sets the this joint channels order
+	/** Sets the this joint channels order
      *  @param   arg    The channels order of this joint
      */
-    void set_channels_order(const std::vector <Channel>& arg) {
-      channels_order_ = arg;
-    }
+	void set_channels_order(const std::vector<Channel> &arg)
+	{
+		channels_order_ = arg;
+	}
 
-    /** Sets the this joint children
+	/** Sets the this joint children
      *  @param   arg    The children of this joint
      */
-    void set_children(const std::vector <std::shared_ptr <Joint>>& arg) {
-      children_ = arg;
-    }
+	void set_children(const std::vector<std::shared_ptr<Joint> > &arg)
+	{
+		children_ = arg;
+	}
 
-    /** Sets the this joint channels data
+	/** Sets the this joint channels data
      *  @param   arg    The channels data of this joint
      */
-    void set_channel_data(const std::vector <std::vector <float>>& arg) {
-      channel_data_ = arg;
-    }
+	void set_channel_data(const std::vector<std::vector<float> > &arg)
+	{
+		channel_data_ = arg;
+	}
 
-    /** Sets local transformation matrix for selected frame
+	/** Sets local transformation matrix for selected frame
      *  @param  matrix  The local transformation matrix to be set
      *  @param  frame   The number of frame for which you want set ltm. As
      *                  default it is set to 0.
      */
-    void set_ltm(const cv::Mat matrix, unsigned frame = 0) {
-      if (frame > 0 && frame < ltm_.size())
-        ltm_[frame] = matrix;
-      else
-        ltm_.push_back(matrix);
-    }
+	void set_ltm(const cv::Mat matrix, unsigned frame = 0)
+	{
+		if (frame > 0 && frame < ltm_.size())
+			ltm_[frame] = matrix;
+		else
+			ltm_.push_back(matrix);
+	}
 
-    /** Sets local transformation matrix for selected frame
+	/** Sets local transformation matrix for selected frame
      *  @param  pos     The position of joint in selected frame to be set
      *  @param  frame   The number of frame for which you want set position. As
      *                  default it is set to 0.
      */
-    void set_pos(const cv::Vec3f pos, unsigned frame = 0) {
-      if (frame > 0 && frame < pos_.size())
-        pos_[frame] = pos;
-      else
-        pos_.push_back(pos);
-    }
+	void set_pos(const cv::Vec3f pos, unsigned frame = 0)
+	{
+		if (frame > 0 && frame < pos_.size())
+			pos_[frame] = pos;
+		else
+			pos_.push_back(pos);
+	}
 
-    /** Gets channels name of this joint
+	/** Gets channels name of this joint
      *  @return The joint's channels name
      */
-    const std::vector<std::string> get_channels_name() const {
-      std::vector<std::string> channel_names;
-
-      for (const auto &channel : channels_order_)
-        channel_names.push_back(channel_name_str[static_cast<int>(channel)]);
-
-      return channel_names;
-    }
-
-  private:
-    /** Parent joint in file hierarchy */
-    std::shared_ptr <Joint> parent_;
-    std::string name_;
-    Offset offset_;
-    /** Order of joint's input channels */
-    std::vector <Channel> channels_order_;
-    /** Pointers to joints that are children of this in hierarchy */
-    std::vector <std::shared_ptr <Joint>> children_;
-    /** Structure for keep joint's channel's data.
+	const std::vector<std::string> get_channels_name() const
+	{
+		std::vector<std::string> channel_names;
+
+		for (const auto &channel : channels_order_)
+			channel_names.push_back(channel_name_str[static_cast<int>(channel)]);
+
+		return channel_names;
+	}
+
+private:
+	/** Parent joint in file hierarchy */
+	std::shared_ptr<Joint> parent_;
+	std::string name_;
+	Offset offset_;
+	/** Order of joint's input channels */
+	std::vector<Channel> channels_order_;
+	/** Pointers to joints that are children of this in hierarchy */
+	std::vector<std::shared_ptr<Joint> > children_;
+	/** Structure for keep joint's channel's data.
      *  Each vector keep data for one channel.
      */
-    std::vector <std::vector <float> > channel_data_;
-    /** Local transformation matrix for each frame */
-    std::vector <cv::Mat> ltm_;
-    /** Vector x, y, z of joint position for each frame */
-    std::vector <cv::Vec3f> pos_;
-  };
+	std::vector<std::vector<float> > channel_data_;
+	/** Local transformation matrix for each frame */
+	std::vector<cv::Mat> ltm_;
+	/** Vector x, y, z of joint position for each frame */
+	std::vector<cv::Vec3f> pos_;
+};
 }
 } // namespace
 #endif // __MEDIA_VISION_JOINT_H__
diff --git a/mv_machine_learning/inference/include/Landmark.h b/mv_machine_learning/inference/include/Landmark.h
index 87f0c03..f429361 100644
--- a/mv_machine_learning/inference/include/Landmark.h
+++ b/mv_machine_learning/inference/include/Landmark.h
@@ -37,252 +37,262 @@ namespace mediavision
 {
 namespace inference
 {
-	typedef struct _LandmarkPoint
-	{
-		float score;
-		cv::Point heatMapLoc;
-		cv::Point2f decodedLoc;
-		int id;
-		bool valid;
-	} LandmarkPoint;
-
-	typedef struct _LandmarkResults
-	{
-		std::vector<LandmarkPoint> landmarks;
-		float score;
-	} LandmarkResults;
-
-	typedef struct _HeatMapInfo {
-		int wIdx;
-		int hIdx;
-		int cIdx;
-		float nmsRadius;
-		inference_tensor_shape_type_e shapeType;
-	} HeatMapInfo;
-
-	class Landmark
-	{
-	private:
-		std::string name;
-		DimInfo dimInfo;
-		inference_landmark_type_e type; /**< 0: 2D_SINGLE, 1: 2D_MULTI, 2: 3D_SINGLE */
-		int offset;
-		inference_landmark_coorindate_type_e coordinate; /**< 0: RATIO, 1: PIXEL */
-		inference_landmark_decoding_type_e decodingType; /**< 0: decoding  unnecessary,
+typedef struct _LandmarkPoint
+{
+	float score;
+	cv::Point heatMapLoc;
+	cv::Point2f decodedLoc;
+	int id;
+	bool valid;
+} LandmarkPoint;
+
+typedef struct _LandmarkResults
+{
+	std::vector<LandmarkPoint> landmarks;
+	float score;
+} LandmarkResults;
+
+typedef struct _HeatMapInfo
+{
+	int wIdx;
+	int hIdx;
+	int cIdx;
+	float nmsRadius;
+	inference_tensor_shape_type_e shapeType;
+} HeatMapInfo;
+
+class Landmark
+{
+private:
+	std::string name;
+	DimInfo dimInfo;
+	inference_landmark_type_e type; /**< 0: 2D_SINGLE, 1: 2D_MULTI, 2: 3D_SINGLE */
+	int offset;
+	inference_landmark_coorindate_type_e coordinate; /**< 0: RATIO, 1: PIXEL */
+	inference_landmark_decoding_type_e decodingType; /**< 0: decoding  unnecessary,
 															1: decoding heatmap,
 															2: decoding heatmap with refinement */
-		HeatMapInfo heatMapInfo;
-		std::vector<DispVec> dispVecs;
-		Edge edgeMap;
-
-		std::map<std::string, inference_landmark_type_e> supportedLandmarkTypes;
-		std::map<std::string, inference_landmark_coorindate_type_e> supportedLandmarkCoordinateTypes;
-		std::map<std::string, inference_landmark_decoding_type_e> supportedLandmarkDecodingTypes;
-
-	public:
-
-		Landmark() :
-			name(),
-			dimInfo(),
-			type(INFERENCE_LANDMARK_TYPE_2D_SINGLE),
-			offset(),
-			coordinate(INFERENCE_LANDMARK_COORDINATE_TYPE_RATIO),
-			decodingType(INFERENCE_LANDMARK_DECODING_TYPE_BYPASS),
-			heatMapInfo()
-
-		{
-			supportedLandmarkTypes.insert({"2D_SINGLE", INFERENCE_LANDMARK_TYPE_2D_SINGLE});
-			supportedLandmarkTypes.insert({"2D_MULTI",  INFERENCE_LANDMARK_TYPE_2D_MULTI});
-			supportedLandmarkTypes.insert({"3D_SINGLE", INFERENCE_LANDMARK_TYPE_3D_SINGLE});
-
-			supportedLandmarkCoordinateTypes.insert({"RATIO", INFERENCE_LANDMARK_COORDINATE_TYPE_RATIO});
-			supportedLandmarkCoordinateTypes.insert({"PIXEL", INFERENCE_LANDMARK_COORDINATE_TYPE_PIXEL});
-
-			supportedLandmarkDecodingTypes.insert({"BYPASS", INFERENCE_LANDMARK_DECODING_TYPE_BYPASS});
-			supportedLandmarkDecodingTypes.insert({"BYPASS_MULTICHANNEL", INFERENCE_LANDMARK_DECODING_TYPE_BYPASS_MULTICHANNEL});
-			supportedLandmarkDecodingTypes.insert({"HEATMAP", INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP});
-			supportedLandmarkDecodingTypes.insert({"HEATMAP_REFINE", INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP_REFINE});
-		}
+	HeatMapInfo heatMapInfo;
+	std::vector<DispVec> dispVecs;
+	Edge edgeMap;
+
+	std::map<std::string, inference_landmark_type_e> supportedLandmarkTypes;
+	std::map<std::string, inference_landmark_coorindate_type_e> supportedLandmarkCoordinateTypes;
+	std::map<std::string, inference_landmark_decoding_type_e> supportedLandmarkDecodingTypes;
+
+public:
+	Landmark()
+			: name()
+			, dimInfo()
+			, type(INFERENCE_LANDMARK_TYPE_2D_SINGLE)
+			, offset()
+			, coordinate(INFERENCE_LANDMARK_COORDINATE_TYPE_RATIO)
+			, decodingType(INFERENCE_LANDMARK_DECODING_TYPE_BYPASS)
+			, heatMapInfo()
+
+	{
+		supportedLandmarkTypes.insert({ "2D_SINGLE", INFERENCE_LANDMARK_TYPE_2D_SINGLE });
+		supportedLandmarkTypes.insert({ "2D_MULTI", INFERENCE_LANDMARK_TYPE_2D_MULTI });
+		supportedLandmarkTypes.insert({ "3D_SINGLE", INFERENCE_LANDMARK_TYPE_3D_SINGLE });
+
+		supportedLandmarkCoordinateTypes.insert({ "RATIO", INFERENCE_LANDMARK_COORDINATE_TYPE_RATIO });
+		supportedLandmarkCoordinateTypes.insert({ "PIXEL", INFERENCE_LANDMARK_COORDINATE_TYPE_PIXEL });
+
+		supportedLandmarkDecodingTypes.insert({ "BYPASS", INFERENCE_LANDMARK_DECODING_TYPE_BYPASS });
+		supportedLandmarkDecodingTypes.insert(
+				{ "BYPASS_MULTICHANNEL", INFERENCE_LANDMARK_DECODING_TYPE_BYPASS_MULTICHANNEL });
+		supportedLandmarkDecodingTypes.insert({ "HEATMAP", INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP });
+		supportedLandmarkDecodingTypes.insert({ "HEATMAP_REFINE", INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP_REFINE });
+	}
+
+	~Landmark() = default;
+
+	int ParseLandmark(JsonObject *root)
+	{
+		// box
+		JsonArray *rootArray = json_object_get_array_member(root, "landmark");
+		unsigned int elements = json_array_get_length(rootArray);
+
+		// TODO: handling error
+		for (unsigned int elem = 0; elem < elements; ++elem) {
+			JsonNode *pNode = json_array_get_element(rootArray, elem);
+			JsonObject *pObject = json_node_get_object(pNode);
+
+			name = static_cast<const char *>(json_object_get_string_member(pObject, "name"));
+			LOGI("layer: %s", name.c_str());
+
+			JsonArray *array = json_object_get_array_member(pObject, "index");
+			unsigned int elements2 = json_array_get_length(array);
+			LOGI("range dim: size[%u]", elements2);
+			for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
+				if (static_cast<int>(json_array_get_int_element(array, elem2)) == 1)
+					dimInfo.SetValidIndex(elem2);
+			}
 
-		~Landmark() = default;
-
-		int ParseLandmark(JsonObject *root)
-		{
-			// box
-			JsonArray * rootArray = json_object_get_array_member(root, "landmark");
-			unsigned int elements = json_array_get_length(rootArray);
-
-			// TODO: handling error
-			for (unsigned int elem = 0; elem < elements; ++elem) {
-
-				JsonNode *pNode = json_array_get_element(rootArray, elem);
-				JsonObject *pObject = json_node_get_object(pNode);
-
-				name =
-					static_cast<const char*>(json_object_get_string_member(pObject,"name"));
-				LOGI("layer: %s", name.c_str());
-
-				JsonArray * array = json_object_get_array_member(pObject, "index");
-				unsigned int elements2 = json_array_get_length(array);
-				LOGI("range dim: size[%u]", elements2);
-				for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
-					if (static_cast<int>(json_array_get_int_element(array, elem2)) == 1)
-						dimInfo.SetValidIndex(elem2);
-				}
-
-				try {
-					type = GetSupportedType(pObject, "landmark_type", supportedLandmarkTypes);
-					coordinate = GetSupportedType(pObject, "landmark_coordinate", supportedLandmarkCoordinateTypes);
-					decodingType = GetSupportedType(pObject, "decoding_type", supportedLandmarkDecodingTypes);
-				} catch (const std::exception& e) {
-					LOGE("Invalid %s", e.what());
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-				if (json_object_has_member(pObject, "landmark_offset")) {
-					offset = static_cast<int>(json_object_get_int_member(pObject, "landmark_offset"));
-					LOGI("(optional) landmark offset: %d", offset);
-				}
+			try {
+				type = GetSupportedType(pObject, "landmark_type", supportedLandmarkTypes);
+				coordinate = GetSupportedType(pObject, "landmark_coordinate", supportedLandmarkCoordinateTypes);
+				decodingType = GetSupportedType(pObject, "decoding_type", supportedLandmarkDecodingTypes);
+			} catch (const std::exception &e) {
+				LOGE("Invalid %s", e.what());
+				return MEDIA_VISION_ERROR_INVALID_OPERATION;
+			}
+			if (json_object_has_member(pObject, "landmark_offset")) {
+				offset = static_cast<int>(json_object_get_int_member(pObject, "landmark_offset"));
+				LOGI("(optional) landmark offset: %d", offset);
 			}
+		}
+
+		LOGI("LEAVE");
+		return MEDIA_VISION_ERROR_NONE;
+	}
+
+	int ParseDisplacement(JsonObject *root,
+						  const std::map<std::string, inference_tensor_shape_type_e> &supportedShapeType)
+	{
+		LOGI("ENTER");
 
+		if (!json_object_has_member(root, "displacement")) {
+			LOGI("No displacement outputmetadata");
 			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
 		}
 
-		int ParseDisplacement(JsonObject *root,
-							  const std::map<std::string, inference_tensor_shape_type_e>& supportedShapeType)
-		{
-			LOGI("ENTER");
+		JsonArray *rootArray = json_object_get_array_member(root, "displacement");
+		unsigned int elements = json_array_get_length(rootArray);
 
-			if (!json_object_has_member(root, "displacement")) {
-				LOGI("No displacement outputmetadata");
-				LOGI("LEAVE");
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
+		dispVecs.resize(elements);
+		unsigned int elem = 0;
+		for (auto &disp : dispVecs) {
+			JsonNode *pNode = json_array_get_element(rootArray, elem++);
+			JsonObject *pObject = json_node_get_object(pNode);
 
-			JsonArray * rootArray = json_object_get_array_member(root, "displacement");
-			unsigned int elements = json_array_get_length(rootArray);
+			disp.ParseDisplacement(pObject, supportedShapeType);
+		}
 
-			dispVecs.resize(elements);
-			unsigned int elem = 0;
-			for (auto& disp : dispVecs) {
-				JsonNode *pNode = json_array_get_element(rootArray, elem++);
-				JsonObject *pObject = json_node_get_object(pNode);
+		LOGI("LEAVE");
+		return MEDIA_VISION_ERROR_NONE;
+	}
 
-				disp.ParseDisplacement(pObject, supportedShapeType);
-			}
+	int ParseEdgeMap(JsonObject *root)
+	{
+		LOGI("ENTER");
 
+		if (!json_object_has_member(root, "edgemap")) {
+			LOGI("No edgemap outputmetadata");
 			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
 		}
 
-		int ParseEdgeMap(JsonObject * root)
-		{
-			LOGI("ENTER");
+		edgeMap.ParseEdge(root);
+
+		LOGI("LEAVE");
+		return MEDIA_VISION_ERROR_NONE;
+	}
 
-			if (!json_object_has_member(root, "edgemap")) {
-				LOGI("No edgemap outputmetadata");
+	int ParseDecodeInfo(JsonObject *root,
+						const std::map<std::string, inference_tensor_shape_type_e> &supportedShapeType)
+	{
+		LOGI("ENTER");
+
+		// box
+		JsonArray *rootArray = json_object_get_array_member(root, "landmark");
+		unsigned int elements = json_array_get_length(rootArray);
+
+		// TODO: handling error
+		for (unsigned int elem = 0; elem < elements; ++elem) {
+			JsonNode *pNode = json_array_get_element(rootArray, elem);
+			JsonObject *pObject = json_node_get_object(pNode);
+
+			if (!json_object_has_member(pObject, "decoding_info")) {
+				LOGE("decoding_info is mandatory. Invalid metadata");
 				LOGI("LEAVE");
+
 				return MEDIA_VISION_ERROR_INVALID_OPERATION;
 			}
 
-			edgeMap.ParseEdge(root);
+			JsonObject *cObject = json_object_get_object_member(pObject, "decoding_info");
+			if (!json_object_has_member(cObject, "heatmap")) {
+				LOGE("heatmap is mandatory. Invalid metadata");
+				LOGI("LEAVE");
 
-			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
-		}
+				return MEDIA_VISION_ERROR_INVALID_OPERATION;
+			}
 
-		int ParseDecodeInfo(JsonObject *root,
-							const std::map<std::string, inference_tensor_shape_type_e>& supportedShapeType)
-		{
-			LOGI("ENTER");
-
-			// box
-			JsonArray * rootArray = json_object_get_array_member(root, "landmark");
-			unsigned int elements = json_array_get_length(rootArray);
-
-			// TODO: handling error
-			for (unsigned int elem = 0; elem < elements; ++elem) {
-
-				JsonNode *pNode = json_array_get_element(rootArray, elem);
-				JsonObject *pObject = json_node_get_object(pNode);
-
-				if (!json_object_has_member(pObject, "decoding_info")) {
-					LOGE("decoding_info is mandatory. Invalid metadata");
-					LOGI("LEAVE");
-
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-
-				JsonObject *cObject = json_object_get_object_member(pObject, "decoding_info");
-				if (!json_object_has_member(cObject, "heatmap")) {
-					LOGE("heatmap is mandatory. Invalid metadata");
-					LOGI("LEAVE");
-
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-
-				JsonObject *object = json_object_get_object_member(cObject, "heatmap") ;
-				try {
-					GetHeatMapInfo().shapeType = GetSupportedType(object, "shape_type", supportedShapeType);
-				} catch (const std::exception& e) {
-					LOGE("Invalid %s", e.what());
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-
-				std::vector<int> heatMapIndexes = GetDimInfo().GetValidIndexAll();
-				if (GetHeatMapInfo().shapeType == INFERENCE_TENSOR_SHAPE_NCHW) {
-					GetHeatMapInfo().cIdx = heatMapIndexes[0];
-					GetHeatMapInfo().hIdx = heatMapIndexes[1];
-					GetHeatMapInfo().wIdx = heatMapIndexes[2];
-				} else {
-					GetHeatMapInfo().hIdx = heatMapIndexes[0];
-					GetHeatMapInfo().wIdx = heatMapIndexes[1];
-					GetHeatMapInfo().cIdx = heatMapIndexes[2];
-				}
-
-				if (json_object_has_member(object, "nms_radius")) {
-					GetHeatMapInfo().nmsRadius = static_cast<float>(json_object_get_double_member(object, "nms_radius"));
-					LOGI("nms is enabled with %3.f", GetHeatMapInfo().nmsRadius );
-				}
+			JsonObject *object = json_object_get_object_member(cObject, "heatmap");
+			try {
+				GetHeatMapInfo().shapeType = GetSupportedType(object, "shape_type", supportedShapeType);
+			} catch (const std::exception &e) {
+				LOGE("Invalid %s", e.what());
+				return MEDIA_VISION_ERROR_INVALID_OPERATION;
 			}
 
-			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
-		}
+			std::vector<int> heatMapIndexes = GetDimInfo().GetValidIndexAll();
+			if (GetHeatMapInfo().shapeType == INFERENCE_TENSOR_SHAPE_NCHW) {
+				GetHeatMapInfo().cIdx = heatMapIndexes[0];
+				GetHeatMapInfo().hIdx = heatMapIndexes[1];
+				GetHeatMapInfo().wIdx = heatMapIndexes[2];
+			} else {
+				GetHeatMapInfo().hIdx = heatMapIndexes[0];
+				GetHeatMapInfo().wIdx = heatMapIndexes[1];
+				GetHeatMapInfo().cIdx = heatMapIndexes[2];
+			}
 
-		inference_landmark_type_e GetType()
-		{
-			return type;
+			if (json_object_has_member(object, "nms_radius")) {
+				GetHeatMapInfo().nmsRadius = static_cast<float>(json_object_get_double_member(object, "nms_radius"));
+				LOGI("nms is enabled with %3.f", GetHeatMapInfo().nmsRadius);
+			}
 		}
 
-		int GetOffset()
-		{
-			return offset;
-		}
+		LOGI("LEAVE");
+		return MEDIA_VISION_ERROR_NONE;
+	}
 
-		inference_landmark_coorindate_type_e GetCoordinate()
-		{
-			return coordinate;
-		}
+	inference_landmark_type_e GetType()
+	{
+		return type;
+	}
 
-		inference_landmark_decoding_type_e GetDecodingType()
-		{
-			return decodingType;
-		}
+	int GetOffset()
+	{
+		return offset;
+	}
 
-		HeatMapInfo& GetHeatMapInfo()
-		{
-			return heatMapInfo;
-		}
+	inference_landmark_coorindate_type_e GetCoordinate()
+	{
+		return coordinate;
+	}
 
-		std::string GetName() { return name; }
+	inference_landmark_decoding_type_e GetDecodingType()
+	{
+		return decodingType;
+	}
 
-		DimInfo GetDimInfo() { return dimInfo; }
+	HeatMapInfo &GetHeatMapInfo()
+	{
+		return heatMapInfo;
+	}
+
+	std::string GetName()
+	{
+		return name;
+	}
 
-		std::vector<DispVec>& GetDispVecAll() { return dispVecs; }
+	DimInfo GetDimInfo()
+	{
+		return dimInfo;
+	}
 
-		std::vector<std::pair<int, int>>& GetEdges() { return edgeMap.GetEdgesAll(); }
-	};
+	std::vector<DispVec> &GetDispVecAll()
+	{
+		return dispVecs;
+	}
+
+	std::vector<std::pair<int, int> > &GetEdges()
+	{
+		return edgeMap.GetEdgesAll();
+	}
+};
 } /* Inference */
 } /* MediaVision */
 
diff --git a/mv_machine_learning/inference/include/Metadata.h b/mv_machine_learning/inference/include/Metadata.h
index ecf9ef6..6ff9c39 100644
--- a/mv_machine_learning/inference/include/Metadata.h
+++ b/mv_machine_learning/inference/include/Metadata.h
@@ -37,52 +37,52 @@ namespace mediavision
 {
 namespace inference
 {
-	class Metadata
-	{
-	public:
-		/**
+class Metadata
+{
+public:
+	/**
 		 * @brief   Creates an Metadata class instance.
 		 *
 		 * @since_tizen 6.5
 		 */
-		Metadata() = default;
+	Metadata() = default;
 
-		/**
+	/**
 		 * @brief   Destroys an Metadata class instance including
 		 *          its all resources.
 		 *
 		 * @since_tizen 6.5
 		 */
-		~Metadata() = default;
+	~Metadata() = default;
 
-		/**
+	/**
 		 * @brief Initializes an Metadata class
 		 *
 		 * @since_tizen 6.5
 		 */
-		int Init(const std::string& filename);
+	int Init(const std::string &filename);
 
-		/**
+	/**
 		 * @brief Parses a metafile and set values to InputMetadata
 		 *        and OutputMetadata
 		 *
 		 * @since_tizen 6.5
 		 */
-		int Parse();
+	int Parse();
 
-		InputMetadata& GetInputMeta();
-		OutputMetadata& GetOutputMeta();
+	InputMetadata &GetInputMeta();
+	OutputMetadata &GetOutputMeta();
 
-	private:
-		int ParseInputMeta(JsonObject *object);
-		int ParseOutputMeta(JsonObject *object);
+private:
+	int ParseInputMeta(JsonObject *object);
+	int ParseOutputMeta(JsonObject *object);
 
-	private:
-		std::string mMetafile;
+private:
+	std::string mMetafile;
 
-		InputMetadata mInputMeta;
-		OutputMetadata mOutputMeta;
-	};
+	InputMetadata mInputMeta;
+	OutputMetadata mOutputMeta;
+};
 
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/include/ObjectDecoder.h b/mv_machine_learning/inference/include/ObjectDecoder.h
old mode 100755
new mode 100644
index 9d725ee..50817d7
--- a/mv_machine_learning/inference/include/ObjectDecoder.h
+++ b/mv_machine_learning/inference/include/ObjectDecoder.h
@@ -37,35 +37,38 @@ namespace mediavision
 {
 namespace inference
 {
-	class ObjectDecoder
-	{
-	private:
-		TensorBuffer mTensorBuffer;
-		OutputMetadata mMeta;
-		int mBoxOffset;
-		int mNumberOfOjects;
-		float mScaleW;
-		float mScaleH;
-		Boxes mResultBoxes;
+class ObjectDecoder
+{
+private:
+	TensorBuffer mTensorBuffer;
+	OutputMetadata mMeta;
+	int mBoxOffset;
+	int mNumberOfOjects;
+	float mScaleW;
+	float mScaleH;
+	Boxes mResultBoxes;
 
-		float decodeScore(int idx);
-		Box decodeBox(int idx, float score, int label = -1, int offset = 0);
-		Box decodeBoxWithAnchor(int idx, int anchorIdx, float score, cv::Rect2f& anchor);
+	float decodeScore(int idx);
+	Box decodeBox(int idx, float score, int label = -1, int offset = 0);
+	Box decodeBoxWithAnchor(int idx, int anchorIdx, float score, cv::Rect2f &anchor);
 
-	public:
-		ObjectDecoder(TensorBuffer& buffer, OutputMetadata& metaData,
-					int boxOffset, float scaleW, float scaleH, int numberOfObjects = 0) :
-					mTensorBuffer(buffer), mMeta(metaData),
-					mBoxOffset(boxOffset), mNumberOfOjects(numberOfObjects),
-					mScaleW(scaleW), mScaleH(scaleH), mResultBoxes() {
-					};
+public:
+	ObjectDecoder(TensorBuffer &buffer, OutputMetadata &metaData, int boxOffset, float scaleW, float scaleH,
+				  int numberOfObjects = 0)
+			: mTensorBuffer(buffer)
+			, mMeta(metaData)
+			, mBoxOffset(boxOffset)
+			, mNumberOfOjects(numberOfObjects)
+			, mScaleW(scaleW)
+			, mScaleH(scaleH)
+			, mResultBoxes() {};
 
-		~ObjectDecoder() = default;
+	~ObjectDecoder() = default;
 
-		int init();
-		int decode();
-		Boxes& getObjectAll();
-	};
+	int init();
+	int decode();
+	Boxes &getObjectAll();
+};
 
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/include/OffsetVec.h b/mv_machine_learning/inference/include/OffsetVec.h
index c5fe30b..e3504ba 100644
--- a/mv_machine_learning/inference/include/OffsetVec.h
+++ b/mv_machine_learning/inference/include/OffsetVec.h
@@ -29,55 +29,63 @@ namespace mediavision
 {
 namespace inference
 {
-	class OffsetVec
-	{
-	private:
-		std::string name;
-		DimInfo dimInfo;
-		int shapeType;
-	public:
-		OffsetVec() : name(), dimInfo(), shapeType() { }
-		~OffsetVec() = default;
-		std::string GetName() { return name; }
-		DimInfo GetDimInfo() { return dimInfo; }
-		int GetShapeType() { return shapeType; }
-
-		int ParseOffset(JsonObject *root, const std::map<std::string, inference_tensor_shape_type_e>& supportedShapeType)
-		{
-			JsonArray * rootArray = json_object_get_array_member(root, "offset");
-			unsigned int elements = json_array_get_length(rootArray);
-
-			// TODO: handling error
-			for (unsigned int elem = 0; elem < elements; ++elem) {
+class OffsetVec
+{
+private:
+	std::string name;
+	DimInfo dimInfo;
+	int shapeType;
 
-				JsonNode *pNode = json_array_get_element(rootArray, elem);
-				JsonObject *pObject = json_node_get_object(pNode);
+public:
+	OffsetVec() : name(), dimInfo(), shapeType()
+	{}
+	~OffsetVec() = default;
+	std::string GetName()
+	{
+		return name;
+	}
+	DimInfo GetDimInfo()
+	{
+		return dimInfo;
+	}
+	int GetShapeType()
+	{
+		return shapeType;
+	}
 
-				name =
-					static_cast<const char*>(json_object_get_string_member(pObject,"name"));
-				LOGI("layer: %s", name.c_str());
+	int ParseOffset(JsonObject *root, const std::map<std::string, inference_tensor_shape_type_e> &supportedShapeType)
+	{
+		JsonArray *rootArray = json_object_get_array_member(root, "offset");
+		unsigned int elements = json_array_get_length(rootArray);
 
-				JsonArray * array = json_object_get_array_member(pObject, "index");
-				unsigned int elements2 = json_array_get_length(array);
-				LOGI("range dim: size[%u]", elements2);
-				for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
-					if (static_cast<int>(json_array_get_int_element(array, elem2)) == 1)
-						dimInfo.SetValidIndex(elem2);
-				}
+		// TODO: handling error
+		for (unsigned int elem = 0; elem < elements; ++elem) {
+			JsonNode *pNode = json_array_get_element(rootArray, elem);
+			JsonObject *pObject = json_node_get_object(pNode);
 
-				try {
-					shapeType = GetSupportedType(pObject, "shape_type", supportedShapeType);
-				} catch (const std::exception& e) {
-					LOGE("Invalid %s", e.what());
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
+			name = static_cast<const char *>(json_object_get_string_member(pObject, "name"));
+			LOGI("layer: %s", name.c_str());
 
+			JsonArray *array = json_object_get_array_member(pObject, "index");
+			unsigned int elements2 = json_array_get_length(array);
+			LOGI("range dim: size[%u]", elements2);
+			for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
+				if (static_cast<int>(json_array_get_int_element(array, elem2)) == 1)
+					dimInfo.SetValidIndex(elem2);
 			}
 
-			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
+			try {
+				shapeType = GetSupportedType(pObject, "shape_type", supportedShapeType);
+			} catch (const std::exception &e) {
+				LOGE("Invalid %s", e.what());
+				return MEDIA_VISION_ERROR_INVALID_OPERATION;
+			}
 		}
-	};
+
+		LOGI("LEAVE");
+		return MEDIA_VISION_ERROR_NONE;
+	}
+};
 } /* Inference */
 } /* MediaVision */
 
diff --git a/mv_machine_learning/inference/include/OutputMetadata.h b/mv_machine_learning/inference/include/OutputMetadata.h
index 9385aa7..a19ef59 100644
--- a/mv_machine_learning/inference/include/OutputMetadata.h
+++ b/mv_machine_learning/inference/include/OutputMetadata.h
@@ -46,75 +46,162 @@ namespace mediavision
 {
 namespace inference
 {
-	class OutputMetadata
-	{
-	private:
-		bool parsed;
-		ScoreInfo score;
-		box::BoxInfo box;
-		Landmark landmark;
-		OffsetVec offsetVec;
-		std::map<std::string, inference_tensor_shape_type_e> mSupportedShapeType;
+class OutputMetadata
+{
+private:
+	bool parsed;
+	ScoreInfo score;
+	box::BoxInfo box;
+	Landmark landmark;
+	OffsetVec offsetVec;
+	std::map<std::string, inference_tensor_shape_type_e> mSupportedShapeType;
 
-		int ParseScore(JsonObject *root);
-		int ParseBox(JsonObject *root);
-		int ParseLandmark(JsonObject *root);
-		int ParseOffset(JsonObject *root);
+	int ParseScore(JsonObject *root);
+	int ParseBox(JsonObject *root);
+	int ParseLandmark(JsonObject *root);
+	int ParseOffset(JsonObject *root);
 
-	public:
-		/**
+public:
+	/**
 		 * @brief   Creates an OutputMetadata class instance.
 		 *
 		 * @since_tizen 6.5
 		 */
-		OutputMetadata();
+	OutputMetadata();
 
-		/**
+	/**
 		 * @brief   Destroys an OutputMetadata class instance including
 		 *          its all resources.
 		 *
 		 * @since_tizen 6.5
 		 */
-		~OutputMetadata() = default;
+	~OutputMetadata() = default;
 
-		/** @brief Parses an OutputMetadata
+	/** @brief Parses an OutputMetadata
 		 *
 		 * @since_tizen 6.5
 		 */
-		int Parse(JsonObject *root);
+	int Parse(JsonObject *root);
 
-		bool IsParsed() { return parsed; }
+	bool IsParsed()
+	{
+		return parsed;
+	}
 
-		std::string GetScoreName() { return score.GetName(); }
-		DimInfo GetScoreDimInfo() { return score.GetDimInfo(); }
-		inference_score_type_e GetScoreType() { return score.GetType(); }
-		double GetScoreThreshold() { return score.GetThresHold(); }
-		int GetScoreTopNumber() { return score.GetTopNumber(); }
-		std::shared_ptr<DeQuantization> GetScoreDeQuant() { return score.GetDeQuant(); }
-		double GetScoreDeQuantScale() { return score.GetDeQuantScale(); }
-		double GetScoreDeQuantZeroPoint() { return score.GetDeQuantZeroPoint(); }
-		std::string GetBoxName() { return box.GetName(); }
-		DimInfo GetBoxDimInfo() { return box.GetDimInfo(); }
-		std::vector<int> GetBoxOrder() { return box.GetOrder(); }
-		box::DecodeInfo& GetBoxDecodeInfo() { return box.GetDecodeInfo(); }
-		inference_box_type_e GetBoxType() { return box.GetType(); }
-		std::string GetBoxLabelName() { return box.GetLabelName(); }
-		std::string GetBoxNumberName() { return box.GetNumberName(); }
-		DimInfo GetBoxNumberDimInfo() { return box.GetNumberDimInfo(); }
+	std::string GetScoreName()
+	{
+		return score.GetName();
+	}
+	DimInfo GetScoreDimInfo()
+	{
+		return score.GetDimInfo();
+	}
+	inference_score_type_e GetScoreType()
+	{
+		return score.GetType();
+	}
+	double GetScoreThreshold()
+	{
+		return score.GetThresHold();
+	}
+	int GetScoreTopNumber()
+	{
+		return score.GetTopNumber();
+	}
+	std::shared_ptr<DeQuantization> GetScoreDeQuant()
+	{
+		return score.GetDeQuant();
+	}
+	double GetScoreDeQuantScale()
+	{
+		return score.GetDeQuantScale();
+	}
+	double GetScoreDeQuantZeroPoint()
+	{
+		return score.GetDeQuantZeroPoint();
+	}
+	std::string GetBoxName()
+	{
+		return box.GetName();
+	}
+	DimInfo GetBoxDimInfo()
+	{
+		return box.GetDimInfo();
+	}
+	std::vector<int> GetBoxOrder()
+	{
+		return box.GetOrder();
+	}
+	box::DecodeInfo &GetBoxDecodeInfo()
+	{
+		return box.GetDecodeInfo();
+	}
+	inference_box_type_e GetBoxType()
+	{
+		return box.GetType();
+	}
+	std::string GetBoxLabelName()
+	{
+		return box.GetLabelName();
+	}
+	std::string GetBoxNumberName()
+	{
+		return box.GetNumberName();
+	}
+	DimInfo GetBoxNumberDimInfo()
+	{
+		return box.GetNumberDimInfo();
+	}
 
-		int GetScoreCoordinate() { return box.GetCoordinate(); }
-		std::string GetLandmarkName() { return landmark.GetName(); }
-		int GetLandmarkOffset() { return landmark.GetOffset(); }
-		inference_landmark_type_e GetLandmarkType() { return landmark.GetType(); }
-		DimInfo GetLandmarkDimInfo() { return landmark.GetDimInfo(); }
-		HeatMapInfo& GetLandmarkHeatMapInfo() { return landmark.GetHeatMapInfo(); }
-		inference_landmark_coorindate_type_e GetLandmarkCoordinate() { return landmark.GetCoordinate(); }
-		inference_landmark_decoding_type_e GetLandmarkDecodingType() { return landmark.GetDecodingType(); }
-		std::vector<DispVec>& GetLandmarkDispVecAll() { return landmark.GetDispVecAll(); }
-		std::vector<std::pair<int, int>>& GetLandmarkEdges() { return landmark.GetEdges(); }
-		std::string GetOffsetVecName() { return offsetVec.GetName(); }
-		inference_box_decoding_type_e GetBoxDecodingType() { return box.GetDecodingType(); }
-	};
+	int GetScoreCoordinate()
+	{
+		return box.GetCoordinate();
+	}
+	std::string GetLandmarkName()
+	{
+		return landmark.GetName();
+	}
+	int GetLandmarkOffset()
+	{
+		return landmark.GetOffset();
+	}
+	inference_landmark_type_e GetLandmarkType()
+	{
+		return landmark.GetType();
+	}
+	DimInfo GetLandmarkDimInfo()
+	{
+		return landmark.GetDimInfo();
+	}
+	HeatMapInfo &GetLandmarkHeatMapInfo()
+	{
+		return landmark.GetHeatMapInfo();
+	}
+	inference_landmark_coorindate_type_e GetLandmarkCoordinate()
+	{
+		return landmark.GetCoordinate();
+	}
+	inference_landmark_decoding_type_e GetLandmarkDecodingType()
+	{
+		return landmark.GetDecodingType();
+	}
+	std::vector<DispVec> &GetLandmarkDispVecAll()
+	{
+		return landmark.GetDispVecAll();
+	}
+	std::vector<std::pair<int, int> > &GetLandmarkEdges()
+	{
+		return landmark.GetEdges();
+	}
+	std::string GetOffsetVecName()
+	{
+		return offsetVec.GetName();
+	}
+	inference_box_decoding_type_e GetBoxDecodingType()
+	{
+		return box.GetDecodingType();
+	}
+};
 } /* Inference */
 } /* MediaVision */
 
diff --git a/mv_machine_learning/inference/include/OutputMetadataTypes.h b/mv_machine_learning/inference/include/OutputMetadataTypes.h
index 10fe920..1ce8c9e 100644
--- a/mv_machine_learning/inference/include/OutputMetadataTypes.h
+++ b/mv_machine_learning/inference/include/OutputMetadataTypes.h
@@ -26,57 +26,66 @@ namespace mediavision
 {
 namespace inference
 {
-	// score
-    typedef enum {
-		INFERENCE_SCORE_TYPE_NORMAL,
-		INFERENCE_SCORE_TYPE_SIGMOID
-	} inference_score_type_e;
+// score
+typedef enum
+{
+	INFERENCE_SCORE_TYPE_NORMAL,
+	INFERENCE_SCORE_TYPE_SIGMOID
+} inference_score_type_e;
 
-	// box
-	typedef enum {
-		INFERENCE_BOX_TYPE_ORIGIN_LEFTTOP,
-		INFERENCE_BOX_TYPE_ORIGIN_CENTER
-	} inference_box_type_e;
+// box
+typedef enum
+{
+	INFERENCE_BOX_TYPE_ORIGIN_LEFTTOP,
+	INFERENCE_BOX_TYPE_ORIGIN_CENTER
+} inference_box_type_e;
 
-	typedef enum {
-		INFERENCE_BOX_COORDINATE_TYPE_RATIO,
-		INFERENCE_BOX_COORDINATE_TYPE_PIXEL
-	} inference_box_coordinate_type_e;
+typedef enum
+{
+	INFERENCE_BOX_COORDINATE_TYPE_RATIO,
+	INFERENCE_BOX_COORDINATE_TYPE_PIXEL
+} inference_box_coordinate_type_e;
 
-	typedef enum {
-		INFERENCE_BOX_DECODING_TYPE_BYPASS,
-		INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR,
-		INFERENCE_BOX_DECODING_TYPE_YOLO_ANCHOR
-	} inference_box_decoding_type_e;
+typedef enum
+{
+	INFERENCE_BOX_DECODING_TYPE_BYPASS,
+	INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR,
+	INFERENCE_BOX_DECODING_TYPE_YOLO_ANCHOR
+} inference_box_decoding_type_e;
 
-	typedef enum {
-		INFERENCE_BOX_NMS_TYPE_NONE = -1,
-		INFERENCE_BOX_NMS_TYPE_STANDARD
-	} inference_box_nms_type_e;
+typedef enum
+{
+	INFERENCE_BOX_NMS_TYPE_NONE = -1,
+	INFERENCE_BOX_NMS_TYPE_STANDARD
+} inference_box_nms_type_e;
 
-	// landmark
-	typedef enum {
-		INFERENCE_LANDMARK_TYPE_2D_SINGLE,
-		INFERENCE_LANDMARK_TYPE_2D_MULTI,
-		INFERENCE_LANDMARK_TYPE_3D_SINGLE
-	} inference_landmark_type_e;
+// landmark
+typedef enum
+{
+	INFERENCE_LANDMARK_TYPE_2D_SINGLE,
+	INFERENCE_LANDMARK_TYPE_2D_MULTI,
+	INFERENCE_LANDMARK_TYPE_3D_SINGLE
+} inference_landmark_type_e;
 
-	typedef enum {
-		INFERENCE_LANDMARK_COORDINATE_TYPE_RATIO,
-		INFERENCE_LANDMARK_COORDINATE_TYPE_PIXEL
-	} inference_landmark_coorindate_type_e;
+typedef enum
+{
+	INFERENCE_LANDMARK_COORDINATE_TYPE_RATIO,
+	INFERENCE_LANDMARK_COORDINATE_TYPE_PIXEL
+} inference_landmark_coorindate_type_e;
 
-	typedef enum {
-		INFERENCE_LANDMARK_DECODING_TYPE_BYPASS,
-		INFERENCE_LANDMARK_DECODING_TYPE_BYPASS_MULTICHANNEL,
-		INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP,
-		INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP_REFINE
-	} inference_landmark_decoding_type_e;
+typedef enum
+{
+	INFERENCE_LANDMARK_DECODING_TYPE_BYPASS,
+	INFERENCE_LANDMARK_DECODING_TYPE_BYPASS_MULTICHANNEL,
+	INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP,
+	INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP_REFINE
+} inference_landmark_decoding_type_e;
 
-	typedef enum {
-		INFERENCE_DISPLACEMENT_TYPE_FORWARD,
-		INFERENCE_DISPLACEMENT_TYPE_BACKWARD
-	} inference_displacement_type_e;
+typedef enum
+{
+	INFERENCE_DISPLACEMENT_TYPE_FORWARD,
+	INFERENCE_DISPLACEMENT_TYPE_BACKWARD
+} inference_displacement_type_e;
 }
 }
 
diff --git a/mv_machine_learning/inference/include/PoseDecoder.h b/mv_machine_learning/inference/include/PoseDecoder.h
index 4960d68..22e3fc1 100644
--- a/mv_machine_learning/inference/include/PoseDecoder.h
+++ b/mv_machine_learning/inference/include/PoseDecoder.h
@@ -36,58 +36,56 @@ namespace mediavision
 {
 namespace inference
 {
-	class PoseDecoder
+class PoseDecoder
+{
+private:
+	TensorBuffer mTensorBuffer;
+	OutputMetadata mMeta;
+	int mHeatMapWidth;
+	int mHeatMapHeight;
+	int mHeatMapChannel;
+	int mNumberOfLandmarks;
+
+	std::list<LandmarkPoint> mCandidates;
+	std::vector<LandmarkResults> mPoseLandmarks;
+
+	int getIndexToPos(LandmarkPoint &point, float scaleW, float scaleH);
+	int getPosToIndex(LandmarkPoint &landmark);
+	int getOffsetValue(LandmarkPoint &landmark, cv::Point2f &offsetVal);
+	int findPose(LandmarkPoint &root, std::vector<LandmarkPoint> &decodedLandmarks, float scaleW, float scaleH);
+	int traverseToNeighbor(int edgeId, int toId, inference_displacement_type_e dir, LandmarkPoint fromLandmark,
+						   LandmarkPoint &toLandmark, float scaleW, float scaleH);
+	int getEdgeVector(cv::Point index, int edgeId, inference_displacement_type_e dir, cv::Point2f &vector);
+
+	int convertXYZtoX(int x, int y, int c);
+
+	cv::Point convertXYZtoXY(int x, int y, int c);
+
+public:
+	PoseDecoder(TensorBuffer &buffer, const OutputMetadata &metaData, int heatMapWidth, int heatMapHeight,
+				int heatMapChannel, int numberOfLandmarks)
+			: mTensorBuffer(buffer)
+			, mHeatMapWidth(heatMapWidth)
+			, mHeatMapHeight(heatMapHeight)
+			, mHeatMapChannel(heatMapChannel)
+			, mNumberOfLandmarks(numberOfLandmarks)
 	{
-	private:
-		TensorBuffer mTensorBuffer;
-		OutputMetadata mMeta;
-		int mHeatMapWidth;
-		int mHeatMapHeight;
-		int mHeatMapChannel;
-		int mNumberOfLandmarks;
-
-		std::list<LandmarkPoint> mCandidates;
-		std::vector<LandmarkResults> mPoseLandmarks;
-
-		int getIndexToPos(LandmarkPoint& point, float scaleW, float scaleH);
-		int getPosToIndex(LandmarkPoint& landmark);
-		int getOffsetValue(LandmarkPoint& landmark, cv::Point2f &offsetVal);
-		int findPose(LandmarkPoint& root, std::vector<LandmarkPoint>& decodedLandmarks,
-							float scaleW, float scaleH);
-		int traverseToNeighbor(int edgeId, int toId, inference_displacement_type_e dir,
-								LandmarkPoint fromLandmark, LandmarkPoint& toLandmark,
-								float scaleW, float scaleH);
-		int getEdgeVector(cv::Point index, int edgeId, inference_displacement_type_e dir, cv::Point2f& vector);
-
-		int convertXYZtoX(int x, int y, int c);
-
-		cv::Point convertXYZtoXY(int x, int y, int c);
-
-	public:
-		PoseDecoder(TensorBuffer& buffer, const OutputMetadata& metaData,
-					int heatMapWidth, int heatMapHeight, int heatMapChannel,
-					int numberOfLandmarks) :
-					mTensorBuffer(buffer),
-					mHeatMapWidth(heatMapWidth),
-					mHeatMapHeight(heatMapHeight),
-					mHeatMapChannel(heatMapChannel),
-					mNumberOfLandmarks(numberOfLandmarks) {
-						mMeta = metaData;
-					};
-
-		~PoseDecoder() = default;
-
-		int init();
-
-		int decode(float scaleWidth, float scaleHeight, float thresHoldRadius);
-
-		int getNumberOfPose();
-
-		float getPointX(int poseIdx, int partIdx);
-		float getPointY(int poseIdx, int partIdx);
-		float getScore(int poseIdx, int partIdx);
+		mMeta = metaData;
 	};
 
+	~PoseDecoder() = default;
+
+	int init();
+
+	int decode(float scaleWidth, float scaleHeight, float thresHoldRadius);
+
+	int getNumberOfPose();
+
+	float getPointX(int poseIdx, int partIdx);
+	float getPointY(int poseIdx, int partIdx);
+	float getScore(int poseIdx, int partIdx);
+};
+
 } /* Inference */
 } /* MediaVision */
 
diff --git a/mv_machine_learning/inference/include/PostProcess.h b/mv_machine_learning/inference/include/PostProcess.h
index fbf64be..33fa95d 100644
--- a/mv_machine_learning/inference/include/PostProcess.h
+++ b/mv_machine_learning/inference/include/PostProcess.h
@@ -27,7 +27,6 @@
 #include <opencv2/core.hpp>
 #include <opencv2/imgproc.hpp>
 
-
 /**
  * @file PostProcess.h
  * @brief This file contains the PostProcess class definition which
@@ -39,8 +38,9 @@
  * @details Box structure includes index, score, location.
  *
  */
-typedef struct _Box {
-	int index;   /**< index of box belonging to a category */
+typedef struct _Box
+{
+	int index; /**< index of box belonging to a category */
 	float score; /**< score of box belonging to the index */
 	cv::Rect2f location; /**< location of a box */
 } Box;
@@ -52,45 +52,44 @@ namespace mediavision
 {
 namespace inference
 {
-	class PostProcess
-	{
-	public:
-		/**
+class PostProcess
+{
+public:
+	/**
 		 * @brief   Creates an PostProcess class instance.
 		 *
 		 * @since_tizen 6.5
 		 */
-		PostProcess() : mMaxScoreSize(3) {};
+	PostProcess() : mMaxScoreSize(3) {};
 
-		/**
+	/**
 		 * @brief   Destroys an PostProcess class instance including
 		 *           its all resources.
 		 *
 		 * @since_tizen 6.5
 		 */
-		~PostProcess() = default;
+	~PostProcess() = default;
 
-		/**
+	/**
 		 * @brief   Calculates sigmoid.
 		 *
 		 * @since_tizen 6.5
 		 */
-		static float sigmoid(float value);
-		static float dequant(float value, float scale, float zeropoint);
+	static float sigmoid(float value);
+	static float dequant(float value, float scale, float zeropoint);
 
-		int ScoreClear(int size);
-		int ScorePush(float value, int index);
-		int ScorePop(std::vector<std::pair<float, int>>& top);
-		int Nms(BoxesList& boxeslist, int mode, float threshold, Boxes& nmsboxes);
+	int ScoreClear(int size);
+	int ScorePush(float value, int index);
+	int ScorePop(std::vector<std::pair<float, int> > &top);
+	int Nms(BoxesList &boxeslist, int mode, float threshold, Boxes &nmsboxes);
 
-	private:
-		std::priority_queue<std::pair<float, int>,
-							std::vector<std::pair<float, int>>,
-							std::greater<std::pair<float, int>>> mScore;
-	private:
-		int mMaxScoreSize;
+private:
+	std::priority_queue<std::pair<float, int>, std::vector<std::pair<float, int> >, std::greater<std::pair<float, int> > >
+			mScore;
 
-	};
+private:
+	int mMaxScoreSize;
+};
 
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/include/Posture.h b/mv_machine_learning/inference/include/Posture.h
index 4c67fdc..0359d70 100644
--- a/mv_machine_learning/inference/include/Posture.h
+++ b/mv_machine_learning/inference/include/Posture.h
@@ -37,57 +37,53 @@ namespace mediavision
 {
 namespace inference
 {
-	class Posture
-	{
-	public:
-		/**
+class Posture
+{
+public:
+	/**
 		 * @brief   Creates an Posture class instance.
 		 *
 		 * @since_tizen 6.0
 		 */
-		Posture();
+	Posture();
 
-		/**
+	/**
 		 * @brief   Destroys an Posture class instance including
 		 *           its all resources.
 		 *
 		 * @since_tizen 6.0
 		 */
-		~Posture();
+	~Posture();
 
-		/**
+	/**
 		 * @brief   Sets file path
 		 *
 		 * @since_tizen 6.0
 		 */
-		int setPoseFromFile(const std::string motionCaptureFilePath,
-							const std::string motionMappingFilePath);
+	int setPoseFromFile(const std::string motionCaptureFilePath, const std::string motionMappingFilePath);
 
-		/**
+	/**
 		 * @brief   Compares a pose for @a part and returns score
 		 *
 		 * @since_tizen 6.0
 		 */
-		int compare(int parts, std::vector<std::pair<bool, cv::Point>> action,
-					float* score);
+	int compare(int parts, std::vector<std::pair<bool, cv::Point> > action, float *score);
 
-	private:
-        cv::Vec2f getUnitVectors(cv::Point point1, cv::Point point2);
-		int getParts(int parts,
-					std::vector<std::pair<bool, cv::Point>>& pose,
-					std::vector<std::pair<bool, std::vector<cv::Vec2f>>>& posePart);
-		float getSimilarity(int parts,
-					std::vector<std::pair<bool, std::vector<cv::Vec2f>>>& posePart,
-					std::vector<std::pair<bool, std::vector<cv::Vec2f>>>& actionPart);
-		float cosineSimilarity(std::vector<cv::Vec2f> vec1, std::vector<cv::Vec2f> vec2, int size);
+private:
+	cv::Vec2f getUnitVectors(cv::Point point1, cv::Point point2);
+	int getParts(int parts, std::vector<std::pair<bool, cv::Point> > &pose,
+				 std::vector<std::pair<bool, std::vector<cv::Vec2f> > > &posePart);
+	float getSimilarity(int parts, std::vector<std::pair<bool, std::vector<cv::Vec2f> > > &posePart,
+						std::vector<std::pair<bool, std::vector<cv::Vec2f> > > &actionPart);
+	float cosineSimilarity(std::vector<cv::Vec2f> vec1, std::vector<cv::Vec2f> vec2, int size);
 
-	private:
-        BvhParser mBvhParser;
-        Bvh mBvh;
-		std::map<std::string, int> mMotionToPoseMap; /**< name, index */
-		std::vector<std::pair<bool, cv::Point>> mPose;
-		std::vector<std::pair<bool, std::vector<cv::Vec2f>>> mPoseParts;
-	};
+private:
+	BvhParser mBvhParser;
+	Bvh mBvh;
+	std::map<std::string, int> mMotionToPoseMap; /**< name, index */
+	std::vector<std::pair<bool, cv::Point> > mPose;
+	std::vector<std::pair<bool, std::vector<cv::Vec2f> > > mPoseParts;
+};
 
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/include/PreProcess.h b/mv_machine_learning/inference/include/PreProcess.h
index 4121557..de76926 100644
--- a/mv_machine_learning/inference/include/PreProcess.h
+++ b/mv_machine_learning/inference/include/PreProcess.h
@@ -26,7 +26,6 @@
 #include <opencv2/core.hpp>
 #include <opencv2/imgproc.hpp>
 
-
 /**
  * @file PreProcess.h
  * @brief This file contains the PreProcess class definition which
@@ -37,41 +36,39 @@ namespace mediavision
 {
 namespace inference
 {
-	class PreProcess
-	{
-	public:
-		/**
+class PreProcess
+{
+public:
+	/**
 		 * @brief   Creates an PreProcess class instance.
 		 *
 		 * @since_tizen 6.5
 		 */
-		PreProcess() = default;
+	PreProcess() = default;
 
-		/**
+	/**
 		 * @brief   Destroys an PreProcess class instance including
 		 *           its all resources.
 		 *
 		 * @since_tizen 6.5
 		 */
-		~PreProcess() = default;
+	~PreProcess() = default;
 
-		/**
+	/**
 		 * @brief   Runs PreProcess with layerInfo and options
 		 *
 		 * @since_tizen 6.5
 		 */
-		int Run(cv::Mat& source, const int colorSpace, const int dataType, const LayerInfo& layerInfo,
-				const Options& options, void* buffer);
-
-	private:
-		int Resize(cv::Mat& source, cv::Mat& dest, cv::Size size);
-		int ColorConvert(cv::Mat& source, cv::Mat& dest, int sType, int dType);
-		int Normalize(cv::Mat& source, cv::Mat& dest,
-					const std::vector<double>& mean, const std::vector<double>& std);
-		int Quantize(cv::Mat& source, cv::Mat& dest,
-					const std::vector<double>& scale, const std::vector<double>& zeropoint);
+	int Run(cv::Mat &source, const int colorSpace, const int dataType, const LayerInfo &layerInfo,
+			const Options &options, void *buffer);
 
-	};
+private:
+	int Resize(cv::Mat &source, cv::Mat &dest, cv::Size size);
+	int ColorConvert(cv::Mat &source, cv::Mat &dest, int sType, int dType);
+	int Normalize(cv::Mat &source, cv::Mat &dest, const std::vector<double> &mean, const std::vector<double> &std);
+	int Quantize(cv::Mat &source, cv::Mat &dest, const std::vector<double> &scale,
+				 const std::vector<double> &zeropoint);
+};
 
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/include/ScoreInfo.h b/mv_machine_learning/inference/include/ScoreInfo.h
index 5810324..bf861c0 100644
--- a/mv_machine_learning/inference/include/ScoreInfo.h
+++ b/mv_machine_learning/inference/include/ScoreInfo.h
@@ -113,9 +113,7 @@ public:
 		MEDIA_VISION_NULL_ARG_CHECK(array);
 
 		unsigned int elements1 = json_array_get_length(array);
-		MEDIA_VISION_CHECK_CONDITION(elements1 > 0,
-									 MEDIA_VISION_ERROR_INVALID_PARAMETER,
-									 "No name on meta file");
+		MEDIA_VISION_CHECK_CONDITION(elements1 > 0, MEDIA_VISION_ERROR_INVALID_PARAMETER, "No name on meta file");
 
 		for (unsigned int elem1 = 0; elem1 < elements1; ++elem1) {
 			names.push_back(json_array_get_string_element(array, elem1));
@@ -129,13 +127,11 @@ public:
 				dimInfo.SetValidIndex(elem2);
 		}
 		if (json_object_has_member(pObject, "top_number"))
-			topNumber = static_cast<int>(
-					json_object_get_int_member(pObject, "top_number"));
+			topNumber = static_cast<int>(json_object_get_int_member(pObject, "top_number"));
 		LOGI("top number: %d", topNumber);
 
 		if (json_object_has_member(pObject, "threshold"))
-			threshold = static_cast<double>(
-					json_object_get_double_member(pObject, "threshold"));
+			threshold = static_cast<double>(json_object_get_double_member(pObject, "threshold"));
 		LOGI("threshold: %1.3f", threshold);
 
 		try {
@@ -150,9 +146,8 @@ public:
 			JsonNode *node = json_array_get_element(array, 0);
 			JsonObject *object = json_node_get_object(node);
 
-			deQuantization = std::make_shared<DeQuantization>(
-					json_object_get_double_member(object, "scale"),
-					json_object_get_double_member(object, "zeropoint"));
+			deQuantization = std::make_shared<DeQuantization>(json_object_get_double_member(object, "scale"),
+															  json_object_get_double_member(object, "zeropoint"));
 		}
 
 		LOGI("LEAVE");
diff --git a/mv_machine_learning/inference/include/TensorBuffer.h b/mv_machine_learning/inference/include/TensorBuffer.h
index 2f48d4c..05bbb20 100644
--- a/mv_machine_learning/inference/include/TensorBuffer.h
+++ b/mv_machine_learning/inference/include/TensorBuffer.h
@@ -25,7 +25,6 @@
 #include <inference_engine_type.h>
 #include <mv_inference_type.h>
 
-
 /**
  * @file TensorBuffer.h
  * @brief This file contains the tensor buffer class definition which
@@ -37,32 +36,29 @@ namespace mediavision
 {
 namespace inference
 {
-	class TensorBuffer
-	{
-	private:
-		IETensorBuffer _tensorBuffer;
+class TensorBuffer
+{
+private:
+	IETensorBuffer _tensorBuffer;
 
-	public:
-		TensorBuffer() = default;
-		~TensorBuffer() = default;
+public:
+	TensorBuffer() = default;
+	~TensorBuffer() = default;
 
-		bool empty();
-		bool exist(std::string name);
-		int allocate(inference_engine_tensor_buffer& tensor_buffer,
-					 const inference_engine_tensor_info& tensor_info);
-		void release();
-		size_t size();
+	bool empty();
+	bool exist(std::string name);
+	int allocate(inference_engine_tensor_buffer &tensor_buffer, const inference_engine_tensor_info &tensor_info);
+	void release();
+	size_t size();
 
-		IETensorBuffer& getIETensorBuffer();
-		bool addTensorBuffer(std::string name, inference_engine_tensor_buffer& buffer);
-		int GetTensorInfo(inference_engine_layer_property& layerProperty, tensor_t& tensorInfo);
-		inference_engine_tensor_buffer* getTensorBuffer(std::string name);
-		template <typename T>
-		int convertToFloat(inference_engine_tensor_buffer *tensorBuffer);
+	IETensorBuffer &getIETensorBuffer();
+	bool addTensorBuffer(std::string name, inference_engine_tensor_buffer &buffer);
+	int GetTensorInfo(inference_engine_layer_property &layerProperty, tensor_t &tensorInfo);
+	inference_engine_tensor_buffer *getTensorBuffer(std::string name);
+	template<typename T> int convertToFloat(inference_engine_tensor_buffer *tensorBuffer);
 
-		template <typename T>
-		T getValue(std::string name, int idx);
-	};
+	template<typename T> T getValue(std::string name, int idx);
+};
 } /* Inference */
 } /* MediaVision */
 
diff --git a/mv_machine_learning/inference/include/Utils.h b/mv_machine_learning/inference/include/Utils.h
index d5db2b5..1a15cd5 100644
--- a/mv_machine_learning/inference/include/Utils.h
+++ b/mv_machine_learning/inference/include/Utils.h
@@ -29,18 +29,18 @@ namespace mediavision
 {
 namespace inference
 {
-	template <typename T>
-	T GetSupportedType(JsonObject* root, std::string typeName, const std::map<std::string, T>& supportedTypes)
-	{
-		auto supportedType = supportedTypes.find(json_object_get_string_member(root, typeName.c_str()));
-		if (supportedType == supportedTypes.end()) {
-			throw std::invalid_argument(typeName);
-		}
+template<typename T>
+T GetSupportedType(JsonObject *root, std::string typeName, const std::map<std::string, T> &supportedTypes)
+{
+	auto supportedType = supportedTypes.find(json_object_get_string_member(root, typeName.c_str()));
+	if (supportedType == supportedTypes.end()) {
+		throw std::invalid_argument(typeName);
+	}
 
-		LOGI("%s: %d:%s", typeName.c_str(), supportedType->second, supportedType->first.c_str());
+	LOGI("%s: %d:%s", typeName.c_str(), supportedType->second, supportedType->first.c_str());
 
-		return supportedType->second;
-	}
+	return supportedType->second;
+}
 } /* Inference */
 } /* MediaVision */
 
diff --git a/mv_machine_learning/inference/include/mv_inference_open.h b/mv_machine_learning/inference/include/mv_inference_open.h
index c005bd0..1001a29 100644
--- a/mv_machine_learning/inference/include/mv_inference_open.h
+++ b/mv_machine_learning/inference/include/mv_inference_open.h
@@ -22,22 +22,21 @@
 #include <mv_inference.h>
 
 #ifdef __cplusplus
-extern "C"
-{
+extern "C" {
 #endif /* __cplusplus */
 
-	/**
+/**
 	 * @file   mv_inference_open.h
 	 * @brief  This file contains the Media Vision Inference Open API.
 	 */
 
-	/*************/
-	/* Inference */
-	/*************/
+/*************/
+/* Inference */
+/*************/
 
-	mv_engine_config_h mv_inference_get_engine_config(mv_inference_h infer);
+mv_engine_config_h mv_inference_get_engine_config(mv_inference_h infer);
 
-	/**
+/**
 	 * @brief Create infernce handle.
 	 * @details Use this function to create an inference handle. After creation
 	 *          the inference handle has to be prepared with
@@ -59,9 +58,9 @@ extern "C"
 	 * @see mv_inference_destroy_open()
 	 * @see mv_inference_prepare_open()
 	 */
-	int mv_inference_create_open(mv_inference_h *infer);
+int mv_inference_create_open(mv_inference_h *infer);
 
-	/**
+/**
 	 * @brief Destroy inference handle and releases all its resources.
 	 *
 	 * @since_tizen 5.5
@@ -76,9 +75,9 @@ extern "C"
 	 *
 	 * @see mv_inference_create_open()
 	 */
-	int mv_inference_destroy_open(mv_inference_h infer);
+int mv_inference_destroy_open(mv_inference_h infer);
 
-	/**
+/**
 	 * @brief Configure the backend to the inference handle
 	 *
 	 * @since_tizen 5.5
@@ -97,10 +96,9 @@ extern "C"
 	 * @retval #MEDIA_VISION_ERROR_OUT_OF_MEMORY Out of memory
 	 * @retval #MEDIA_VISION_ERROR_NOT_SUPPORTED Not supported
 	 */
-	int mv_inference_configure_engine_open(mv_inference_h infer,
-										   mv_engine_config_h engine_config);
+int mv_inference_configure_engine_open(mv_inference_h infer, mv_engine_config_h engine_config);
 
-	/**
+/**
 	 * @brief Configure the number of output to the inference handle
 	 *
 	 * @since_tizen 5.5
@@ -120,10 +118,9 @@ extern "C"
 	 * @retval #MEDIA_VISION_ERROR_OUT_OF_MEMORY Out of memory
 	 * @retval #MEDIA_VISION_ERROR_NOT_SUPPORTED Not supported
 	 */
-	int mv_inference_configure_output_open(mv_inference_h infer,
-										   mv_engine_config_h engine_config);
+int mv_inference_configure_output_open(mv_inference_h infer, mv_engine_config_h engine_config);
 
-	/**
+/**
 	 * @brief Configure the confidence threshold value to the inference handle
 	 *
 	 * @since_tizen 5.5
@@ -143,10 +140,9 @@ extern "C"
 	 * @retval #MEDIA_VISION_ERROR_OUT_OF_MEMORY Out of memory
 	 * @retval #MEDIA_VISION_ERROR_NOT_SUPPORTED Not supported
 	 */
-	int mv_inference_configure_confidence_threshold_open(
-			mv_inference_h infer, mv_engine_config_h engine_config);
+int mv_inference_configure_confidence_threshold_open(mv_inference_h infer, mv_engine_config_h engine_config);
 
-	/**
+/**
 	 * @brief Configure the set of output node names to the inference handle
 	 *
 	 * @since_tizen 5.5
@@ -166,10 +162,9 @@ extern "C"
 	 * @retval #MEDIA_VISION_ERROR_OUT_OF_MEMORY Out of memory
 	 * @retval #MEDIA_VISION_ERROR_NOT_SUPPORTED Not supported
 	 */
-	int mv_inference_configure_output_node_names_open(
-			mv_inference_h infer, mv_engine_config_h engine_config);
+int mv_inference_configure_output_node_names_open(mv_inference_h infer, mv_engine_config_h engine_config);
 
-	/**
+/**
 	 * @brief Prepare inference.
 	 * @details Use this function to prepare inference based on
 	 *          the configured network.
@@ -187,9 +182,9 @@ extern "C"
 	 * @retval #MEDIA_VISION_ERROR_INVALID_DATA Invalid model data
 	 * @retval #MEDIA_VISION_ERROR_OUT_OF_MEMORY Out of memory
 	 */
-	int mv_inference_prepare_open(mv_inference_h infer);
+int mv_inference_prepare_open(mv_inference_h infer);
 
-	/**
+/**
 	 * @brief Traverses the list of supported engines for inference.
 	 * @details Using this function the supported engines can be obtained.
 	 *          The names can be used with mv_engine_config_h related
@@ -211,11 +206,10 @@ extern "C"
 	 * @see mv_engine_config_set_string_attribute()
 	 * @see mv_engine_config_get_string_attribute()
 	 */
-	int mv_inference_foreach_supported_engine_open(
-			mv_inference_h infer, mv_inference_supported_engine_cb callback,
-			void *user_data);
+int mv_inference_foreach_supported_engine_open(mv_inference_h infer, mv_inference_supported_engine_cb callback,
+											   void *user_data);
 
-	/**
+/**
 	 * @brief Performs image classification on the @a source
 	 * @details Use this function to launch image classification.
 	 *          Each time when mv_inference_image_classify is
@@ -252,11 +246,10 @@ extern "C"
 	 *
 	 * @see mv_inference_image_classified_cb
 	 */
-	int mv_inference_image_classify_open(
-			mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
-			mv_inference_image_classified_cb classified_cb, void *user_data);
+int mv_inference_image_classify_open(mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
+									 mv_inference_image_classified_cb classified_cb, void *user_data);
 
-	/**
+/**
 	 * @brief Performs object detection on the @a source
 	 * @details Use this function to launch object detection.
 	 *          Each time when mv_inference_object_detection is
@@ -290,12 +283,10 @@ extern "C"
 	 *
 	 * @see mv_inference_object_detected_cb
 	 */
-	int
-	mv_inference_object_detect_open(mv_source_h source, mv_inference_h infer,
-									mv_inference_object_detected_cb detected_cb,
-									void *user_data);
+int mv_inference_object_detect_open(mv_source_h source, mv_inference_h infer,
+									mv_inference_object_detected_cb detected_cb, void *user_data);
 
-	/**
+/**
 	 * @brief Performs face detection on the @a source
 	 * @details Use this function to launch face detection.
 	 *          Each time when mv_inference_face_detection is
@@ -329,11 +320,10 @@ extern "C"
 	 *
 	 * @see mv_inference_face_detected_cb
 	 */
-	int mv_inference_face_detect_open(mv_source_h source, mv_inference_h infer,
-									  mv_inference_face_detected_cb detected_cb,
-									  void *user_data);
+int mv_inference_face_detect_open(mv_source_h source, mv_inference_h infer, mv_inference_face_detected_cb detected_cb,
+								  void *user_data);
 
-	/**
+/**
 	 * @brief Performs facial landmarks detection on the @a source
 	 * @details Use this function to launch facial landmark detection.
 	 *          Each time when mv_inference_facial_landmark_detect() is
@@ -371,12 +361,10 @@ extern "C"
 	 *
 	 * @see mv_inference_facial_landmark_detected_cb
 	 */
-	int mv_inference_facial_landmark_detect_open(
-			mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
-			mv_inference_facial_landmark_detected_cb detected_cb,
-			void *user_data);
+int mv_inference_facial_landmark_detect_open(mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
+											 mv_inference_facial_landmark_detected_cb detected_cb, void *user_data);
 
-	/**
+/**
 	 * @brief Performs pose landmarks detection on the @a source.
 	 * @details Use this function to launch pose landmark detection.
 	 *          Each time when mv_inference_pose_landmark_detect_open() is
@@ -411,12 +399,10 @@ extern "C"
 	 *
 	 * @see mv_inference_pose_landmark_detected_cb()
 	 */
-	int mv_inference_pose_landmark_detect_open(
-			mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
-			mv_inference_pose_landmark_detected_cb detected_cb,
-			void *user_data);
+int mv_inference_pose_landmark_detect_open(mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
+										   mv_inference_pose_landmark_detected_cb detected_cb, void *user_data);
 
-	/**
+/**
 	 * @brief Gets the number of pose.
 	 *
 	 * @since_tizen 6.0
@@ -429,10 +415,9 @@ extern "C"
 	 * @retval #MEDIA_VISION_ERROR_NOT_SUPPORTED Not supported
 	 * @retval #MEDIA_VISION_ERROR_INVALID_PARAMETER Invalid parameter
 	 */
-	int mv_inference_pose_get_number_of_poses_open(
-		mv_inference_pose_result_h result, int *number_of_poses);
+int mv_inference_pose_get_number_of_poses_open(mv_inference_pose_result_h result, int *number_of_poses);
 
-	/**
+/**
 	 * @brief Gets the number of landmark per a pose.
 	 *
 	 * @since_tizen 6.0
@@ -445,10 +430,9 @@ extern "C"
 	 * @retval #MEDIA_VISION_ERROR_NOT_SUPPORTED Not supported
 	 * @retval #MEDIA_VISION_ERROR_INVALID_PARAMETER Invalid parameter
 	 */
-	int mv_inference_pose_get_number_of_landmarks_open(
-		mv_inference_pose_result_h result, int *number_of_landmarks);
+int mv_inference_pose_get_number_of_landmarks_open(mv_inference_pose_result_h result, int *number_of_landmarks);
 
-	/**
+/**
 	 * @brief Gets landmark location of a part of a pose.
 	 *
 	 * @since_tizen 6.0
@@ -465,10 +449,10 @@ extern "C"
 	 * @retval #MEDIA_VISION_ERROR_INVALID_PARAMETER Invalid parameter
 	 *
 	 */
-	int mv_inference_pose_get_landmark_open(
-		mv_inference_pose_result_h result, int pose_index, int part_index, mv_point_s *location, float *score);
+int mv_inference_pose_get_landmark_open(mv_inference_pose_result_h result, int pose_index, int part_index,
+										mv_point_s *location, float *score);
 
-	/**
+/**
 	 * @brief Gets a label of a pose.
 	 *
 	 * @since_tizen 6.0
@@ -489,10 +473,9 @@ extern "C"
 	 * @see mv_inference_pose_landmark_detected_cb()
 	 * @see mv_inference_pose_result_h
 	 */
-	int mv_inference_pose_get_label_open(
-		mv_inference_pose_result_h result, int pose_index, int *label);
+int mv_inference_pose_get_label_open(mv_inference_pose_result_h result, int pose_index, int *label);
 
-	/**
+/**
 	 * @brief Creates pose handle.
 	 * @details Use this function to create a pose.
 	 *
@@ -510,9 +493,9 @@ extern "C"
 	 *
 	 * @see mv_pose_destroy_open()
 	 */
-	int mv_pose_create_open(mv_pose_h *pose);
+int mv_pose_create_open(mv_pose_h *pose);
 
-	/**
+/**
 	 * @brief Destroys pose handle and releases all its resources.
 	 *
 	 * @since_tizen 6.0
@@ -528,9 +511,9 @@ extern "C"
 	 *
 	 * @see mv_pose_create_open()
 	 */
-	int mv_pose_destroy_open(mv_pose_h pose);
+int mv_pose_destroy_open(mv_pose_h pose);
 
-	/**
+/**
 	 * @brief Sets a motion capture file and its pose mapping file to the pose.
 	 * @details Use this function to set a motion capture file and
 	 *          its pose mapping file. These are used by mv_pose_compare_open()
@@ -558,9 +541,9 @@ extern "C"
 	 * @retval #MEDIA_VISION_ERROR_INVALID_PATH Invalid path of file paths
 	 * @retval #MEDIA_VISION_ERROR_INTERNAL Internal error
 	 */
-	int mv_pose_set_from_file_open(mv_pose_h pose, const char *motionCaptureFilePath, const char *motionMappingFilePath);
+int mv_pose_set_from_file_open(mv_pose_h pose, const char *motionCaptureFilePath, const char *motionMappingFilePath);
 
-	/**
+/**
 	 * @brief Compares an action pose with the pose which is set by mv_pose_set_from_file_open().
 	 * @details Use this function to compare action pose with the pose
 	 *          which is set by mv_pose_set_from_file_open().
@@ -582,7 +565,7 @@ extern "C"
 	 *
 	 * @pre Sets the pose by using mv_pose_set_from_file()
 	 */
-	int mv_pose_compare_open(mv_pose_h pose, mv_inference_pose_result_h action, int parts, float *score);
+int mv_pose_compare_open(mv_pose_h pose, mv_inference_pose_result_h action, int parts, float *score);
 
 #ifdef __cplusplus
 }
diff --git a/mv_machine_learning/inference/src/BoxInfo.cpp b/mv_machine_learning/inference/src/BoxInfo.cpp
index 1e57a19..5091db2 100644
--- a/mv_machine_learning/inference/src/BoxInfo.cpp
+++ b/mv_machine_learning/inference/src/BoxInfo.cpp
@@ -44,9 +44,7 @@ int BoxInfo::ParseBox(JsonObject *root)
 	MEDIA_VISION_NULL_ARG_CHECK(array);
 
 	unsigned int elements1 = json_array_get_length(array);
-	MEDIA_VISION_CHECK_CONDITION(elements1 > 0,
-								 MEDIA_VISION_ERROR_INVALID_PARAMETER,
-								 "No name on meta file");
+	MEDIA_VISION_CHECK_CONDITION(elements1 > 0, MEDIA_VISION_ERROR_INVALID_PARAMETER, "No name on meta file");
 
 	for (unsigned int elem1 = 0; elem1 < elements1; ++elem1) {
 		names.push_back(json_array_get_string_element(array, elem1));
@@ -63,10 +61,8 @@ int BoxInfo::ParseBox(JsonObject *root)
 
 	try {
 		type = GetSupportedType(pObject, "box_type", supportedBoxTypes);
-		coordinate = GetSupportedType(pObject, "box_coordinate",
-									  supportedBoxCoordinateTypes);
-		decodingType = GetSupportedType(pObject, "decoding_type",
-										supportedBoxDecodingTypes);
+		coordinate = GetSupportedType(pObject, "box_coordinate", supportedBoxCoordinateTypes);
+		decodingType = GetSupportedType(pObject, "decoding_type", supportedBoxDecodingTypes);
 	} catch (const std::exception &e) {
 		LOGE("Invalid %s", e.what());
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
@@ -77,8 +73,7 @@ int BoxInfo::ParseBox(JsonObject *root)
 	LOGI("box order should have 4 elements and it has [%u]", elements2);
 
 	for (unsigned int elem2_idx = 0; elem2_idx < elements2; ++elem2_idx) {
-		auto val =
-				static_cast<int>(json_array_get_int_element(array, elem2_idx));
+		auto val = static_cast<int>(json_array_get_int_element(array, elem2_idx));
 		order.push_back(val);
 		LOGI("%d", val);
 	}
@@ -177,8 +172,7 @@ int BoxInfo::ParseDecodeInfo(JsonObject *root)
 	}
 
 	int ret = MEDIA_VISION_ERROR_NONE;
-	JsonObject *cObject =
-			json_object_get_object_member(pObject, "decoding_info");
+	JsonObject *cObject = json_object_get_object_member(pObject, "decoding_info");
 	if (json_object_has_member(cObject, "anchor")) {
 		ret = GetDecodeInfo().ParseAnchorParam(cObject);
 		if (ret != MEDIA_VISION_ERROR_NONE) {
diff --git a/mv_machine_learning/inference/src/Bvh.cpp b/mv_machine_learning/inference/src/Bvh.cpp
index 1322eac..6e56276 100644
--- a/mv_machine_learning/inference/src/Bvh.cpp
+++ b/mv_machine_learning/inference/src/Bvh.cpp
@@ -14,7 +14,6 @@
  * limitations under the License.
  */
 
-
 #include "Bvh.h"
 #include "BvhUtils.h"
 #include "mv_private.h"
@@ -24,73 +23,71 @@ namespace mediavision
 {
 namespace inference
 {
-
-  void Bvh::recalculate_joints_ltm(std::shared_ptr<Joint> start_joint) {
-
-    LOGI("ENTER");
-
-    if (start_joint == NULL)
-    {
-      if (root_joint_ == NULL)
-        return;
-      else
-        start_joint = root_joint_;
-    }
-
-    LOGD("%s joint", start_joint->name().c_str());
-    //LOG(DEBUG) << "recalculate_joints_ltm: " << start_joint->name();
-    cv::Mat offmat_backup = cv::Mat::eye(4,4, CV_32F);
-    offmat_backup.at<float>(0,3) = start_joint->offset().x;
-    offmat_backup.at<float>(1,3) = start_joint->offset().y;
-    offmat_backup.at<float>(2,3) = start_joint->offset().z;
-
-    std::vector<std::vector<float>> data = start_joint->channel_data();
-
-    for (unsigned i = 0; i < num_frames_; i++) {
-      cv::Mat offmat = offmat_backup; // offset matrix
-      cv::Mat rmat = cv::Mat::eye(4,4,CV_32F);  // identity matrix set on rotation matrix
-      cv::Mat tmat = cv::Mat::eye(4,4,CV_32F);  // identity matrix set on translation matrix
-
-      for (size_t j = 0;  j < start_joint->channels_order().size(); j++) {
-        if (start_joint->channels_order()[j] == Joint::Channel::XPOSITION)
-          tmat.at<float>(0,3) = data[i][j];
-        else if (start_joint->channels_order()[j] == Joint::Channel::YPOSITION)
-          tmat.at<float>(1,3) = data[i][j];
-        else if (start_joint->channels_order()[j] == Joint::Channel::ZPOSITION)
-          tmat.at<float>(2,3) = data[i][j];
-        else if (start_joint->channels_order()[j] == Joint::Channel::XROTATION)
-          rmat = rotate(rmat, data[i][j], Axis::X);
-        else if (start_joint->channels_order()[j] == Joint::Channel::YROTATION)
-          rmat = rotate(rmat, data[i][j], Axis::Y);
-        else if (start_joint->channels_order()[j] == Joint::Channel::ZROTATION)
-          rmat = rotate(rmat, data[i][j], Axis::Z);
-      }
-
-      cv::Mat ltm = cv::Mat::eye(4,4,CV_32F); // local transformation matrix
-
-      if (start_joint->parent() != NULL)
-        ltm = start_joint->parent()->ltm(i) * offmat;
-      else
-        ltm = tmat * offmat;
-
-      cv::Vec3f wPos(ltm.at<float>(0,3),ltm.at<float>(1,3), ltm.at<float>(2,3));
-      start_joint->set_pos(wPos);
-      //LOG(TRACE) << "Joint world position: " << utils::vec3tos(ltm[3]);
-      LOGD("Joint world position: %f, %f, %f", wPos[0], wPos[1], wPos[2]);
-
-      ltm = ltm * rmat;
-
-      //LOG(TRACE) << "Local transformation matrix: \n" << utils::mat4tos(ltm);
-
-      start_joint->set_ltm(ltm, i);
-    } // num frame
-
-    for (auto& child : start_joint->children()) {
-      recalculate_joints_ltm(child);
-    }
-
-    LOGI("LEAVE");
-  } // recalculate_joints_ltm
-
-}  // end of bvh
+void Bvh::recalculate_joints_ltm(std::shared_ptr<Joint> start_joint)
+{
+	LOGI("ENTER");
+
+	if (start_joint == NULL) {
+		if (root_joint_ == NULL)
+			return;
+		else
+			start_joint = root_joint_;
+	}
+
+	LOGD("%s joint", start_joint->name().c_str());
+	//LOG(DEBUG) << "recalculate_joints_ltm: " << start_joint->name();
+	cv::Mat offmat_backup = cv::Mat::eye(4, 4, CV_32F);
+	offmat_backup.at<float>(0, 3) = start_joint->offset().x;
+	offmat_backup.at<float>(1, 3) = start_joint->offset().y;
+	offmat_backup.at<float>(2, 3) = start_joint->offset().z;
+
+	std::vector<std::vector<float> > data = start_joint->channel_data();
+
+	for (unsigned i = 0; i < num_frames_; i++) {
+		cv::Mat offmat = offmat_backup; // offset matrix
+		cv::Mat rmat = cv::Mat::eye(4, 4, CV_32F); // identity matrix set on rotation matrix
+		cv::Mat tmat = cv::Mat::eye(4, 4, CV_32F); // identity matrix set on translation matrix
+
+		for (size_t j = 0; j < start_joint->channels_order().size(); j++) {
+			if (start_joint->channels_order()[j] == Joint::Channel::XPOSITION)
+				tmat.at<float>(0, 3) = data[i][j];
+			else if (start_joint->channels_order()[j] == Joint::Channel::YPOSITION)
+				tmat.at<float>(1, 3) = data[i][j];
+			else if (start_joint->channels_order()[j] == Joint::Channel::ZPOSITION)
+				tmat.at<float>(2, 3) = data[i][j];
+			else if (start_joint->channels_order()[j] == Joint::Channel::XROTATION)
+				rmat = rotate(rmat, data[i][j], Axis::X);
+			else if (start_joint->channels_order()[j] == Joint::Channel::YROTATION)
+				rmat = rotate(rmat, data[i][j], Axis::Y);
+			else if (start_joint->channels_order()[j] == Joint::Channel::ZROTATION)
+				rmat = rotate(rmat, data[i][j], Axis::Z);
+		}
+
+		cv::Mat ltm = cv::Mat::eye(4, 4, CV_32F); // local transformation matrix
+
+		if (start_joint->parent() != NULL)
+			ltm = start_joint->parent()->ltm(i) * offmat;
+		else
+			ltm = tmat * offmat;
+
+		cv::Vec3f wPos(ltm.at<float>(0, 3), ltm.at<float>(1, 3), ltm.at<float>(2, 3));
+		start_joint->set_pos(wPos);
+		//LOG(TRACE) << "Joint world position: " << utils::vec3tos(ltm[3]);
+		LOGD("Joint world position: %f, %f, %f", wPos[0], wPos[1], wPos[2]);
+
+		ltm = ltm * rmat;
+
+		//LOG(TRACE) << "Local transformation matrix: \n" << utils::mat4tos(ltm);
+
+		start_joint->set_ltm(ltm, i);
+	} // num frame
+
+	for (auto &child : start_joint->children()) {
+		recalculate_joints_ltm(child);
+	}
+
+	LOGI("LEAVE");
+} // recalculate_joints_ltm
+
+} // end of bvh
 }
diff --git a/mv_machine_learning/inference/src/BvhParser.cpp b/mv_machine_learning/inference/src/BvhParser.cpp
index 66c040b..317c529 100644
--- a/mv_machine_learning/inference/src/BvhParser.cpp
+++ b/mv_machine_learning/inference/src/BvhParser.cpp
@@ -27,8 +27,8 @@
   */
 #define MULTI_HIERARCHY 0
 
-namespace {
-
+namespace
+{
 const std::string kChannels = "CHANNELS";
 const std::string kEnd = "End";
 const std::string kEndSite = "End Site";
@@ -53,345 +53,344 @@ namespace mediavision
 {
 namespace inference
 {
+//##############################################################################
+// Main parse function
+//##############################################################################
+int BvhParser::parse(const std::string &path, Bvh *bvh)
+{
+	LOGI("ENTER");
+	//LOG(INFO) << "Parsing file : " << path;
+
+	path_ = path;
+	bvh_ = bvh;
+
+	std::ifstream file;
+	file.open(path_);
+
+	if (file.is_open()) {
+		std::string token;
+
+#if MULTI_HIERARCHY == 1
+		while (file.good()) {
+#endif
+			file >> token;
+			if (token == kHierarchy) {
+				int ret = parse_hierarchy(file);
+				if (ret)
+					return ret;
+			} else {
+				//LOG(ERROR) << "Bad structure of .bvh file. " << kHierarchy
+				//          << " should be on the top of the file";
+				return -1;
+			}
+#if MULTI_HIERARCHY == 1
+		}
+#endif
+	} else {
+		//LOG(ERROR) << "Cannot open file to parse : " << path_;
+		return -1;
+	}
+
+	LOGI("LEAVE");
+	return 0;
+}
+
+//##############################################################################
+// Function parsing hierarchy
+//##############################################################################
+int BvhParser::parse_hierarchy(std::ifstream &file)
+{
+	//LOG(INFO) << "Parsing hierarchy";
+
+	std::string token;
+	int ret;
+
+	if (file.good()) {
+		file >> token;
+
+		//##########################################################################
+		// Parsing joints
+		//##########################################################################
+		if (token == kRoot) {
+			std::shared_ptr<Joint> rootJoint;
+			ret = parse_joint(file, nullptr, rootJoint);
+
+			if (ret)
+				return ret;
+
+			LOGI("There is %d data channels", bvh_->num_channels());
+
+			bvh_->set_root_joint(rootJoint);
+		} else {
+			LOGE("Bad structure of .bvh file.");
+
+			return -1;
+		}
+	}
+
+	if (file.good()) {
+		file >> token;
+
+		//##########################################################################
+		// Parsing motion data
+		//##########################################################################
+		if (token == kMotion) {
+			ret = parse_motion(file);
+
+			if (ret)
+				return ret;
+		} else {
+			LOGE("Bad structure of .bvh file.");
+
+			return -1;
+		}
+	}
+	return 0;
+}
+
+//##############################################################################
+// Function parsing joint
+//##############################################################################
+int BvhParser::parse_joint(std::ifstream &file, std::shared_ptr<Joint> parent, std::shared_ptr<Joint> &parsed)
+{
+	//LOG(TRACE) << "Parsing joint";
+
+	std::shared_ptr<Joint> joint = std::make_shared<Joint>();
+	joint->set_parent(parent);
+
+	std::string name;
+	file >> name;
 
-  //##############################################################################
-  // Main parse function
-  //##############################################################################
-  int BvhParser::parse(const std::string& path, Bvh* bvh) {
-    LOGI("ENTER");
-    //LOG(INFO) << "Parsing file : " << path;
-
-    path_ = path;
-    bvh_ = bvh;
-
-    std::ifstream file;
-    file.open(path_);
-
-    if (file.is_open()) {
-      std::string token;
-
-  #if MULTI_HIERARCHY == 1
-      while (file.good()) {
-  #endif
-        file >> token;
-        if (token == kHierarchy) {
-          int ret = parse_hierarchy(file);
-          if (ret)
-            return ret;
-        } else {
-          //LOG(ERROR) << "Bad structure of .bvh file. " << kHierarchy
-          //          << " should be on the top of the file";
-          return -1;
-        }
-  #if MULTI_HIERARCHY == 1
-      }
-  #endif
-    } else {
-      //LOG(ERROR) << "Cannot open file to parse : " << path_;
-      return -1;
-    }
-
-    LOGI("LEAVE");
-    return 0;
-  }
-
-  //##############################################################################
-  // Function parsing hierarchy
-  //##############################################################################
-  int BvhParser::parse_hierarchy(std::ifstream& file) {
-    //LOG(INFO) << "Parsing hierarchy";
-
-    std::string token;
-    int ret;
-
-    if (file.good()) {
-      file >> token;
-
-      //##########################################################################
-      // Parsing joints
-      //##########################################################################
-      if (token == kRoot) {
-        std::shared_ptr <Joint> rootJoint;
-        ret = parse_joint(file, nullptr, rootJoint);
-
-        if (ret)
-          return ret;
-
-        LOGI("There is %d data channels", bvh_->num_channels());
-
-        bvh_->set_root_joint(rootJoint);
-      } else {
-        LOGE("Bad structure of .bvh file.");
-
-        return -1;
-      }
-    }
-
-    if (file.good()) {
-      file >> token;
-
-      //##########################################################################
-      // Parsing motion data
-      //##########################################################################
-      if (token == kMotion) {
-        ret = parse_motion(file);
-
-        if (ret)
-          return ret;
-      } else {
-        LOGE("Bad structure of .bvh file.");
-
-        return -1;
-      }
-    }
-    return 0;
-  }
-
-  //##############################################################################
-  // Function parsing joint
-  //##############################################################################
-  int BvhParser::parse_joint(std::ifstream& file,
-      std::shared_ptr <Joint> parent, std::shared_ptr <Joint>& parsed) {
-
-    //LOG(TRACE) << "Parsing joint";
-
-    std::shared_ptr<Joint> joint = std::make_shared<Joint>();
-    joint->set_parent(parent);
-
-    std::string name;
-    file >> name;
-
-    LOGD("Joint name %s", name.c_str());
-
-    joint->set_name(name);
-
-    std::string token;
-    std::vector <std::shared_ptr <Joint>> children;
-    int ret;
-
-    file >> token;  // Consuming '{'
-    file >> token;
-
-    //############################################################################
-    // Offset parsing
-    //############################################################################
-    if (token == kOffset) {
-      Joint::Offset offset;
-
-      try {
-        file >> offset.x >> offset.y >> offset.z;
-      } catch (const std::ios_base::failure& e) {
-        //LOG(ERROR) << "Failure while parsing offset";
-        return -1;
-      }
+	LOGD("Joint name %s", name.c_str());
 
-      joint->set_offset(offset);
+	joint->set_name(name);
 
-      //LOG(TRACE) << "Offset x: " << offset.x << ", y: " << offset.y << ", z: "
-      //          << offset.z;
+	std::string token;
+	std::vector<std::shared_ptr<Joint> > children;
+	int ret;
 
-    } else {
-      //LOG(ERROR) << "Bad structure of .bvh file. Expected " << kOffset << ", but "
-      //          << "found \"" << token << "\"";
+	file >> token; // Consuming '{'
+	file >> token;
 
-      return -1;
-    }
+	//############################################################################
+	// Offset parsing
+	//############################################################################
+	if (token == kOffset) {
+		Joint::Offset offset;
 
-    file >> token;
+		try {
+			file >> offset.x >> offset.y >> offset.z;
+		} catch (const std::ios_base::failure &e) {
+			//LOG(ERROR) << "Failure while parsing offset";
+			return -1;
+		}
 
-    //############################################################################
-    // Channels parsing
-    //############################################################################
-    if (token == kChannels) {
-      ret = parse_channel_order(file, joint);
+		joint->set_offset(offset);
 
-      //LOG(TRACE) << "Joint has " << joint->num_channels() << " data channels";
+		//LOG(TRACE) << "Offset x: " << offset.x << ", y: " << offset.y << ", z: "
+		//          << offset.z;
 
-      if (ret)
-        return ret;
-    } else {
-      //LOG(ERROR) << "Bad structure of .bvh file. Expected " << kChannels
-      //           << ", but found \"" << token << "\"";
+	} else {
+		//LOG(ERROR) << "Bad structure of .bvh file. Expected " << kOffset << ", but "
+		//          << "found \"" << token << "\"";
 
-      return -1;
-    }
+		return -1;
+	}
 
-    file >> token;
+	file >> token;
 
-    bvh_->add_joint(joint);
+	//############################################################################
+	// Channels parsing
+	//############################################################################
+	if (token == kChannels) {
+		ret = parse_channel_order(file, joint);
 
-    //############################################################################
-    // Children parsing
-    //############################################################################
+		//LOG(TRACE) << "Joint has " << joint->num_channels() << " data channels";
 
-    while (file.good()) {
-      //##########################################################################
-      // Child joint parsing
-      //##########################################################################
-      if (token == kJoint) {
-        std::shared_ptr <Joint> child;
-        ret = parse_joint(file, joint, child);
+		if (ret)
+			return ret;
+	} else {
+		//LOG(ERROR) << "Bad structure of .bvh file. Expected " << kChannels
+		//           << ", but found \"" << token << "\"";
 
-        if (ret)
-          return ret;
+		return -1;
+	}
 
-        children.push_back(child);
+	file >> token;
 
-      //##########################################################################
-      // Child joint parsing
-      //##########################################################################
-      } else if (token == kEnd) {
-        file >> token >> token;  // Consuming "Site {"
-
-        std::shared_ptr <Joint> tmp_joint = std::make_shared <Joint> ();
-
-        tmp_joint->set_parent(joint);
-        tmp_joint->set_name(kEndSite);
-        children.push_back(tmp_joint);
+	bvh_->add_joint(joint);
 
-        file >> token;
+	//############################################################################
+	// Children parsing
+	//############################################################################
 
-        //########################################################################
-        // End site offset parsing
-        //########################################################################
-        if (token == kOffset) {
-          Joint::Offset offset;
+	while (file.good()) {
+		//##########################################################################
+		// Child joint parsing
+		//##########################################################################
+		if (token == kJoint) {
+			std::shared_ptr<Joint> child;
+			ret = parse_joint(file, joint, child);
 
-          try {
-            file >> offset.x >> offset.y >> offset.z;
-          } catch (const std::ios_base::failure& e) {
-            //LOG(ERROR) << "Failure while parsing offset";
-            return -1;
-          }
-
-          tmp_joint->set_offset(offset);
-
-          // LOG(TRACE) << "Joint name : EndSite";
-          // LOG(TRACE) << "Offset x: " << offset.x << ", y: " << offset.y << ", z: "
-          //           << offset.z;
-
-          file >> token;  // Consuming "}"
-
-        } else {
-          //LOG(ERROR) << "Bad structure of .bvh file. Expected " << kOffset
-          //           << ", but found \"" << token << "\"";
-
-          return -1;
-        }
-
-        bvh_->add_joint(tmp_joint);
-      //##########################################################################
-      // End joint parsing
-      //##########################################################################
-      } else if (token == "}") {
-        joint->set_children(children);
-        parsed = joint;
-        return 0;
-      }
-
-      file >> token;
-    }
-
-    //LOG(ERROR) << "Cannot parse joint, unexpected end of file. Last token : "
-    //           << token;
-    return -1;
-  }
-
-  //##############################################################################
-  // Motion data parse function
-  //##############################################################################
-  int BvhParser::parse_motion(std::ifstream& file) {
-
-    LOGI("ENTER");
-
-    std::string token;
-    file >> token;
-
-    int frames_num;
-
-    if (token == kFrames) {
-      file >> frames_num;
-      bvh_->set_num_frames(frames_num);
-      LOGD("Num of frames: %d", frames_num);
-    } else {
-      LOGE("Bad structure of .bvh file");
-
-      return -1;
-    }
-
-    file >> token;
-
-    double frame_time;
-
-    if (token == kFrame) {
-      file >> token;  // Consuming 'Time:'
-      file >> frame_time;
-      bvh_->set_frame_time(frame_time);
-      LOGD("Frame time: %f",frame_time);
-
-      float number;
-      for (int i = 0; i < frames_num; i++) {
-        for (auto joint : bvh_->joints()) {
-          std::vector <float> data;
-          for (unsigned j = 0; j < joint->num_channels(); j++) {
-            file >> number;
-            data.push_back(number);
-          }
-          LOGD("%s joint", joint->name().c_str());
-          joint->add_frame_motion_data(data);
-        }
-      }
-    } else {
-      LOGE("Bad structure of .bvh file.");
-      return -1;
-    }
-
-    LOGI("LEAVE");
-
-    return 0;
-  }
-
-  //##############################################################################
-  // Channels order parse function
-  //##############################################################################
-  int BvhParser::parse_channel_order(std::ifstream& file,
-      std::shared_ptr <Joint> joint) {
-
-    LOGI("ENTER");
-
-    int num;
-    file >> num;
-    LOGD("Number of channels: %d",num);
-
-    std::vector <Joint::Channel> channels;
-    std::string token;
-
-    for (int i = 0; i < num; i++) {
-      file >> token;
-      if (token == kXpos)
-        channels.push_back(Joint::Channel::XPOSITION);
-      else if (token == kYpos)
-        channels.push_back(Joint::Channel::YPOSITION);
-      else if (token == kZpos)
-        channels.push_back(Joint::Channel::ZPOSITION);
-      else if (token == kXrot)
-        channels.push_back(Joint::Channel::XROTATION);
-      else if (token == kYrot)
-        channels.push_back(Joint::Channel::YROTATION);
-      else if (token == kZrot)
-        channels.push_back(Joint::Channel::ZROTATION);
-      else {
-        //LOG(ERROR) << "Not valid channel!";
-        return -1;
-      }
-    }
-
-    joint->set_channels_order(channels);
-
-    LOGI("LEAVE");
-
-    return 0;
-  }
+			if (ret)
+				return ret;
+
+			children.push_back(child);
+
+			//##########################################################################
+			// Child joint parsing
+			//##########################################################################
+		} else if (token == kEnd) {
+			file >> token >> token; // Consuming "Site {"
+
+			std::shared_ptr<Joint> tmp_joint = std::make_shared<Joint>();
+
+			tmp_joint->set_parent(joint);
+			tmp_joint->set_name(kEndSite);
+			children.push_back(tmp_joint);
+
+			file >> token;
+
+			//########################################################################
+			// End site offset parsing
+			//########################################################################
+			if (token == kOffset) {
+				Joint::Offset offset;
+
+				try {
+					file >> offset.x >> offset.y >> offset.z;
+				} catch (const std::ios_base::failure &e) {
+					//LOG(ERROR) << "Failure while parsing offset";
+					return -1;
+				}
+
+				tmp_joint->set_offset(offset);
+
+				// LOG(TRACE) << "Joint name : EndSite";
+				// LOG(TRACE) << "Offset x: " << offset.x << ", y: " << offset.y << ", z: "
+				//           << offset.z;
+
+				file >> token; // Consuming "}"
+
+			} else {
+				//LOG(ERROR) << "Bad structure of .bvh file. Expected " << kOffset
+				//           << ", but found \"" << token << "\"";
+
+				return -1;
+			}
+
+			bvh_->add_joint(tmp_joint);
+			//##########################################################################
+			// End joint parsing
+			//##########################################################################
+		} else if (token == "}") {
+			joint->set_children(children);
+			parsed = joint;
+			return 0;
+		}
+
+		file >> token;
+	}
+
+	//LOG(ERROR) << "Cannot parse joint, unexpected end of file. Last token : "
+	//           << token;
+	return -1;
+}
+
+//##############################################################################
+// Motion data parse function
+//##############################################################################
+int BvhParser::parse_motion(std::ifstream &file)
+{
+	LOGI("ENTER");
+
+	std::string token;
+	file >> token;
+
+	int frames_num;
+
+	if (token == kFrames) {
+		file >> frames_num;
+		bvh_->set_num_frames(frames_num);
+		LOGD("Num of frames: %d", frames_num);
+	} else {
+		LOGE("Bad structure of .bvh file");
+
+		return -1;
+	}
+
+	file >> token;
+
+	double frame_time;
+
+	if (token == kFrame) {
+		file >> token; // Consuming 'Time:'
+		file >> frame_time;
+		bvh_->set_frame_time(frame_time);
+		LOGD("Frame time: %f", frame_time);
+
+		float number;
+		for (int i = 0; i < frames_num; i++) {
+			for (auto joint : bvh_->joints()) {
+				std::vector<float> data;
+				for (unsigned j = 0; j < joint->num_channels(); j++) {
+					file >> number;
+					data.push_back(number);
+				}
+				LOGD("%s joint", joint->name().c_str());
+				joint->add_frame_motion_data(data);
+			}
+		}
+	} else {
+		LOGE("Bad structure of .bvh file.");
+		return -1;
+	}
+
+	LOGI("LEAVE");
+
+	return 0;
+}
+
+//##############################################################################
+// Channels order parse function
+//##############################################################################
+int BvhParser::parse_channel_order(std::ifstream &file, std::shared_ptr<Joint> joint)
+{
+	LOGI("ENTER");
+
+	int num;
+	file >> num;
+	LOGD("Number of channels: %d", num);
+
+	std::vector<Joint::Channel> channels;
+	std::string token;
+
+	for (int i = 0; i < num; i++) {
+		file >> token;
+		if (token == kXpos)
+			channels.push_back(Joint::Channel::XPOSITION);
+		else if (token == kYpos)
+			channels.push_back(Joint::Channel::YPOSITION);
+		else if (token == kZpos)
+			channels.push_back(Joint::Channel::ZPOSITION);
+		else if (token == kXrot)
+			channels.push_back(Joint::Channel::XROTATION);
+		else if (token == kYrot)
+			channels.push_back(Joint::Channel::YROTATION);
+		else if (token == kZrot)
+			channels.push_back(Joint::Channel::ZROTATION);
+		else {
+			//LOG(ERROR) << "Not valid channel!";
+			return -1;
+		}
+	}
+
+	joint->set_channels_order(channels);
+
+	LOGI("LEAVE");
+
+	return 0;
+}
 
 }
 } // namespace
diff --git a/mv_machine_learning/inference/src/BvhUtils.cpp b/mv_machine_learning/inference/src/BvhUtils.cpp
index ba11a91..181c46e 100644
--- a/mv_machine_learning/inference/src/BvhUtils.cpp
+++ b/mv_machine_learning/inference/src/BvhUtils.cpp
@@ -17,56 +17,57 @@
 #include "BvhUtils.h"
 #include <cmath>
 
-#define DegreeToRadian(degree) ((degree) * (M_PI/180.f))
+#define DegreeToRadian(degree) ((degree) * (M_PI / 180.f))
 
 namespace mediavision
 {
 namespace inference
 {
-  cv::Mat rotation_matrix(float angle, Axis axis) {
-    cv::Mat matrix = cv::Mat::eye(4,4,CV_32F);
+cv::Mat rotation_matrix(float angle, Axis axis)
+{
+	cv::Mat matrix = cv::Mat::eye(4, 4, CV_32F);
 
-    float rangle = DegreeToRadian(angle);
+	float rangle = DegreeToRadian(angle);
 
-    // We want to unique situation when in matrix are -0.0f, so we perform
-    // additional checking
-    float sin_a = sin(rangle);
-    if (fabs(sin_a) < std::numeric_limits<float>::epsilon())
-      sin_a = 0.0f;
-    float cos_a = cos(rangle);
-    if (fabs(cos_a) < std::numeric_limits<float>::epsilon())
-      cos_a = 0.0f;
-    float msin_a = fabs(sin_a) < std::numeric_limits<float>::epsilon() ?
-        0.0f : (-1.0f) * sin_a;
+	// We want to unique situation when in matrix are -0.0f, so we perform
+	// additional checking
+	float sin_a = sin(rangle);
+	if (fabs(sin_a) < std::numeric_limits<float>::epsilon())
+		sin_a = 0.0f;
+	float cos_a = cos(rangle);
+	if (fabs(cos_a) < std::numeric_limits<float>::epsilon())
+		cos_a = 0.0f;
+	float msin_a = fabs(sin_a) < std::numeric_limits<float>::epsilon() ? 0.0f : (-1.0f) * sin_a;
 
-    if (axis == Axis::X) {
-        matrix.at<float>(1,1) = cos_a;
-        matrix.at<float>(2,1) = sin_a;
-        matrix.at<float>(1,2) = msin_a;
-        matrix.at<float>(2,2) = cos_a;
-    } else if (axis == Axis::Y) {
-      matrix.at<float>(0,0) = cos_a;
-      matrix.at<float>(2,0) = msin_a;
-      matrix.at<float>(0,2) = sin_a;
-      matrix.at<float>(2,2) = cos_a;
-    } else {
-      matrix.at<float>(0,0) = cos_a;
-      matrix.at<float>(1,0) = sin_a;
-      matrix.at<float>(0,1) = msin_a;
-      matrix.at<float>(1,1) = cos_a;
-    }
+	if (axis == Axis::X) {
+		matrix.at<float>(1, 1) = cos_a;
+		matrix.at<float>(2, 1) = sin_a;
+		matrix.at<float>(1, 2) = msin_a;
+		matrix.at<float>(2, 2) = cos_a;
+	} else if (axis == Axis::Y) {
+		matrix.at<float>(0, 0) = cos_a;
+		matrix.at<float>(2, 0) = msin_a;
+		matrix.at<float>(0, 2) = sin_a;
+		matrix.at<float>(2, 2) = cos_a;
+	} else {
+		matrix.at<float>(0, 0) = cos_a;
+		matrix.at<float>(1, 0) = sin_a;
+		matrix.at<float>(0, 1) = msin_a;
+		matrix.at<float>(1, 1) = cos_a;
+	}
 
-    return matrix;
-  }
+	return matrix;
+}
 
-  /** Rotates matrix
+/** Rotates matrix
    *  @param  matrix  The matrix to be rotated
    *  @param  angle   The rotation angle
    *  @param  axis    The rotation axis
    *  @return  The rotation matrix
    */
-  cv::Mat rotate(cv::Mat matrix, float angle, Axis axis) {
-    return matrix * rotation_matrix(angle, axis);
-  }
+cv::Mat rotate(cv::Mat matrix, float angle, Axis axis)
+{
+	return matrix * rotation_matrix(angle, axis);
+}
 }
 }
\ No newline at end of file
diff --git a/mv_machine_learning/inference/src/Inference.cpp b/mv_machine_learning/inference/src/Inference.cpp
old mode 100755
new mode 100644
index 6a5a6ca..150c3d5
--- a/mv_machine_learning/inference/src/Inference.cpp
+++ b/mv_machine_learning/inference/src/Inference.cpp
@@ -34,7 +34,8 @@
 #define MV_INFERENCE_CONFIDENCE_THRESHOLD_MAX 1.0
 #define MV_INFERENCE_CONFIDENCE_THRESHOLD_MIN 0.0
 
-typedef enum {
+typedef enum
+{
 	InputAttrNoType = 0,
 	InputAttrFloat32 = 1,
 	InputAttrInt32 = 2,
@@ -50,1649 +51,1615 @@ namespace mediavision
 {
 namespace inference
 {
-	InferenceConfig::InferenceConfig() :
-			mConfigFilePath(),
-			mWeightFilePath(),
-			mUserFilePath(),
-			mDataType(MV_INFERENCE_DATA_FLOAT32),
-			mTargetTypes(MV_INFERENCE_TARGET_DEVICE_CPU),
-			mConfidenceThresHold(),
-			mMeanValue(),
-			mStdValue(),
-			mMaxOutputNumbers(1)
-	{
-		mTensorInfo.width = -1;
-		mTensorInfo.height = -1;
-		mTensorInfo.dim = -1;
-		mTensorInfo.ch = -1;
-	}
-
-	Inference::Inference() :
-			mCanRun(),
-			mConfig(),
-			mBackendCapacity(),
-			mSupportedInferenceBackend(),
-			mInputSize(cv::Size()),
-			mSourceSize(cv::Size()),
-			engine_config(),
-			mBackend(),
-			mMetadata(),
-			mPreProc()
-	{
-		LOGI("ENTER");
-
-		// Mediavision can support several inference engines via ML Single API
-		// "mlapi" means that the inference backend is used via ML Single API.
-		mSupportedInferenceBackend.insert(std::make_pair(
-				MV_INFERENCE_BACKEND_OPENCV, std::make_pair("opencv", false)));
-		mSupportedInferenceBackend.insert(std::make_pair(
-				MV_INFERENCE_BACKEND_TFLITE, std::make_pair("tflite", false)));
-		mSupportedInferenceBackend.insert(std::make_pair(
-				MV_INFERENCE_BACKEND_ARMNN, std::make_pair("armnn", false)));
-		mSupportedInferenceBackend.insert(std::make_pair(
-				MV_INFERENCE_BACKEND_MLAPI, std::make_pair("mlapi", false)));
-		mSupportedInferenceBackend.insert(std::make_pair(
-				MV_INFERENCE_BACKEND_ONE, std::make_pair("mlapi", false)));
-		mSupportedInferenceBackend.insert(std::make_pair(
-				MV_INFERENCE_BACKEND_NNTRAINER, std::make_pair("mlapi", false)));
-		mSupportedInferenceBackend.insert(std::make_pair(
-				MV_INFERENCE_BACKEND_SNPE, std::make_pair("mlapi", false)));
-
-		CheckSupportedInferenceBackend();
-
-		for (auto& backend : mSupportedInferenceBackend) {
-			LOGI("%s: %s", backend.second.first.c_str(),
-				 backend.second.second ? "TRUE" : "FALSE");
-		}
+InferenceConfig::InferenceConfig()
+		: mConfigFilePath()
+		, mWeightFilePath()
+		, mUserFilePath()
+		, mDataType(MV_INFERENCE_DATA_FLOAT32)
+		, mTargetTypes(MV_INFERENCE_TARGET_DEVICE_CPU)
+		, mConfidenceThresHold()
+		, mMeanValue()
+		, mStdValue()
+		, mMaxOutputNumbers(1)
+{
+	mTensorInfo.width = -1;
+	mTensorInfo.height = -1;
+	mTensorInfo.dim = -1;
+	mTensorInfo.ch = -1;
+}
+
+Inference::Inference()
+		: mCanRun()
+		, mConfig()
+		, mBackendCapacity()
+		, mSupportedInferenceBackend()
+		, mInputSize(cv::Size())
+		, mSourceSize(cv::Size())
+		, engine_config()
+		, mBackend()
+		, mMetadata()
+		, mPreProc()
+{
+	LOGI("ENTER");
+
+	// Mediavision can support several inference engines via ML Single API
+	// "mlapi" means that the inference backend is used via ML Single API.
+	mSupportedInferenceBackend.insert(std::make_pair(MV_INFERENCE_BACKEND_OPENCV, std::make_pair("opencv", false)));
+	mSupportedInferenceBackend.insert(std::make_pair(MV_INFERENCE_BACKEND_TFLITE, std::make_pair("tflite", false)));
+	mSupportedInferenceBackend.insert(std::make_pair(MV_INFERENCE_BACKEND_ARMNN, std::make_pair("armnn", false)));
+	mSupportedInferenceBackend.insert(std::make_pair(MV_INFERENCE_BACKEND_MLAPI, std::make_pair("mlapi", false)));
+	mSupportedInferenceBackend.insert(std::make_pair(MV_INFERENCE_BACKEND_ONE, std::make_pair("mlapi", false)));
+	mSupportedInferenceBackend.insert(std::make_pair(MV_INFERENCE_BACKEND_NNTRAINER, std::make_pair("mlapi", false)));
+	mSupportedInferenceBackend.insert(std::make_pair(MV_INFERENCE_BACKEND_SNPE, std::make_pair("mlapi", false)));
+
+	CheckSupportedInferenceBackend();
+
+	for (auto &backend : mSupportedInferenceBackend) {
+		LOGI("%s: %s", backend.second.first.c_str(), backend.second.second ? "TRUE" : "FALSE");
+	}
 
-		mModelFormats.insert(std::make_pair<std::string, int>(
-				"caffemodel", INFERENCE_MODEL_CAFFE));
-		mModelFormats.insert(
-				std::make_pair<std::string, int>("pb", INFERENCE_MODEL_TF));
-		mModelFormats.insert(std::make_pair<std::string, int>(
-				"tflite", INFERENCE_MODEL_TFLITE));
-		mModelFormats.insert(
-				std::make_pair<std::string, int>("t7", INFERENCE_MODEL_TORCH));
-		mModelFormats.insert(std::make_pair<std::string, int>(
-				"weights", INFERENCE_MODEL_DARKNET));
-		mModelFormats.insert(
-				std::make_pair<std::string, int>("bin", INFERENCE_MODEL_DLDT));
-		mModelFormats.insert(
-				std::make_pair<std::string, int>("onnx", INFERENCE_MODEL_ONNX));
-		mModelFormats.insert(std::make_pair<std::string, int>(
-				"nb", INFERENCE_MODEL_VIVANTE));
-		mModelFormats.insert(std::make_pair<std::string, int>(
-				"ini", INFERENCE_MODEL_NNTRAINER));
-		mModelFormats.insert(std::make_pair<std::string, int>(
-				"dlc", INFERENCE_MODEL_SNPE));
-
-		LOGI("LEAVE");
-	}
-
-	Inference::~Inference()
-	{
-		CleanupTensorBuffers();
-
-		if (!mInputLayerProperty.layers.empty()) {
-			mInputLayerProperty.layers.clear();
-			std::map<std::string, inference_engine_tensor_info>().swap(
-					mInputLayerProperty.layers);
-		}
-		if (!mOutputLayerProperty.layers.empty()) {
-			mOutputLayerProperty.layers.clear();
-			std::map<std::string, inference_engine_tensor_info>().swap(
-					mOutputLayerProperty.layers);
-		}
+	mModelFormats.insert(std::make_pair<std::string, int>("caffemodel", INFERENCE_MODEL_CAFFE));
+	mModelFormats.insert(std::make_pair<std::string, int>("pb", INFERENCE_MODEL_TF));
+	mModelFormats.insert(std::make_pair<std::string, int>("tflite", INFERENCE_MODEL_TFLITE));
+	mModelFormats.insert(std::make_pair<std::string, int>("t7", INFERENCE_MODEL_TORCH));
+	mModelFormats.insert(std::make_pair<std::string, int>("weights", INFERENCE_MODEL_DARKNET));
+	mModelFormats.insert(std::make_pair<std::string, int>("bin", INFERENCE_MODEL_DLDT));
+	mModelFormats.insert(std::make_pair<std::string, int>("onnx", INFERENCE_MODEL_ONNX));
+	mModelFormats.insert(std::make_pair<std::string, int>("nb", INFERENCE_MODEL_VIVANTE));
+	mModelFormats.insert(std::make_pair<std::string, int>("ini", INFERENCE_MODEL_NNTRAINER));
+	mModelFormats.insert(std::make_pair<std::string, int>("dlc", INFERENCE_MODEL_SNPE));
+
+	LOGI("LEAVE");
+}
+
+Inference::~Inference()
+{
+	CleanupTensorBuffers();
 
-		mModelFormats.clear();
+	if (!mInputLayerProperty.layers.empty()) {
+		mInputLayerProperty.layers.clear();
+		std::map<std::string, inference_engine_tensor_info>().swap(mInputLayerProperty.layers);
+	}
+	if (!mOutputLayerProperty.layers.empty()) {
+		mOutputLayerProperty.layers.clear();
+		std::map<std::string, inference_engine_tensor_info>().swap(mOutputLayerProperty.layers);
+	}
 
-		// Release backend engine.
-		if (mBackend) {
-			mBackend->UnbindBackend();
-			delete mBackend;
-		}
+	mModelFormats.clear();
 
-		LOGI("Released backend engine.");
+	// Release backend engine.
+	if (mBackend) {
+		mBackend->UnbindBackend();
+		delete mBackend;
 	}
 
-	void Inference::CheckSupportedInferenceBackend()
-	{
-		LOGI("ENTER");
+	LOGI("Released backend engine.");
+}
 
-		InferenceInI ini;
-		ini.LoadInI();
+void Inference::CheckSupportedInferenceBackend()
+{
+	LOGI("ENTER");
 
-		std::vector<int> supportedBackend = ini.GetSupportedInferenceEngines();
-		for (auto& backend : supportedBackend) {
-			LOGI("engine: %d", backend);
+	InferenceInI ini;
+	ini.LoadInI();
 
-			mSupportedInferenceBackend[backend].second = true;
-		}
+	std::vector<int> supportedBackend = ini.GetSupportedInferenceEngines();
+	for (auto &backend : supportedBackend) {
+		LOGI("engine: %d", backend);
 
-		LOGI("LEAVE");
+		mSupportedInferenceBackend[backend].second = true;
 	}
 
-	int Inference::ConvertEngineErrorToVisionError(int error)
-	{
-		int ret = MEDIA_VISION_ERROR_NONE;
+	LOGI("LEAVE");
+}
 
-		switch (error) {
-		case INFERENCE_ENGINE_ERROR_NONE:
-			ret = MEDIA_VISION_ERROR_NONE;
-			break;
-		case INFERENCE_ENGINE_ERROR_NOT_SUPPORTED:
-			ret = MEDIA_VISION_ERROR_NOT_SUPPORTED;
-			break;
-		case INFERENCE_ENGINE_ERROR_MSG_TOO_LONG:
-			ret = MEDIA_VISION_ERROR_MSG_TOO_LONG;
-			break;
-		case INFERENCE_ENGINE_ERROR_NO_DATA:
-			ret = MEDIA_VISION_ERROR_NO_DATA;
-			break;
-		case INFERENCE_ENGINE_ERROR_KEY_NOT_AVAILABLE:
-			ret = MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE;
-			break;
-		case INFERENCE_ENGINE_ERROR_OUT_OF_MEMORY:
-			ret = MEDIA_VISION_ERROR_OUT_OF_MEMORY;
-			break;
-		case INFERENCE_ENGINE_ERROR_INVALID_PARAMETER:
-			ret = MEDIA_VISION_ERROR_INVALID_PARAMETER;
-			break;
-		case INFERENCE_ENGINE_ERROR_INVALID_OPERATION:
-			ret = MEDIA_VISION_ERROR_INVALID_OPERATION;
-			break;
-		case INFERENCE_ENGINE_ERROR_PERMISSION_DENIED:
-			ret = MEDIA_VISION_ERROR_PERMISSION_DENIED;
-			break;
-		case INFERENCE_ENGINE_ERROR_NOT_SUPPORTED_FORMAT:
-			ret = MEDIA_VISION_ERROR_NOT_SUPPORTED_FORMAT;
-			break;
-		case INFERENCE_ENGINE_ERROR_INTERNAL:
-			ret = MEDIA_VISION_ERROR_INTERNAL;
-			break;
-		case INFERENCE_ENGINE_ERROR_INVALID_DATA:
-			ret = MEDIA_VISION_ERROR_INVALID_DATA;
-			break;
-		case INFERENCE_ENGINE_ERROR_INVALID_PATH:
-			ret = MEDIA_VISION_ERROR_INVALID_PATH;
-			break;
-		default:
-			LOGE("Unknown inference engine error type");
-		}
+int Inference::ConvertEngineErrorToVisionError(int error)
+{
+	int ret = MEDIA_VISION_ERROR_NONE;
 
-		return ret;
+	switch (error) {
+	case INFERENCE_ENGINE_ERROR_NONE:
+		ret = MEDIA_VISION_ERROR_NONE;
+		break;
+	case INFERENCE_ENGINE_ERROR_NOT_SUPPORTED:
+		ret = MEDIA_VISION_ERROR_NOT_SUPPORTED;
+		break;
+	case INFERENCE_ENGINE_ERROR_MSG_TOO_LONG:
+		ret = MEDIA_VISION_ERROR_MSG_TOO_LONG;
+		break;
+	case INFERENCE_ENGINE_ERROR_NO_DATA:
+		ret = MEDIA_VISION_ERROR_NO_DATA;
+		break;
+	case INFERENCE_ENGINE_ERROR_KEY_NOT_AVAILABLE:
+		ret = MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE;
+		break;
+	case INFERENCE_ENGINE_ERROR_OUT_OF_MEMORY:
+		ret = MEDIA_VISION_ERROR_OUT_OF_MEMORY;
+		break;
+	case INFERENCE_ENGINE_ERROR_INVALID_PARAMETER:
+		ret = MEDIA_VISION_ERROR_INVALID_PARAMETER;
+		break;
+	case INFERENCE_ENGINE_ERROR_INVALID_OPERATION:
+		ret = MEDIA_VISION_ERROR_INVALID_OPERATION;
+		break;
+	case INFERENCE_ENGINE_ERROR_PERMISSION_DENIED:
+		ret = MEDIA_VISION_ERROR_PERMISSION_DENIED;
+		break;
+	case INFERENCE_ENGINE_ERROR_NOT_SUPPORTED_FORMAT:
+		ret = MEDIA_VISION_ERROR_NOT_SUPPORTED_FORMAT;
+		break;
+	case INFERENCE_ENGINE_ERROR_INTERNAL:
+		ret = MEDIA_VISION_ERROR_INTERNAL;
+		break;
+	case INFERENCE_ENGINE_ERROR_INVALID_DATA:
+		ret = MEDIA_VISION_ERROR_INVALID_DATA;
+		break;
+	case INFERENCE_ENGINE_ERROR_INVALID_PATH:
+		ret = MEDIA_VISION_ERROR_INVALID_PATH;
+		break;
+	default:
+		LOGE("Unknown inference engine error type");
 	}
 
-	int Inference::ConvertTargetTypes(int given_types)
-	{
-		int target_types = INFERENCE_TARGET_NONE;
-
-		if (given_types & MV_INFERENCE_TARGET_DEVICE_CPU)
-			target_types |= INFERENCE_TARGET_CPU;
-		if (given_types & MV_INFERENCE_TARGET_DEVICE_GPU)
-			target_types |= INFERENCE_TARGET_GPU;
-		if (given_types & MV_INFERENCE_TARGET_DEVICE_CUSTOM)
-			target_types |= INFERENCE_TARGET_CUSTOM;
+	return ret;
+}
 
-		return target_types;
-	}
+int Inference::ConvertTargetTypes(int given_types)
+{
+	int target_types = INFERENCE_TARGET_NONE;
 
-	int Inference::ConvertToCv(int given_type)
-	{
-		int type = 0;
-		const int ch = mConfig.mTensorInfo.ch;
+	if (given_types & MV_INFERENCE_TARGET_DEVICE_CPU)
+		target_types |= INFERENCE_TARGET_CPU;
+	if (given_types & MV_INFERENCE_TARGET_DEVICE_GPU)
+		target_types |= INFERENCE_TARGET_GPU;
+	if (given_types & MV_INFERENCE_TARGET_DEVICE_CUSTOM)
+		target_types |= INFERENCE_TARGET_CUSTOM;
 
-		switch (given_type) {
-		case INFERENCE_TENSOR_DATA_TYPE_UINT8:
-			LOGI("Type is %d ch with UINT8", ch);
-			type = ch == 1 ? CV_8UC1 : CV_8UC3;
-			break;
-		case INFERENCE_TENSOR_DATA_TYPE_FLOAT32:
-			LOGI("Type is %d ch with FLOAT32", ch);
-			type = ch == 1 ? CV_32FC1 : CV_32FC3;
-			break;
-		default:
-			LOGI("unknown data type so FLOAT32 data type will be used in default");
-			type = ch == 1 ? CV_32FC1 : CV_32FC3;
-			break;
-		}
+	return target_types;
+}
 
-		return type;
+int Inference::ConvertToCv(int given_type)
+{
+	int type = 0;
+	const int ch = mConfig.mTensorInfo.ch;
+
+	switch (given_type) {
+	case INFERENCE_TENSOR_DATA_TYPE_UINT8:
+		LOGI("Type is %d ch with UINT8", ch);
+		type = ch == 1 ? CV_8UC1 : CV_8UC3;
+		break;
+	case INFERENCE_TENSOR_DATA_TYPE_FLOAT32:
+		LOGI("Type is %d ch with FLOAT32", ch);
+		type = ch == 1 ? CV_32FC1 : CV_32FC3;
+		break;
+	default:
+		LOGI("unknown data type so FLOAT32 data type will be used in default");
+		type = ch == 1 ? CV_32FC1 : CV_32FC3;
+		break;
 	}
 
-	inference_tensor_data_type_e Inference::ConvertToIE(int given_type)
-	{
-		inference_tensor_data_type_e type = INFERENCE_TENSOR_DATA_TYPE_FLOAT32;
+	return type;
+}
 
-		switch (given_type) {
-		case MV_INFERENCE_DATA_FLOAT32:
-			type = INFERENCE_TENSOR_DATA_TYPE_FLOAT32;
-			break;
-		case MV_INFERENCE_DATA_UINT8:
-			type = INFERENCE_TENSOR_DATA_TYPE_UINT8;
-			break;
-		default:
-			LOGI("unknown data type so FLOAT32 data type will be used in default");
-			break;
-		}
-
-		return type;
+inference_tensor_data_type_e Inference::ConvertToIE(int given_type)
+{
+	inference_tensor_data_type_e type = INFERENCE_TENSOR_DATA_TYPE_FLOAT32;
+
+	switch (given_type) {
+	case MV_INFERENCE_DATA_FLOAT32:
+		type = INFERENCE_TENSOR_DATA_TYPE_FLOAT32;
+		break;
+	case MV_INFERENCE_DATA_UINT8:
+		type = INFERENCE_TENSOR_DATA_TYPE_UINT8;
+		break;
+	default:
+		LOGI("unknown data type so FLOAT32 data type will be used in default");
+		break;
 	}
 
-	int Inference::SetUserFile(std::string filename)
-	{
-		std::ifstream fp(filename.c_str());
-		if (!fp.is_open()) {
-			return MEDIA_VISION_ERROR_INVALID_PATH;
-		}
-
-		std::string userListName;
-		while (!fp.eof()) {
-			std::getline(fp, userListName);
-			if (userListName.length())
-				mUserListName.push_back(userListName);
-		}
-
-		fp.close();
+	return type;
+}
 
-		return MEDIA_VISION_ERROR_NONE;
+int Inference::SetUserFile(std::string filename)
+{
+	std::ifstream fp(filename.c_str());
+	if (!fp.is_open()) {
+		return MEDIA_VISION_ERROR_INVALID_PATH;
 	}
 
-	void Inference::ConfigureModelFiles(const std::string modelConfigFilePath,
-										const std::string modelWeightFilePath,
-										const std::string modelUserFilePath)
-	{
-		LOGI("ENTER");
+	std::string userListName;
+	while (!fp.eof()) {
+		std::getline(fp, userListName);
+		if (userListName.length())
+			mUserListName.push_back(userListName);
+	}
 
-		mConfig.mConfigFilePath = modelConfigFilePath;
-		mConfig.mWeightFilePath = modelWeightFilePath;
-		mConfig.mUserFilePath = modelUserFilePath;
+	fp.close();
 
-		LOGI("LEAVE");
-	}
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-	void Inference::ConfigureInputInfo(int width, int height, int dim, int ch,
-									   double stdValue, double meanValue,
-									   int dataType,
-									   const std::vector<std::string> names)
-	{
-		LOGI("ENTER");
+void Inference::ConfigureModelFiles(const std::string modelConfigFilePath, const std::string modelWeightFilePath,
+									const std::string modelUserFilePath)
+{
+	LOGI("ENTER");
 
-		// FIXME: mConfig should be removed
-		mConfig.mTensorInfo = { width, height, dim, ch };
-		mConfig.mStdValue = stdValue;
-		mConfig.mMeanValue = meanValue;
-		mConfig.mDataType = static_cast<mv_inference_data_type_e>(dataType);
-		mConfig.mInputLayerNames = names;
+	mConfig.mConfigFilePath = modelConfigFilePath;
+	mConfig.mWeightFilePath = modelWeightFilePath;
+	mConfig.mUserFilePath = modelUserFilePath;
 
-		if (mMetadata.GetInputMeta().IsParsed()) {
-			LOGI("use input meta");
-			auto& layerInfo = mMetadata.GetInputMeta().GetLayer().begin()->second;
-			if (layerInfo.shapeType == INFERENCE_TENSOR_SHAPE_NCHW) { // NCHW
-				mConfig.mTensorInfo.ch = layerInfo.dims[1];
-				mConfig.mTensorInfo.dim = layerInfo.dims[0];
-				mConfig.mTensorInfo.width = layerInfo.dims[3];
-				mConfig.mTensorInfo.height = layerInfo.dims[2];
-			} else if (layerInfo.shapeType == INFERENCE_TENSOR_SHAPE_NHWC) {// NHWC
-				mConfig.mTensorInfo.ch = layerInfo.dims[3];
-				mConfig.mTensorInfo.dim = layerInfo.dims[0];
-				mConfig.mTensorInfo.width = layerInfo.dims[2];
-				mConfig.mTensorInfo.height = layerInfo.dims[1];
-			} else {
-				LOGE("Invalid shape type[%d]", layerInfo.shapeType);
-			}
+	LOGI("LEAVE");
+}
 
-			if (!mMetadata.GetInputMeta().GetOption().empty()) {
-				auto& option = mMetadata.GetInputMeta().GetOption().begin()->second;
-				if (option.normalization.use) {
-					mConfig.mMeanValue = option.normalization.mean[0];
-					mConfig.mStdValue = option.normalization.std[0];
-				}
-			}
+void Inference::ConfigureInputInfo(int width, int height, int dim, int ch, double stdValue, double meanValue,
+								   int dataType, const std::vector<std::string> names)
+{
+	LOGI("ENTER");
+
+	// FIXME: mConfig should be removed
+	mConfig.mTensorInfo = { width, height, dim, ch };
+	mConfig.mStdValue = stdValue;
+	mConfig.mMeanValue = meanValue;
+	mConfig.mDataType = static_cast<mv_inference_data_type_e>(dataType);
+	mConfig.mInputLayerNames = names;
+
+	if (mMetadata.GetInputMeta().IsParsed()) {
+		LOGI("use input meta");
+		auto &layerInfo = mMetadata.GetInputMeta().GetLayer().begin()->second;
+		if (layerInfo.shapeType == INFERENCE_TENSOR_SHAPE_NCHW) { // NCHW
+			mConfig.mTensorInfo.ch = layerInfo.dims[1];
+			mConfig.mTensorInfo.dim = layerInfo.dims[0];
+			mConfig.mTensorInfo.width = layerInfo.dims[3];
+			mConfig.mTensorInfo.height = layerInfo.dims[2];
+		} else if (layerInfo.shapeType == INFERENCE_TENSOR_SHAPE_NHWC) { // NHWC
+			mConfig.mTensorInfo.ch = layerInfo.dims[3];
+			mConfig.mTensorInfo.dim = layerInfo.dims[0];
+			mConfig.mTensorInfo.width = layerInfo.dims[2];
+			mConfig.mTensorInfo.height = layerInfo.dims[1];
+		} else {
+			LOGE("Invalid shape type[%d]", layerInfo.shapeType);
+		}
 
-			mConfig.mDataType = layerInfo.dataType;
-			mConfig.mInputLayerNames.clear();
-			for (auto& layer : mMetadata.GetInputMeta().GetLayer()) {
-				mConfig.mInputLayerNames.push_back(layer.first);
+		if (!mMetadata.GetInputMeta().GetOption().empty()) {
+			auto &option = mMetadata.GetInputMeta().GetOption().begin()->second;
+			if (option.normalization.use) {
+				mConfig.mMeanValue = option.normalization.mean[0];
+				mConfig.mStdValue = option.normalization.std[0];
 			}
 		}
 
-		mInputSize = cv::Size(mConfig.mTensorInfo.width, mConfig.mTensorInfo.height);
-
-		inference_engine_layer_property property;
-		// In case of that a inference plugin deosn't support to get properties,
-		// the tensor info given by a user will be used.
-		// If the plugin supports that, the given info will be ignored.
+		mConfig.mDataType = layerInfo.dataType;
+		mConfig.mInputLayerNames.clear();
+		for (auto &layer : mMetadata.GetInputMeta().GetLayer()) {
+			mConfig.mInputLayerNames.push_back(layer.first);
+		}
+	}
 
-		for (auto& name : mConfig.mInputLayerNames) {
-			inference_engine_tensor_info tensor_info;
-			tensor_info.data_type = ConvertToIE(mConfig.mDataType);
+	mInputSize = cv::Size(mConfig.mTensorInfo.width, mConfig.mTensorInfo.height);
 
-			// In case of OpenCV, only supports NCHW
-			tensor_info.shape_type = INFERENCE_TENSOR_SHAPE_NCHW;
-			// modify to handle multiple tensor infos
-			tensor_info.shape.push_back(mConfig.mTensorInfo.dim);
-			tensor_info.shape.push_back(mConfig.mTensorInfo.ch);
-			tensor_info.shape.push_back(mConfig.mTensorInfo.height);
-			tensor_info.shape.push_back(mConfig.mTensorInfo.width);
+	inference_engine_layer_property property;
+	// In case of that a inference plugin deosn't support to get properties,
+	// the tensor info given by a user will be used.
+	// If the plugin supports that, the given info will be ignored.
 
-			tensor_info.size = 1;
-			for (auto& dim : tensor_info.shape) {
-				tensor_info.size *= dim;
-			}
+	for (auto &name : mConfig.mInputLayerNames) {
+		inference_engine_tensor_info tensor_info;
+		tensor_info.data_type = ConvertToIE(mConfig.mDataType);
 
-			property.layers.insert(std::make_pair(name, tensor_info));
-		}
+		// In case of OpenCV, only supports NCHW
+		tensor_info.shape_type = INFERENCE_TENSOR_SHAPE_NCHW;
+		// modify to handle multiple tensor infos
+		tensor_info.shape.push_back(mConfig.mTensorInfo.dim);
+		tensor_info.shape.push_back(mConfig.mTensorInfo.ch);
+		tensor_info.shape.push_back(mConfig.mTensorInfo.height);
+		tensor_info.shape.push_back(mConfig.mTensorInfo.width);
 
-		int ret = mBackend->SetInputLayerProperty(property);
-		if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-			LOGE("Fail to set input layer property");
+		tensor_info.size = 1;
+		for (auto &dim : tensor_info.shape) {
+			tensor_info.size *= dim;
 		}
 
-		LOGI("InputSize is %d x %d\n", mInputSize.width, mInputSize.height);
-		LOGI("mean %.4f, deviation %.4f", mConfig.mMeanValue,  mConfig.mStdValue);
-		LOGI("outputNumber %d", mConfig.mMaxOutputNumbers);
+		property.layers.insert(std::make_pair(name, tensor_info));
+	}
 
-		LOGI("LEAVE");
+	int ret = mBackend->SetInputLayerProperty(property);
+	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
+		LOGE("Fail to set input layer property");
 	}
 
-	void Inference::ConfigureOutputInfo(const std::vector<std::string> names,
-										std::vector<inference_engine_tensor_info>& tensors_info)
-	{
-		LOGI("ENTER");
+	LOGI("InputSize is %d x %d\n", mInputSize.width, mInputSize.height);
+	LOGI("mean %.4f, deviation %.4f", mConfig.mMeanValue, mConfig.mStdValue);
+	LOGI("outputNumber %d", mConfig.mMaxOutputNumbers);
 
-		mConfig.mOutputLayerNames = names;
+	LOGI("LEAVE");
+}
 
-		OutputMetadata& outputMeta = mMetadata.GetOutputMeta();
-		if (mMetadata.GetOutputMeta().IsParsed()) {
-			mConfig.mOutputLayerNames.clear();
-			if (!outputMeta.GetScoreName().empty())
-				mConfig.mOutputLayerNames.push_back(outputMeta.GetScoreName());
+void Inference::ConfigureOutputInfo(const std::vector<std::string> names,
+									std::vector<inference_engine_tensor_info> &tensors_info)
+{
+	LOGI("ENTER");
 
-			if (!outputMeta.GetBoxName().empty())
-				mConfig.mOutputLayerNames.push_back(outputMeta.GetBoxName());
+	mConfig.mOutputLayerNames = names;
 
-			if (!outputMeta.GetBoxLabelName().empty())
-				mConfig.mOutputLayerNames.push_back(outputMeta.GetBoxLabelName());
+	OutputMetadata &outputMeta = mMetadata.GetOutputMeta();
+	if (mMetadata.GetOutputMeta().IsParsed()) {
+		mConfig.mOutputLayerNames.clear();
+		if (!outputMeta.GetScoreName().empty())
+			mConfig.mOutputLayerNames.push_back(outputMeta.GetScoreName());
 
-			if (!outputMeta.GetBoxNumberName().empty())
-				mConfig.mOutputLayerNames.push_back(outputMeta.GetBoxNumberName());
+		if (!outputMeta.GetBoxName().empty())
+			mConfig.mOutputLayerNames.push_back(outputMeta.GetBoxName());
 
-			if (!outputMeta.GetLandmarkName().empty())
-				mConfig.mOutputLayerNames.push_back(outputMeta.GetLandmarkName());
+		if (!outputMeta.GetBoxLabelName().empty())
+			mConfig.mOutputLayerNames.push_back(outputMeta.GetBoxLabelName());
 
-			if (!outputMeta.GetOffsetVecName().empty())
-				mConfig.mOutputLayerNames.push_back(outputMeta.GetOffsetVecName());
+		if (!outputMeta.GetBoxNumberName().empty())
+			mConfig.mOutputLayerNames.push_back(outputMeta.GetBoxNumberName());
 
-			for (auto& dispVec : outputMeta.GetLandmarkDispVecAll()) {
-				mConfig.mOutputLayerNames.push_back(dispVec.GetName());
-			}
-		}
-
-		inference_engine_layer_property property;
+		if (!outputMeta.GetLandmarkName().empty())
+			mConfig.mOutputLayerNames.push_back(outputMeta.GetLandmarkName());
 
-		if (tensors_info.empty()) {
-			inference_engine_tensor_info tensor_info = { std::vector<size_t>{1},
-								INFERENCE_TENSOR_SHAPE_NCHW,
-								INFERENCE_TENSOR_DATA_TYPE_FLOAT32,
-								1};
+		if (!outputMeta.GetOffsetVecName().empty())
+			mConfig.mOutputLayerNames.push_back(outputMeta.GetOffsetVecName());
 
-			for (auto& name : mConfig.mOutputLayerNames) {
-				LOGI("Configure %s layer as output", name.c_str());
-				property.layers.insert(std::make_pair(name, tensor_info));
-			}
-		} else {
-			if (mConfig.mOutputLayerNames.size() != tensors_info.size()) {
-				LOGE("Output layer count is different from tensor info count.");
-				return;
-			}
-
-			for (size_t idx = 0; idx < mConfig.mOutputLayerNames.size(); ++idx) {
-				LOGI("Configure %s layer as output", mConfig.mOutputLayerNames[idx].c_str());
-				property.layers.insert(std::make_pair(mConfig.mOutputLayerNames[idx], tensors_info[idx]));
-			}
+		for (auto &dispVec : outputMeta.GetLandmarkDispVecAll()) {
+			mConfig.mOutputLayerNames.push_back(dispVec.GetName());
 		}
+	}
 
-		int ret = mBackend->SetOutputLayerProperty(property);
-		if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-			LOGE("Fail to set output layer property");
-		}
+	inference_engine_layer_property property;
 
-		LOGI("LEAVE");
-	}
+	if (tensors_info.empty()) {
+		inference_engine_tensor_info tensor_info = { std::vector<size_t> { 1 }, INFERENCE_TENSOR_SHAPE_NCHW,
+													 INFERENCE_TENSOR_DATA_TYPE_FLOAT32, 1 };
 
-	int Inference::CheckBackendType(const mv_inference_backend_type_e backendType)
-	{
-		// Check if a given backend type is valid or not.
-		if (backendType <= MV_INFERENCE_BACKEND_NONE ||
-				backendType >= MV_INFERENCE_BACKEND_MAX) {
-			LOGE("Invalid backend type.");
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+		for (auto &name : mConfig.mOutputLayerNames) {
+			LOGI("Configure %s layer as output", name.c_str());
+			property.layers.insert(std::make_pair(name, tensor_info));
 		}
-
-		std::pair<std::string, bool> backend =
-				mSupportedInferenceBackend[backendType];
-		if (backend.second == false) {
-			LOGE("%s type is not supported", (backend.first).c_str());
-			return MEDIA_VISION_ERROR_NOT_SUPPORTED;
+	} else {
+		if (mConfig.mOutputLayerNames.size() != tensors_info.size()) {
+			LOGE("Output layer count is different from tensor info count.");
+			return;
 		}
 
-		LOGI("backend engine : %d", backendType);
-
-		return MEDIA_VISION_ERROR_NONE;
+		for (size_t idx = 0; idx < mConfig.mOutputLayerNames.size(); ++idx) {
+			LOGI("Configure %s layer as output", mConfig.mOutputLayerNames[idx].c_str());
+			property.layers.insert(std::make_pair(mConfig.mOutputLayerNames[idx], tensors_info[idx]));
+		}
 	}
 
-	int Inference::ConfigureTargetTypes(int targetType, bool isNewVersion)
-	{
-		if (isNewVersion) {
-			if (MV_INFERENCE_TARGET_DEVICE_NONE >= targetType ||
-				MV_INFERENCE_TARGET_DEVICE_MAX <= targetType) {
-				LOGE("Invalid target device.");
-				return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-			}
-		} else {
-			if (MV_INFERENCE_TARGET_NONE >= targetType ||
-				MV_INFERENCE_TARGET_MAX <= targetType) {
-				LOGE("Invalid target device.");
-				return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-			}
-
-			LOGI("Before converting target types : %d", targetType);
+	int ret = mBackend->SetOutputLayerProperty(property);
+	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
+		LOGE("Fail to set output layer property");
+	}
 
-			// Convert old type to new one.
-			switch (targetType) {
-			case MV_INFERENCE_TARGET_CPU:
-				targetType = MV_INFERENCE_TARGET_DEVICE_CPU;
-				break;
-			case MV_INFERENCE_TARGET_GPU:
+	LOGI("LEAVE");
+}
 
-				targetType = MV_INFERENCE_TARGET_DEVICE_GPU;
-				break;
-			case MV_INFERENCE_TARGET_CUSTOM:
-				targetType = MV_INFERENCE_TARGET_DEVICE_CUSTOM;
-				break;
-			}
+int Inference::CheckBackendType(const mv_inference_backend_type_e backendType)
+{
+	// Check if a given backend type is valid or not.
+	if (backendType <= MV_INFERENCE_BACKEND_NONE || backendType >= MV_INFERENCE_BACKEND_MAX) {
+		LOGE("Invalid backend type.");
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+	}
 
-			LOGI("After converting target types : %d", targetType);
-		}
+	std::pair<std::string, bool> backend = mSupportedInferenceBackend[backendType];
+	if (backend.second == false) {
+		LOGE("%s type is not supported", (backend.first).c_str());
+		return MEDIA_VISION_ERROR_NOT_SUPPORTED;
+	}
 
-		mConfig.mTargetTypes = targetType;
+	LOGI("backend engine : %d", backendType);
 
-		return MEDIA_VISION_ERROR_NONE;
-	}
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-	int Inference::ConfigureTargetDevices(const int targetDevices)
-	{
-		// Check if given target types are valid or not.
-		if (MV_INFERENCE_TARGET_DEVICE_NONE >= targetDevices ||
-			MV_INFERENCE_TARGET_DEVICE_MAX <= targetDevices) {
+int Inference::ConfigureTargetTypes(int targetType, bool isNewVersion)
+{
+	if (isNewVersion) {
+		if (MV_INFERENCE_TARGET_DEVICE_NONE >= targetType || MV_INFERENCE_TARGET_DEVICE_MAX <= targetType) {
+			LOGE("Invalid target device.");
+			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+		}
+	} else {
+		if (MV_INFERENCE_TARGET_NONE >= targetType || MV_INFERENCE_TARGET_MAX <= targetType) {
 			LOGE("Invalid target device.");
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 		}
 
-		LOGI("target devices : %d", targetDevices);
+		LOGI("Before converting target types : %d", targetType);
 
-		if (!(mBackendCapacity.supported_accel_devices & targetDevices)) {
-			LOGE("Backend doesn't support a given device acceleration.");
-			return MEDIA_VISION_ERROR_NOT_SUPPORTED;
-		}
+		// Convert old type to new one.
+		switch (targetType) {
+		case MV_INFERENCE_TARGET_CPU:
+			targetType = MV_INFERENCE_TARGET_DEVICE_CPU;
+			break;
+		case MV_INFERENCE_TARGET_GPU:
 
-		mConfig.mTargetTypes = targetDevices;
+			targetType = MV_INFERENCE_TARGET_DEVICE_GPU;
+			break;
+		case MV_INFERENCE_TARGET_CUSTOM:
+			targetType = MV_INFERENCE_TARGET_DEVICE_CUSTOM;
+			break;
+		}
 
-		return MEDIA_VISION_ERROR_NONE;
+		LOGI("After converting target types : %d", targetType);
 	}
 
-	bool Inference::IsTargetDeviceSupported(const int targetDevices)
-	{
-		if (!(mBackendCapacity.supported_accel_devices & targetDevices)) {
-			LOGE("Backend doesn't support a given %x device acceleration.", targetDevices);
-			return false;
-		}
+	mConfig.mTargetTypes = targetType;
+
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		return true;
+int Inference::ConfigureTargetDevices(const int targetDevices)
+{
+	// Check if given target types are valid or not.
+	if (MV_INFERENCE_TARGET_DEVICE_NONE >= targetDevices || MV_INFERENCE_TARGET_DEVICE_MAX <= targetDevices) {
+		LOGE("Invalid target device.");
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	void Inference::ConfigureOutput(const int maxOutputNumbers)
-	{
-		mConfig.mMaxOutputNumbers = std::max(
-				std::min(maxOutputNumbers, MV_INFERENCE_OUTPUT_NUMBERS_MAX),
-				MV_INFERENCE_OUTPUT_NUMBERS_MIN);
+	LOGI("target devices : %d", targetDevices);
+
+	if (!(mBackendCapacity.supported_accel_devices & targetDevices)) {
+		LOGE("Backend doesn't support a given device acceleration.");
+		return MEDIA_VISION_ERROR_NOT_SUPPORTED;
 	}
 
-	void Inference::ConfigureThreshold(const double threshold)
-	{
-		mConfig.mConfidenceThresHold = std::max(
-				std::min(threshold, MV_INFERENCE_CONFIDENCE_THRESHOLD_MAX),
-				MV_INFERENCE_CONFIDENCE_THRESHOLD_MIN);
+	mConfig.mTargetTypes = targetDevices;
+
+	return MEDIA_VISION_ERROR_NONE;
+}
+
+bool Inference::IsTargetDeviceSupported(const int targetDevices)
+{
+	if (!(mBackendCapacity.supported_accel_devices & targetDevices)) {
+		LOGE("Backend doesn't support a given %x device acceleration.", targetDevices);
+		return false;
 	}
 
-	int Inference::ParseMetadata(const std::string filePath)
-	{
-		LOGI("ENTER");
-		int ret = mMetadata.Init(filePath);
-		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to init metadata[%d]", ret);
-			return ret;
-		}
+	return true;
+}
 
-		ret = mMetadata.Parse();
-		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to parse metadata[%d]", ret);
-			return ret;
-		}
+void Inference::ConfigureOutput(const int maxOutputNumbers)
+{
+	mConfig.mMaxOutputNumbers =
+			std::max(std::min(maxOutputNumbers, MV_INFERENCE_OUTPUT_NUMBERS_MAX), MV_INFERENCE_OUTPUT_NUMBERS_MIN);
+}
 
-		LOGI("LEAVE");
+void Inference::ConfigureThreshold(const double threshold)
+{
+	mConfig.mConfidenceThresHold =
+			std::max(std::min(threshold, MV_INFERENCE_CONFIDENCE_THRESHOLD_MAX), MV_INFERENCE_CONFIDENCE_THRESHOLD_MIN);
+}
 
-		return MEDIA_VISION_ERROR_NONE;
+int Inference::ParseMetadata(const std::string filePath)
+{
+	LOGI("ENTER");
+	int ret = mMetadata.Init(filePath);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to init metadata[%d]", ret);
+		return ret;
 	}
 
-	void Inference::CleanupTensorBuffers(void)
-	{
-		LOGI("ENTER");
+	ret = mMetadata.Parse();
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to parse metadata[%d]", ret);
+		return ret;
+	}
 
-		if (!mInputTensorBuffers.empty()) {
-			mInputTensorBuffers.release();
-		}
+	LOGI("LEAVE");
 
-		if (!mOutputTensorBuffers.empty()) {
-			mOutputTensorBuffers.release();
-		}
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		LOGI("LEAVE");
+void Inference::CleanupTensorBuffers(void)
+{
+	LOGI("ENTER");
+
+	if (!mInputTensorBuffers.empty()) {
+		mInputTensorBuffers.release();
 	}
 
-	int Inference::PrepareTenosrBuffers(void)
-	{
-		// If there are input and output tensor buffers allocated before then release the buffers.
-		// They will be allocated again according to a new model file to be loaded.
-		CleanupTensorBuffers();
+	if (!mOutputTensorBuffers.empty()) {
+		mOutputTensorBuffers.release();
+	}
 
-		// IF model file is loaded again then the model type could be different so
-		// clean up input and output layer properties so that they can be updated again
-		// after reloading the model file.
-		if (!mInputLayerProperty.layers.empty()) {
-			mInputLayerProperty.layers.clear();
-			std::map<std::string, inference_engine_tensor_info>().swap(
-					mInputLayerProperty.layers);
-		}
-		if (!mOutputLayerProperty.layers.empty()) {
-			mOutputLayerProperty.layers.clear();
-			std::map<std::string, inference_engine_tensor_info>().swap(
-					mOutputLayerProperty.layers);
-		}
+	LOGI("LEAVE");
+}
 
-		// Get input tensor buffers from a backend engine if the backend engine allocated.
-		auto& inputTensorBuffers = mInputTensorBuffers.getIETensorBuffer();
-		int ret = mBackend->GetInputTensorBuffers(inputTensorBuffers);
-		if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-			LOGE("Fail to get input tensor buffers from backend engine.");
-			return ConvertEngineErrorToVisionError(ret);
-		}
+int Inference::PrepareTenosrBuffers(void)
+{
+	// If there are input and output tensor buffers allocated before then release the buffers.
+	// They will be allocated again according to a new model file to be loaded.
+	CleanupTensorBuffers();
+
+	// IF model file is loaded again then the model type could be different so
+	// clean up input and output layer properties so that they can be updated again
+	// after reloading the model file.
+	if (!mInputLayerProperty.layers.empty()) {
+		mInputLayerProperty.layers.clear();
+		std::map<std::string, inference_engine_tensor_info>().swap(mInputLayerProperty.layers);
+	}
+	if (!mOutputLayerProperty.layers.empty()) {
+		mOutputLayerProperty.layers.clear();
+		std::map<std::string, inference_engine_tensor_info>().swap(mOutputLayerProperty.layers);
+	}
 
-		ret = mBackend->GetInputLayerProperty(mInputLayerProperty);
-		if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-			LOGE("Fail to get input layer property from backend engine.");
-			return ConvertEngineErrorToVisionError(ret);
-		}
+	// Get input tensor buffers from a backend engine if the backend engine allocated.
+	auto &inputTensorBuffers = mInputTensorBuffers.getIETensorBuffer();
+	int ret = mBackend->GetInputTensorBuffers(inputTensorBuffers);
+	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
+		LOGE("Fail to get input tensor buffers from backend engine.");
+		return ConvertEngineErrorToVisionError(ret);
+	}
 
-		// If the backend engine isn't able to allocate input tensor buffers internally,
-		// then allocate the buffers at here.
-		if (mInputTensorBuffers.empty()) {
-			for(auto& layer : mInputLayerProperty.layers) {
-				inference_engine_tensor_buffer tensor_buffer;
-
-				ret = mInputTensorBuffers.allocate(tensor_buffer, layer.second);
-				if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-					LOGE("Fail to allocate tensor buffer.");
-					mInputTensorBuffers.release();
-					return ret;
-				}
+	ret = mBackend->GetInputLayerProperty(mInputLayerProperty);
+	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
+		LOGE("Fail to get input layer property from backend engine.");
+		return ConvertEngineErrorToVisionError(ret);
+	}
 
-				mInputTensorBuffers.addTensorBuffer(layer.first, tensor_buffer);
+	// If the backend engine isn't able to allocate input tensor buffers internally,
+	// then allocate the buffers at here.
+	if (mInputTensorBuffers.empty()) {
+		for (auto &layer : mInputLayerProperty.layers) {
+			inference_engine_tensor_buffer tensor_buffer;
+
+			ret = mInputTensorBuffers.allocate(tensor_buffer, layer.second);
+			if (ret != INFERENCE_ENGINE_ERROR_NONE) {
+				LOGE("Fail to allocate tensor buffer.");
+				mInputTensorBuffers.release();
+				return ret;
 			}
+
+			mInputTensorBuffers.addTensorBuffer(layer.first, tensor_buffer);
 		}
+	}
 
-		LOGI("Input tensor buffer count is %zu", mInputTensorBuffers.size());
+	LOGI("Input tensor buffer count is %zu", mInputTensorBuffers.size());
 
-		// Get output tensor buffers from a backend engine if the backend engine allocated.
-		auto& outputTensorBuffers = mOutputTensorBuffers.getIETensorBuffer();
-		ret = mBackend->GetOutputTensorBuffers(outputTensorBuffers);
-		if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-			LOGE("Fail to get output tensor buffers from backend engine.");
-			return ConvertEngineErrorToVisionError(ret);
-		}
+	// Get output tensor buffers from a backend engine if the backend engine allocated.
+	auto &outputTensorBuffers = mOutputTensorBuffers.getIETensorBuffer();
+	ret = mBackend->GetOutputTensorBuffers(outputTensorBuffers);
+	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
+		LOGE("Fail to get output tensor buffers from backend engine.");
+		return ConvertEngineErrorToVisionError(ret);
+	}
 
-		ret = mBackend->GetOutputLayerProperty(mOutputLayerProperty);
-		if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-			LOGE("Fail to get output layer property from backend engine.");
-			return ConvertEngineErrorToVisionError(ret);
-		}
+	ret = mBackend->GetOutputLayerProperty(mOutputLayerProperty);
+	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
+		LOGE("Fail to get output layer property from backend engine.");
+		return ConvertEngineErrorToVisionError(ret);
+	}
 
-		// If the backend engine isn't able to allocate output tensor buffers internally,
-		// then allocate the buffers at here.
-		if (mOutputTensorBuffers.empty()) {
-			for (auto& layer : mOutputLayerProperty.layers) {
-				inference_engine_tensor_buffer tensor_buffer;
-
-				ret = mInputTensorBuffers.allocate(tensor_buffer, layer.second);
-				if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-					LOGE("Fail to allocate tensor buffer.");
-					mInputTensorBuffers.release();
-					return ret;
-				}
+	// If the backend engine isn't able to allocate output tensor buffers internally,
+	// then allocate the buffers at here.
+	if (mOutputTensorBuffers.empty()) {
+		for (auto &layer : mOutputLayerProperty.layers) {
+			inference_engine_tensor_buffer tensor_buffer;
 
-				mOutputTensorBuffers.addTensorBuffer(layer.first, tensor_buffer);
+			ret = mInputTensorBuffers.allocate(tensor_buffer, layer.second);
+			if (ret != INFERENCE_ENGINE_ERROR_NONE) {
+				LOGE("Fail to allocate tensor buffer.");
+				mInputTensorBuffers.release();
+				return ret;
 			}
+
+			mOutputTensorBuffers.addTensorBuffer(layer.first, tensor_buffer);
 		}
+	}
 
-		LOGI("Output tensor buffer count is %zu", mOutputTensorBuffers.size());
+	LOGI("Output tensor buffer count is %zu", mOutputTensorBuffers.size());
 
-		return MEDIA_VISION_ERROR_NONE;
-	}
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-	int Inference::ConvertOutputDataTypeToFloat()
-	{
-		IETensorBuffer& ieTensorBuffers = mOutputTensorBuffers.getIETensorBuffer();
+int Inference::ConvertOutputDataTypeToFloat()
+{
+	IETensorBuffer &ieTensorBuffers = mOutputTensorBuffers.getIETensorBuffer();
 
-		for (auto& ieTensorBuffer : ieTensorBuffers) {
-			auto& tensorBuffer = ieTensorBuffer.second;
+	for (auto &ieTensorBuffer : ieTensorBuffers) {
+		auto &tensorBuffer = ieTensorBuffer.second;
 
-			// Normalize output tensor data converting it to float type in case of quantized model.
-			if (tensorBuffer.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT8) {
-				int ret = mOutputTensorBuffers.convertToFloat<unsigned char>(&tensorBuffer);
-				if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to convert tensor data to float type.");
-					return ret;
-				}
+		// Normalize output tensor data converting it to float type in case of quantized model.
+		if (tensorBuffer.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT8) {
+			int ret = mOutputTensorBuffers.convertToFloat<unsigned char>(&tensorBuffer);
+			if (ret != MEDIA_VISION_ERROR_NONE) {
+				LOGE("Fail to convert tensor data to float type.");
+				return ret;
 			}
+		}
 
-			if (tensorBuffer.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT16) {
-				int ret = mOutputTensorBuffers.convertToFloat<unsigned short>(&tensorBuffer);
-				if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to convert tensor data to float type.");
-					return ret;
-				}
+		if (tensorBuffer.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT16) {
+			int ret = mOutputTensorBuffers.convertToFloat<unsigned short>(&tensorBuffer);
+			if (ret != MEDIA_VISION_ERROR_NONE) {
+				LOGE("Fail to convert tensor data to float type.");
+				return ret;
 			}
 		}
-
-		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	int Inference::Bind(int backend_type, int device_type)
-	{
-		LOGI("ENTER");
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		int ret = CheckBackendType(static_cast<mv_inference_backend_type_e>(backend_type));
-		if (ret != MEDIA_VISION_ERROR_NONE)
-			return ret;
+int Inference::Bind(int backend_type, int device_type)
+{
+	LOGI("ENTER");
+
+	int ret = CheckBackendType(static_cast<mv_inference_backend_type_e>(backend_type));
+	if (ret != MEDIA_VISION_ERROR_NONE)
+		return ret;
 
-		std::string backendName = mSupportedInferenceBackend[backend_type].first;
-		LOGI("backend string name: %s", backendName.c_str());
+	std::string backendName = mSupportedInferenceBackend[backend_type].first;
+	LOGI("backend string name: %s", backendName.c_str());
 
-		inference_engine_config config = {
-			.backend_name = backendName,
-			.backend_type = backend_type,
-			// As a default, Target device is CPU. If user defined desired device type in json file
-			// then the device type will be set by Load callback.
-			.target_devices = device_type,
-		};
+	inference_engine_config config = {
+		.backend_name = backendName,
+		.backend_type = backend_type,
+		// As a default, Target device is CPU. If user defined desired device type in json file
+		// then the device type will be set by Load callback.
+		.target_devices = device_type,
+	};
 
-		// Create a backend class object.
-		try {
-			mBackend = new InferenceEngineCommon();
+	// Create a backend class object.
+	try {
+		mBackend = new InferenceEngineCommon();
 
 #if ENABLE_INFERENCE_PROFILER
-			mBackend->EnableProfiler(true);
-			mBackend->DumpProfileToFile("profile_data_" + backendName + ".txt");
+		mBackend->EnableProfiler(true);
+		mBackend->DumpProfileToFile("profile_data_" + backendName + ".txt");
 #endif
-		} catch (const std::bad_alloc &ex) {
-			LOGE("Fail to create backend : %s", ex.what());
-			return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
-		}
+	} catch (const std::bad_alloc &ex) {
+		LOGE("Fail to create backend : %s", ex.what());
+		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
+	}
 
-		ret = MEDIA_VISION_ERROR_NONE;
+	ret = MEDIA_VISION_ERROR_NONE;
 
-		// Load configuration file if a given backend type is mlapi.
-		if (config.backend_type == MV_INFERENCE_BACKEND_MLAPI) {
-			ret = mBackend->LoadConfigFile();
-			if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
-		}
-
-		// Bind a backend library.
-		ret = mBackend->BindBackend(&config);
+	// Load configuration file if a given backend type is mlapi.
+	if (config.backend_type == MV_INFERENCE_BACKEND_MLAPI) {
+		ret = mBackend->LoadConfigFile();
 		if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-			LOGE("Fail to bind backend library.(%d)", ret);
 			return MEDIA_VISION_ERROR_INVALID_OPERATION;
 		}
+	}
 
-		// Get capacity information from a backend.
-		ret = mBackend->GetBackendCapacity(&mBackendCapacity);
-		if (ret != MEDIA_VISION_ERROR_NONE) {
-			mBackend->UnbindBackend();
-			LOGE("Fail to get backend capacity.");
-			return ret;
-		}
+	// Bind a backend library.
+	ret = mBackend->BindBackend(&config);
+	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
+		LOGE("Fail to bind backend library.(%d)", ret);
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
+	}
 
-		if (!IsTargetDeviceSupported(mConfig.mTargetTypes)) {
-			mBackend->UnbindBackend();
-			LOGE("Tried to configure invalid target types.");
-			return MEDIA_VISION_ERROR_NOT_SUPPORTED;
-		}
+	// Get capacity information from a backend.
+	ret = mBackend->GetBackendCapacity(&mBackendCapacity);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		mBackend->UnbindBackend();
+		LOGE("Fail to get backend capacity.");
+		return ret;
+	}
+
+	if (!IsTargetDeviceSupported(mConfig.mTargetTypes)) {
+		mBackend->UnbindBackend();
+		LOGE("Tried to configure invalid target types.");
+		return MEDIA_VISION_ERROR_NOT_SUPPORTED;
+	}
 
-		LOGI("LEAVE");
+	LOGI("LEAVE");
 
-		return MEDIA_VISION_ERROR_NONE;
+	return MEDIA_VISION_ERROR_NONE;
+}
+
+int Inference::Load(void)
+{
+	LOGI("ENTER");
+
+	std::string label_file = mConfig.mUserFilePath;
+	size_t userFileLength = label_file.length();
+	if (userFileLength > 0 && access(label_file.c_str(), F_OK)) {
+		LOGE("Label file path in [%s] ", label_file.c_str());
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	int Inference::Load(void)
-	{
-		LOGI("ENTER");
+	int ret = (userFileLength > 0) ? SetUserFile(label_file) : MEDIA_VISION_ERROR_NONE;
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to load label file.");
+		return ret;
+	}
 
-		std::string label_file = mConfig.mUserFilePath;
-		size_t userFileLength = label_file.length();
-		if (userFileLength > 0 && access(label_file.c_str(), F_OK)) {
-			LOGE("Label file path in [%s] ", label_file.c_str());
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-		}
+	// Check if model file is valid or not.
+	std::string ext_str = mConfig.mWeightFilePath.substr(mConfig.mWeightFilePath.find_last_of(".") + 1);
+	std::map<std::string, int>::iterator key = mModelFormats.find(ext_str);
+	if (key == mModelFormats.end()) {
+		LOGE("Invalid model file format.(ext = %s)", ext_str.c_str());
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+	}
+
+	LOGI("%s model file has been detected.", ext_str.c_str());
+
+	std::vector<std::string> models;
+
+	inference_model_format_e model_format = static_cast<inference_model_format_e>(key->second);
+
+	// Push model file information to models vector properly according to detected model format.
+	switch (model_format) {
+	case INFERENCE_MODEL_CAFFE:
+	case INFERENCE_MODEL_TF:
+	case INFERENCE_MODEL_DARKNET:
+	case INFERENCE_MODEL_DLDT:
+	case INFERENCE_MODEL_ONNX:
+	case INFERENCE_MODEL_VIVANTE:
+		models.push_back(mConfig.mWeightFilePath);
+		models.push_back(mConfig.mConfigFilePath);
+		break;
+	case INFERENCE_MODEL_TFLITE:
+	case INFERENCE_MODEL_TORCH:
+	case INFERENCE_MODEL_NNTRAINER:
+	case INFERENCE_MODEL_SNPE:
+		models.push_back(mConfig.mWeightFilePath);
+		break;
+	default:
+		break;
+	}
+
+	// Request model loading to backend engine.
+	ret = mBackend->Load(models, model_format);
+	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
+		LOGE("Fail to load model");
+		mCanRun = false;
+		std::vector<std::string>().swap(models);
+		return ConvertEngineErrorToVisionError(ret);
+	}
+
+	std::vector<std::string>().swap(models);
+
+	// Prepare input and output tensor buffers.
+	ret = PrepareTenosrBuffers();
+	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
+		LOGE("Fail to prepare buffer");
+		mCanRun = false;
+		return ret;
+	}
+
+	mCanRun = true;
+
+	LOGI("LEAVE");
+
+	return ConvertEngineErrorToVisionError(ret);
+}
 
-		int ret = (userFileLength > 0) ? SetUserFile(label_file) :
-										 MEDIA_VISION_ERROR_NONE;
+int Inference::Preprocess(std::vector<mv_source_h> &mv_sources, std::vector<cv::Mat> &cv_sources)
+{
+	unsigned int src_idx = 0;
+
+	for (auto &buffer : mInputTensorBuffers.getIETensorBuffer()) {
+		inference_engine_tensor_buffer &tensor_buffer = buffer.second;
+		int data_type = ConvertToCv(tensor_buffer.data_type);
+		LayerInfo layerInfo;
+		Options opt;
+		mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
+
+		mv_source_get_colorspace(mv_sources[src_idx], &colorspace);
+
+		if (mMetadata.GetInputMeta().IsParsed()) {
+			layerInfo = mMetadata.GetInputMeta().GetLayer().at(buffer.first);
+
+			if (!mMetadata.GetInputMeta().GetOption().empty())
+				opt = mMetadata.GetInputMeta().GetOption().at(buffer.first);
+		} else {
+			// Ps. in case of legacy way, there is no way to set model specific dequantization parameters - zero point and scale.
+			// TODO. find a proper way for it.
+			opt.normalization.use = true;
+			opt.normalization.mean.assign(3, mConfig.mMeanValue);
+			opt.normalization.std.assign(3, mConfig.mStdValue);
+
+			layerInfo.name = buffer.first;
+			layerInfo.dims.push_back(mConfig.mTensorInfo.dim);
+			layerInfo.dims.push_back(mConfig.mTensorInfo.height);
+			layerInfo.dims.push_back(mConfig.mTensorInfo.width);
+			layerInfo.dims.push_back(mConfig.mTensorInfo.ch);
+
+			// Ps. in case of legacy way, there is no way to use model specific color space but only fixed one.
+			// TODO. find a proper way for it.
+			layerInfo.colorSpace = MEDIA_VISION_COLORSPACE_RGB888;
+			layerInfo.dataType = mConfig.mDataType;
+			// TODO. find a proper way for setting the shape type. In case of legacy way, there is no way to change the shape type properly.
+			//       According to a given inference engine, different shape type can be needed.
+			layerInfo.shapeType = INFERENCE_TENSOR_SHAPE_NHWC;
+		}
+
+		// TODO: try-catch{} error handling
+		int ret = mPreProc.Run(cv_sources[src_idx++], colorspace, data_type, layerInfo, opt, tensor_buffer.buffer);
 		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to load label file.");
+			LOGE("Fail to run pre-process.");
 			return ret;
 		}
+	}
 
-		// Check if model file is valid or not.
-		std::string ext_str = mConfig.mWeightFilePath.substr(
-				mConfig.mWeightFilePath.find_last_of(".") + 1);
-		std::map<std::string, int>::iterator key = mModelFormats.find(ext_str);
-		if (key == mModelFormats.end()) {
-			LOGE("Invalid model file format.(ext = %s)", ext_str.c_str());
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-		}
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		LOGI("%s model file has been detected.", ext_str.c_str());
+int Inference::Run(std::vector<mv_source_h> &mvSources, std::vector<mv_rectangle_s> &rects)
+{
+	int ret = INFERENCE_ENGINE_ERROR_NONE;
 
-		std::vector<std::string> models;
+	if (!mCanRun) {
+		LOGE("Invalid to run inference");
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
+	}
 
-		inference_model_format_e model_format =
-				static_cast<inference_model_format_e>(key->second);
+	if (mvSources.empty()) {
+		LOGE("mvSources should contain only one cv source.");
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+	}
 
-		// Push model file information to models vector properly according to detected model format.
-		switch (model_format) {
-		case INFERENCE_MODEL_CAFFE:
-		case INFERENCE_MODEL_TF:
-		case INFERENCE_MODEL_DARKNET:
-		case INFERENCE_MODEL_DLDT:
-		case INFERENCE_MODEL_ONNX:
-		case INFERENCE_MODEL_VIVANTE:
-			models.push_back(mConfig.mWeightFilePath);
-			models.push_back(mConfig.mConfigFilePath);
-			break;
-		case INFERENCE_MODEL_TFLITE:
-		case INFERENCE_MODEL_TORCH:
-		case INFERENCE_MODEL_NNTRAINER:
-		case INFERENCE_MODEL_SNPE:
-			models.push_back(mConfig.mWeightFilePath);
-			break;
-		default:
-			break;
-		}
+	// We are able to request Only one input data for the inference as of now.
+	if (mvSources.size() > 1) {
+		LOGE("It allows only one mv source for the inference.");
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+	}
 
-		// Request model loading to backend engine.
-		ret = mBackend->Load(models, model_format);
-		if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-			LOGE("Fail to load model");
-			mCanRun = false;
-			std::vector<std::string>().swap(models);
-			return ConvertEngineErrorToVisionError(ret);
-		}
+	if (!rects.empty() && rects.size() != mvSources.size()) {
+		LOGE("mvSources.size() should be same as rects.size() if rects.empty() is false.");
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+	}
 
-		std::vector<std::string>().swap(models);
+	if (mConfig.mTensorInfo.ch != 1 && mConfig.mTensorInfo.ch != 3) {
+		LOGE("Channel not supported.");
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+	}
 
-		// Prepare input and output tensor buffers.
-		ret = PrepareTenosrBuffers();
-		if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-			LOGE("Fail to prepare buffer");
-			mCanRun = false;
-			return ret;
-		}
+	std::vector<cv::Mat> cvSources;
 
-		mCanRun = true;
+	ret = ConvertToCvSource(mvSources, cvSources, rects);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to convert mv source to cv source.");
+		return ret;
+	}
 
-		LOGI("LEAVE");
+	// mSourceSize is original input image's size
+	// TODO. consider multiple cv sources.
+	mSourceSize = cvSources[0].size();
 
-		return ConvertEngineErrorToVisionError(ret);
+	ret = Preprocess(mvSources, cvSources);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to preprocess given input sources.");
+		return ret;
 	}
 
-	int Inference::Preprocess(std::vector<mv_source_h>& mv_sources, std::vector<cv::Mat>& cv_sources)
-	{
-		unsigned int src_idx = 0;
-
-		for (auto& buffer : mInputTensorBuffers.getIETensorBuffer()) {
-			inference_engine_tensor_buffer& tensor_buffer = buffer.second;
-			int data_type = ConvertToCv(tensor_buffer.data_type);
-			LayerInfo layerInfo;
-			Options opt;
-			mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
-
-			mv_source_get_colorspace(mv_sources[src_idx], &colorspace);
-
-			if (mMetadata.GetInputMeta().IsParsed()) {
-				layerInfo = mMetadata.GetInputMeta().GetLayer().at(buffer.first);
-
-				if (!mMetadata.GetInputMeta().GetOption().empty())
-					opt = mMetadata.GetInputMeta().GetOption().at(buffer.first);
-			} else {
-				// Ps. in case of legacy way, there is no way to set model specific dequantization parameters - zero point and scale.
-				// TODO. find a proper way for it.
-				opt.normalization.use = true;
-				opt.normalization.mean.assign(3, mConfig.mMeanValue);
-				opt.normalization.std.assign(3, mConfig.mStdValue);
-
-				layerInfo.name = buffer.first;
-				layerInfo.dims.push_back(mConfig.mTensorInfo.dim);
-				layerInfo.dims.push_back(mConfig.mTensorInfo.height);
-				layerInfo.dims.push_back(mConfig.mTensorInfo.width);
-				layerInfo.dims.push_back(mConfig.mTensorInfo.ch);
-
-				// Ps. in case of legacy way, there is no way to use model specific color space but only fixed one.
-				// TODO. find a proper way for it.
-				layerInfo.colorSpace = MEDIA_VISION_COLORSPACE_RGB888;
-				layerInfo.dataType = mConfig.mDataType;
-				// TODO. find a proper way for setting the shape type. In case of legacy way, there is no way to change the shape type properly.
-				//       According to a given inference engine, different shape type can be needed.
-				layerInfo.shapeType = INFERENCE_TENSOR_SHAPE_NHWC;
-			}
+	ret = mBackend->Run(mInputTensorBuffers.getIETensorBuffer(), mOutputTensorBuffers.getIETensorBuffer());
+	if (ret != INFERENCE_ENGINE_ERROR_NONE)
+		return ret;
 
-			// TODO: try-catch{} error handling
-			int ret = mPreProc.Run(cv_sources[src_idx++], colorspace, data_type, layerInfo, opt, tensor_buffer.buffer);
-			if (ret != MEDIA_VISION_ERROR_NONE) {
-				LOGE("Fail to run pre-process.");
-				return ret;
-			}
-		}
+	return ConvertOutputDataTypeToFloat();
+}
 
-		return MEDIA_VISION_ERROR_NONE;
+int Inference::Run(std::vector<void *> &buffer_objs)
+{
+	int ret = INFERENCE_ENGINE_ERROR_NONE;
 
+	if (!mCanRun) {
+		LOGE("Invalid to run inference");
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
-	int Inference::Run(std::vector<mv_source_h> &mvSources,
-					   std::vector<mv_rectangle_s> &rects)
-	{
-		int ret = INFERENCE_ENGINE_ERROR_NONE;
+	if (buffer_objs.empty()) {
+		LOGE("cvSources should contain only one cv source.");
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+	}
 
-		if (!mCanRun) {
-			LOGE("Invalid to run inference");
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
+	// We are able to request Only one input data for the inference as of now.
+	if (buffer_objs.size() > 1) {
+		LOGE("It allows only one source for the inference.");
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+	}
 
-		if (mvSources.empty()) {
-			LOGE("mvSources should contain only one cv source.");
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-		}
+	if (mInputTensorBuffers.getIETensorBuffer().size() != buffer_objs.size()) {
+		LOGE("Raw source count is not invalid.");
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+	}
 
-		// We are able to request Only one input data for the inference as of now.
-		if (mvSources.size() > 1) {
-			LOGE("It allows only one mv source for the inference.");
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-		}
+	unsigned int buffer_idx = 0;
 
-		if (!rects.empty() && rects.size() != mvSources.size()) {
-			LOGE("mvSources.size() should be same as rects.size() if rects.empty() is false.");
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-		}
+	for (auto &buffer : mInputTensorBuffers.getIETensorBuffer()) {
+		inference_engine_tensor_buffer &tensor_buffer = buffer.second;
+		inference_engine_tensor_buffer *buffer_obj =
+				static_cast<inference_engine_tensor_buffer *>(buffer_objs[buffer_idx]);
 
-		if (mConfig.mTensorInfo.ch != 1 && mConfig.mTensorInfo.ch != 3) {
-			LOGE("Channel not supported.");
+		if (tensor_buffer.size != buffer_obj->size) {
+			LOGE("Raw buffer size is invalid.");
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 		}
 
-		std::vector<cv::Mat> cvSources;
+		LOGI("A number of tensor bytes : %zu", buffer_obj->size);
 
-		ret = ConvertToCvSource(mvSources, cvSources, rects);
-		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to convert mv source to cv source.");
-			return ret;
-		}
+		memcpy(tensor_buffer.buffer, buffer_obj->buffer, tensor_buffer.size);
+		buffer_idx++;
+	}
 
-		// mSourceSize is original input image's size
-		// TODO. consider multiple cv sources.
-		mSourceSize = cvSources[0].size();
+	ret = mBackend->Run(mInputTensorBuffers.getIETensorBuffer(), mOutputTensorBuffers.getIETensorBuffer());
+	if (ret != INFERENCE_ENGINE_ERROR_NONE)
+		return ret;
 
-		ret = Preprocess(mvSources, cvSources);
-		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to preprocess given input sources.");
-			return ret;
-		}
+	return ConvertOutputDataTypeToFloat();
+}
 
-		ret = mBackend->Run(mInputTensorBuffers.getIETensorBuffer(),
-							mOutputTensorBuffers.getIETensorBuffer());
-		if (ret != INFERENCE_ENGINE_ERROR_NONE)
-			return ret;
+std::pair<std::string, bool> Inference::GetSupportedInferenceBackend(int backend)
+{
+	return mSupportedInferenceBackend[backend];
+}
 
-		return ConvertOutputDataTypeToFloat();
+int Inference::GetClassficationResults(ImageClassificationResults *results)
+{
+	// Will contain top N results in ascending order.
+	std::vector<std::pair<float, int> > topScore;
+	auto threadHold = mConfig.mConfidenceThresHold;
+	constexpr unsigned int default_top_number = 5;
+	tensor_t outputTensorInfo;
+
+	// Get inference result and contain it to outputTensorInfo.
+	int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to get output result.");
+		return ret;
 	}
 
-	int Inference::Run(std::vector<void *>& buffer_objs)
-	{
-		int ret = INFERENCE_ENGINE_ERROR_NONE;
+	PostProcess postProc;
+	unsigned int classes = outputTensorInfo.dimInfo[0][1];
+	unsigned int top_number = default_top_number;
+
+	if (mMetadata.GetOutputMeta().IsParsed()) {
+		OutputMetadata outputMetadata = mMetadata.GetOutputMeta();
+		std::vector<int> indexes = outputMetadata.GetScoreDimInfo().GetValidIndexAll();
 
-		if (!mCanRun) {
-			LOGE("Invalid to run inference");
+		if (indexes.size() != 1) {
+			LOGE("Invalid dim size. It should be 1");
 			return MEDIA_VISION_ERROR_INVALID_OPERATION;
 		}
 
-		if (buffer_objs.empty()) {
-			LOGE("cvSources should contain only one cv source.");
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+		if (!mOutputTensorBuffers.exist(outputMetadata.GetScoreName())) {
+			LOGE("output buffe is NULL");
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
 		}
 
-		// We are able to request Only one input data for the inference as of now.
-		if (buffer_objs.size() > 1) {
-			LOGE("It allows only one source for the inference.");
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-		}
+		top_number = outputMetadata.GetScoreTopNumber();
+		threadHold = outputMetadata.GetScoreThreshold();
 
-		if (mInputTensorBuffers.getIETensorBuffer().size() != buffer_objs.size()) {
-			LOGE("Raw source count is not invalid.");
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-		}
+		classes = mOutputLayerProperty.layers[outputMetadata.GetScoreName()].shape[indexes[0]];
+	}
 
-		unsigned int buffer_idx = 0;
+	postProc.ScoreClear(top_number);
 
-		for (auto& buffer : mInputTensorBuffers.getIETensorBuffer()) {
-			inference_engine_tensor_buffer& tensor_buffer = buffer.second;
-			inference_engine_tensor_buffer *buffer_obj = static_cast<inference_engine_tensor_buffer *>(buffer_objs[buffer_idx]);
+	auto *prediction = reinterpret_cast<float *>(outputTensorInfo.data[0]);
 
-			if (tensor_buffer.size != buffer_obj->size) {
-				LOGE("Raw buffer size is invalid.");
-				return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-			}
+	LOGI("class count: %d", classes);
+
+	for (unsigned int idx = 0; idx < classes; ++idx) {
+		float value = prediction[idx];
+
+		if (mMetadata.GetOutputMeta().IsParsed()) {
+			OutputMetadata outputMetadata = mMetadata.GetOutputMeta();
 
-			LOGI("A number of tensor bytes : %zu", buffer_obj->size);
+			if (outputMetadata.GetScoreDeQuant()) {
+				value = PostProcess::dequant(value, outputMetadata.GetScoreDeQuantScale(),
+											 outputMetadata.GetScoreDeQuantZeroPoint());
+			}
 
-			memcpy(tensor_buffer.buffer, buffer_obj->buffer, tensor_buffer.size);
-			buffer_idx++;
+			if (outputMetadata.GetScoreType() == INFERENCE_SCORE_TYPE_SIGMOID)
+				value = PostProcess::sigmoid(value);
 		}
 
-		ret = mBackend->Run(mInputTensorBuffers.getIETensorBuffer(),
-							mOutputTensorBuffers.getIETensorBuffer());
-		if (ret != INFERENCE_ENGINE_ERROR_NONE)
-			return ret;
+		if (value < threadHold)
+			continue;
 
-		return ConvertOutputDataTypeToFloat();
+		postProc.ScorePush(value, idx);
 	}
 
-	std::pair<std::string, bool>
-	Inference::GetSupportedInferenceBackend(int backend)
-	{
-		return mSupportedInferenceBackend[backend];
+	postProc.ScorePop(topScore);
+	results->number_of_classes = 0;
+
+	for (auto &score : topScore) {
+		LOGI("score: %.3f, threshold: %.3f", score.first, threadHold);
+		LOGI("idx:%d", score.second);
+		LOGI("classProb: %.3f", score.first);
+
+		results->indices.push_back(score.second);
+		results->confidences.push_back(score.first);
+		results->names.push_back(mUserListName[score.second]);
+		results->number_of_classes++;
 	}
 
-	int Inference::GetClassficationResults(ImageClassificationResults *results)
-	{
-		// Will contain top N results in ascending order.
-		std::vector<std::pair<float, int>> topScore;
-		auto threadHold = mConfig.mConfidenceThresHold;
-		constexpr unsigned int default_top_number = 5;
-		tensor_t outputTensorInfo;
+	LOGE("Inference: GetClassificationResults: %d\n", results->number_of_classes);
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		// Get inference result and contain it to outputTensorInfo.
-		int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
-		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to get output result.");
-			return ret;
+int Inference::GetObjectDetectionResults(ObjectDetectionResults *results)
+{
+	if (mMetadata.GetOutputMeta().IsParsed()) {
+		OutputMetadata &outputMeta = mMetadata.GetOutputMeta();
+
+		// decoding type
+		if (!mOutputTensorBuffers.exist(outputMeta.GetBoxName()) ||
+			!mOutputTensorBuffers.exist(outputMeta.GetScoreName())) {
+			LOGE("output buffers named of %s or %s are NULL", outputMeta.GetBoxName().c_str(),
+				 outputMeta.GetScoreName().c_str());
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
 		}
 
-		PostProcess postProc;
-		unsigned int classes = outputTensorInfo.dimInfo[0][1];
-		unsigned int top_number = default_top_number;
+		int boxOffset = 0;
+		int numberOfObjects = 0;
 
-		if (mMetadata.GetOutputMeta().IsParsed()) {
-			OutputMetadata outputMetadata = mMetadata.GetOutputMeta();
-			std::vector<int> indexes = outputMetadata.GetScoreDimInfo().GetValidIndexAll();
-
-			if (indexes.size() != 1) {
+		if (outputMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_BYPASS) {
+			std::vector<int> boxIndexes = outputMeta.GetBoxDimInfo().GetValidIndexAll();
+			if (boxIndexes.size() != 1) {
 				LOGE("Invalid dim size. It should be 1");
 				return MEDIA_VISION_ERROR_INVALID_OPERATION;
 			}
-
-			if (!mOutputTensorBuffers.exist(outputMetadata.GetScoreName())) {
-				LOGE("output buffe is NULL");
+			boxOffset = mOutputLayerProperty.layers[outputMeta.GetBoxName()].shape[boxIndexes[0]];
+		} else if (outputMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR) {
+			std::vector<int> boxIndexes = outputMeta.GetBoxDimInfo().GetValidIndexAll();
+			if (boxIndexes.size() != 1) {
+				LOGE("Invalid dim size. It should be 1");
 				return MEDIA_VISION_ERROR_INVALID_OPERATION;
 			}
+			boxOffset = mOutputLayerProperty.layers[outputMeta.GetBoxName()].shape[boxIndexes[0]];
 
-			top_number = outputMetadata.GetScoreTopNumber();
-			threadHold = outputMetadata.GetScoreThreshold();
+			std::vector<int> scoreIndexes = outputMeta.GetScoreDimInfo().GetValidIndexAll();
+			if (scoreIndexes.size() != 1) {
+				LOGE("Invalid dim size. It should be 1");
+				return MEDIA_VISION_ERROR_INVALID_OPERATION;
+			}
+			numberOfObjects = mOutputLayerProperty.layers[outputMeta.GetScoreName()].shape[scoreIndexes[0]];
+		} else { // INFERENCE_BOX_DECODING_TYPE_YOLO_ANCHOR
+			std::vector<int> boxIndexes = outputMeta.GetBoxDimInfo().GetValidIndexAll();
+			if (boxIndexes.size() != 1) {
+				LOGE("Invalid dim size. It should be 1");
+				return MEDIA_VISION_ERROR_INVALID_OPERATION;
+			}
+			boxOffset = mOutputLayerProperty.layers[outputMeta.GetBoxName()].shape[boxIndexes[0]];
+			numberOfObjects = boxOffset / outputMeta.GetBoxDecodeInfo().GetCellNumScales() - 5;
+		}
+
+		ObjectDecoder objDecoder(mOutputTensorBuffers, outputMeta, boxOffset,
+								 static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getWidth()),
+								 static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getHeight()),
+								 numberOfObjects);
+
+		objDecoder.init();
+		objDecoder.decode();
+		results->number_of_objects = 0;
+
+		for (auto &box : objDecoder.getObjectAll()) {
+			results->indices.push_back(box.index);
+			results->names.push_back(mUserListName[box.index]);
+			results->confidences.push_back(box.score);
+			results->locations.push_back(
+					cv::Rect(static_cast<int>((box.location.x - box.location.width * 0.5f) *
+											  static_cast<float>(mSourceSize.width)),
+							 static_cast<int>((box.location.y - box.location.height * 0.5f) *
+											  static_cast<float>(mSourceSize.height)),
+							 static_cast<int>(box.location.width * static_cast<float>(mSourceSize.width)),
+							 static_cast<int>(box.location.height * static_cast<float>(mSourceSize.height))));
+			results->number_of_objects++;
+		}
+
+		LOGI("Inference: GetObjectDetectionResults: %d\n", results->number_of_objects);
+	} else {
+		tensor_t outputTensorInfo;
 
-			classes = mOutputLayerProperty.layers[outputMetadata.GetScoreName()].shape[indexes[0]];
+		// Get inference result and contain it to outputTensorInfo.
+		int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
+		if (ret != MEDIA_VISION_ERROR_NONE) {
+			LOGE("Fail to get output result.");
+			return ret;
 		}
 
-		postProc.ScoreClear(top_number);
+		// In case of object detection,
+		// a model may apply post-process but others may not.
+		// Thus, those cases should be hanlded separately.
+
+		float *boxes = nullptr;
+		float *classes = nullptr;
+		float *scores = nullptr;
+		int number_of_detections = 0;
+
+		if (outputTensorInfo.dimInfo.size() == 1) {
+			// there is no way to know how many objects are detect unless the number of objects aren't
+			// provided. In the case, each backend should provide the number of results manually.
+			// For example, in OpenCV, MobilenetV1-SSD doesn't provide it so the number of objects are
+			// written to the 1st element i.e., outputTensorInfo.data[0] (the shape is 1x1xNx7 and the 1st of 7
+			// indicates the image id. But it is useless if a batch mode isn't supported.
+			// So, use the 1st of 7.
+
+			number_of_detections = static_cast<int>(*reinterpret_cast<float *>(outputTensorInfo.data[0]));
+			cv::Mat cvOutputData(number_of_detections, outputTensorInfo.dimInfo[0][3], CV_32F,
+								 outputTensorInfo.data[0]);
+
+			// boxes
+			cv::Mat cvLeft = cvOutputData.col(3).clone();
+			cv::Mat cvTop = cvOutputData.col(4).clone();
+			cv::Mat cvRight = cvOutputData.col(5).clone();
+			cv::Mat cvBottom = cvOutputData.col(6).clone();
+			cv::Mat cvScores, cvClasses, cvBoxes;
+			cv::Mat cvBoxElems[] = { cvTop, cvLeft, cvBottom, cvRight };
 
-		auto *prediction = reinterpret_cast<float *>(outputTensorInfo.data[0]);
+			cv::hconcat(cvBoxElems, 4, cvBoxes);
 
-		LOGI("class count: %d", classes);
+			// classes
+			cvClasses = cvOutputData.col(1).clone();
 
-		for (unsigned int idx = 0; idx < classes; ++idx) {
-			float value = prediction[idx];
+			// scores
+			cvScores = cvOutputData.col(2).clone();
 
-			if (mMetadata.GetOutputMeta().IsParsed()) {
-				OutputMetadata outputMetadata = mMetadata.GetOutputMeta();
+			boxes = cvBoxes.ptr<float>(0);
+			classes = cvClasses.ptr<float>(0);
+			scores = cvScores.ptr<float>(0);
+		} else {
+			boxes = reinterpret_cast<float *>(outputTensorInfo.data[0]);
+			classes = reinterpret_cast<float *>(outputTensorInfo.data[1]);
+			scores = reinterpret_cast<float *>(outputTensorInfo.data[2]);
+			number_of_detections = (int) (*reinterpret_cast<float *>(outputTensorInfo.data[3]));
+		}
 
-				if (outputMetadata.GetScoreDeQuant()) {
-					value = PostProcess::dequant(value,
-											outputMetadata.GetScoreDeQuantScale(),
-											outputMetadata.GetScoreDeQuantZeroPoint());
-				}
+		LOGI("number_of_detections = %d", number_of_detections);
 
-				if (outputMetadata.GetScoreType() == INFERENCE_SCORE_TYPE_SIGMOID)
-					value = PostProcess::sigmoid(value);
-			}
+		results->number_of_objects = 0;
 
-			if (value < threadHold)
+		for (int idx = 0; idx < number_of_detections; ++idx) {
+			if (scores[idx] < mConfig.mConfidenceThresHold)
 				continue;
 
-			postProc.ScorePush(value, idx);
-		}
+			int left = static_cast<int>(boxes[idx * 4 + 1] * mSourceSize.width);
+			int top = static_cast<int>(boxes[idx * 4 + 0] * mSourceSize.height);
+			int right = static_cast<int>(boxes[idx * 4 + 3] * mSourceSize.width);
+			int bottom = static_cast<int>(boxes[idx * 4 + 2] * mSourceSize.height);
+			cv::Rect loc;
 
-		postProc.ScorePop(topScore);
-		results->number_of_classes = 0;
+			loc.x = left;
+			loc.y = top;
+			loc.width = right - left + 1;
+			loc.height = bottom - top + 1;
 
-		for (auto& score : topScore) {
-			LOGI("score: %.3f, threshold: %.3f", score.first, threadHold);
-			LOGI("idx:%d", score.second);
-			LOGI("classProb: %.3f", score.first);
+			results->indices.push_back(static_cast<int>(classes[idx]));
+			results->confidences.push_back(scores[idx]);
+			results->names.push_back(mUserListName[static_cast<int>(classes[idx])]);
+			results->locations.push_back(loc);
+			results->number_of_objects++;
 
-			results->indices.push_back(score.second);
-			results->confidences.push_back(score.first);
-			results->names.push_back(mUserListName[score.second]);
-			results->number_of_classes++;
+			LOGI("objectClass: %d", static_cast<int>(classes[idx]));
+			LOGI("confidence:%f", scores[idx]);
+			LOGI("left:%d, top:%d, right:%d, bottom:%d", left, top, right, bottom);
 		}
 
-		LOGE("Inference: GetClassificationResults: %d\n", results->number_of_classes);
-		return MEDIA_VISION_ERROR_NONE;
+		LOGI("Inference: GetObjectDetectionResults: %d\n", results->number_of_objects);
 	}
 
-	int Inference::GetObjectDetectionResults(
-			ObjectDetectionResults *results)
-	{
-		if (mMetadata.GetOutputMeta().IsParsed()) {
-			OutputMetadata& outputMeta = mMetadata.GetOutputMeta();
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-			// decoding type
-			if (!mOutputTensorBuffers.exist(outputMeta.GetBoxName()) ||
-				!mOutputTensorBuffers.exist(outputMeta.GetScoreName()) ){
-				LOGE("output buffers named of %s or %s are NULL",
-					outputMeta.GetBoxName().c_str(), outputMeta.GetScoreName().c_str());
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
-
-			int boxOffset = 0;
-			int numberOfObjects = 0;
-
-			if (outputMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_BYPASS) {
-				std::vector<int> boxIndexes = outputMeta.GetBoxDimInfo().GetValidIndexAll();
-				if (boxIndexes.size() != 1) {
-					LOGE("Invalid dim size. It should be 1");
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-				boxOffset = mOutputLayerProperty.layers[outputMeta.GetBoxName()].shape[boxIndexes[0]];
-			} else if (outputMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR) {
-				std::vector<int> boxIndexes = outputMeta.GetBoxDimInfo().GetValidIndexAll();
-				if (boxIndexes.size() != 1) {
-					LOGE("Invalid dim size. It should be 1");
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-				boxOffset = mOutputLayerProperty.layers[outputMeta.GetBoxName()].shape[boxIndexes[0]];
+int Inference::GetFaceDetectionResults(FaceDetectionResults *results)
+{
+	if (mMetadata.GetOutputMeta().IsParsed()) {
+		OutputMetadata &outputMeta = mMetadata.GetOutputMeta();
+
+		// decoding type
+		if (!mOutputTensorBuffers.exist(outputMeta.GetBoxName()) ||
+			!mOutputTensorBuffers.exist(outputMeta.GetScoreName())) {
+			LOGE("output buffers named of %s or %s are NULL", outputMeta.GetBoxName().c_str(),
+				 outputMeta.GetScoreName().c_str());
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
+		}
 
-				std::vector<int> scoreIndexes = outputMeta.GetScoreDimInfo().GetValidIndexAll();
-				if (scoreIndexes.size() != 1) {
-					LOGE("Invalid dim size. It should be 1");
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-				numberOfObjects = mOutputLayerProperty.layers[outputMeta.GetScoreName()].shape[scoreIndexes[0]];
-			} else { // INFERENCE_BOX_DECODING_TYPE_YOLO_ANCHOR
-				std::vector<int> boxIndexes = outputMeta.GetBoxDimInfo().GetValidIndexAll();
-				if (boxIndexes.size() != 1) {
-					LOGE("Invalid dim size. It should be 1");
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-				boxOffset = mOutputLayerProperty.layers[outputMeta.GetBoxName()].shape[boxIndexes[0]];
-				numberOfObjects = boxOffset / outputMeta.GetBoxDecodeInfo().GetCellNumScales() - 5;
-			}
+		int boxOffset = 0;
+		int numberOfFaces = 0;
 
-			ObjectDecoder objDecoder(mOutputTensorBuffers, outputMeta, boxOffset,
-						static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getWidth()),
-						static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getHeight()),
-						numberOfObjects);
-
-			objDecoder.init();
-			objDecoder.decode();
-			results->number_of_objects = 0;
-
-			for (auto& box : objDecoder.getObjectAll()) {
-				results->indices.push_back(box.index);
-				results->names.push_back(mUserListName[box.index]);
-				results->confidences.push_back(box.score);
-				results->locations.push_back(cv::Rect(
-						static_cast<int>((box.location.x -  box.location.width * 0.5f) * static_cast<float>(mSourceSize.width)),
-						static_cast<int>((box.location.y -  box.location.height * 0.5f) * static_cast<float>(mSourceSize.height)),
-						static_cast<int>(box.location.width *  static_cast<float>(mSourceSize.width)),
-						static_cast<int>(box.location.height * static_cast<float>(mSourceSize.height))));
-				results->number_of_objects++;
+		if (outputMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_BYPASS) {
+			std::vector<int> boxIndexes = outputMeta.GetBoxDimInfo().GetValidIndexAll();
+			if (boxIndexes.size() != 1) {
+				LOGE("Invalid dim size. It should be 1");
+				return MEDIA_VISION_ERROR_INVALID_OPERATION;
 			}
-
-			LOGI("Inference: GetObjectDetectionResults: %d\n", results->number_of_objects);
+			boxOffset = mOutputLayerProperty.layers[outputMeta.GetBoxName()].shape[boxIndexes[0]];
 		} else {
-			tensor_t outputTensorInfo;
-
-			// Get inference result and contain it to outputTensorInfo.
-			int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
-			if (ret != MEDIA_VISION_ERROR_NONE) {
-				LOGE("Fail to get output result.");
-				return ret;
-			}
-
-			// In case of object detection,
-			// a model may apply post-process but others may not.
-			// Thus, those cases should be hanlded separately.
-
-			float *boxes = nullptr;
-			float *classes = nullptr;
-			float *scores = nullptr;
-			int number_of_detections = 0;
-
-			if (outputTensorInfo.dimInfo.size() == 1) {
-				// there is no way to know how many objects are detect unless the number of objects aren't
-				// provided. In the case, each backend should provide the number of results manually.
-				// For example, in OpenCV, MobilenetV1-SSD doesn't provide it so the number of objects are
-				// written to the 1st element i.e., outputTensorInfo.data[0] (the shape is 1x1xNx7 and the 1st of 7
-				// indicates the image id. But it is useless if a batch mode isn't supported.
-				// So, use the 1st of 7.
-
-				number_of_detections = static_cast<int>(
-						*reinterpret_cast<float *>(outputTensorInfo.data[0]));
-				cv::Mat cvOutputData(number_of_detections, outputTensorInfo.dimInfo[0][3],
-									CV_32F, outputTensorInfo.data[0]);
-
-				// boxes
-				cv::Mat cvLeft = cvOutputData.col(3).clone();
-				cv::Mat cvTop = cvOutputData.col(4).clone();
-				cv::Mat cvRight = cvOutputData.col(5).clone();
-				cv::Mat cvBottom = cvOutputData.col(6).clone();
-				cv::Mat cvScores, cvClasses, cvBoxes;
-				cv::Mat cvBoxElems[] = { cvTop, cvLeft, cvBottom, cvRight };
-
-				cv::hconcat(cvBoxElems, 4, cvBoxes);
-
-				// classes
-				cvClasses = cvOutputData.col(1).clone();
-
-				// scores
-				cvScores = cvOutputData.col(2).clone();
-
-				boxes = cvBoxes.ptr<float>(0);
-				classes = cvClasses.ptr<float>(0);
-				scores = cvScores.ptr<float>(0);
-			} else {
-				boxes = reinterpret_cast<float *>(outputTensorInfo.data[0]);
-				classes = reinterpret_cast<float *>(outputTensorInfo.data[1]);
-				scores = reinterpret_cast<float *>(outputTensorInfo.data[2]);
-				number_of_detections = (int) (*reinterpret_cast<float *>(outputTensorInfo.data[3]));
+			std::vector<int> boxIndexes = outputMeta.GetBoxDimInfo().GetValidIndexAll();
+			if (boxIndexes.size() != 1) {
+				LOGE("Invalid dim size. It should be 1");
+				return MEDIA_VISION_ERROR_INVALID_OPERATION;
 			}
+			boxOffset = mOutputLayerProperty.layers[outputMeta.GetBoxName()].shape[boxIndexes[0]];
 
-			LOGI("number_of_detections = %d", number_of_detections);
-
-			results->number_of_objects = 0;
-
-			for (int idx = 0; idx < number_of_detections; ++idx) {
-				if (scores[idx] < mConfig.mConfidenceThresHold)
-					continue;
-
-				int left = static_cast<int>(boxes[idx * 4 + 1] * mSourceSize.width);
-				int top = static_cast<int>(boxes[idx * 4 + 0] * mSourceSize.height);
-				int right = static_cast<int>(boxes[idx * 4 + 3] * mSourceSize.width);
-				int bottom = static_cast<int>(boxes[idx * 4 + 2] * mSourceSize.height);
-				cv::Rect loc;
-
-				loc.x = left;
-				loc.y = top;
-				loc.width = right - left + 1;
-				loc.height = bottom - top + 1;
-
-				results->indices.push_back(static_cast<int>(classes[idx]));
-				results->confidences.push_back(scores[idx]);
-				results->names.push_back(
-						mUserListName[static_cast<int>(classes[idx])]);
-				results->locations.push_back(loc);
-				results->number_of_objects++;
-
-				LOGI("objectClass: %d", static_cast<int>(classes[idx]));
-				LOGI("confidence:%f", scores[idx]);
-				LOGI("left:%d, top:%d, right:%d, bottom:%d", left, top, right,
-					bottom);
+			std::vector<int> scoreIndexes = outputMeta.GetScoreDimInfo().GetValidIndexAll();
+			if (scoreIndexes.size() != 1) {
+				LOGE("Invaid dim size. It should be 1");
+				return MEDIA_VISION_ERROR_INVALID_OPERATION;
 			}
-
-			LOGI("Inference: GetObjectDetectionResults: %d\n", results->number_of_objects);
+			numberOfFaces = mOutputLayerProperty.layers[outputMeta.GetScoreName()].shape[scoreIndexes[0]];
 		}
 
-		return MEDIA_VISION_ERROR_NONE;
-	}
+		ObjectDecoder objDecoder(mOutputTensorBuffers, outputMeta, boxOffset,
+								 static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getWidth()),
+								 static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getHeight()),
+								 numberOfFaces);
 
-	int Inference::GetFaceDetectionResults(FaceDetectionResults *results)
-	{
-		if (mMetadata.GetOutputMeta().IsParsed()) {
-			OutputMetadata& outputMeta = mMetadata.GetOutputMeta();
+		objDecoder.init();
+		objDecoder.decode();
+		results->number_of_faces = 0;
 
-			// decoding type
-			if (!mOutputTensorBuffers.exist(outputMeta.GetBoxName()) ||
-				!mOutputTensorBuffers.exist(outputMeta.GetScoreName())){
-				LOGE("output buffers named of %s or %s are NULL",
-					outputMeta.GetBoxName().c_str(), outputMeta.GetScoreName().c_str());
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
-
-			int boxOffset = 0;
-			int numberOfFaces = 0;
-
-			if (outputMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_BYPASS) {
-				std::vector<int> boxIndexes = outputMeta.GetBoxDimInfo().GetValidIndexAll();
-				if (boxIndexes.size() != 1) {
-					LOGE("Invalid dim size. It should be 1");
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-				boxOffset = mOutputLayerProperty.layers[outputMeta.GetBoxName()].shape[boxIndexes[0]];
-			} else {
-				std::vector<int> boxIndexes = outputMeta.GetBoxDimInfo().GetValidIndexAll();
-				if (boxIndexes.size() != 1) {
-					LOGE("Invalid dim size. It should be 1");
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-				boxOffset = mOutputLayerProperty.layers[outputMeta.GetBoxName()].shape[boxIndexes[0]];
+		for (auto &face : objDecoder.getObjectAll()) {
+			results->confidences.push_back(face.score);
+			results->locations.push_back(
+					cv::Rect(static_cast<int>((face.location.x - face.location.width * 0.5f) *
+											  static_cast<float>(mSourceSize.width)),
+							 static_cast<int>((face.location.y - face.location.height * 0.5f) *
+											  static_cast<float>(mSourceSize.height)),
+							 static_cast<int>(face.location.width * static_cast<float>(mSourceSize.width)),
+							 static_cast<int>(face.location.height * static_cast<float>(mSourceSize.height))));
+			results->number_of_faces++;
+		}
 
-				std::vector<int> scoreIndexes = outputMeta.GetScoreDimInfo().GetValidIndexAll();
-				if (scoreIndexes.size() != 1) {
-					LOGE("Invaid dim size. It should be 1");
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-				numberOfFaces = mOutputLayerProperty.layers[outputMeta.GetScoreName()].shape[scoreIndexes[0]];
-			}
+		LOGE("Inference: GetFaceDetectionResults: %d\n", results->number_of_faces);
+	} else {
+		tensor_t outputTensorInfo;
 
-			ObjectDecoder objDecoder(mOutputTensorBuffers, outputMeta, boxOffset,
-						static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getWidth()),
-						static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getHeight()),
-						numberOfFaces);
-
-			objDecoder.init();
-			objDecoder.decode();
-			results->number_of_faces = 0;
-
-			for (auto& face : objDecoder.getObjectAll()) {
-				results->confidences.push_back(face.score);
-				results->locations.push_back(cv::Rect(
-						static_cast<int>((face.location.x -  face.location.width * 0.5f) * static_cast<float>(mSourceSize.width)),
-						static_cast<int>((face.location.y -  face.location.height * 0.5f) * static_cast<float>(mSourceSize.height)),
-						static_cast<int>(face.location.width *  static_cast<float>(mSourceSize.width)),
-						static_cast<int>(face.location.height * static_cast<float>(mSourceSize.height))));
-				results->number_of_faces++;
-			}
+		// Get inference result and contain it to outputTensorInfo.
+		int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
+		if (ret != MEDIA_VISION_ERROR_NONE) {
+			LOGE("Fail to get output result.");
+			return ret;
+		}
 
-			LOGE("Inference: GetFaceDetectionResults: %d\n", results->number_of_faces);
+		// In case of object detection,
+		// a model may apply post-process but others may not.
+		// Thus, those cases should be handled separately.
+
+		float *boxes = nullptr;
+		float *classes = nullptr;
+		float *scores = nullptr;
+		int number_of_detections = 0;
+		cv::Mat cvScores, cvClasses, cvBoxes;
+
+		if (outputTensorInfo.dimInfo.size() == 1) {
+			// there is no way to know how many objects are detect unless the number of objects aren't
+			// provided. In the case, each backend should provide the number of results manually.
+			// For example, in OpenCV, MobilenetV1-SSD doesn't provide it so the number of objects are
+			// written to the 1st element i.e., outputTensorInfo.data[0] (the shape is 1x1xNx7 and the 1st of 7
+			// indicates the image id. But it is useless if a batch mode isn't supported.
+			// So, use the 1st of 7.
+
+			number_of_detections = static_cast<int>(*reinterpret_cast<float *>(outputTensorInfo.data[0]));
+			cv::Mat cvOutputData(number_of_detections, outputTensorInfo.dimInfo[0][3], CV_32F,
+								 outputTensorInfo.data[0]);
+
+			// boxes
+			cv::Mat cvLeft = cvOutputData.col(3).clone();
+			cv::Mat cvTop = cvOutputData.col(4).clone();
+			cv::Mat cvRight = cvOutputData.col(5).clone();
+			cv::Mat cvBottom = cvOutputData.col(6).clone();
+			cv::Mat cvBoxElems[] = { cvTop, cvLeft, cvBottom, cvRight };
+			cv::hconcat(cvBoxElems, 4, cvBoxes);
+
+			// classes
+			cvClasses = cvOutputData.col(1).clone();
+
+			// scores
+			cvScores = cvOutputData.col(2).clone();
+
+			boxes = cvBoxes.ptr<float>(0);
+			classes = cvClasses.ptr<float>(0);
+			scores = cvScores.ptr<float>(0);
 		} else {
-			tensor_t outputTensorInfo;
-
-			// Get inference result and contain it to outputTensorInfo.
-			int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
-			if (ret != MEDIA_VISION_ERROR_NONE) {
-				LOGE("Fail to get output result.");
-				return ret;
-			}
+			boxes = reinterpret_cast<float *>(outputTensorInfo.data[0]);
+			classes = reinterpret_cast<float *>(outputTensorInfo.data[1]);
+			scores = reinterpret_cast<float *>(outputTensorInfo.data[2]);
+			number_of_detections = static_cast<int>(*reinterpret_cast<float *>(outputTensorInfo.data[3]));
+		}
 
-			// In case of object detection,
-			// a model may apply post-process but others may not.
-			// Thus, those cases should be handled separately.
+		results->number_of_faces = 0;
 
-			float *boxes = nullptr;
-			float *classes = nullptr;
-			float *scores = nullptr;
-			int number_of_detections = 0;
-			cv::Mat cvScores, cvClasses, cvBoxes;
+		for (int idx = 0; idx < number_of_detections; ++idx) {
+			if (scores[idx] < mConfig.mConfidenceThresHold)
+				continue;
 
-			if (outputTensorInfo.dimInfo.size() == 1) {
-				// there is no way to know how many objects are detect unless the number of objects aren't
-				// provided. In the case, each backend should provide the number of results manually.
-				// For example, in OpenCV, MobilenetV1-SSD doesn't provide it so the number of objects are
-				// written to the 1st element i.e., outputTensorInfo.data[0] (the shape is 1x1xNx7 and the 1st of 7
-				// indicates the image id. But it is useless if a batch mode isn't supported.
-				// So, use the 1st of 7.
-
-				number_of_detections = static_cast<int>(*reinterpret_cast<float *>(outputTensorInfo.data[0]));
-				cv::Mat cvOutputData(number_of_detections, outputTensorInfo.dimInfo[0][3], CV_32F, outputTensorInfo.data[0]);
-
-				// boxes
-				cv::Mat cvLeft = cvOutputData.col(3).clone();
-				cv::Mat cvTop = cvOutputData.col(4).clone();
-				cv::Mat cvRight = cvOutputData.col(5).clone();
-				cv::Mat cvBottom = cvOutputData.col(6).clone();
-				cv::Mat cvBoxElems[] = { cvTop, cvLeft, cvBottom, cvRight };
-				cv::hconcat(cvBoxElems, 4, cvBoxes);
-
-				// classes
-				cvClasses = cvOutputData.col(1).clone();
-
-				// scores
-				cvScores = cvOutputData.col(2).clone();
-
-				boxes = cvBoxes.ptr<float>(0);
-				classes = cvClasses.ptr<float>(0);
-				scores = cvScores.ptr<float>(0);
-			} else {
-				boxes = reinterpret_cast<float *>(outputTensorInfo.data[0]);
-				classes = reinterpret_cast<float *>(outputTensorInfo.data[1]);
-				scores = reinterpret_cast<float *>(outputTensorInfo.data[2]);
-				number_of_detections = static_cast<int>(*reinterpret_cast<float *>(outputTensorInfo.data[3]));
-			}
+			int left = static_cast<int>(boxes[idx * 4 + 1] * mSourceSize.width);
+			int top = static_cast<int>(boxes[idx * 4 + 0] * mSourceSize.height);
+			int right = static_cast<int>(boxes[idx * 4 + 3] * mSourceSize.width);
+			int bottom = static_cast<int>(boxes[idx * 4 + 2] * mSourceSize.height);
+			cv::Rect loc;
 
-			results->number_of_faces = 0;
-
-			for (int idx = 0; idx < number_of_detections; ++idx) {
-				if (scores[idx] < mConfig.mConfidenceThresHold)
-					continue;
-
-				int left = static_cast<int>(boxes[idx * 4 + 1] * mSourceSize.width);
-				int top = static_cast<int>(boxes[idx * 4 + 0] * mSourceSize.height);
-				int right = static_cast<int>(boxes[idx * 4 + 3] * mSourceSize.width);
-				int bottom = static_cast<int>(boxes[idx * 4 + 2] * mSourceSize.height);
-				cv::Rect loc;
-
-				loc.x = left;
-				loc.y = top;
-				loc.width = right - left + 1;
-				loc.height = bottom - top + 1;
-				results->confidences.push_back(scores[idx]);
-				results->locations.push_back(loc);
-				results->number_of_faces++;
-
-				LOGI("confidence:%f", scores[idx]);
-				LOGI("class: %f", classes[idx]);
-				LOGI("left:%f, top:%f, right:%f, bottom:%f", boxes[idx * 4 + 1],
-					boxes[idx * 4 + 0], boxes[idx * 4 + 3], boxes[idx * 4 + 2]);
-				LOGI("left:%d, top:%d, right:%d, bottom:%d", left, top, right, bottom);
-			}
+			loc.x = left;
+			loc.y = top;
+			loc.width = right - left + 1;
+			loc.height = bottom - top + 1;
+			results->confidences.push_back(scores[idx]);
+			results->locations.push_back(loc);
+			results->number_of_faces++;
 
-			LOGE("Inference: GetFaceDetectionResults: %d\n", results->number_of_faces);
+			LOGI("confidence:%f", scores[idx]);
+			LOGI("class: %f", classes[idx]);
+			LOGI("left:%f, top:%f, right:%f, bottom:%f", boxes[idx * 4 + 1], boxes[idx * 4 + 0], boxes[idx * 4 + 3],
+				 boxes[idx * 4 + 2]);
+			LOGI("left:%d, top:%d, right:%d, bottom:%d", left, top, right, bottom);
 		}
 
-		return MEDIA_VISION_ERROR_NONE;
+		LOGE("Inference: GetFaceDetectionResults: %d\n", results->number_of_faces);
 	}
 
-	int Inference::GetFacialLandMarkDetectionResults(FacialLandMarkDetectionResults *results)
-	{
-		LOGI("ENTER");
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		if (mMetadata.GetOutputMeta().IsParsed()) {
-			OutputMetadata& outputMeta = mMetadata.GetOutputMeta();
+int Inference::GetFacialLandMarkDetectionResults(FacialLandMarkDetectionResults *results)
+{
+	LOGI("ENTER");
 
-			if (!mOutputTensorBuffers.exist(outputMeta.GetLandmarkName()) ||
-				!mOutputTensorBuffers.exist(outputMeta.GetScoreName())) {
-				LOGE("output buffers named of %s or %s are NULL",
-					outputMeta.GetLandmarkName().c_str(), outputMeta.GetScoreName().c_str());
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
+	if (mMetadata.GetOutputMeta().IsParsed()) {
+		OutputMetadata &outputMeta = mMetadata.GetOutputMeta();
 
-			int heatMapWidth = 0;
-			int heatMapHeight = 0;
-			int heatMapChannel = 0;
-			std::vector<int> channelIndexes = outputMeta.GetLandmarkDimInfo().GetValidIndexAll();
-			int number_of_landmarks = heatMapChannel;
-
-			if (outputMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS) {
-				LOGI("landmark dim size: %zd and idx[0] is %d", channelIndexes.size(), channelIndexes[0]);
-				number_of_landmarks = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()].shape[channelIndexes[0]]
-									/ outputMeta.GetLandmarkOffset();
-			} else if (outputMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS_MULTICHANNEL) {
-				number_of_landmarks = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()].shape[channelIndexes[0]];
-			} else {
-				heatMapWidth = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()].shape[outputMeta.GetLandmarkHeatMapInfo().wIdx];
-				heatMapHeight = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()].shape[outputMeta.GetLandmarkHeatMapInfo().hIdx];
-				heatMapChannel = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()].shape[outputMeta.GetLandmarkHeatMapInfo().cIdx];
-			}
+		if (!mOutputTensorBuffers.exist(outputMeta.GetLandmarkName()) ||
+			!mOutputTensorBuffers.exist(outputMeta.GetScoreName())) {
+			LOGE("output buffers named of %s or %s are NULL", outputMeta.GetLandmarkName().c_str(),
+				 outputMeta.GetScoreName().c_str());
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
+		}
 
-			LOGI("heatMap: w[%d], h[%d], c[%d]", heatMapWidth, heatMapHeight, heatMapChannel);
+		int heatMapWidth = 0;
+		int heatMapHeight = 0;
+		int heatMapChannel = 0;
+		std::vector<int> channelIndexes = outputMeta.GetLandmarkDimInfo().GetValidIndexAll();
+		int number_of_landmarks = heatMapChannel;
 
-			// decoding
-			PoseDecoder poseDecoder(mOutputTensorBuffers, outputMeta,
-									heatMapWidth, heatMapHeight, heatMapChannel,
-									number_of_landmarks);
+		if (outputMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS) {
+			LOGI("landmark dim size: %zd and idx[0] is %d", channelIndexes.size(), channelIndexes[0]);
+			number_of_landmarks = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()].shape[channelIndexes[0]] /
+								  outputMeta.GetLandmarkOffset();
+		} else if (outputMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS_MULTICHANNEL) {
+			number_of_landmarks = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()].shape[channelIndexes[0]];
+		} else {
+			heatMapWidth = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()]
+								   .shape[outputMeta.GetLandmarkHeatMapInfo().wIdx];
+			heatMapHeight = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()]
+									.shape[outputMeta.GetLandmarkHeatMapInfo().hIdx];
+			heatMapChannel = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()]
+									 .shape[outputMeta.GetLandmarkHeatMapInfo().cIdx];
+		}
 
-			// initialize decorder queue with landmarks to be decoded.
-			int ret = poseDecoder.init();
-			if (ret != MEDIA_VISION_ERROR_NONE) {
-				LOGE("Fail to init poseDecoder");
-				return ret;
-			}
+		LOGI("heatMap: w[%d], h[%d], c[%d]", heatMapWidth, heatMapHeight, heatMapChannel);
 
-			float inputW = 1.f;
-			float inputH = 1.f;
+		// decoding
+		PoseDecoder poseDecoder(mOutputTensorBuffers, outputMeta, heatMapWidth, heatMapHeight, heatMapChannel,
+								number_of_landmarks);
 
-			if (outputMeta.GetLandmarkCoordinate() == INFERENCE_LANDMARK_COORDINATE_TYPE_PIXEL) {
-				inputW = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getWidth());
-				inputH = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getHeight());
-			}
+		// initialize decorder queue with landmarks to be decoded.
+		int ret = poseDecoder.init();
+		if (ret != MEDIA_VISION_ERROR_NONE) {
+			LOGE("Fail to init poseDecoder");
+			return ret;
+		}
+
+		float inputW = 1.f;
+		float inputH = 1.f;
+
+		if (outputMeta.GetLandmarkCoordinate() == INFERENCE_LANDMARK_COORDINATE_TYPE_PIXEL) {
+			inputW = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getWidth());
+			inputH = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getHeight());
+		}
 
-			float thresRadius = outputMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE ? 0.0 :
-														outputMeta.GetLandmarkHeatMapInfo().nmsRadius;
+		float thresRadius = outputMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE ?
+									0.0 :
+									outputMeta.GetLandmarkHeatMapInfo().nmsRadius;
 
-			poseDecoder.decode(inputW, inputH, thresRadius);
+		poseDecoder.decode(inputW, inputH, thresRadius);
 
-			for (int landmarkIndex = 0; landmarkIndex < number_of_landmarks; landmarkIndex++) {
-				results->locations.push_back(
+		for (int landmarkIndex = 0; landmarkIndex < number_of_landmarks; landmarkIndex++) {
+			results->locations.push_back(
 					cv::Point(poseDecoder.getPointX(0, landmarkIndex) * static_cast<float>(mSourceSize.width),
 							  poseDecoder.getPointY(0, landmarkIndex) * static_cast<float>(mSourceSize.height)));
-			}
+		}
 
-			results->number_of_landmarks = results->locations.size();
-		} else {
-			tensor_t outputTensorInfo;
+		results->number_of_landmarks = results->locations.size();
+	} else {
+		tensor_t outputTensorInfo;
 
-			// Get inference result and contain it to outputTensorInfo.
-			int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
-			if (ret != MEDIA_VISION_ERROR_NONE) {
-				LOGE("Fail to get output result.");
-				return ret;
-			}
+		// Get inference result and contain it to outputTensorInfo.
+		int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
+		if (ret != MEDIA_VISION_ERROR_NONE) {
+			LOGE("Fail to get output result.");
+			return ret;
+		}
 
-			int number_of_detections = outputTensorInfo.dimInfo[0][1] >> 1;
+		int number_of_detections = outputTensorInfo.dimInfo[0][1] >> 1;
 
-			results->number_of_landmarks = number_of_detections;
-			results->locations.resize(number_of_detections);
+		results->number_of_landmarks = number_of_detections;
+		results->locations.resize(number_of_detections);
 
-			LOGI("imgW:%d, imgH:%d", mSourceSize.width, mSourceSize.height);
+		LOGI("imgW:%d, imgH:%d", mSourceSize.width, mSourceSize.height);
 
-			float *loc = reinterpret_cast<float *>(outputTensorInfo.data[0]);
+		float *loc = reinterpret_cast<float *>(outputTensorInfo.data[0]);
 
-			for (auto& point : results->locations) {
-				point.x = static_cast<int>(*loc++ * mSourceSize.width);
-				point.y = static_cast<int>(*loc++ * mSourceSize.height);
+		for (auto &point : results->locations) {
+			point.x = static_cast<int>(*loc++ * mSourceSize.width);
+			point.y = static_cast<int>(*loc++ * mSourceSize.height);
 
-				LOGI("x:%d, y:%d", point.x, point.y);
-			}
+			LOGI("x:%d, y:%d", point.x, point.y);
 		}
-
-		LOGI("Inference: FacialLandmarkDetectionResults: %d\n",
-			 results->number_of_landmarks);
-		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	int Inference::GetPoseLandmarkDetectionResults(
-			std::unique_ptr<mv_inference_pose_s> &detectionResults, int width, int height)
-	{
-		LOGI("ENTER");
+	LOGI("Inference: FacialLandmarkDetectionResults: %d\n", results->number_of_landmarks);
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		auto poseResult = std::make_unique<mv_inference_pose_s>();
+int Inference::GetPoseLandmarkDetectionResults(std::unique_ptr<mv_inference_pose_s> &detectionResults, int width,
+											   int height)
+{
+	LOGI("ENTER");
 
-		if (mMetadata.GetOutputMeta().IsParsed()) {
-			OutputMetadata& outputMeta = mMetadata.GetOutputMeta();
+	auto poseResult = std::make_unique<mv_inference_pose_s>();
 
-			if (!mOutputTensorBuffers.exist(outputMeta.GetLandmarkName()) ||
-				!mOutputTensorBuffers.exist(outputMeta.GetScoreName())) {
-				LOGE("output buffers named of %s or %s are NULL",
-					outputMeta.GetLandmarkName().c_str(), outputMeta.GetScoreName().c_str());
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
+	if (mMetadata.GetOutputMeta().IsParsed()) {
+		OutputMetadata &outputMeta = mMetadata.GetOutputMeta();
 
-			int heatMapWidth = 0;
-			int heatMapHeight = 0;
-			int heatMapChannel = 0;
+		if (!mOutputTensorBuffers.exist(outputMeta.GetLandmarkName()) ||
+			!mOutputTensorBuffers.exist(outputMeta.GetScoreName())) {
+			LOGE("output buffers named of %s or %s are NULL", outputMeta.GetLandmarkName().c_str(),
+				 outputMeta.GetScoreName().c_str());
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
+		}
 
-			if (outputMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP ||
-				outputMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP_REFINE) {
-				heatMapWidth = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()].shape[outputMeta.GetLandmarkHeatMapInfo().wIdx];
-				heatMapHeight = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()].shape[outputMeta.GetLandmarkHeatMapInfo().hIdx];
-				heatMapChannel = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()].shape[outputMeta.GetLandmarkHeatMapInfo().cIdx];
-			}
+		int heatMapWidth = 0;
+		int heatMapHeight = 0;
+		int heatMapChannel = 0;
 
-			LOGI("heatMap: w[%d], h[%d], c[%d]", heatMapWidth, heatMapHeight, heatMapChannel);
+		if (outputMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP ||
+			outputMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP_REFINE) {
+			heatMapWidth = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()]
+								   .shape[outputMeta.GetLandmarkHeatMapInfo().wIdx];
+			heatMapHeight = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()]
+									.shape[outputMeta.GetLandmarkHeatMapInfo().hIdx];
+			heatMapChannel = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()]
+									 .shape[outputMeta.GetLandmarkHeatMapInfo().cIdx];
+		}
 
-			std::vector<int> channelIndexes = outputMeta.GetLandmarkDimInfo().GetValidIndexAll();
+		LOGI("heatMap: w[%d], h[%d], c[%d]", heatMapWidth, heatMapHeight, heatMapChannel);
 
-			// If INFERENCE_LANDMARK_DECODING_TYPE_BYPASS,
-			// the landmarkChannel is guessed from the shape of the landmark output tensor.
-			// Otherwise, it is guessed from the heatMapChannel. (heatMapChannel is used in default).
-			int landmarkChannel = heatMapChannel;
+		std::vector<int> channelIndexes = outputMeta.GetLandmarkDimInfo().GetValidIndexAll();
 
-			if (outputMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS)
-				landmarkChannel = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()].shape[channelIndexes[0]] / outputMeta.GetLandmarkOffset();
-			else if (outputMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS_MULTICHANNEL)
-				landmarkChannel = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()].shape[channelIndexes[0]];
+		// If INFERENCE_LANDMARK_DECODING_TYPE_BYPASS,
+		// the landmarkChannel is guessed from the shape of the landmark output tensor.
+		// Otherwise, it is guessed from the heatMapChannel. (heatMapChannel is used in default).
+		int landmarkChannel = heatMapChannel;
 
-			poseResult->number_of_landmarks_per_pose = mUserListName.empty() ? landmarkChannel :
-														static_cast<int>(mUserListName.size());
+		if (outputMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS)
+			landmarkChannel = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()].shape[channelIndexes[0]] /
+							  outputMeta.GetLandmarkOffset();
+		else if (outputMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS_MULTICHANNEL)
+			landmarkChannel = mOutputLayerProperty.layers[outputMeta.GetLandmarkName()].shape[channelIndexes[0]];
 
-			LOGE("number of landmarks per pose: %d", poseResult->number_of_landmarks_per_pose );
+		poseResult->number_of_landmarks_per_pose = mUserListName.empty() ? landmarkChannel :
+																		   static_cast<int>(mUserListName.size());
 
-			if (poseResult->number_of_landmarks_per_pose >= MAX_NUMBER_OF_LANDMARKS_PER_POSE) {
-				LOGE("Exceeded maxinum number of landmarks per pose(%d >= %d).",
-					poseResult->number_of_landmarks_per_pose, MAX_NUMBER_OF_LANDMARKS_PER_POSE);
-				return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-			}
+		LOGE("number of landmarks per pose: %d", poseResult->number_of_landmarks_per_pose);
 
-			// decoding
-			PoseDecoder poseDecoder(mOutputTensorBuffers, outputMeta,
-									heatMapWidth, heatMapHeight, heatMapChannel,
-									poseResult->number_of_landmarks_per_pose);
+		if (poseResult->number_of_landmarks_per_pose >= MAX_NUMBER_OF_LANDMARKS_PER_POSE) {
+			LOGE("Exceeded maxinum number of landmarks per pose(%d >= %d).", poseResult->number_of_landmarks_per_pose,
+				 MAX_NUMBER_OF_LANDMARKS_PER_POSE);
+			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+		}
 
-			// initialize decorder queue with landmarks to be decoded.
-			int ret = poseDecoder.init();
-			if (ret != MEDIA_VISION_ERROR_NONE) {
-				LOGE("Fail to init poseDecoder");
-				return ret;
-			}
+		// decoding
+		PoseDecoder poseDecoder(mOutputTensorBuffers, outputMeta, heatMapWidth, heatMapHeight, heatMapChannel,
+								poseResult->number_of_landmarks_per_pose);
 
-			float inputW = 1.f;
-			float inputH = 1.f;
-			float thresRadius = outputMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE ? 0.0 :
-														outputMeta.GetLandmarkHeatMapInfo().nmsRadius;
-			if (outputMeta.GetLandmarkCoordinate() == INFERENCE_LANDMARK_COORDINATE_TYPE_PIXEL) {
-				inputW = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getWidth());
-				inputH = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getHeight());
-			}
+		// initialize decorder queue with landmarks to be decoded.
+		int ret = poseDecoder.init();
+		if (ret != MEDIA_VISION_ERROR_NONE) {
+			LOGE("Fail to init poseDecoder");
+			return ret;
+		}
 
-			poseDecoder.decode(inputW, inputH, thresRadius);
-			poseResult->number_of_poses = poseDecoder.getNumberOfPose();
-
-			for (int poseIndex = 0; poseIndex < poseResult->number_of_poses; ++poseIndex) {
-				for (int landmarkIndex = 0; landmarkIndex < poseResult->number_of_landmarks_per_pose; ++ landmarkIndex) {
-					int part = landmarkIndex;
-					if (!mUserListName.empty()) {
-						part = std::stoi(mUserListName[landmarkIndex]) - 1;
-						if (part < 0) {
-							continue;
-						}
-					}
+		float inputW = 1.f;
+		float inputH = 1.f;
+		float thresRadius = outputMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE ?
+									0.0 :
+									outputMeta.GetLandmarkHeatMapInfo().nmsRadius;
+		if (outputMeta.GetLandmarkCoordinate() == INFERENCE_LANDMARK_COORDINATE_TYPE_PIXEL) {
+			inputW = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getWidth());
+			inputH = static_cast<float>(mMetadata.GetInputMeta().GetLayer().begin()->second.getHeight());
+		}
 
-					poseResult->landmarks[poseIndex][landmarkIndex].isAvailable = true;
-					poseResult->landmarks[poseIndex][landmarkIndex].point.x =
-										poseDecoder.getPointX(poseIndex, part) * static_cast<float>(mSourceSize.width);
-					poseResult->landmarks[poseIndex][landmarkIndex].point.y =
-										poseDecoder.getPointY(poseIndex, part) * static_cast<float>(mSourceSize.height);
-					poseResult->landmarks[poseIndex][landmarkIndex].label = landmarkIndex;
-					poseResult->landmarks[poseIndex][landmarkIndex].score =
-										poseDecoder.getScore(poseIndex, part);
+		poseDecoder.decode(inputW, inputH, thresRadius);
+		poseResult->number_of_poses = poseDecoder.getNumberOfPose();
+
+		for (int poseIndex = 0; poseIndex < poseResult->number_of_poses; ++poseIndex) {
+			for (int landmarkIndex = 0; landmarkIndex < poseResult->number_of_landmarks_per_pose; ++landmarkIndex) {
+				int part = landmarkIndex;
+				if (!mUserListName.empty()) {
+					part = std::stoi(mUserListName[landmarkIndex]) - 1;
+					if (part < 0) {
+						continue;
+					}
 				}
+
+				poseResult->landmarks[poseIndex][landmarkIndex].isAvailable = true;
+				poseResult->landmarks[poseIndex][landmarkIndex].point.x =
+						poseDecoder.getPointX(poseIndex, part) * static_cast<float>(mSourceSize.width);
+				poseResult->landmarks[poseIndex][landmarkIndex].point.y =
+						poseDecoder.getPointY(poseIndex, part) * static_cast<float>(mSourceSize.height);
+				poseResult->landmarks[poseIndex][landmarkIndex].label = landmarkIndex;
+				poseResult->landmarks[poseIndex][landmarkIndex].score = poseDecoder.getScore(poseIndex, part);
 			}
+		}
 
-			detectionResults = std::move(poseResult);
-		} else {
-			tensor_t outputTensorInfo;
+		detectionResults = std::move(poseResult);
+	} else {
+		tensor_t outputTensorInfo;
 
-			// Get inference result and contain it to outputTensorInfo.
-			int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
-			if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to get output result.");
-					return ret;
-			}
+		// Get inference result and contain it to outputTensorInfo.
+		int ret = mOutputTensorBuffers.GetTensorInfo(mOutputLayerProperty, outputTensorInfo);
+		if (ret != MEDIA_VISION_ERROR_NONE) {
+			LOGE("Fail to get output result.");
+			return ret;
+		}
 
-			cv::Mat reShapeTest(cv::Size(outputTensorInfo.dimInfo[0][2], outputTensorInfo.dimInfo[0][1]),
-										 CV_32FC(outputTensorInfo.dimInfo[0][3]), outputTensorInfo.data[0]);
-			cv::Mat multiChannels[outputTensorInfo.dimInfo[0][3]];
+		cv::Mat reShapeTest(cv::Size(outputTensorInfo.dimInfo[0][2], outputTensorInfo.dimInfo[0][1]),
+							CV_32FC(outputTensorInfo.dimInfo[0][3]), outputTensorInfo.data[0]);
+		cv::Mat multiChannels[outputTensorInfo.dimInfo[0][3]];
 
-			split(reShapeTest, multiChannels);
+		split(reShapeTest, multiChannels);
 
-			float ratioX = static_cast<float>(outputTensorInfo.dimInfo[0][2]);
-			float ratioY = static_cast<float>(outputTensorInfo.dimInfo[0][1]);
+		float ratioX = static_cast<float>(outputTensorInfo.dimInfo[0][2]);
+		float ratioY = static_cast<float>(outputTensorInfo.dimInfo[0][1]);
 
-			poseResult->number_of_poses = 1;
-			poseResult->number_of_landmarks_per_pose = outputTensorInfo.dimInfo[0][3];
+		poseResult->number_of_poses = 1;
+		poseResult->number_of_landmarks_per_pose = outputTensorInfo.dimInfo[0][3];
 
-			if (poseResult->number_of_landmarks_per_pose >= MAX_NUMBER_OF_LANDMARKS_PER_POSE) {
-				LOGE("Exeeded maxinum number of landmarks per pose(%d >= %d).",
-					poseResult->number_of_landmarks_per_pose, MAX_NUMBER_OF_LANDMARKS_PER_POSE);
-				return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-			}
+		if (poseResult->number_of_landmarks_per_pose >= MAX_NUMBER_OF_LANDMARKS_PER_POSE) {
+			LOGE("Exeeded maxinum number of landmarks per pose(%d >= %d).", poseResult->number_of_landmarks_per_pose,
+				 MAX_NUMBER_OF_LANDMARKS_PER_POSE);
+			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+		}
 
-			for (int poseIndex = 0; poseIndex < poseResult->number_of_poses; ++poseIndex) {
-				for (int landmarkIndex = 0; landmarkIndex < poseResult->number_of_landmarks_per_pose; landmarkIndex++) {
-					int part = landmarkIndex;
-					if (!mUserListName.empty()) {
-						part = std::stoi(mUserListName[landmarkIndex]) - 1;
-						if (part < 0) {
-							continue;
-						}
+		for (int poseIndex = 0; poseIndex < poseResult->number_of_poses; ++poseIndex) {
+			for (int landmarkIndex = 0; landmarkIndex < poseResult->number_of_landmarks_per_pose; landmarkIndex++) {
+				int part = landmarkIndex;
+				if (!mUserListName.empty()) {
+					part = std::stoi(mUserListName[landmarkIndex]) - 1;
+					if (part < 0) {
+						continue;
 					}
+				}
 
-					cv::Mat heatMap = multiChannels[part];
-					double score;
-					cv::Point loc;
-					cv::Point2f loc2f;
-					cv::Mat blurredHeatMap;
+				cv::Mat heatMap = multiChannels[part];
+				double score;
+				cv::Point loc;
+				cv::Point2f loc2f;
+				cv::Mat blurredHeatMap;
 
-					cv::GaussianBlur(heatMap, blurredHeatMap, cv::Size(), 5.0, 5.0);
-					cv::minMaxLoc(heatMap, NULL, &score, NULL, &loc);
+				cv::GaussianBlur(heatMap, blurredHeatMap, cv::Size(), 5.0, 5.0);
+				cv::minMaxLoc(heatMap, NULL, &score, NULL, &loc);
 
-					loc2f.x = (static_cast<float>(loc.x) / ratioX);
-					loc2f.y = (static_cast<float>(loc.y) / ratioY);
+				loc2f.x = (static_cast<float>(loc.x) / ratioX);
+				loc2f.y = (static_cast<float>(loc.y) / ratioY);
 
-					LOGI("landmarkIndex[%2d] - mapping to [%2d]: x[%.3f], y[%.3f], score[%.3f]",
-							landmarkIndex, part, loc2f.x, loc2f.y, score);
+				LOGI("landmarkIndex[%2d] - mapping to [%2d]: x[%.3f], y[%.3f], score[%.3f]", landmarkIndex, part,
+					 loc2f.x, loc2f.y, score);
 
-					poseResult->landmarks[poseIndex][landmarkIndex].isAvailable = true;
-					poseResult->landmarks[poseIndex][landmarkIndex].point.x = static_cast<int>(static_cast<float>(width) * loc2f.x);
-					poseResult->landmarks[poseIndex][landmarkIndex].point.y = static_cast<int>(static_cast<float>(height) * loc2f.y);
-					poseResult->landmarks[poseIndex][landmarkIndex].score = score;
-					poseResult->landmarks[poseIndex][landmarkIndex].label = -1;
-				}
+				poseResult->landmarks[poseIndex][landmarkIndex].isAvailable = true;
+				poseResult->landmarks[poseIndex][landmarkIndex].point.x =
+						static_cast<int>(static_cast<float>(width) * loc2f.x);
+				poseResult->landmarks[poseIndex][landmarkIndex].point.y =
+						static_cast<int>(static_cast<float>(height) * loc2f.y);
+				poseResult->landmarks[poseIndex][landmarkIndex].score = score;
+				poseResult->landmarks[poseIndex][landmarkIndex].label = -1;
 			}
-
-			detectionResults = std::move(poseResult);
 		}
 
-		return MEDIA_VISION_ERROR_NONE;
+		detectionResults = std::move(poseResult);
 	}
 
+	return MEDIA_VISION_ERROR_NONE;
+}
+
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/src/InferenceIni.cpp b/mv_machine_learning/inference/src/InferenceIni.cpp
index 7dc5fa5..a0c978f 100644
--- a/mv_machine_learning/inference/src/InferenceIni.cpp
+++ b/mv_machine_learning/inference/src/InferenceIni.cpp
@@ -25,80 +25,72 @@ namespace mediavision
 {
 namespace inference
 {
-	const std::string INFERENCE_INI_FILENAME =
-			"/inference/inference_engine.ini";
-
-	static inline std::string &rtrim(std::string &s,
-									 const char *t = " \t\n\r\f\v")
-	{
-		s.erase(s.find_last_not_of(t) + 1);
-		return s;
-	}
+const std::string INFERENCE_INI_FILENAME = "/inference/inference_engine.ini";
 
-	static inline std::string &ltrim(std::string &s,
-									 const char *t = " \t\n\r\f\v")
-	{
-		s.erase(s.find_first_not_of(t) + 1);
-		return s;
-	}
+static inline std::string &rtrim(std::string &s, const char *t = " \t\n\r\f\v")
+{
+	s.erase(s.find_last_not_of(t) + 1);
+	return s;
+}
 
-	static inline std::string &trim(std::string &s,
-									const char *t = " \t\n\r\f\v")
-	{
-		return ltrim(rtrim(s, t), t);
-	}
+static inline std::string &ltrim(std::string &s, const char *t = " \t\n\r\f\v")
+{
+	s.erase(s.find_first_not_of(t) + 1);
+	return s;
+}
 
-	InferenceInI::InferenceInI()
-			: mIniDefaultPath(SYSCONFDIR)
-			, mDefaultBackend("OPENCV")
-			, mDelimeter(",")
-	{
-		mIniDefaultPath += INFERENCE_INI_FILENAME;
-	}
+static inline std::string &trim(std::string &s, const char *t = " \t\n\r\f\v")
+{
+	return ltrim(rtrim(s, t), t);
+}
+
+InferenceInI::InferenceInI() : mIniDefaultPath(SYSCONFDIR), mDefaultBackend("OPENCV"), mDelimeter(",")
+{
+	mIniDefaultPath += INFERENCE_INI_FILENAME;
+}
 
-	InferenceInI::~InferenceInI()
-	{}
-
-	int InferenceInI::LoadInI()
-	{
-		LOGI("ENTER");
-		dictionary *dict = iniparser_load(mIniDefaultPath.c_str());
-		if (dict == NULL) {
-			LOGE("Fail to load ini");
-			return -1;
-		}
-
-		std::string list = std::string(iniparser_getstring(
-				dict, "inference backend:supported backend types",
-				(char *) mDefaultBackend.c_str()));
-
-		size_t pos = 0;
-		while ((pos = list.find(mDelimeter)) != std::string::npos) {
-			std::string tmp = list.substr(0, pos);
-			mSupportedInferenceBackend.push_back(atoi(tmp.c_str()));
-
-			list.erase(0, pos + mDelimeter.length());
-		}
-		mSupportedInferenceBackend.push_back(atoi(list.c_str()));
-
-		if (dict) {
-			iniparser_freedict(dict);
-			dict = NULL;
-		}
-
-		LOGI("LEAVE");
-		return 0;
+InferenceInI::~InferenceInI()
+{}
+
+int InferenceInI::LoadInI()
+{
+	LOGI("ENTER");
+	dictionary *dict = iniparser_load(mIniDefaultPath.c_str());
+	if (dict == NULL) {
+		LOGE("Fail to load ini");
+		return -1;
 	}
 
-	void InferenceInI::UnLoadInI()
-	{
-		;
+	std::string list = std::string(
+			iniparser_getstring(dict, "inference backend:supported backend types", (char *) mDefaultBackend.c_str()));
+
+	size_t pos = 0;
+	while ((pos = list.find(mDelimeter)) != std::string::npos) {
+		std::string tmp = list.substr(0, pos);
+		mSupportedInferenceBackend.push_back(atoi(tmp.c_str()));
+
+		list.erase(0, pos + mDelimeter.length());
 	}
+	mSupportedInferenceBackend.push_back(atoi(list.c_str()));
 
-	std::vector<int> InferenceInI::GetSupportedInferenceEngines()
-	{
-		return mSupportedInferenceBackend;
+	if (dict) {
+		iniparser_freedict(dict);
+		dict = NULL;
 	}
 
+	LOGI("LEAVE");
+	return 0;
+}
+
+void InferenceInI::UnLoadInI()
+{
+	;
+}
+
+std::vector<int> InferenceInI::GetSupportedInferenceEngines()
+{
+	return mSupportedInferenceBackend;
+}
+
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/src/InputMetadata.cpp b/mv_machine_learning/inference/src/InputMetadata.cpp
index 22b8383..a2bbceb 100644
--- a/mv_machine_learning/inference/src/InputMetadata.cpp
+++ b/mv_machine_learning/inference/src/InputMetadata.cpp
@@ -29,181 +29,177 @@ namespace mediavision
 {
 namespace inference
 {
-	InputMetadata::InputMetadata() :
-			parsed(false),
-			layer(),
-			option()
-	{
-		// shape_type
-		mSupportedShapeType.insert({"NCHW", INFERENCE_TENSOR_SHAPE_NCHW});
-		mSupportedShapeType.insert({"NHWC", INFERENCE_TENSOR_SHAPE_NHWC});
-
-		// data_type
-		mSupportedDataType.insert({"FLOAT32", MV_INFERENCE_DATA_FLOAT32});
-		mSupportedDataType.insert({"UINT8", MV_INFERENCE_DATA_UINT8});
-
-		// color_space
-		mSupportedColorSpace.insert({"RGB888", MEDIA_VISION_COLORSPACE_RGB888});
-		mSupportedColorSpace.insert({"GRAY8", MEDIA_VISION_COLORSPACE_Y800});
-	}
+InputMetadata::InputMetadata() : parsed(false), layer(), option()
+{
+	// shape_type
+	mSupportedShapeType.insert({ "NCHW", INFERENCE_TENSOR_SHAPE_NCHW });
+	mSupportedShapeType.insert({ "NHWC", INFERENCE_TENSOR_SHAPE_NHWC });
 
-	int InputMetadata::GetTensorInfo(JsonObject *root)
-	{
-		LOGI("ENTER");
+	// data_type
+	mSupportedDataType.insert({ "FLOAT32", MV_INFERENCE_DATA_FLOAT32 });
+	mSupportedDataType.insert({ "UINT8", MV_INFERENCE_DATA_UINT8 });
 
-		if (!json_object_has_member(root, "tensor_info")) {
-			LOGE("No tensor_info inputmetadata");
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
+	// color_space
+	mSupportedColorSpace.insert({ "RGB888", MEDIA_VISION_COLORSPACE_RGB888 });
+	mSupportedColorSpace.insert({ "GRAY8", MEDIA_VISION_COLORSPACE_Y800 });
+}
 
-		// tensor_info
-		int ret = MEDIA_VISION_ERROR_NONE;
-		JsonArray * rootArray = json_object_get_array_member(root, "tensor_info");
-		unsigned int elements = json_array_get_length(rootArray);
-
-		std::map<std::string, LayerInfo>().swap(layer);
-		// TODO: handling error
-		// FIXEME: LayerInfo.set()??
-		for (unsigned int elem = 0; elem < elements; ++elem) {
-			LayerInfo info;
-			JsonNode *pNode = json_array_get_element(rootArray, elem);
-			JsonObject *pObject = json_node_get_object(pNode);
-
-			info.name =
-					static_cast<const char*>(json_object_get_string_member(pObject,"name"));
-			LOGI("layer: %s", info.name.c_str());
-
-			try {
-				info.shapeType = GetSupportedType(pObject, "shape_type", mSupportedShapeType);
-				info.dataType = GetSupportedType(pObject, "data_type", mSupportedDataType);
-				info.colorSpace = GetSupportedType(pObject, "color_space", mSupportedColorSpace);
-			} catch (const std::exception& e) {
-				LOGE("Invalid %s", e.what());
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
+int InputMetadata::GetTensorInfo(JsonObject *root)
+{
+	LOGI("ENTER");
 
-			// dims
-			JsonArray * array = json_object_get_array_member(pObject, "shape_dims");
-			unsigned int elements2 = json_array_get_length(array);
-			LOGI("shape dim: size[%u]", elements2);
-			for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
-				auto dim = static_cast<int>(json_array_get_int_element(array, elem2));
-				info.dims.push_back(dim);
-				LOGI("%d", dim);
-			}
+	if (!json_object_has_member(root, "tensor_info")) {
+		LOGE("No tensor_info inputmetadata");
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
+	}
 
-			layer.insert(std::make_pair(info.name, info));
+	// tensor_info
+	int ret = MEDIA_VISION_ERROR_NONE;
+	JsonArray *rootArray = json_object_get_array_member(root, "tensor_info");
+	unsigned int elements = json_array_get_length(rootArray);
+
+	std::map<std::string, LayerInfo>().swap(layer);
+	// TODO: handling error
+	// FIXEME: LayerInfo.set()??
+	for (unsigned int elem = 0; elem < elements; ++elem) {
+		LayerInfo info;
+		JsonNode *pNode = json_array_get_element(rootArray, elem);
+		JsonObject *pObject = json_node_get_object(pNode);
+
+		info.name = static_cast<const char *>(json_object_get_string_member(pObject, "name"));
+		LOGI("layer: %s", info.name.c_str());
+
+		try {
+			info.shapeType = GetSupportedType(pObject, "shape_type", mSupportedShapeType);
+			info.dataType = GetSupportedType(pObject, "data_type", mSupportedDataType);
+			info.colorSpace = GetSupportedType(pObject, "color_space", mSupportedColorSpace);
+		} catch (const std::exception &e) {
+			LOGE("Invalid %s", e.what());
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
 		}
 
-		LOGI("LEAVE");
+		// dims
+		JsonArray *array = json_object_get_array_member(pObject, "shape_dims");
+		unsigned int elements2 = json_array_get_length(array);
+		LOGI("shape dim: size[%u]", elements2);
+		for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
+			auto dim = static_cast<int>(json_array_get_int_element(array, elem2));
+			info.dims.push_back(dim);
+			LOGI("%d", dim);
+		}
 
-		return ret;
+		layer.insert(std::make_pair(info.name, info));
 	}
 
-	int InputMetadata::GetPreProcess(JsonObject *root)
-	{
-		LOGI("ENTER");
+	LOGI("LEAVE");
 
-		if (!json_object_has_member(root, "preprocess")) {
-			LOGI("No preprocess inputmetadata");
-			return MEDIA_VISION_ERROR_NONE;
-		}
+	return ret;
+}
+
+int InputMetadata::GetPreProcess(JsonObject *root)
+{
+	LOGI("ENTER");
+
+	if (!json_object_has_member(root, "preprocess")) {
+		LOGI("No preprocess inputmetadata");
+		return MEDIA_VISION_ERROR_NONE;
+	}
 
-		// preprocess
-		JsonArray * rootArray = json_object_get_array_member(root, "preprocess");
-		unsigned int elements = json_array_get_length(rootArray);
-
-		std::map<std::string, Options>().swap(option);
-		// TODO: iterLayer should be the same with elements.
-		auto iterLayer = layer.begin();
-		// TODO: handling error
-		for (unsigned int elem = 0; elem < elements; ++elem, ++iterLayer) {
-			Options opt;
-
-			JsonNode *pNode = json_array_get_element(rootArray, elem);
-			JsonObject *pObject = json_node_get_object(pNode);
-
-			// normalization
-			if (json_object_has_member(pObject, "normalization")) {
-				JsonArray * array = json_object_get_array_member(pObject, "normalization");
-				JsonNode *  node = json_array_get_element(array, 0);
-				JsonObject * object = json_node_get_object(node);
-
-				opt.normalization.use = true;
-				LOGI("use normalization");
-
-				JsonArray * arrayMean = json_object_get_array_member(object, "mean");
-				JsonArray * arrayStd = json_object_get_array_member(object, "std");
-				unsigned int elemMean = json_array_get_length(arrayMean);
-				unsigned int elemStd = json_array_get_length(arrayStd);
-				if (elemMean != elemStd) {
-					LOGE("Invalid mean and std values");
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-
-				for (unsigned int elem = 0; elem < elemMean; ++elem) {
-					auto m = static_cast<double>(json_array_get_double_element(arrayMean, elem));
-					auto s = static_cast<double>(json_array_get_double_element(arrayStd, elem));
-					opt.normalization.mean.push_back(m);
-					opt.normalization.std.push_back(s);
-					LOGI("%u: mean[%3.2f], std[%3.2f]", elem, m, s);
-				}
+	// preprocess
+	JsonArray *rootArray = json_object_get_array_member(root, "preprocess");
+	unsigned int elements = json_array_get_length(rootArray);
+
+	std::map<std::string, Options>().swap(option);
+	// TODO: iterLayer should be the same with elements.
+	auto iterLayer = layer.begin();
+	// TODO: handling error
+	for (unsigned int elem = 0; elem < elements; ++elem, ++iterLayer) {
+		Options opt;
+
+		JsonNode *pNode = json_array_get_element(rootArray, elem);
+		JsonObject *pObject = json_node_get_object(pNode);
+
+		// normalization
+		if (json_object_has_member(pObject, "normalization")) {
+			JsonArray *array = json_object_get_array_member(pObject, "normalization");
+			JsonNode *node = json_array_get_element(array, 0);
+			JsonObject *object = json_node_get_object(node);
+
+			opt.normalization.use = true;
+			LOGI("use normalization");
+
+			JsonArray *arrayMean = json_object_get_array_member(object, "mean");
+			JsonArray *arrayStd = json_object_get_array_member(object, "std");
+			unsigned int elemMean = json_array_get_length(arrayMean);
+			unsigned int elemStd = json_array_get_length(arrayStd);
+			if (elemMean != elemStd) {
+				LOGE("Invalid mean and std values");
+				return MEDIA_VISION_ERROR_INVALID_OPERATION;
 			}
 
-			if (json_object_has_member(pObject, "quantization")) {
-				JsonArray * array = json_object_get_array_member(pObject, "quantization");
-				JsonNode *  node = json_array_get_element(array, 0);
-				JsonObject * object = json_node_get_object(node);
-
-				opt.quantization.use = true;
-				LOGI("use quantization");
-
-				JsonArray * arrayScale = json_object_get_array_member(object, "scale");
-				JsonArray * arrayZero = json_object_get_array_member(object, "zeropoint");
-				unsigned int elemScale = json_array_get_length(arrayScale);
-				unsigned int elemZero= json_array_get_length(arrayZero);
-				if (elemScale != elemZero) {
-					LOGE("Invalid scale and zero values");
-					return MEDIA_VISION_ERROR_INVALID_OPERATION;
-				}
-
-				for (unsigned int elem = 0; elem < elemScale; ++elem) {
-					auto s = static_cast<double>(json_array_get_double_element(arrayScale, elem));
-					auto z = static_cast<double>(json_array_get_double_element(arrayZero, elem));
-					opt.quantization.scale.push_back(s);
-					opt.quantization.zeropoint.push_back(z);
-					LOGI("%u: scale[%3.2f], zeropoint[%3.2f]", elem, s, z);
-				}
+			for (unsigned int elem = 0; elem < elemMean; ++elem) {
+				auto m = static_cast<double>(json_array_get_double_element(arrayMean, elem));
+				auto s = static_cast<double>(json_array_get_double_element(arrayStd, elem));
+				opt.normalization.mean.push_back(m);
+				opt.normalization.std.push_back(s);
+				LOGI("%u: mean[%3.2f], std[%3.2f]", elem, m, s);
 			}
-			option.insert(std::make_pair(iterLayer->first, opt));
 		}
 
-		LOGI("LEAVE");
+		if (json_object_has_member(pObject, "quantization")) {
+			JsonArray *array = json_object_get_array_member(pObject, "quantization");
+			JsonNode *node = json_array_get_element(array, 0);
+			JsonObject *object = json_node_get_object(node);
 
-		return MEDIA_VISION_ERROR_NONE;
-	}
+			opt.quantization.use = true;
+			LOGI("use quantization");
 
-	int InputMetadata::Parse(JsonObject *root)
-	{
-		LOGI("ENTER");
+			JsonArray *arrayScale = json_object_get_array_member(object, "scale");
+			JsonArray *arrayZero = json_object_get_array_member(object, "zeropoint");
+			unsigned int elemScale = json_array_get_length(arrayScale);
+			unsigned int elemZero = json_array_get_length(arrayZero);
+			if (elemScale != elemZero) {
+				LOGE("Invalid scale and zero values");
+				return MEDIA_VISION_ERROR_INVALID_OPERATION;
+			}
 
-		int ret = GetTensorInfo(root);
-		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to GetTensorInfo[%d]", ret);
-			return ret;
+			for (unsigned int elem = 0; elem < elemScale; ++elem) {
+				auto s = static_cast<double>(json_array_get_double_element(arrayScale, elem));
+				auto z = static_cast<double>(json_array_get_double_element(arrayZero, elem));
+				opt.quantization.scale.push_back(s);
+				opt.quantization.zeropoint.push_back(z);
+				LOGI("%u: scale[%3.2f], zeropoint[%3.2f]", elem, s, z);
+			}
 		}
+		option.insert(std::make_pair(iterLayer->first, opt));
+	}
 
-		ret = GetPreProcess(root);
-		if (ret != MEDIA_VISION_ERROR_NONE)	 {
-			LOGE("Fail to GetPreProcess[%d]", ret);
-			return ret;
-		}
+	LOGI("LEAVE");
 
-		parsed = true;
-		LOGI("LEAVE");
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		return MEDIA_VISION_ERROR_NONE;
+int InputMetadata::Parse(JsonObject *root)
+{
+	LOGI("ENTER");
+
+	int ret = GetTensorInfo(root);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to GetTensorInfo[%d]", ret);
+		return ret;
+	}
+
+	ret = GetPreProcess(root);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to GetPreProcess[%d]", ret);
+		return ret;
 	}
 
+	parsed = true;
+	LOGI("LEAVE");
+
+	return MEDIA_VISION_ERROR_NONE;
+}
+
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/src/Metadata.cpp b/mv_machine_learning/inference/src/Metadata.cpp
index b2ae9ff..34f83a6 100644
--- a/mv_machine_learning/inference/src/Metadata.cpp
+++ b/mv_machine_learning/inference/src/Metadata.cpp
@@ -29,93 +29,92 @@ namespace mediavision
 {
 namespace inference
 {
-	int Metadata::Init(const std::string& filename)
-	{
-		LOGI("ENTER");
+int Metadata::Init(const std::string &filename)
+{
+	LOGI("ENTER");
+
+	if (access(filename.c_str(), F_OK | R_OK)) {
+		LOGE("meta file is in [%s] ", filename.c_str());
+		return MEDIA_VISION_ERROR_INVALID_PATH;
+	}
+
+	mMetafile = filename;
+
+	LOGI("LEAVE");
+
+	return MEDIA_VISION_ERROR_NONE;
+}
+
+int Metadata::Parse()
+{
+	LOGI("ENTER");
+
+	if (mMetafile.empty()) {
+		LOGE("meta file is empty");
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
+	}
 
-		if (access(filename.c_str(), F_OK | R_OK)) {
-			LOGE("meta file is in [%s] ", filename.c_str());
-			return MEDIA_VISION_ERROR_INVALID_PATH;
-		}
+	GError *error = NULL;
+	JsonNode *node = NULL;
+	JsonObject *object = NULL;
+	int ret = MEDIA_VISION_ERROR_NONE;
 
-		mMetafile = filename;
+	JsonParser *parser = json_parser_new();
+	if (parser == NULL) {
+		LOGE("Fail to create json parser");
+		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
+	}
 
-		LOGI("LEAVE");
+	gboolean jsonRet = json_parser_load_from_file(parser, mMetafile.c_str(), &error);
+	if (!jsonRet) {
+		LOGE("Unable to parser file %s by %s", mMetafile.c_str(), error == NULL ? "Unknown" : error->message);
+		g_error_free(error);
+		ret = MEDIA_VISION_ERROR_INVALID_DATA;
+		goto _ERROR_;
+	}
 
-		return MEDIA_VISION_ERROR_NONE;
+	node = json_parser_get_root(parser);
+	if (JSON_NODE_TYPE(node) != JSON_NODE_OBJECT) {
+		LOGE("Fail to json_parser_get_root. It's an incorrect markup");
+		ret = MEDIA_VISION_ERROR_INVALID_DATA;
+		goto _ERROR_;
 	}
 
-	int Metadata::Parse()
-	{
-		LOGI("ENTER");
-
-		if (mMetafile.empty()) {
-			LOGE("meta file is empty");
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
-
-		GError *error = NULL;
-		JsonNode *node = NULL;
-		JsonObject *object = NULL;
-		int ret = MEDIA_VISION_ERROR_NONE;
-
-		JsonParser *parser = json_parser_new();
-		if (parser == NULL) {
-			LOGE("Fail to create json parser");
-			return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
-		}
-
-		gboolean jsonRet = json_parser_load_from_file(parser, mMetafile.c_str(), &error);
-		if (!jsonRet) {
-			LOGE("Unable to parser file %s by %s", mMetafile.c_str(),
-								error == NULL ? "Unknown" : error->message);
-			g_error_free(error);
-			ret =  MEDIA_VISION_ERROR_INVALID_DATA;
-			goto _ERROR_;
-		}
-
-		node = json_parser_get_root(parser);
-		if (JSON_NODE_TYPE(node) != JSON_NODE_OBJECT) {
-			LOGE("Fail to json_parser_get_root. It's an incorrect markup");
-			ret =  MEDIA_VISION_ERROR_INVALID_DATA;
-			goto _ERROR_;
-		}
-
-		object = json_node_get_object(node);
-		if (!object) {
-			LOGE("Fail to json_node_get_object. object is NULL");
-			ret =  MEDIA_VISION_ERROR_INVALID_DATA;
-			goto _ERROR_;
-		}
-
-		ret = mInputMeta.Parse(json_object_get_object_member(object, "inputmetadata"));
-		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to parse input Meta[%d]",ret);
-			goto _ERROR_;
-		}
-
-		ret = mOutputMeta.Parse(json_object_get_object_member(object, "outputmetadata"));
-		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to parse output meta[%d]",ret);
-			goto _ERROR_;
-		}
-
-	_ERROR_ :
-		g_object_unref(parser);
-		parser = NULL;
-		LOGI("LEAVE");
-
-		return ret;
+	object = json_node_get_object(node);
+	if (!object) {
+		LOGE("Fail to json_node_get_object. object is NULL");
+		ret = MEDIA_VISION_ERROR_INVALID_DATA;
+		goto _ERROR_;
 	}
 
-	InputMetadata& Metadata::GetInputMeta()
-	{
-		return mInputMeta;
+	ret = mInputMeta.Parse(json_object_get_object_member(object, "inputmetadata"));
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to parse input Meta[%d]", ret);
+		goto _ERROR_;
 	}
 
-	OutputMetadata& Metadata::GetOutputMeta()
-	{
-		return mOutputMeta;
+	ret = mOutputMeta.Parse(json_object_get_object_member(object, "outputmetadata"));
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to parse output meta[%d]", ret);
+		goto _ERROR_;
 	}
+
+_ERROR_:
+	g_object_unref(parser);
+	parser = NULL;
+	LOGI("LEAVE");
+
+	return ret;
+}
+
+InputMetadata &Metadata::GetInputMeta()
+{
+	return mInputMeta;
+}
+
+OutputMetadata &Metadata::GetOutputMeta()
+{
+	return mOutputMeta;
+}
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/src/ObjectDecoder.cpp b/mv_machine_learning/inference/src/ObjectDecoder.cpp
old mode 100755
new mode 100644
index 96193da..c617f2d
--- a/mv_machine_learning/inference/src/ObjectDecoder.cpp
+++ b/mv_machine_learning/inference/src/ObjectDecoder.cpp
@@ -25,230 +25,214 @@ namespace mediavision
 {
 namespace inference
 {
-	int ObjectDecoder::init()
-	{
-		if (mMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_BYPASS) {
-			if (!mTensorBuffer.exist(mMeta.GetBoxLabelName()) ||
-				!mTensorBuffer.exist(mMeta.GetBoxNumberName()) ) {
-				LOGE("buffer buffers named of %s or %s are NULL",
-					mMeta.GetBoxLabelName().c_str(), mMeta.GetBoxNumberName().c_str());
-
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
+int ObjectDecoder::init()
+{
+	if (mMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_BYPASS) {
+		if (!mTensorBuffer.exist(mMeta.GetBoxLabelName()) || !mTensorBuffer.exist(mMeta.GetBoxNumberName())) {
+			LOGE("buffer buffers named of %s or %s are NULL", mMeta.GetBoxLabelName().c_str(),
+				 mMeta.GetBoxNumberName().c_str());
 
-			std::vector<int> indexes = mMeta.GetBoxNumberDimInfo().GetValidIndexAll();
-			if (indexes.size() != 1) {
-				LOGE("Invalid dim size. It should be 1");
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
+		}
 
-			// mNumberOfObjects is set again if INFERENCE_BOX_DECODING_TYPE_BYPASS.
-			// Otherwise it is set already within ctor.
-			mNumberOfOjects = mTensorBuffer.getValue<int>(
-								mMeta.GetBoxNumberName(), indexes[0]);
-		} else if (mMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR) {
-			if (mMeta.GetBoxDecodeInfo().IsAnchorBoxEmpty()) {
-				LOGE("Anchor boxes are required but empty.");
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
-		} else {
-			LOGI("YOLO_ANCHOR does nothing");
+		std::vector<int> indexes = mMeta.GetBoxNumberDimInfo().GetValidIndexAll();
+		if (indexes.size() != 1) {
+			LOGE("Invalid dim size. It should be 1");
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
 		}
 
-		return MEDIA_VISION_ERROR_NONE;
+		// mNumberOfObjects is set again if INFERENCE_BOX_DECODING_TYPE_BYPASS.
+		// Otherwise it is set already within ctor.
+		mNumberOfOjects = mTensorBuffer.getValue<int>(mMeta.GetBoxNumberName(), indexes[0]);
+	} else if (mMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR) {
+		if (mMeta.GetBoxDecodeInfo().IsAnchorBoxEmpty()) {
+			LOGE("Anchor boxes are required but empty.");
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
+		}
+	} else {
+		LOGI("YOLO_ANCHOR does nothing");
 	}
 
-	float ObjectDecoder::decodeScore(int idx)
-	{
-		float score = mTensorBuffer.getValue<float>(mMeta.GetScoreName(), idx);
-		if (mMeta.GetScoreType() == INFERENCE_SCORE_TYPE_SIGMOID) {
-			score = PostProcess::sigmoid(score);
-		}
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		return score < mMeta.GetScoreThreshold() ? 0.0f : score;
+float ObjectDecoder::decodeScore(int idx)
+{
+	float score = mTensorBuffer.getValue<float>(mMeta.GetScoreName(), idx);
+	if (mMeta.GetScoreType() == INFERENCE_SCORE_TYPE_SIGMOID) {
+		score = PostProcess::sigmoid(score);
 	}
 
-	Box ObjectDecoder::decodeBox(int idx, float score, int label, int offset)
-	{
-		// assume type is (cx,cy,w,h)
-		// left or cx
-		float cx = mTensorBuffer.getValue<float>(mMeta.GetBoxName(),
-									idx * mBoxOffset + offset + mMeta.GetBoxOrder()[0]);
-		// top or cy
-		float cy = mTensorBuffer.getValue<float>(mMeta.GetBoxName(),
-									idx * mBoxOffset + offset + mMeta.GetBoxOrder()[1]);
-		// right or width
-		float cWidth = mTensorBuffer.getValue<float>(mMeta.GetBoxName(),
-									idx * mBoxOffset + offset + mMeta.GetBoxOrder()[2]);
-		// bottom or height
-		float cHeight = mTensorBuffer.getValue<float>(mMeta.GetBoxName(),
-									idx * mBoxOffset + offset + mMeta.GetBoxOrder()[3]);
-
-		if (mMeta.GetBoxDecodeInfo().GetCellType() == INFERENCE_SCORE_TYPE_SIGMOID) {
-			cx = PostProcess::sigmoid(cx);
-			cy = PostProcess::sigmoid(cy);
-			cWidth = PostProcess::sigmoid(cWidth);
-			cHeight = PostProcess::sigmoid(cHeight);
-		}
-
-		LOGI("cx:%.2f, cy:%.2f, cW:%.2f, cH:%.2f", cx, cy, cWidth, cHeight);
-		// convert type to ORIGIN_CENTER if ORIGIN_LEFTTOP
-		if (mMeta.GetBoxType() == INFERENCE_BOX_TYPE_ORIGIN_LEFTTOP) {
-			float tmpCx = cx;
-			float tmpCy = cy;
-			cx = (cx + cWidth) * 0.5f; // (left + right)/2
-			cy = (cy + cHeight) * 0.5f; // (top + bottom)/2
-			cWidth = cWidth - tmpCx ; // right - left
-			cHeight = cHeight - tmpCy; // bottom - top
-		}
+	return score < mMeta.GetScoreThreshold() ? 0.0f : score;
+}
 
-		// convert coordinate to RATIO if PIXEL
-		if (mMeta.GetScoreCoordinate() == INFERENCE_BOX_COORDINATE_TYPE_PIXEL) {
-			cx /= mScaleW;
-			cy /= mScaleH;
-			cWidth /= mScaleW;
-			cHeight /= mScaleH;
-		}
+Box ObjectDecoder::decodeBox(int idx, float score, int label, int offset)
+{
+	// assume type is (cx,cy,w,h)
+	// left or cx
+	float cx = mTensorBuffer.getValue<float>(mMeta.GetBoxName(), idx * mBoxOffset + offset + mMeta.GetBoxOrder()[0]);
+	// top or cy
+	float cy = mTensorBuffer.getValue<float>(mMeta.GetBoxName(), idx * mBoxOffset + offset + mMeta.GetBoxOrder()[1]);
+	// right or width
+	float cWidth =
+			mTensorBuffer.getValue<float>(mMeta.GetBoxName(), idx * mBoxOffset + offset + mMeta.GetBoxOrder()[2]);
+	// bottom or height
+	float cHeight =
+			mTensorBuffer.getValue<float>(mMeta.GetBoxName(), idx * mBoxOffset + offset + mMeta.GetBoxOrder()[3]);
+
+	if (mMeta.GetBoxDecodeInfo().GetCellType() == INFERENCE_SCORE_TYPE_SIGMOID) {
+		cx = PostProcess::sigmoid(cx);
+		cy = PostProcess::sigmoid(cy);
+		cWidth = PostProcess::sigmoid(cWidth);
+		cHeight = PostProcess::sigmoid(cHeight);
+	}
 
-		Box box = {
-			.index = mMeta.GetBoxLabelName().empty() ?
-						label :
-						mTensorBuffer.getValue<int>(mMeta.GetBoxLabelName(), idx),
-			.score = score,
-			.location = cv::Rect2f(cx, cy, cWidth, cHeight)
-		};
+	LOGI("cx:%.2f, cy:%.2f, cW:%.2f, cH:%.2f", cx, cy, cWidth, cHeight);
+	// convert type to ORIGIN_CENTER if ORIGIN_LEFTTOP
+	if (mMeta.GetBoxType() == INFERENCE_BOX_TYPE_ORIGIN_LEFTTOP) {
+		float tmpCx = cx;
+		float tmpCy = cy;
+		cx = (cx + cWidth) * 0.5f; // (left + right)/2
+		cy = (cy + cHeight) * 0.5f; // (top + bottom)/2
+		cWidth = cWidth - tmpCx; // right - left
+		cHeight = cHeight - tmpCy; // bottom - top
+	}
 
-		return box;
+	// convert coordinate to RATIO if PIXEL
+	if (mMeta.GetScoreCoordinate() == INFERENCE_BOX_COORDINATE_TYPE_PIXEL) {
+		cx /= mScaleW;
+		cy /= mScaleH;
+		cWidth /= mScaleW;
+		cHeight /= mScaleH;
 	}
 
-	Box ObjectDecoder::decodeBoxWithAnchor(int idx, int anchorIdx, float score, cv::Rect2f& anchor)
-	{
-		// location coordinate of box, the output of decodeBox(), is relative between 0 ~ 1
-		Box box = decodeBox(anchorIdx, score, idx);
-
-		if (mMeta.GetBoxDecodeInfo().IsFixedAnchorSize()) {
-			box.location.x += anchor.x;
-			box.location.y += anchor.y;
-		} else {
-			box.location.x = box.location.x / mMeta.GetBoxDecodeInfo().GetAnchorXscale() *
-							 anchor.width + anchor.x;
-			box.location.y = box.location.y / mMeta.GetBoxDecodeInfo().GetAnchorYscale() *
-							 anchor.height + anchor.y;
-		}
+	Box box = { .index = mMeta.GetBoxLabelName().empty() ? label :
+														   mTensorBuffer.getValue<int>(mMeta.GetBoxLabelName(), idx),
+				.score = score,
+				.location = cv::Rect2f(cx, cy, cWidth, cHeight) };
 
-		if (mMeta.GetBoxDecodeInfo().IsExponentialBoxScale()) {
-			box.location.width = anchor.width *
-						std::exp(box.location.width / mMeta.GetBoxDecodeInfo().GetAnchorWscale());
-			box.location.height = anchor.height *
-						std::exp(box.location.height / mMeta.GetBoxDecodeInfo().GetAnchorHscale());
-		} else {
-			box.location.width = anchor.width *
-						box.location.width / mMeta.GetBoxDecodeInfo().GetAnchorWscale();
-			box.location.height = anchor.height *
-						box.location.height / mMeta.GetBoxDecodeInfo().GetAnchorHscale();
-		}
+	return box;
+}
+
+Box ObjectDecoder::decodeBoxWithAnchor(int idx, int anchorIdx, float score, cv::Rect2f &anchor)
+{
+	// location coordinate of box, the output of decodeBox(), is relative between 0 ~ 1
+	Box box = decodeBox(anchorIdx, score, idx);
+
+	if (mMeta.GetBoxDecodeInfo().IsFixedAnchorSize()) {
+		box.location.x += anchor.x;
+		box.location.y += anchor.y;
+	} else {
+		box.location.x = box.location.x / mMeta.GetBoxDecodeInfo().GetAnchorXscale() * anchor.width + anchor.x;
+		box.location.y = box.location.y / mMeta.GetBoxDecodeInfo().GetAnchorYscale() * anchor.height + anchor.y;
+	}
 
-		return box;
+	if (mMeta.GetBoxDecodeInfo().IsExponentialBoxScale()) {
+		box.location.width = anchor.width * std::exp(box.location.width / mMeta.GetBoxDecodeInfo().GetAnchorWscale());
+		box.location.height =
+				anchor.height * std::exp(box.location.height / mMeta.GetBoxDecodeInfo().GetAnchorHscale());
+	} else {
+		box.location.width = anchor.width * box.location.width / mMeta.GetBoxDecodeInfo().GetAnchorWscale();
+		box.location.height = anchor.height * box.location.height / mMeta.GetBoxDecodeInfo().GetAnchorHscale();
 	}
 
-	int ObjectDecoder::decode()
-	{
-		LOGI("ENTER");
-
-		BoxesList boxList;
-		Boxes boxes;
-		int ret = MEDIA_VISION_ERROR_NONE;
-		int totalIdx = mNumberOfOjects;
-
-		if (mMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_YOLO_ANCHOR) {
-			totalIdx = 0;
-			for (auto& scale : mMeta.GetBoxDecodeInfo().GetCellScalesAll()) {
-				totalIdx += (static_cast<int>(mScaleW) / scale
-							* static_cast<int>(mScaleH) / scale)
-							* mMeta.GetBoxDecodeInfo().GetCellNumScales()
-							/ mMeta.GetBoxDecodeInfo().GetCellOffsetScales();
-			}
-			boxList.reserve(mNumberOfOjects);
+	return box;
+}
+
+int ObjectDecoder::decode()
+{
+	LOGI("ENTER");
+
+	BoxesList boxList;
+	Boxes boxes;
+	int ret = MEDIA_VISION_ERROR_NONE;
+	int totalIdx = mNumberOfOjects;
+
+	if (mMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_YOLO_ANCHOR) {
+		totalIdx = 0;
+		for (auto &scale : mMeta.GetBoxDecodeInfo().GetCellScalesAll()) {
+			totalIdx += (static_cast<int>(mScaleW) / scale * static_cast<int>(mScaleH) / scale) *
+						mMeta.GetBoxDecodeInfo().GetCellNumScales() / mMeta.GetBoxDecodeInfo().GetCellOffsetScales();
 		}
+		boxList.reserve(mNumberOfOjects);
+	}
 
-		for (int idx = 0; idx < totalIdx; ++idx) {
-			if (mMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_BYPASS) {
-				float score = decodeScore(idx);
-				if (score <= 0.0f)
-					continue;
+	for (int idx = 0; idx < totalIdx; ++idx) {
+		if (mMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_BYPASS) {
+			float score = decodeScore(idx);
+			if (score <= 0.0f)
+				continue;
 
-				Box box = decodeBox(idx, score);
-				mResultBoxes.push_back(box);
-			} else if (mMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR) {
-				int anchorIdx = -1;
+			Box box = decodeBox(idx, score);
+			mResultBoxes.push_back(box);
+		} else if (mMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR) {
+			int anchorIdx = -1;
 
-				boxes.clear();
-				for (auto& anchorBox : mMeta.GetBoxDecodeInfo().GetAnchorBoxAll()) {
-					anchorIdx++;
+			boxes.clear();
+			for (auto &anchorBox : mMeta.GetBoxDecodeInfo().GetAnchorBoxAll()) {
+				anchorIdx++;
 
-					float score = decodeScore(anchorIdx * mNumberOfOjects + idx);
+				float score = decodeScore(anchorIdx * mNumberOfOjects + idx);
 
-					if (score <= 0.0f)
-						continue;
+				if (score <= 0.0f)
+					continue;
 
-					Box box = decodeBoxWithAnchor(idx, anchorIdx, score, anchorBox);
-					boxes.push_back(box);
+				Box box = decodeBoxWithAnchor(idx, anchorIdx, score, anchorBox);
+				boxes.push_back(box);
+			}
+			boxList.push_back(boxes);
+		} else { // INFERENCE_BOX_DECODING_TYPE_YOLO_ANCHOR
+			int cellIdx = idx * mBoxOffset;
+			for (int j = 0; j < mMeta.GetBoxDecodeInfo().GetCellOffsetScales(); ++j) {
+				float score = decodeScore(cellIdx + (mNumberOfOjects + 5) * j + 4);
+				if (score <= 0.0f) {
+					continue;
 				}
-				boxList.push_back(boxes);
-			} else { // INFERENCE_BOX_DECODING_TYPE_YOLO_ANCHOR
-				int cellIdx = idx * mBoxOffset;
-				for (int j = 0; j < mMeta.GetBoxDecodeInfo().GetCellOffsetScales(); ++j) {
-					float score = decodeScore(cellIdx + (mNumberOfOjects + 5) * j + 4);
-					if (score <= 0.0f) {
-						continue;
-					}
-					LOGI("score[%d]: %.2f", j, score);
-					// need to check the score
-					float topObjScore = 0.0f;
-					int topObjIdx = 0;
-					for (int objIdx_ = 0; objIdx_ < mNumberOfOjects; ++objIdx_) {
-						float objScore_ = decodeScore(cellIdx + (mNumberOfOjects + 5) * j + 5 + objIdx_);
-						if (objScore_ > topObjScore) {
-							topObjScore = objScore_;
-							topObjIdx = objIdx_;
-						}
+				LOGI("score[%d]: %.2f", j, score);
+				// need to check the score
+				float topObjScore = 0.0f;
+				int topObjIdx = 0;
+				for (int objIdx_ = 0; objIdx_ < mNumberOfOjects; ++objIdx_) {
+					float objScore_ = decodeScore(cellIdx + (mNumberOfOjects + 5) * j + 5 + objIdx_);
+					if (objScore_ > topObjScore) {
+						topObjScore = objScore_;
+						topObjIdx = objIdx_;
 					}
+				}
 
-					if (topObjScore <  mMeta.GetScoreThreshold())
-						continue;
+				if (topObjScore < mMeta.GetScoreThreshold())
+					continue;
 
-					Box box = decodeBox(idx, topObjScore, topObjIdx, (mNumberOfOjects + 5) * j);
-					boxes.push_back(box);
-				}
+				Box box = decodeBox(idx, topObjScore, topObjIdx, (mNumberOfOjects + 5) * j);
+				boxes.push_back(box);
 			}
 		}
+	}
 
-		if (mMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR ||
-			mMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_YOLO_ANCHOR)
-			boxList.push_back(boxes);
-
-		if (!boxList.empty()) {
-			PostProcess postProc;
-			ret = postProc.Nms(boxList,
-					mMeta.GetBoxDecodeInfo().GetNmsMode(),
-					mMeta.GetBoxDecodeInfo().GetNmsIouThreshold(),
-					mResultBoxes);
-			if (ret != MEDIA_VISION_ERROR_NONE) {
-				LOGE("Fail to non-maximum suppression[%d]", ret);
-				return ret;
-			}
-		} else {
-			LOGW("boxlist empty!");
+	if (mMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR ||
+		mMeta.GetBoxDecodingType() == INFERENCE_BOX_DECODING_TYPE_YOLO_ANCHOR)
+		boxList.push_back(boxes);
+
+	if (!boxList.empty()) {
+		PostProcess postProc;
+		ret = postProc.Nms(boxList, mMeta.GetBoxDecodeInfo().GetNmsMode(),
+						   mMeta.GetBoxDecodeInfo().GetNmsIouThreshold(), mResultBoxes);
+		if (ret != MEDIA_VISION_ERROR_NONE) {
+			LOGE("Fail to non-maximum suppression[%d]", ret);
+			return ret;
 		}
+	} else {
+		LOGW("boxlist empty!");
+	}
 
-		LOGI("LEAVE");
+	LOGI("LEAVE");
 
-		return ret;
-	}
+	return ret;
+}
 
-	Boxes& ObjectDecoder::getObjectAll()
-	{
-		return mResultBoxes;
-	}
+Boxes &ObjectDecoder::getObjectAll()
+{
+	return mResultBoxes;
+}
 }
 }
diff --git a/mv_machine_learning/inference/src/OutputMetadata.cpp b/mv_machine_learning/inference/src/OutputMetadata.cpp
old mode 100755
new mode 100644
index 12a2da3..4f44bb2
--- a/mv_machine_learning/inference/src/OutputMetadata.cpp
+++ b/mv_machine_learning/inference/src/OutputMetadata.cpp
@@ -31,522 +31,505 @@ namespace mediavision
 {
 namespace inference
 {
-	OutputMetadata::OutputMetadata() :
-			parsed(false),
-			score(),
-			box(),
-			landmark(),
-			offsetVec()
-	{
-		// shape_type
-		mSupportedShapeType.insert({"NCHW", INFERENCE_TENSOR_SHAPE_NCHW});
-		mSupportedShapeType.insert({"NHWC", INFERENCE_TENSOR_SHAPE_NHWC});
-	}
-
-	int OutputMetadata::ParseScore(JsonObject *root)
-	{
-		if (!json_object_has_member(root, "score")) {
-			LOGI("No score outputmetadata");
-			return MEDIA_VISION_ERROR_NONE;
-		}
-
-		return score.ParseScore(root);
-	}
-
-	void DecodeInfo::AddAnchorBox(cv::Rect2f& anchor)
-	{
-		anchorBoxes.push_back(anchor);
-	}
-
-	void DecodeInfo::ClearAnchorBox()
-	{
-		anchorBoxes.clear();
-	}
+OutputMetadata::OutputMetadata() : parsed(false), score(), box(), landmark(), offsetVec()
+{
+	// shape_type
+	mSupportedShapeType.insert({ "NCHW", INFERENCE_TENSOR_SHAPE_NCHW });
+	mSupportedShapeType.insert({ "NHWC", INFERENCE_TENSOR_SHAPE_NHWC });
+}
 
-	std::vector<cv::Rect2f>& DecodeInfo::GetAnchorBoxAll()
-	{
-		return anchorBoxes;
+int OutputMetadata::ParseScore(JsonObject *root)
+{
+	if (!json_object_has_member(root, "score")) {
+		LOGI("No score outputmetadata");
+		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	bool DecodeInfo::IsAnchorBoxEmpty()
-	{
-		return anchorBoxes.empty();
-	}
+	return score.ParseScore(root);
+}
 
-	int OutputMetadata::ParseBox(JsonObject *root)
-	{
-		if (!json_object_has_member(root, "box")) {
-			LOGE("No box outputmetadata");
-			return MEDIA_VISION_ERROR_NONE;
-		}
+void DecodeInfo::AddAnchorBox(cv::Rect2f &anchor)
+{
+	anchorBoxes.push_back(anchor);
+}
 
-		return box.ParseBox(root);
-	}
+void DecodeInfo::ClearAnchorBox()
+{
+	anchorBoxes.clear();
+}
 
-	int DecodeInfo::ParseAnchorParam(JsonObject *root)
-	{
-		JsonObject *object = json_object_get_object_member(root, "anchor") ;
-
-		this->anchorParam.mode = static_cast<int>(json_object_get_int_member(object, "mode"));
-
-		this->anchorParam.numLayers = static_cast<int>(json_object_get_int_member(object, "num_layers"));
-		this->anchorParam.minScale = static_cast<float>(json_object_get_double_member(object, "min_scale"));
-		this->anchorParam.maxScale = static_cast<float>(json_object_get_double_member(object, "max_scale"));
-		this->anchorParam.inputSizeHeight = static_cast<int>(json_object_get_int_member(object, "input_size_height"));
-		this->anchorParam.inputSizeWidth = static_cast<int>(json_object_get_int_member(object, "input_size_width"));
-		this->anchorParam.anchorOffsetX = static_cast<float>(json_object_get_double_member(object, "anchor_offset_x"));
-		this->anchorParam.anchorOffsetY = static_cast<float>(json_object_get_double_member(object, "anchor_offset_y"));
-		this->anchorParam.isReduceBoxedInLowestLayer =
-										static_cast<bool>(json_object_get_boolean_member(object, "reduce_boxed_in_lowest_layer"));
-		this->anchorParam.interpolatedScaleAspectRatio =
-										static_cast<float>(json_object_get_double_member(object, "interpolated_scale_aspect_ratio"));
-		this->anchorParam.isFixedAnchorSize =
-										static_cast<bool>(json_object_get_boolean_member(object, "fixed_anchor_size"));
-		this->anchorParam.isExponentialBoxScale =
-										static_cast<bool>(json_object_get_boolean_member(object, "exponential_box_scale"));
-
-		this->anchorParam.xScale = static_cast<float>(json_object_get_double_member(object, "x_scale"));
-		this->anchorParam.yScale = static_cast<float>(json_object_get_double_member(object, "y_scale"));
-		this->anchorParam.wScale = static_cast<float>(json_object_get_double_member(object, "w_scale"));
-		this->anchorParam.hScale = static_cast<float>(json_object_get_double_member(object, "h_scale"));
-
-		JsonArray * array = json_object_get_array_member(object, "strides");
-		unsigned int elements2 = json_array_get_length(array);
-		for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
-			auto stride = static_cast<int>(json_array_get_int_element(array, elem2));
-			this->anchorParam.strides.push_back(stride);
-			LOGI("stride: %d", stride);
-		}
+std::vector<cv::Rect2f> &DecodeInfo::GetAnchorBoxAll()
+{
+	return anchorBoxes;
+}
 
-		array = json_object_get_array_member(object, "aspect_ratios");
-		elements2 = json_array_get_length(array);
-		for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
-			auto aspectRatio = static_cast<float>(json_array_get_double_element(array, elem2));
-			this->anchorParam.aspectRatios.push_back(aspectRatio);
-			LOGI("aspectRatio: %.4f", aspectRatio);
-		}
+bool DecodeInfo::IsAnchorBoxEmpty()
+{
+	return anchorBoxes.empty();
+}
 
+int OutputMetadata::ParseBox(JsonObject *root)
+{
+	if (!json_object_has_member(root, "box")) {
+		LOGE("No box outputmetadata");
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	int DecodeInfo::ParseCellParam(JsonObject *root)
-	{
-		JsonObject *object = json_object_get_object_member(root, "cell") ;
-
-		this->cellParam.numScales = static_cast<int>(json_object_get_int_member(object, "num_scales"));
+	return box.ParseBox(root);
+}
 
-		JsonArray * array = json_object_get_array_member(object, "scales");
-		unsigned int elements2 = json_array_get_length(array);
-		for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
-			auto scale = static_cast<int>(json_array_get_int_element(array, elem2));
-			this->cellParam.scales.push_back(scale);
-			LOGI("scale: %d", scale);
-		}
+int DecodeInfo::ParseAnchorParam(JsonObject *root)
+{
+	JsonObject *object = json_object_get_object_member(root, "anchor");
+
+	this->anchorParam.mode = static_cast<int>(json_object_get_int_member(object, "mode"));
+
+	this->anchorParam.numLayers = static_cast<int>(json_object_get_int_member(object, "num_layers"));
+	this->anchorParam.minScale = static_cast<float>(json_object_get_double_member(object, "min_scale"));
+	this->anchorParam.maxScale = static_cast<float>(json_object_get_double_member(object, "max_scale"));
+	this->anchorParam.inputSizeHeight = static_cast<int>(json_object_get_int_member(object, "input_size_height"));
+	this->anchorParam.inputSizeWidth = static_cast<int>(json_object_get_int_member(object, "input_size_width"));
+	this->anchorParam.anchorOffsetX = static_cast<float>(json_object_get_double_member(object, "anchor_offset_x"));
+	this->anchorParam.anchorOffsetY = static_cast<float>(json_object_get_double_member(object, "anchor_offset_y"));
+	this->anchorParam.isReduceBoxedInLowestLayer =
+			static_cast<bool>(json_object_get_boolean_member(object, "reduce_boxed_in_lowest_layer"));
+	this->anchorParam.interpolatedScaleAspectRatio =
+			static_cast<float>(json_object_get_double_member(object, "interpolated_scale_aspect_ratio"));
+	this->anchorParam.isFixedAnchorSize =
+			static_cast<bool>(json_object_get_boolean_member(object, "fixed_anchor_size"));
+	this->anchorParam.isExponentialBoxScale =
+			static_cast<bool>(json_object_get_boolean_member(object, "exponential_box_scale"));
+
+	this->anchorParam.xScale = static_cast<float>(json_object_get_double_member(object, "x_scale"));
+	this->anchorParam.yScale = static_cast<float>(json_object_get_double_member(object, "y_scale"));
+	this->anchorParam.wScale = static_cast<float>(json_object_get_double_member(object, "w_scale"));
+	this->anchorParam.hScale = static_cast<float>(json_object_get_double_member(object, "h_scale"));
+
+	JsonArray *array = json_object_get_array_member(object, "strides");
+	unsigned int elements2 = json_array_get_length(array);
+	for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
+		auto stride = static_cast<int>(json_array_get_int_element(array, elem2));
+		this->anchorParam.strides.push_back(stride);
+		LOGI("stride: %d", stride);
+	}
+
+	array = json_object_get_array_member(object, "aspect_ratios");
+	elements2 = json_array_get_length(array);
+	for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
+		auto aspectRatio = static_cast<float>(json_array_get_double_element(array, elem2));
+		this->anchorParam.aspectRatios.push_back(aspectRatio);
+		LOGI("aspectRatio: %.4f", aspectRatio);
+	}
+
+	return MEDIA_VISION_ERROR_NONE;
+}
+
+int DecodeInfo::ParseCellParam(JsonObject *root)
+{
+	JsonObject *object = json_object_get_object_member(root, "cell");
 
-		this->cellParam.offsetScales = static_cast<int>(json_object_get_int_member(object, "offset_scales"));
-		try {
-			this->cellParam.type = GetSupportedType(object, "type", this->cellParam.supportedCellType);
-		} catch (const std::exception& e) {
-			LOGE("Invalid %s", e.what());
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
+	this->cellParam.numScales = static_cast<int>(json_object_get_int_member(object, "num_scales"));
 
-		return MEDIA_VISION_ERROR_NONE;
+	JsonArray *array = json_object_get_array_member(object, "scales");
+	unsigned int elements2 = json_array_get_length(array);
+	for (unsigned int elem2 = 0; elem2 < elements2; ++elem2) {
+		auto scale = static_cast<int>(json_array_get_int_element(array, elem2));
+		this->cellParam.scales.push_back(scale);
+		LOGI("scale: %d", scale);
 	}
 
-	std::vector<int>& DecodeInfo::GetCellScalesAll()
-	{
-		return this->cellParam.scales;
+	this->cellParam.offsetScales = static_cast<int>(json_object_get_int_member(object, "offset_scales"));
+	try {
+		this->cellParam.type = GetSupportedType(object, "type", this->cellParam.supportedCellType);
+	} catch (const std::exception &e) {
+		LOGE("Invalid %s", e.what());
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
-	int DecodeInfo::GetCellNumScales()
-	{
-		return this->cellParam.numScales;
-	}
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-	int DecodeInfo::GetCellOffsetScales()
-	{
-		return this->cellParam.offsetScales;
-	}
+std::vector<int> &DecodeInfo::GetCellScalesAll()
+{
+	return this->cellParam.scales;
+}
 
-	inference_score_type_e DecodeInfo::GetCellType()
-	{
-		return this->cellParam.type;
-	}
+int DecodeInfo::GetCellNumScales()
+{
+	return this->cellParam.numScales;
+}
 
-	float DecodeInfo::CalculateScale(float min, float max, int index, int maxStride)
-	{
-		return min + (max - min) * 1.0 * index / (maxStride - 1.0f);
-	}
+int DecodeInfo::GetCellOffsetScales()
+{
+	return this->cellParam.offsetScales;
+}
 
-	bool DecodeInfo::IsFixedAnchorSize()
-	{
-		return this->anchorParam.isFixedAnchorSize;;
-	}
+inference_score_type_e DecodeInfo::GetCellType()
+{
+	return this->cellParam.type;
+}
 
-	bool DecodeInfo::IsExponentialBoxScale()
-	{
-		return this->anchorParam.isExponentialBoxScale;
-	}
+float DecodeInfo::CalculateScale(float min, float max, int index, int maxStride)
+{
+	return min + (max - min) * 1.0 * index / (maxStride - 1.0f);
+}
 
-	float DecodeInfo::GetAnchorXscale()
-	{
-		return this->anchorParam.xScale;
-	}
+bool DecodeInfo::IsFixedAnchorSize()
+{
+	return this->anchorParam.isFixedAnchorSize;
+	;
+}
 
-	float DecodeInfo::GetAnchorYscale()
-	{
-		return this->anchorParam.yScale;
-	}
+bool DecodeInfo::IsExponentialBoxScale()
+{
+	return this->anchorParam.isExponentialBoxScale;
+}
 
-	float DecodeInfo::GetAnchorWscale()
-	{
-		return this->anchorParam.wScale;
-	}
+float DecodeInfo::GetAnchorXscale()
+{
+	return this->anchorParam.xScale;
+}
 
-	float DecodeInfo::GetAnchorHscale()
-	{
-		return this->anchorParam.hScale;
-	}
+float DecodeInfo::GetAnchorYscale()
+{
+	return this->anchorParam.yScale;
+}
 
-	int DecodeInfo::GenerateAnchor()
-	{
-		if (this->anchorParam.strides.empty() ||
-			this->anchorParam.aspectRatios.empty()) {
-			LOGE("Invalid anchor parameters");
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
+float DecodeInfo::GetAnchorWscale()
+{
+	return this->anchorParam.wScale;
+}
 
-		int layerId = 0;
-		this->ClearAnchorBox();
-		while (layerId < this->anchorParam.numLayers) {
-			std::vector<float> anchorHeight;
-			std::vector<float> anchorWidth;
-			std::vector<float> aspectRatios;
-			std::vector<float> scales;
-
-			int lastSameStrideLayer = layerId;
-			std::vector<float>::iterator iter1, iter2;
-			while ((lastSameStrideLayer < this->anchorParam.numLayers) &&
-				(this->anchorParam.strides[lastSameStrideLayer] ==
-				 this->anchorParam.strides[layerId])) {
-				const float scale = CalculateScale(this->anchorParam.minScale,
-										this->anchorParam.maxScale,
-										lastSameStrideLayer,
-										this->anchorParam.strides.size());
-
-				if (lastSameStrideLayer == 0 &&
-					this->anchorParam.isReduceBoxedInLowestLayer) {
-					aspectRatios.push_back(1.0);
-					aspectRatios.push_back(2.0);
-					aspectRatios.push_back(0.5);
-					scales.push_back(0.1);
-					scales.push_back(scale);
+float DecodeInfo::GetAnchorHscale()
+{
+	return this->anchorParam.hScale;
+}
+
+int DecodeInfo::GenerateAnchor()
+{
+	if (this->anchorParam.strides.empty() || this->anchorParam.aspectRatios.empty()) {
+		LOGE("Invalid anchor parameters");
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
+	}
+
+	int layerId = 0;
+	this->ClearAnchorBox();
+	while (layerId < this->anchorParam.numLayers) {
+		std::vector<float> anchorHeight;
+		std::vector<float> anchorWidth;
+		std::vector<float> aspectRatios;
+		std::vector<float> scales;
+
+		int lastSameStrideLayer = layerId;
+		std::vector<float>::iterator iter1, iter2;
+		while ((lastSameStrideLayer < this->anchorParam.numLayers) &&
+			   (this->anchorParam.strides[lastSameStrideLayer] == this->anchorParam.strides[layerId])) {
+			const float scale = CalculateScale(this->anchorParam.minScale, this->anchorParam.maxScale,
+											   lastSameStrideLayer, this->anchorParam.strides.size());
+
+			if (lastSameStrideLayer == 0 && this->anchorParam.isReduceBoxedInLowestLayer) {
+				aspectRatios.push_back(1.0);
+				aspectRatios.push_back(2.0);
+				aspectRatios.push_back(0.5);
+				scales.push_back(0.1);
+				scales.push_back(scale);
+				scales.push_back(scale);
+			} else {
+				for (iter1 = this->anchorParam.aspectRatios.begin(); iter1 != this->anchorParam.aspectRatios.end();
+					 ++iter1) {
+					aspectRatios.push_back((*iter1));
 					scales.push_back(scale);
-				} else {
-					for (iter1 = this->anchorParam.aspectRatios.begin();
-						iter1 != this->anchorParam.aspectRatios.end();
-						++iter1) {
-						aspectRatios.push_back((*iter1));
-						scales.push_back(scale);
-					}
-					if (this->anchorParam.interpolatedScaleAspectRatio > 0.0f) {
-						const float scaleNext =
-							lastSameStrideLayer == static_cast<int>(this->anchorParam.strides.size()) -1
-										? 1.0f
-										: CalculateScale(this->anchorParam.minScale,
-												this->anchorParam.maxScale,
-												lastSameStrideLayer + 1,
-												this->anchorParam.strides.size());
-						scales.push_back(std::sqrt(scale * scaleNext));
-						aspectRatios.push_back(this->anchorParam.interpolatedScaleAspectRatio);
-					}
 				}
-				lastSameStrideLayer++;
-			}
-
-			for (iter1 = aspectRatios.begin(), iter2 = scales.begin();
-				(iter1 != aspectRatios.end() && iter2 != scales.end());
-				++iter1, ++iter2) {
-				const float ratioSqrts = std::sqrt((*iter1));
-				anchorHeight.push_back((*iter2) / ratioSqrts);
-				anchorWidth.push_back((*iter2) * ratioSqrts);
-			}
-
-			const int stride = this->anchorParam.strides[layerId];
-			int featureMapHeight = std::ceil(1.0f * this->anchorParam.inputSizeHeight / stride);
-			int featureMapWidth = std::ceil(1.0f * this->anchorParam.inputSizeWidth / stride);
-
-			for (int y = 0; y < featureMapHeight; ++y) {
-				for (int x = 0; x < featureMapWidth; ++x) {
-					for (int anchorId = 0; anchorId < (int)anchorHeight.size(); ++anchorId) {
-						cv::Rect2f anchor = {
-							cv::Point2f {
-								(x + this->anchorParam.anchorOffsetX) * 1.0f / featureMapWidth,
-								(y + this->anchorParam.anchorOffsetY) * 1.0f / featureMapHeight
-							},
-							this->anchorParam.isFixedAnchorSize ?
-								cv::Size2f {1.0f, 1.0f} :
-								cv::Size2f {anchorWidth[anchorId], anchorWidth[anchorId]}
-						};
-						this->AddAnchorBox(anchor);
-					}
+				if (this->anchorParam.interpolatedScaleAspectRatio > 0.0f) {
+					const float scaleNext =
+							lastSameStrideLayer == static_cast<int>(this->anchorParam.strides.size()) - 1 ?
+									1.0f :
+									CalculateScale(this->anchorParam.minScale, this->anchorParam.maxScale,
+												   lastSameStrideLayer + 1, this->anchorParam.strides.size());
+					scales.push_back(std::sqrt(scale * scaleNext));
+					aspectRatios.push_back(this->anchorParam.interpolatedScaleAspectRatio);
 				}
 			}
-			layerId = lastSameStrideLayer;
+			lastSameStrideLayer++;
 		}
 
-		if (this->IsAnchorBoxEmpty()) {
-			LOGE("Anchor boxes are empty");
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
+		for (iter1 = aspectRatios.begin(), iter2 = scales.begin();
+			 (iter1 != aspectRatios.end() && iter2 != scales.end()); ++iter1, ++iter2) {
+			const float ratioSqrts = std::sqrt((*iter1));
+			anchorHeight.push_back((*iter2) / ratioSqrts);
+			anchorWidth.push_back((*iter2) * ratioSqrts);
 		}
 
-		return MEDIA_VISION_ERROR_NONE;
-	}
-
-	int DecodeInfo::ParseNms(JsonObject *root)
-	{
-		if (!json_object_has_member(root, "nms")) {
-			LOGI("nms is empty. skip it");
-			return MEDIA_VISION_ERROR_NONE;
+		const int stride = this->anchorParam.strides[layerId];
+		int featureMapHeight = std::ceil(1.0f * this->anchorParam.inputSizeHeight / stride);
+		int featureMapWidth = std::ceil(1.0f * this->anchorParam.inputSizeWidth / stride);
+
+		for (int y = 0; y < featureMapHeight; ++y) {
+			for (int x = 0; x < featureMapWidth; ++x) {
+				for (int anchorId = 0; anchorId < (int) anchorHeight.size(); ++anchorId) {
+					cv::Rect2f anchor = { cv::Point2f { (x + this->anchorParam.anchorOffsetX) * 1.0f / featureMapWidth,
+														(y + this->anchorParam.anchorOffsetY) * 1.0f /
+																featureMapHeight },
+										  this->anchorParam.isFixedAnchorSize ?
+												  cv::Size2f { 1.0f, 1.0f } :
+												  cv::Size2f { anchorWidth[anchorId], anchorWidth[anchorId] } };
+					this->AddAnchorBox(anchor);
+				}
+			}
 		}
+		layerId = lastSameStrideLayer;
+	}
 
-		JsonObject *object = json_object_get_object_member(root, "nms");
-		try {
-			this->nmsParam.mode = GetSupportedType(object, "mode", this->nmsParam.supportedBoxNmsTypes);
-		} catch (const std::exception& e) {
-			LOGE("Invalid %s", e.what());
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
+	if (this->IsAnchorBoxEmpty()) {
+		LOGE("Anchor boxes are empty");
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
+	}
 
-		this->nmsParam.iouThreshold = static_cast<float>(json_object_get_double_member(object,"iou_threshold"));
+	return MEDIA_VISION_ERROR_NONE;
+}
 
+int DecodeInfo::ParseNms(JsonObject *root)
+{
+	if (!json_object_has_member(root, "nms")) {
+		LOGI("nms is empty. skip it");
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	int DecodeInfo::GetNmsMode()
-	{
-		return this->nmsParam.mode;
+	JsonObject *object = json_object_get_object_member(root, "nms");
+	try {
+		this->nmsParam.mode = GetSupportedType(object, "mode", this->nmsParam.supportedBoxNmsTypes);
+	} catch (const std::exception &e) {
+		LOGE("Invalid %s", e.what());
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
-	float DecodeInfo::GetNmsIouThreshold()
-	{
-		return this->nmsParam.iouThreshold;
-	}
+	this->nmsParam.iouThreshold = static_cast<float>(json_object_get_double_member(object, "iou_threshold"));
 
-	int DecodeInfo::ParseRotate(JsonObject *root)
-	{
-		if (!json_object_has_member(root, "rotate")) {
-			LOGI("rotate is empty. skip it");
-			return MEDIA_VISION_ERROR_NONE;
-		}
+	return MEDIA_VISION_ERROR_NONE;
+}
+
+int DecodeInfo::GetNmsMode()
+{
+	return this->nmsParam.mode;
+}
 
-		JsonObject *object = json_object_get_object_member(root, "rotate");
-		this->rotParam.baseAngle = static_cast<float>(json_object_get_double_member(object, "base_angle"));
-		this->rotParam.startPointIndex = static_cast<int>(json_object_get_int_member(object, "start_point_index"));
-		this->rotParam.endPointIndex = static_cast<int>(json_object_get_int_member(object, "end_point_index"));
+float DecodeInfo::GetNmsIouThreshold()
+{
+	return this->nmsParam.iouThreshold;
+}
 
+int DecodeInfo::ParseRotate(JsonObject *root)
+{
+	if (!json_object_has_member(root, "rotate")) {
+		LOGI("rotate is empty. skip it");
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	int DecodeInfo::GetRotStartPointIndex()
-	{
-		return this->rotParam.startPointIndex;
-	}
+	JsonObject *object = json_object_get_object_member(root, "rotate");
+	this->rotParam.baseAngle = static_cast<float>(json_object_get_double_member(object, "base_angle"));
+	this->rotParam.startPointIndex = static_cast<int>(json_object_get_int_member(object, "start_point_index"));
+	this->rotParam.endPointIndex = static_cast<int>(json_object_get_int_member(object, "end_point_index"));
 
-	int DecodeInfo::GetRotEndPointIndex()
-	{
-		return this->rotParam.endPointIndex;
-	}
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-	float DecodeInfo::GetBaseAngle()
-	{
-		return this->rotParam.baseAngle;
-	}
+int DecodeInfo::GetRotStartPointIndex()
+{
+	return this->rotParam.startPointIndex;
+}
 
-	int DecodeInfo::GetRoiMode()
-	{
-		return this->roiOptParam.mode;
-	}
+int DecodeInfo::GetRotEndPointIndex()
+{
+	return this->rotParam.endPointIndex;
+}
 
-	int DecodeInfo::GetRoiStartPointIndex()
-	{
-		return this->roiOptParam.startPointIndex;
-	}
+float DecodeInfo::GetBaseAngle()
+{
+	return this->rotParam.baseAngle;
+}
 
-	int DecodeInfo::GetRoiEndPointIndex()
-	{
-		return this->roiOptParam.endPointIndex;
-	}
+int DecodeInfo::GetRoiMode()
+{
+	return this->roiOptParam.mode;
+}
 
-	int DecodeInfo::GetRoiCenterPointIndex()
-	{
-		return this->roiOptParam.centerPointIndex;
-	}
+int DecodeInfo::GetRoiStartPointIndex()
+{
+	return this->roiOptParam.startPointIndex;
+}
 
-	float DecodeInfo::GetShiftX()
-	{
-		return this->roiOptParam.shiftX;
-	}
+int DecodeInfo::GetRoiEndPointIndex()
+{
+	return this->roiOptParam.endPointIndex;
+}
 
-	float DecodeInfo::GetShiftY()
-	{
-		return this->roiOptParam.shiftY;
-	}
+int DecodeInfo::GetRoiCenterPointIndex()
+{
+	return this->roiOptParam.centerPointIndex;
+}
 
-	float DecodeInfo::GetScaleX()
-	{
-		return this->roiOptParam.scaleX;
-	}
+float DecodeInfo::GetShiftX()
+{
+	return this->roiOptParam.shiftX;
+}
 
-	float DecodeInfo::GetScaleY()
-	{
-		return this->roiOptParam.scaleY;
-	}
+float DecodeInfo::GetShiftY()
+{
+	return this->roiOptParam.shiftY;
+}
 
-	int DecodeInfo::ParseRoiOption(JsonObject *root)
-	{
-		if (!json_object_has_member(root, "roi")) {
-			LOGI("roi is empty. skip it");
-			return MEDIA_VISION_ERROR_NONE;
-		}
+float DecodeInfo::GetScaleX()
+{
+	return this->roiOptParam.scaleX;
+}
 
-		JsonObject *object = json_object_get_object_member(root, "roi");
-		this->roiOptParam.startPointIndex = static_cast<int>(json_object_get_int_member(object, "start_point_index"));
-		this->roiOptParam.endPointIndex = static_cast<int>(json_object_get_int_member(object, "end_point_index"));
-		this->roiOptParam.centerPointIndex = static_cast<int>(json_object_get_int_member(object, "center_point_index"));
-		this->roiOptParam.shiftX = static_cast<float>(json_object_get_double_member(object, "shift_x"));
-		this->roiOptParam.shiftY = static_cast<float>(json_object_get_double_member(object, "shift_y"));
-		this->roiOptParam.scaleX = static_cast<float>(json_object_get_double_member(object, "scale_x"));
-		this->roiOptParam.scaleY = static_cast<float>(json_object_get_double_member(object, "scale_y"));
-		this->roiOptParam.mode = static_cast<int>(json_object_get_int_member(object, "scale_mode"));
+float DecodeInfo::GetScaleY()
+{
+	return this->roiOptParam.scaleY;
+}
 
+int DecodeInfo::ParseRoiOption(JsonObject *root)
+{
+	if (!json_object_has_member(root, "roi")) {
+		LOGI("roi is empty. skip it");
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	int OutputMetadata::ParseLandmark(JsonObject *root)
-	{
-		LOGI("ENTER");
+	JsonObject *object = json_object_get_object_member(root, "roi");
+	this->roiOptParam.startPointIndex = static_cast<int>(json_object_get_int_member(object, "start_point_index"));
+	this->roiOptParam.endPointIndex = static_cast<int>(json_object_get_int_member(object, "end_point_index"));
+	this->roiOptParam.centerPointIndex = static_cast<int>(json_object_get_int_member(object, "center_point_index"));
+	this->roiOptParam.shiftX = static_cast<float>(json_object_get_double_member(object, "shift_x"));
+	this->roiOptParam.shiftY = static_cast<float>(json_object_get_double_member(object, "shift_y"));
+	this->roiOptParam.scaleX = static_cast<float>(json_object_get_double_member(object, "scale_x"));
+	this->roiOptParam.scaleY = static_cast<float>(json_object_get_double_member(object, "scale_y"));
+	this->roiOptParam.mode = static_cast<int>(json_object_get_int_member(object, "scale_mode"));
 
-		if (!json_object_has_member(root, "landmark")) {
-			LOGI("No landmark outputmetadata");
-			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
-		}
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		landmark.ParseLandmark(root);
+int OutputMetadata::ParseLandmark(JsonObject *root)
+{
+	LOGI("ENTER");
 
+	if (!json_object_has_member(root, "landmark")) {
+		LOGI("No landmark outputmetadata");
 		LOGI("LEAVE");
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	int OutputMetadata::ParseOffset(JsonObject *root)
-	{
-		LOGI("ENTER");
+	landmark.ParseLandmark(root);
 
-		if (!json_object_has_member(root, "offset")) {
-			LOGI("No offset outputmetadata");
-			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
+	LOGI("LEAVE");
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		offsetVec.ParseOffset(root, mSupportedShapeType);
+int OutputMetadata::ParseOffset(JsonObject *root)
+{
+	LOGI("ENTER");
 
+	if (!json_object_has_member(root, "offset")) {
+		LOGI("No offset outputmetadata");
 		LOGI("LEAVE");
-		return MEDIA_VISION_ERROR_NONE;
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
-	int OutputMetadata::Parse(JsonObject *root)
-	{
-		LOGI("ENTER");
+	offsetVec.ParseOffset(root, mSupportedShapeType);
 
-		int ret = ParseScore(root);
-		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to GetScore[%d]", ret);
-			return ret;
-		}
+	LOGI("LEAVE");
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		ret = ParseBox(root);
-		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to GetBox[%d]", ret);
-			return ret;
-		}
+int OutputMetadata::Parse(JsonObject *root)
+{
+	LOGI("ENTER");
 
-		if (!box.GetName().empty()) {
-			// addtional parsing is required according to decoding type
-			if (box.GetDecodingType() == INFERENCE_BOX_DECODING_TYPE_BYPASS) {
+	int ret = ParseScore(root);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to GetScore[%d]", ret);
+		return ret;
+	}
 
-				ret = box.ParseLabel(root);
-				if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to GetLabel[%d]", ret);
-					return ret;
-				}
+	ret = ParseBox(root);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to GetBox[%d]", ret);
+		return ret;
+	}
 
-				ret = box.ParseNumber(root);
-				if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to GetNumber[%d]", ret);
-					return ret;
-				}
+	if (!box.GetName().empty()) {
+		// addtional parsing is required according to decoding type
+		if (box.GetDecodingType() == INFERENCE_BOX_DECODING_TYPE_BYPASS) {
+			ret = box.ParseLabel(root);
+			if (ret != MEDIA_VISION_ERROR_NONE) {
+				LOGE("Fail to GetLabel[%d]", ret);
+				return ret;
+			}
 
-			} else {
-				ret = box.ParseDecodeInfo(root);
+			ret = box.ParseNumber(root);
+			if (ret != MEDIA_VISION_ERROR_NONE) {
+				LOGE("Fail to GetNumber[%d]", ret);
+				return ret;
+			}
+
+		} else {
+			ret = box.ParseDecodeInfo(root);
+			if (ret != MEDIA_VISION_ERROR_NONE) {
+				LOGE("Fail to GetBoxDecodeInfo[%d]", ret);
+				return ret;
+			}
+
+			if (box.GetDecodingType() == INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR) {
+				ret = box.GetDecodeInfo().GenerateAnchor();
 				if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to GetBoxDecodeInfo[%d]", ret);
+					LOGE("Fail to GenerateAnchor[%d]", ret);
 					return ret;
 				}
-
-				if (box.GetDecodingType() == INFERENCE_BOX_DECODING_TYPE_SSD_ANCHOR) {
-					ret = box.GetDecodeInfo().GenerateAnchor();
-					if (ret != MEDIA_VISION_ERROR_NONE) {
-						LOGE("Fail to GenerateAnchor[%d]", ret);
-						return ret;
-					}
-				}
 			}
 		}
+	}
 
-		ret = ParseLandmark(root);
-		if (ret != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Fail to GetLandmark[%d]", ret);
-			return ret;
-		}
+	ret = ParseLandmark(root);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to GetLandmark[%d]", ret);
+		return ret;
+	}
 
-		if (!landmark.GetName().empty()) {
-			if (landmark.GetDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP ||
-				landmark.GetDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP_REFINE) {
-				ret = landmark.ParseDecodeInfo(root, mSupportedShapeType);
-				if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to GetLandmarkDecodeInfo[%d]", ret);
-					return ret;
-				}
+	if (!landmark.GetName().empty()) {
+		if (landmark.GetDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP ||
+			landmark.GetDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP_REFINE) {
+			ret = landmark.ParseDecodeInfo(root, mSupportedShapeType);
+			if (ret != MEDIA_VISION_ERROR_NONE) {
+				LOGE("Fail to GetLandmarkDecodeInfo[%d]", ret);
+				return ret;
 			}
+		}
 
-			if (landmark.GetDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP_REFINE) {
-				ret = ParseOffset(root);
-				if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to GetOffsetVector[%d]", ret);
-					return ret;
-				}
+		if (landmark.GetDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP_REFINE) {
+			ret = ParseOffset(root);
+			if (ret != MEDIA_VISION_ERROR_NONE) {
+				LOGE("Fail to GetOffsetVector[%d]", ret);
+				return ret;
+			}
 
-				ret = landmark.ParseDisplacement(root, mSupportedShapeType);
-				if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to GetDispVector[%d]", ret);
-					return ret;
-				}
+			ret = landmark.ParseDisplacement(root, mSupportedShapeType);
+			if (ret != MEDIA_VISION_ERROR_NONE) {
+				LOGE("Fail to GetDispVector[%d]", ret);
+				return ret;
+			}
 
-				ret = landmark.ParseEdgeMap(root);
-				if (ret != MEDIA_VISION_ERROR_NONE) {
-					LOGE("Fail to GetEdgeConnection[%d]", ret);
-					return ret;
-				}
+			ret = landmark.ParseEdgeMap(root);
+			if (ret != MEDIA_VISION_ERROR_NONE) {
+				LOGE("Fail to GetEdgeConnection[%d]", ret);
+				return ret;
 			}
 		}
+	}
 
-		parsed = true;
+	parsed = true;
 
-		LOGI("LEAVE");
+	LOGI("LEAVE");
 
-		return MEDIA_VISION_ERROR_NONE;
-	}
+	return MEDIA_VISION_ERROR_NONE;
+}
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/src/PoseDecoder.cpp b/mv_machine_learning/inference/src/PoseDecoder.cpp
index 09c10d8..99ad700 100644
--- a/mv_machine_learning/inference/src/PoseDecoder.cpp
+++ b/mv_machine_learning/inference/src/PoseDecoder.cpp
@@ -28,468 +28,449 @@ namespace mediavision
 {
 namespace inference
 {
-	int PoseDecoder::convertXYZtoX(int x, int y, int c)
-	{
-		return y * mHeatMapWidth * mHeatMapChannel
-					+ x * mHeatMapChannel
-					+ c;
-	}
+int PoseDecoder::convertXYZtoX(int x, int y, int c)
+{
+	return y * mHeatMapWidth * mHeatMapChannel + x * mHeatMapChannel + c;
+}
 
-	cv::Point PoseDecoder::convertXYZtoXY(int x, int y, int c)
-	{
-		int idxY = y * mHeatMapWidth * mHeatMapChannel * 2
-					+ x * mHeatMapChannel * 2
-					+ c;
+cv::Point PoseDecoder::convertXYZtoXY(int x, int y, int c)
+{
+	int idxY = y * mHeatMapWidth * mHeatMapChannel * 2 + x * mHeatMapChannel * 2 + c;
 
-		int idxX = idxY + mHeatMapChannel;
+	int idxX = idxY + mHeatMapChannel;
 
-		return cv::Point(idxX, idxY);
-	}
+	return cv::Point(idxX, idxY);
+}
 
-	int PoseDecoder::init()
-	{
-		LOGI("ENTER");
+int PoseDecoder::init()
+{
+	LOGI("ENTER");
 
-		if (mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS ||
-			mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS_MULTICHANNEL) {
-			LOGI("Skip init");
-			return MEDIA_VISION_ERROR_NONE;
-		}
+	if (mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS ||
+		mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS_MULTICHANNEL) {
+		LOGI("Skip init");
+		return MEDIA_VISION_ERROR_NONE;
+	}
 
-		int x,y,c;
-		int sx, sy, ex, ey, dx, dy;
-		float score, localScore;
-		int idx;
-		bool isLocalMax;
+	int x, y, c;
+	int sx, sy, ex, ey, dx, dy;
+	float score, localScore;
+	int idx;
+	bool isLocalMax;
 
-		mCandidates.clear();
+	mCandidates.clear();
 
-		if (mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE ||
-			mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_3D_SINGLE) {
-			mCandidates.resize(mHeatMapChannel);
-		}
+	if (mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE ||
+		mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_3D_SINGLE) {
+		mCandidates.resize(mHeatMapChannel);
+	}
 
-		for (y = 0; y < mHeatMapHeight; ++y) {
-			for (x = 0; x < mHeatMapWidth; ++x) {
-				std::list<LandmarkPoint>::iterator candidate = mCandidates.begin();
-				for (c = 0; c < mHeatMapChannel; ++c, candidate++) {
-					isLocalMax = true;
-					idx = convertXYZtoX(x, y, c);
-					score = mTensorBuffer.getValue<float>(mMeta.GetScoreName(), idx);
-					if (mMeta.GetScoreType() == INFERENCE_SCORE_TYPE_SIGMOID) {
-						score = PostProcess::sigmoid(score);
-					}
+	for (y = 0; y < mHeatMapHeight; ++y) {
+		for (x = 0; x < mHeatMapWidth; ++x) {
+			std::list<LandmarkPoint>::iterator candidate = mCandidates.begin();
+			for (c = 0; c < mHeatMapChannel; ++c, candidate++) {
+				isLocalMax = true;
+				idx = convertXYZtoX(x, y, c);
+				score = mTensorBuffer.getValue<float>(mMeta.GetScoreName(), idx);
+				if (mMeta.GetScoreType() == INFERENCE_SCORE_TYPE_SIGMOID) {
+					score = PostProcess::sigmoid(score);
+				}
 
-					if (score < mMeta.GetScoreThreshold())
+				if (score < mMeta.GetScoreThreshold())
+					continue;
+
+				if (mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE ||
+					mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_3D_SINGLE) {
+					if (score <= candidate->score)
 						continue;
 
-					if (mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE ||
-						mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_3D_SINGLE) {
-						if (score <= candidate->score)
-							continue;
-
-						candidate->score = score;
-						candidate->heatMapLoc.x = x;
-						candidate->heatMapLoc.y = y;
-						candidate->id = c;
-
-					} else { //landmarkInfo.type == 1
-						sx = std::max(x - 1, 0);
-						sy = std::max(y - 1, 0);
-						ex = std::min(x + 2, mHeatMapWidth);
-						ey = std::min(y + 2, mHeatMapHeight);
-
-						for (dy = sy; dy < ey; ++dy) {
-							for (dx = sx; dx < ex; ++dx) {
-								idx = convertXYZtoX(dx, dy, c);
-								localScore =  mTensorBuffer.getValue<float>(mMeta.GetScoreName(), idx);
-								if (mMeta.GetScoreType() == INFERENCE_SCORE_TYPE_SIGMOID) {
-									localScore = PostProcess::sigmoid(localScore);
-								}
-								if (localScore > score) {
-									isLocalMax = false;
-									break;
-								}
+					candidate->score = score;
+					candidate->heatMapLoc.x = x;
+					candidate->heatMapLoc.y = y;
+					candidate->id = c;
+
+				} else { //landmarkInfo.type == 1
+					sx = std::max(x - 1, 0);
+					sy = std::max(y - 1, 0);
+					ex = std::min(x + 2, mHeatMapWidth);
+					ey = std::min(y + 2, mHeatMapHeight);
+
+					for (dy = sy; dy < ey; ++dy) {
+						for (dx = sx; dx < ex; ++dx) {
+							idx = convertXYZtoX(dx, dy, c);
+							localScore = mTensorBuffer.getValue<float>(mMeta.GetScoreName(), idx);
+							if (mMeta.GetScoreType() == INFERENCE_SCORE_TYPE_SIGMOID) {
+								localScore = PostProcess::sigmoid(localScore);
 							}
-							if (isLocalMax == false)
+							if (localScore > score) {
+								isLocalMax = false;
 								break;
+							}
 						}
-
 						if (isLocalMax == false)
-							continue;
+							break;
+					}
 
-						// add this to list
-						LOGI("[%d x %d][%d]: score %.3f", y, x, c, score);
-						std::list<LandmarkPoint>::iterator iter;
-						for (iter = mCandidates.begin(); iter != mCandidates.end(); ++iter) {
-							if ((*iter).score < score) {
-								break;
-							}
-						}
+					if (isLocalMax == false)
+						continue;
 
-						LandmarkPoint localLandmark;
-						localLandmark.score = score;
-						localLandmark.heatMapLoc.x = x;
-						localLandmark.heatMapLoc.y = y;
-						localLandmark.id = c;
-						localLandmark.valid = false;
-						mCandidates.insert(iter, localLandmark);
+					// add this to list
+					LOGI("[%d x %d][%d]: score %.3f", y, x, c, score);
+					std::list<LandmarkPoint>::iterator iter;
+					for (iter = mCandidates.begin(); iter != mCandidates.end(); ++iter) {
+						if ((*iter).score < score) {
+							break;
+						}
 					}
+
+					LandmarkPoint localLandmark;
+					localLandmark.score = score;
+					localLandmark.heatMapLoc.x = x;
+					localLandmark.heatMapLoc.y = y;
+					localLandmark.id = c;
+					localLandmark.valid = false;
+					mCandidates.insert(iter, localLandmark);
 				}
 			}
-		} // end of init
+		}
+	} // end of init
 
-		LOGI("LEAVE");
+	LOGI("LEAVE");
+
+	return MEDIA_VISION_ERROR_NONE;
+}
 
+int PoseDecoder::getNumberOfPose()
+{
+	return std::min(static_cast<int>(mPoseLandmarks.size()), MAX_NUMBER_OF_POSE);
+}
+
+int PoseDecoder::getOffsetValue(LandmarkPoint &landmark, cv::Point2f &offsetVal)
+{
+	if (!mTensorBuffer.exist(mMeta.GetOffsetVecName())) {
+		offsetVal.x = offsetVal.y = 0.f;
+		LOGI("No offset value");
+		LOGI("LEAVE");
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	int PoseDecoder::getNumberOfPose()
-	{
-		return std::min(static_cast<int>(mPoseLandmarks.size()), MAX_NUMBER_OF_POSE);
-	}
+	cv::Point idx = convertXYZtoXY(landmark.heatMapLoc.x, landmark.heatMapLoc.y, landmark.id);
 
-	int PoseDecoder::getOffsetValue(LandmarkPoint& landmark, cv::Point2f &offsetVal)
-	{
-		if (!mTensorBuffer.exist(mMeta.GetOffsetVecName())) {
-			offsetVal.x = offsetVal.y = 0.f;
-			LOGI("No offset value");
-			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
-		}
+	try {
+		offsetVal.x = mTensorBuffer.getValue<float>(mMeta.GetOffsetVecName(), idx.x);
+		offsetVal.y = mTensorBuffer.getValue<float>(mMeta.GetOffsetVecName(), idx.y);
+	} catch (const std::exception &e) {
+		LOGE("Fail to get value at (%d, %d) from %s", idx.x, idx.y, mMeta.GetOffsetVecName().c_str());
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
+	}
 
-		cv::Point idx = convertXYZtoXY(landmark.heatMapLoc.x, landmark.heatMapLoc.y, landmark.id);
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		try {
-			offsetVal.x = mTensorBuffer.getValue<float>(mMeta.GetOffsetVecName(), idx.x);
-			offsetVal.y = mTensorBuffer.getValue<float>(mMeta.GetOffsetVecName(), idx.y);
-		} catch (const std::exception& e) {
-			LOGE("Fail to get value at (%d, %d) from %s",
-						idx.x, idx.y, mMeta.GetOffsetVecName().c_str());
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
+float PoseDecoder::getPointX(int poseIdx, int partIdx)
+{
+	LOGI("idx[%d]-part[%d]", poseIdx, partIdx);
+	return mPoseLandmarks[poseIdx].landmarks[partIdx].decodedLoc.x;
+}
 
-		return MEDIA_VISION_ERROR_NONE;
-	}
+float PoseDecoder::getPointY(int poseIdx, int partIdx)
+{
+	LOGI("idx[%d]-part[%d]", poseIdx, partIdx);
+	return mPoseLandmarks[poseIdx].landmarks[partIdx].decodedLoc.y;
+}
 
-	float PoseDecoder::getPointX(int poseIdx, int partIdx)
-	{
-		LOGI("idx[%d]-part[%d]", poseIdx, partIdx);
-		return mPoseLandmarks[poseIdx].landmarks[partIdx].decodedLoc.x;
-	}
+float PoseDecoder::getScore(int poseIdx, int partIdx)
+{
+	return mPoseLandmarks[poseIdx].landmarks[partIdx].score;
+}
 
-	float PoseDecoder::getPointY(int poseIdx, int partIdx)
-	{
-		LOGI("idx[%d]-part[%d]", poseIdx, partIdx);
-		return mPoseLandmarks[poseIdx].landmarks[partIdx].decodedLoc.y;
+int PoseDecoder::getIndexToPos(LandmarkPoint &point, float scaleW, float scaleH)
+{
+	if (scaleW <= 0.0f || scaleH <= 0.0f) {
+		LOGE("scale width(%.4f) or height(%.4f) is less than or equal to zero", scaleW, scaleH);
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	float PoseDecoder::getScore(int poseIdx, int partIdx)
-	{
-		return mPoseLandmarks[poseIdx].landmarks[partIdx].score;
-	}
+	cv::Point2f offsetVal;
+	getOffsetValue(point, offsetVal);
 
-	int PoseDecoder::getIndexToPos(LandmarkPoint& point, float scaleW, float scaleH)
-	{
-		if (scaleW <= 0.0f || scaleH <= 0.0f) {
-			LOGE("scale width(%.4f) or height(%.4f) is less than or equal to zero", scaleW, scaleH);
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-		}
+	point.decodedLoc.x = static_cast<float>(point.heatMapLoc.x) / static_cast<float>(mHeatMapWidth - 1);
+	point.decodedLoc.y = static_cast<float>(point.heatMapLoc.y) / static_cast<float>(mHeatMapHeight - 1);
 
-		cv::Point2f offsetVal;
-		getOffsetValue(point, offsetVal);
+	point.decodedLoc.x += offsetVal.x / scaleW;
+	point.decodedLoc.y += offsetVal.y / scaleH;
 
-		point.decodedLoc.x = static_cast<float>(point.heatMapLoc.x) / static_cast<float>(mHeatMapWidth - 1);
-		point.decodedLoc.y = static_cast<float>(point.heatMapLoc.y) / static_cast<float>(mHeatMapHeight - 1);
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		point.decodedLoc.x += offsetVal.x / scaleW;
-		point.decodedLoc.y += offsetVal.y / scaleH;
+int PoseDecoder::getPosToIndex(LandmarkPoint &point)
+{
+	cv::Point posVal;
 
-		return MEDIA_VISION_ERROR_NONE;
-	}
+	posVal.x = roundf(point.decodedLoc.x * static_cast<float>(mHeatMapWidth - 1));
+	posVal.y = roundf(point.decodedLoc.y * static_cast<float>(mHeatMapHeight - 1));
 
-	int PoseDecoder::getPosToIndex(LandmarkPoint& point)
-	{
-		cv::Point posVal;
+	posVal.x = std::max(std::min(posVal.x, mHeatMapWidth - 1), 0);
+	posVal.y = std::max(std::min(posVal.y, mHeatMapHeight - 1), 0);
 
-		posVal.x = roundf(point.decodedLoc.x * static_cast<float>(mHeatMapWidth - 1));
-		posVal.y = roundf(point.decodedLoc.y * static_cast<float>(mHeatMapHeight - 1));
+	point.heatMapLoc = posVal;
 
-		posVal.x = std::max(std::min(posVal.x, mHeatMapWidth - 1), 0);
-		posVal.y = std::max(std::min(posVal.y, mHeatMapHeight - 1), 0);
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		point.heatMapLoc = posVal;
+int PoseDecoder::decode(float scaleWidth, float scaleHeight, float thresHoldRadius)
+{
+	LOGI("ENTER");
 
-		return MEDIA_VISION_ERROR_NONE;
+	if (scaleWidth <= 0.0f || scaleHeight <= 0.0f) {
+		LOGE("scale width(%.4f) or height(%.4f) is less than or equal to zero", scaleWidth, scaleHeight);
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	int PoseDecoder::decode(float scaleWidth, float scaleHeight, float thresHoldRadius)
-	{
-		LOGI("ENTER");
-
-		if (scaleWidth <= 0.0f || scaleHeight <= 0.0f) {
-			LOGE("scale width(%.4f) or height(%.4f) is less than or equal to zero", scaleWidth, scaleHeight);
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-		}
-
-		mPoseLandmarks.clear();
+	mPoseLandmarks.clear();
 
-		LandmarkPoint initValue = {0.0f, cv::Point(0,0), cv::Point2f(0.0f, 0.0f), -1, false};
+	LandmarkPoint initValue = { 0.0f, cv::Point(0, 0), cv::Point2f(0.0f, 0.0f), -1, false };
 
-		if (mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE ||
-			mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_3D_SINGLE) {
-			mPoseLandmarks.resize(1);
+	if (mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE ||
+		mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_3D_SINGLE) {
+		mPoseLandmarks.resize(1);
 
-			if (mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS ||
-				mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS_MULTICHANNEL) {
-				mPoseLandmarks[0].landmarks.resize(mNumberOfLandmarks);
-			} else {
-				mPoseLandmarks[0].landmarks.resize(mHeatMapChannel);
-			}
+		if (mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS ||
+			mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS_MULTICHANNEL) {
+			mPoseLandmarks[0].landmarks.resize(mNumberOfLandmarks);
+		} else {
+			mPoseLandmarks[0].landmarks.resize(mHeatMapChannel);
 		}
+	}
 
-		if (mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP ||
-			mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP_REFINE) {
-			while (!mCandidates.empty()) {
+	if (mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP ||
+		mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_HEATMAP_REFINE) {
+		while (!mCandidates.empty()) {
+			LandmarkPoint &root = mCandidates.front();
 
-				LandmarkPoint &root = mCandidates.front();
+			getIndexToPos(root, scaleWidth, scaleHeight);
 
-				getIndexToPos(root, scaleWidth, scaleHeight);
+			if (mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE) {
+				root.valid = true;
+				mPoseLandmarks[0].landmarks[root.id] = root;
+				mPoseLandmarks[0].score += root.score;
+				mCandidates.pop_front();
+				continue;
+			}
 
-				if (mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE) {
-					root.valid = true;
-					mPoseLandmarks[0].landmarks[root.id] = root;
-					mPoseLandmarks[0].score += root.score;
+			LOGI("root id: %d", root.id);
+
+			if (thresHoldRadius > 0.0f) {
+				bool isSkip = false;
+				for (auto &result : mPoseLandmarks) {
+					cv::Point2f dfRadius = result.landmarks[root.id].decodedLoc;
+					dfRadius -= root.decodedLoc;
+					float radius = std::pow(dfRadius.x * scaleWidth, 2.0f) + std::pow(dfRadius.y * scaleHeight, 2.0f);
+					LOGI("id[%d], radius: %.f vs. %.f", root.id, radius, std::pow(thresHoldRadius, 2.0f));
+					if (radius <= std::pow(thresHoldRadius, 2.0f)) {
+						LOGI("Not local maximum, Skip this");
+						isSkip = true;
+						break;
+					}
+				}
+				if (isSkip) {
 					mCandidates.pop_front();
 					continue;
 				}
+			}
 
-				LOGI("root id: %d", root.id);
-
-				if (thresHoldRadius > 0.0f) {
-					bool isSkip = false;
-					for (auto& result : mPoseLandmarks) {
-						cv::Point2f dfRadius = result.landmarks[root.id].decodedLoc;
-						dfRadius -= root.decodedLoc;
-						float radius =
-							std::pow(dfRadius.x * scaleWidth, 2.0f) +
-							std::pow(dfRadius.y	* scaleHeight, 2.0f);
-						LOGI("id[%d], radius: %.f vs. %.f", root.id, radius, std::pow(thresHoldRadius, 2.0f));
-						if (radius <= std::pow(thresHoldRadius, 2.0f)) {
-							LOGI("Not local maximum, Skip this");
-							isSkip = true;
-							break;
-						}
-					}
-					if (isSkip) {
-						mCandidates.pop_front();
-						continue;
-					}
-				}
-
-				LOGI("Local maximum. Add this");
-
-				std::vector<LandmarkPoint> decodedLandmarks(mHeatMapChannel, initValue);
+			LOGI("Local maximum. Add this");
 
-				findPose(root, decodedLandmarks, scaleWidth, scaleHeight);
+			std::vector<LandmarkPoint> decodedLandmarks(mHeatMapChannel, initValue);
 
-				float poseScore = 0.0f;
-				for (auto& landmark : decodedLandmarks) {
-					poseScore += landmark.score;
-					LOGI("%.3f, %.3f", landmark.decodedLoc.x, landmark.decodedLoc.y);
-				}
+			findPose(root, decodedLandmarks, scaleWidth, scaleHeight);
 
-				mPoseLandmarks.push_back(LandmarkResults {decodedLandmarks, poseScore});
-				if (mPoseLandmarks.size() > MAX_NUMBER_OF_POSE)
-					break;
-				mCandidates.pop_front();
+			float poseScore = 0.0f;
+			for (auto &landmark : decodedLandmarks) {
+				poseScore += landmark.score;
+				LOGI("%.3f, %.3f", landmark.decodedLoc.x, landmark.decodedLoc.y);
 			}
 
-			for (auto& pose : mPoseLandmarks) {
-				pose.score /= static_cast<float>(mHeatMapChannel);
-			}
-		} else if (mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS_MULTICHANNEL) {
-			int landmarkOffset = mMeta.GetLandmarkOffset();
-			for (int idx = 0; idx < mNumberOfLandmarks; ++idx) {
-					float py = mTensorBuffer.getValue<float>(mMeta.GetLandmarkName(), idx * landmarkOffset);
-					float px = mTensorBuffer.getValue<float>(mMeta.GetLandmarkName(), idx * landmarkOffset + 1);
-					float pscore = mTensorBuffer.getValue<float>(mMeta.GetScoreName(), idx * landmarkOffset + 2);
-
-					mPoseLandmarks[0].landmarks[idx].score = pscore;
-					mPoseLandmarks[0].landmarks[idx].heatMapLoc = cv::Point(-1, -1);
-					mPoseLandmarks[0].landmarks[idx].decodedLoc = cv::Point2f(px / scaleWidth, py / scaleHeight);
-					mPoseLandmarks[0].landmarks[idx].id = idx;
-					mPoseLandmarks[0].landmarks[idx].valid =  true;
-
-					LOGI("idx[%d]: %.4f, %.4f, score: %.4f", idx, px, py, pscore);
+			mPoseLandmarks.push_back(LandmarkResults { decodedLandmarks, poseScore });
+			if (mPoseLandmarks.size() > MAX_NUMBER_OF_POSE)
+				break;
+			mCandidates.pop_front();
+		}
+
+		for (auto &pose : mPoseLandmarks) {
+			pose.score /= static_cast<float>(mHeatMapChannel);
+		}
+	} else if (mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS_MULTICHANNEL) {
+		int landmarkOffset = mMeta.GetLandmarkOffset();
+		for (int idx = 0; idx < mNumberOfLandmarks; ++idx) {
+			float py = mTensorBuffer.getValue<float>(mMeta.GetLandmarkName(), idx * landmarkOffset);
+			float px = mTensorBuffer.getValue<float>(mMeta.GetLandmarkName(), idx * landmarkOffset + 1);
+			float pscore = mTensorBuffer.getValue<float>(mMeta.GetScoreName(), idx * landmarkOffset + 2);
+
+			mPoseLandmarks[0].landmarks[idx].score = pscore;
+			mPoseLandmarks[0].landmarks[idx].heatMapLoc = cv::Point(-1, -1);
+			mPoseLandmarks[0].landmarks[idx].decodedLoc = cv::Point2f(px / scaleWidth, py / scaleHeight);
+			mPoseLandmarks[0].landmarks[idx].id = idx;
+			mPoseLandmarks[0].landmarks[idx].valid = true;
+
+			LOGI("idx[%d]: %.4f, %.4f, score: %.4f", idx, px, py, pscore);
+		}
+	} else {
+		// multi pose is not supported
+		std::vector<int> scoreIndexes = mMeta.GetScoreDimInfo().GetValidIndexAll();
+		float poseScore = mMeta.GetScoreThreshold();
+		if (!scoreIndexes.empty()) {
+			poseScore = mTensorBuffer.getValue<float>(mMeta.GetScoreName(), scoreIndexes[scoreIndexes[0]]);
+			if (mMeta.GetScoreType() == INFERENCE_SCORE_TYPE_SIGMOID) {
+				poseScore = PostProcess::sigmoid(poseScore);
 			}
-		} else {
-			// multi pose is not supported
-			std::vector<int> scoreIndexes = mMeta.GetScoreDimInfo().GetValidIndexAll();
-			float poseScore = mMeta.GetScoreThreshold();
-			if (!scoreIndexes.empty()) {
-				poseScore  = mTensorBuffer.getValue<float>(mMeta.GetScoreName(), scoreIndexes[scoreIndexes[0]]);
-				if (mMeta.GetScoreType() == INFERENCE_SCORE_TYPE_SIGMOID) {
-					poseScore = PostProcess::sigmoid(poseScore);
-				}
-				if (poseScore < mMeta.GetScoreThreshold()) {
-					LOGI("pose score %.4f is lower than %.4f\n[LEAVE]", poseScore, mMeta.GetScoreThreshold());
-					return MEDIA_VISION_ERROR_NONE;
-				}
+			if (poseScore < mMeta.GetScoreThreshold()) {
+				LOGI("pose score %.4f is lower than %.4f\n[LEAVE]", poseScore, mMeta.GetScoreThreshold());
+				return MEDIA_VISION_ERROR_NONE;
 			}
+		}
 
-			int landmarkOffset = (mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE ||
-								  mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_MULTI) ? 2 : 3;
-			if (mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS) {
-				landmarkOffset = mMeta.GetLandmarkOffset();
-			}
-			for (int idx = 0; idx < mNumberOfLandmarks; ++idx) {
-					float px = mTensorBuffer.getValue<float>(mMeta.GetLandmarkName(), idx * landmarkOffset);
-					float py = mTensorBuffer.getValue<float>(mMeta.GetLandmarkName(), idx * landmarkOffset + 1);
+		int landmarkOffset = (mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_SINGLE ||
+							  mMeta.GetLandmarkType() == INFERENCE_LANDMARK_TYPE_2D_MULTI) ?
+									 2 :
+									 3;
+		if (mMeta.GetLandmarkDecodingType() == INFERENCE_LANDMARK_DECODING_TYPE_BYPASS) {
+			landmarkOffset = mMeta.GetLandmarkOffset();
+		}
+		for (int idx = 0; idx < mNumberOfLandmarks; ++idx) {
+			float px = mTensorBuffer.getValue<float>(mMeta.GetLandmarkName(), idx * landmarkOffset);
+			float py = mTensorBuffer.getValue<float>(mMeta.GetLandmarkName(), idx * landmarkOffset + 1);
 
-					mPoseLandmarks[0].landmarks[idx].score = poseScore;
-					mPoseLandmarks[0].landmarks[idx].heatMapLoc = cv::Point(-1, -1);
-					mPoseLandmarks[0].landmarks[idx].decodedLoc = cv::Point2f(px/scaleWidth, py/scaleHeight);
-					mPoseLandmarks[0].landmarks[idx].id = idx;
-					mPoseLandmarks[0].landmarks[idx].valid =  true;
+			mPoseLandmarks[0].landmarks[idx].score = poseScore;
+			mPoseLandmarks[0].landmarks[idx].heatMapLoc = cv::Point(-1, -1);
+			mPoseLandmarks[0].landmarks[idx].decodedLoc = cv::Point2f(px / scaleWidth, py / scaleHeight);
+			mPoseLandmarks[0].landmarks[idx].id = idx;
+			mPoseLandmarks[0].landmarks[idx].valid = true;
 
-					LOGI("idx[%d]: %.4f, %.4f", idx, px, py);
-			}
-
-			mPoseLandmarks[0].score = poseScore;
+			LOGI("idx[%d]: %.4f, %.4f", idx, px, py);
 		}
 
-		LOGI("LEAVE");
-		return MEDIA_VISION_ERROR_NONE;
+		mPoseLandmarks[0].score = poseScore;
 	}
 
-	int PoseDecoder::findPose(LandmarkPoint& root, std::vector<LandmarkPoint>& decodedLandmarks,
-							float scaleW, float scaleH)
-	{
-		LOGI("ENTER");
+	LOGI("LEAVE");
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		if (scaleW <= 0.0f || scaleH <= 0.0f) {
-			LOGE("scale width(%.4f) or height(%.4f) is less than or equal to zero", scaleW, scaleH);
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-		}
+int PoseDecoder::findPose(LandmarkPoint &root, std::vector<LandmarkPoint> &decodedLandmarks, float scaleW, float scaleH)
+{
+	LOGI("ENTER");
 
-		decodedLandmarks[root.id] = root;
-		decodedLandmarks[root.id].valid = true;
-		LOGI("KeyId: [%d], heatMap: %d, %d", root.id, root.heatMapLoc.x, root.heatMapLoc.y);
-		LOGI("KeyId: [%d], decoded: %.4f, %.4f, score %.3f", root.id, root.decodedLoc.x, root.decodedLoc.y, root.score);
-
-		int index = static_cast<int>(mMeta.GetLandmarkEdges().size()) - 1;
-		for (auto riter = mMeta.GetLandmarkEdges().rbegin();
-			riter != mMeta.GetLandmarkEdges().rend(); ++riter) {
-			int fromKeyId = riter->second;
-			int toKeyId = riter->first;
-
-			if (decodedLandmarks[fromKeyId].valid == true &&
-				decodedLandmarks[toKeyId].valid == false) {
-				LOGI("BackTravers: from %d to %d", fromKeyId, toKeyId);
-				traverseToNeighbor(index, toKeyId,  INFERENCE_DISPLACEMENT_TYPE_BACKWARD,
-							decodedLandmarks[fromKeyId], decodedLandmarks[toKeyId],
-							scaleW, scaleH);
-				LOGI("tgt_key_id[%d]: %.4f, %.4f, %.4f", toKeyId,
-										decodedLandmarks[toKeyId].decodedLoc.x,
-										decodedLandmarks[toKeyId].decodedLoc.y,
-										decodedLandmarks[toKeyId].score);
-			}
-			index--;
-		}
+	if (scaleW <= 0.0f || scaleH <= 0.0f) {
+		LOGE("scale width(%.4f) or height(%.4f) is less than or equal to zero", scaleW, scaleH);
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+	}
 
-		index = 0;
-		for (auto iter = mMeta.GetLandmarkEdges().begin();
-			iter != mMeta.GetLandmarkEdges().end(); ++iter) {
-			int fromKeyId = iter->first;
-			int toKeyId = iter->second;
-
-			if (decodedLandmarks[fromKeyId].valid == true &&
-				decodedLandmarks[toKeyId].valid == false) {
-				LOGI("FrwdTravers: form %d to %d", fromKeyId, toKeyId);
-				traverseToNeighbor(index, toKeyId,  INFERENCE_DISPLACEMENT_TYPE_FORWARD,
-							decodedLandmarks[fromKeyId], decodedLandmarks[toKeyId],
-							scaleW, scaleH);
-			}
-			index++;
+	decodedLandmarks[root.id] = root;
+	decodedLandmarks[root.id].valid = true;
+	LOGI("KeyId: [%d], heatMap: %d, %d", root.id, root.heatMapLoc.x, root.heatMapLoc.y);
+	LOGI("KeyId: [%d], decoded: %.4f, %.4f, score %.3f", root.id, root.decodedLoc.x, root.decodedLoc.y, root.score);
+
+	int index = static_cast<int>(mMeta.GetLandmarkEdges().size()) - 1;
+	for (auto riter = mMeta.GetLandmarkEdges().rbegin(); riter != mMeta.GetLandmarkEdges().rend(); ++riter) {
+		int fromKeyId = riter->second;
+		int toKeyId = riter->first;
+
+		if (decodedLandmarks[fromKeyId].valid == true && decodedLandmarks[toKeyId].valid == false) {
+			LOGI("BackTravers: from %d to %d", fromKeyId, toKeyId);
+			traverseToNeighbor(index, toKeyId, INFERENCE_DISPLACEMENT_TYPE_BACKWARD, decodedLandmarks[fromKeyId],
+							   decodedLandmarks[toKeyId], scaleW, scaleH);
+			LOGI("tgt_key_id[%d]: %.4f, %.4f, %.4f", toKeyId, decodedLandmarks[toKeyId].decodedLoc.x,
+				 decodedLandmarks[toKeyId].decodedLoc.y, decodedLandmarks[toKeyId].score);
 		}
-		LOGI("LEAVE");
-		return MEDIA_VISION_ERROR_NONE;
+		index--;
 	}
 
-	int PoseDecoder::traverseToNeighbor(int edgeId, int toId, inference_displacement_type_e dir,
-								LandmarkPoint fromLandmark, LandmarkPoint& toLandmark,
-								float scaleW, float scaleH)
-	{
-		if (scaleW <= 0.0f || scaleH <= 0.0f) {
-			LOGE("scale width(%.4f) or height(%.4f) is less than or equal to zero", scaleW, scaleH);
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-		}
+	index = 0;
+	for (auto iter = mMeta.GetLandmarkEdges().begin(); iter != mMeta.GetLandmarkEdges().end(); ++iter) {
+		int fromKeyId = iter->first;
+		int toKeyId = iter->second;
 
-		cv::Point2f edgeVector(0.f, 0.f);
-		cv::Point nearHeatMapLoc;
+		if (decodedLandmarks[fromKeyId].valid == true && decodedLandmarks[toKeyId].valid == false) {
+			LOGI("FrwdTravers: form %d to %d", fromKeyId, toKeyId);
+			traverseToNeighbor(index, toKeyId, INFERENCE_DISPLACEMENT_TYPE_FORWARD, decodedLandmarks[fromKeyId],
+							   decodedLandmarks[toKeyId], scaleW, scaleH);
+		}
+		index++;
+	}
+	LOGI("LEAVE");
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		LOGI("org: %.4f, %.4f", fromLandmark.decodedLoc.x, fromLandmark.decodedLoc.y);
+int PoseDecoder::traverseToNeighbor(int edgeId, int toId, inference_displacement_type_e dir, LandmarkPoint fromLandmark,
+									LandmarkPoint &toLandmark, float scaleW, float scaleH)
+{
+	if (scaleW <= 0.0f || scaleH <= 0.0f) {
+		LOGE("scale width(%.4f) or height(%.4f) is less than or equal to zero", scaleW, scaleH);
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+	}
 
-		// update heatMapLoc from decodedLoc;
-		nearHeatMapLoc.x = roundf(fromLandmark.decodedLoc.x
-					* static_cast<float>(mHeatMapWidth - 1));
-		nearHeatMapLoc.y = roundf(fromLandmark.decodedLoc.y
-					* static_cast<float>(mHeatMapHeight - 1));
+	cv::Point2f edgeVector(0.f, 0.f);
+	cv::Point nearHeatMapLoc;
 
-		nearHeatMapLoc.x = std::max(std::min(nearHeatMapLoc.x, mHeatMapWidth - 1), 0);
-		nearHeatMapLoc.y = std::max(std::min(nearHeatMapLoc.y, mHeatMapHeight - 1), 0);
+	LOGI("org: %.4f, %.4f", fromLandmark.decodedLoc.x, fromLandmark.decodedLoc.y);
 
-		LOGI("src: %d, %d", nearHeatMapLoc.x, nearHeatMapLoc.y);
+	// update heatMapLoc from decodedLoc;
+	nearHeatMapLoc.x = roundf(fromLandmark.decodedLoc.x * static_cast<float>(mHeatMapWidth - 1));
+	nearHeatMapLoc.y = roundf(fromLandmark.decodedLoc.y * static_cast<float>(mHeatMapHeight - 1));
 
-		getEdgeVector(nearHeatMapLoc, edgeId, dir, edgeVector);
+	nearHeatMapLoc.x = std::max(std::min(nearHeatMapLoc.x, mHeatMapWidth - 1), 0);
+	nearHeatMapLoc.y = std::max(std::min(nearHeatMapLoc.y, mHeatMapHeight - 1), 0);
 
-		LOGI("vector: %.4f, %.4f with edgeId %d", edgeVector.x, edgeVector.y, edgeId);
-		toLandmark.decodedLoc.x = fromLandmark.decodedLoc.x + edgeVector.x / scaleW;
-		toLandmark.decodedLoc.y = fromLandmark.decodedLoc.y + edgeVector.y / scaleH;
-		toLandmark.id = toId;
-		LOGI("tgt: %.4f, %.4f", toLandmark.decodedLoc.x, toLandmark.decodedLoc.y);
+	LOGI("src: %d, %d", nearHeatMapLoc.x, nearHeatMapLoc.y);
 
-		for (int iter = 0; iter < MAX_NUMBER_OF_CORRECTION; ++iter) {
-			getPosToIndex(toLandmark);
-			getIndexToPos(toLandmark, scaleW, scaleH);
-		}
+	getEdgeVector(nearHeatMapLoc, edgeId, dir, edgeVector);
 
-		int idx  = convertXYZtoX(toLandmark.heatMapLoc.x, toLandmark.heatMapLoc.y, toLandmark.id);
-		toLandmark.score = mTensorBuffer.getValue<float>(mMeta.GetScoreName(), idx);
-		if (mMeta.GetScoreType() == INFERENCE_SCORE_TYPE_SIGMOID) {
-			toLandmark.score = PostProcess::sigmoid(toLandmark.score);
-		}
+	LOGI("vector: %.4f, %.4f with edgeId %d", edgeVector.x, edgeVector.y, edgeId);
+	toLandmark.decodedLoc.x = fromLandmark.decodedLoc.x + edgeVector.x / scaleW;
+	toLandmark.decodedLoc.y = fromLandmark.decodedLoc.y + edgeVector.y / scaleH;
+	toLandmark.id = toId;
+	LOGI("tgt: %.4f, %.4f", toLandmark.decodedLoc.x, toLandmark.decodedLoc.y);
 
-		toLandmark.valid = true;
-		LOGI("Final: %.4f, %.4f", toLandmark.decodedLoc.x, toLandmark.decodedLoc.y);
+	for (int iter = 0; iter < MAX_NUMBER_OF_CORRECTION; ++iter) {
+		getPosToIndex(toLandmark);
+		getIndexToPos(toLandmark, scaleW, scaleH);
+	}
 
-		return MEDIA_VISION_ERROR_NONE;
+	int idx = convertXYZtoX(toLandmark.heatMapLoc.x, toLandmark.heatMapLoc.y, toLandmark.id);
+	toLandmark.score = mTensorBuffer.getValue<float>(mMeta.GetScoreName(), idx);
+	if (mMeta.GetScoreType() == INFERENCE_SCORE_TYPE_SIGMOID) {
+		toLandmark.score = PostProcess::sigmoid(toLandmark.score);
 	}
 
-	int PoseDecoder::getEdgeVector(cv::Point index, int edgeId, inference_displacement_type_e type, cv::Point2f& vector)
-	{
-		LOGI("ENTER");
+	toLandmark.valid = true;
+	LOGI("Final: %.4f, %.4f", toLandmark.decodedLoc.x, toLandmark.decodedLoc.y);
+
+	return MEDIA_VISION_ERROR_NONE;
+}
+
+int PoseDecoder::getEdgeVector(cv::Point index, int edgeId, inference_displacement_type_e type, cv::Point2f &vector)
+{
+	LOGI("ENTER");
 
-		LOGI("edge size: %zd", mMeta.GetLandmarkEdges().size());
+	LOGI("edge size: %zd", mMeta.GetLandmarkEdges().size());
 
-		int idxY = index.y * mHeatMapWidth
-					* static_cast<int>(mMeta.GetLandmarkEdges().size()) * 2;
+	int idxY = index.y * mHeatMapWidth * static_cast<int>(mMeta.GetLandmarkEdges().size()) * 2;
 
-		idxY += index.x * static_cast<int>(mMeta.GetLandmarkEdges().size()) * 2 + edgeId;
+	idxY += index.x * static_cast<int>(mMeta.GetLandmarkEdges().size()) * 2 + edgeId;
 
-		int idxX = idxY + static_cast<int>(mMeta.GetLandmarkEdges().size());
+	int idxX = idxY + static_cast<int>(mMeta.GetLandmarkEdges().size());
 
-		for(auto& dispVec : mMeta.GetLandmarkDispVecAll()){
-			if (dispVec.GetType() == type) { // 0: forward
-				LOGI("%s", dispVec.GetName().c_str());
-				vector.x = mTensorBuffer.getValue<float>(dispVec.GetName(), idxX);
-				vector.y = mTensorBuffer.getValue<float>(dispVec.GetName(), idxY);
-			}
+	for (auto &dispVec : mMeta.GetLandmarkDispVecAll()) {
+		if (dispVec.GetType() == type) { // 0: forward
+			LOGI("%s", dispVec.GetName().c_str());
+			vector.x = mTensorBuffer.getValue<float>(dispVec.GetName(), idxX);
+			vector.y = mTensorBuffer.getValue<float>(dispVec.GetName(), idxY);
 		}
-
-		LOGI("LEAVE");
-		return MEDIA_VISION_ERROR_NONE;
 	}
+
+	LOGI("LEAVE");
+	return MEDIA_VISION_ERROR_NONE;
+}
 }
 }
diff --git a/mv_machine_learning/inference/src/PostProcess.cpp b/mv_machine_learning/inference/src/PostProcess.cpp
old mode 100755
new mode 100644
index c7335b3..7060da7
--- a/mv_machine_learning/inference/src/PostProcess.cpp
+++ b/mv_machine_learning/inference/src/PostProcess.cpp
@@ -26,133 +26,132 @@ namespace mediavision
 {
 namespace inference
 {
-	float PostProcess::sigmoid(float value)
-	{
-		return 1.0/(1.0+ exp(-value));
-	}
+float PostProcess::sigmoid(float value)
+{
+	return 1.0 / (1.0 + exp(-value));
+}
 
-	float PostProcess::dequant(float value, float scale, float zeropoint)
-	{
-		return value/scale + zeropoint;
-	}
+float PostProcess::dequant(float value, float scale, float zeropoint)
+{
+	return value / scale + zeropoint;
+}
 
-	int PostProcess::ScoreClear(int size)
-	{
-		std::priority_queue<std::pair<float, int>,
-							std::vector<std::pair<float, int>>,
-							std::greater<std::pair<float, int>>>().swap(mScore);
-		mMaxScoreSize = size;
+int PostProcess::ScoreClear(int size)
+{
+	std::priority_queue<std::pair<float, int>, std::vector<std::pair<float, int> >,
+						std::greater<std::pair<float, int> > >()
+			.swap(mScore);
+	mMaxScoreSize = size;
 
-		return MEDIA_VISION_ERROR_NONE;
+	return MEDIA_VISION_ERROR_NONE;
+}
+
+int PostProcess::ScorePush(float value, int index)
+{
+	mScore.push(std::pair<float, int>(value, index));
+	if (mScore.size() > (size_t) mMaxScoreSize) {
+		mScore.pop();
 	}
 
-	int PostProcess::ScorePush(float value, int index)
-	{
-		mScore.push(std::pair<float, int>(value, index));
-		if (mScore.size() > (size_t)mMaxScoreSize) {
-			mScore.pop();
-		}
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		return MEDIA_VISION_ERROR_NONE;
+int PostProcess::ScorePop(std::vector<std::pair<float, int> > &top)
+{
+	top.clear();
+	while (!mScore.empty()) {
+		top.push_back(mScore.top());
+		LOGI("%.3f", mScore.top().first);
+		mScore.pop();
 	}
 
-	int PostProcess::ScorePop(std::vector<std::pair<float, int>>& top)
-	{
-		top.clear();
-		while (!mScore.empty()) {
-			top.push_back(mScore.top());
-			LOGI("%.3f", mScore.top().first);
-			mScore.pop();
-		}
+	std::reverse(top.begin(), top.end());
 
-		std::reverse(top.begin(), top.end());
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		return MEDIA_VISION_ERROR_NONE;
-	}
+static bool compareScore(Box box0, Box box1)
+{
+	return box0.score > box1.score;
+}
 
-	static bool compareScore(Box box0, Box box1)
-	{
-		return box0.score > box1.score;
-	}
+static float calcIntersectionOverUnion(Box box0, Box box1)
+{
+	float area0 = box0.location.width * box0.location.height;
+	float area1 = box1.location.width * box1.location.height;
+
+	if (area0 <= 0.0f || area1 <= 0.0f)
+		return 0.0f;
+
+	float sx0 = box0.location.x - box0.location.width * 0.5f;
+	float sy0 = box0.location.y - box0.location.height * 0.5f;
+	float ex0 = box0.location.x + box0.location.width * 0.5f;
+	float ey0 = box0.location.y + box0.location.height * 0.5f;
+	float sx1 = box1.location.x - box1.location.width * 0.5f;
+	float sy1 = box1.location.y - box1.location.height * 0.5f;
+	float ex1 = box1.location.x + box1.location.width * 0.5f;
+	float ey1 = box1.location.y + box1.location.height * 0.5f;
+
+	float xmin0 = std::min(sx0, ex0);
+	float ymin0 = std::min(sy0, ey0);
+	float xmax0 = std::max(sx0, ex0);
+	float ymax0 = std::max(sy0, ey0);
+	float xmin1 = std::min(sx1, ex1);
+	float ymin1 = std::min(sy1, ey1);
+	float xmax1 = std::max(sx1, ex1);
+	float ymax1 = std::max(sy1, ey1);
+
+	float intersectXmin = std::max(xmin0, xmin1);
+	float intersectYmin = std::max(ymin0, ymin1);
+	float intersectXmax = std::min(xmax0, xmax1);
+	float intersectYmax = std::min(ymax0, ymax1);
+
+	float intersectArea =
+			std::max((intersectYmax - intersectYmin), 0.0f) * std::max((intersectXmax - intersectXmin), 0.0f);
+	return intersectArea / (area0 + area1 - intersectArea);
+}
+
+int PostProcess::Nms(BoxesList &boxeslist, int mode, float threshold, Boxes &nmsboxes)
+{
+	LOGI("ENTER");
 
-	static float calcIntersectionOverUnion(Box box0, Box box1)
-	{
-
-		float area0 = box0.location.width * box0.location.height;
-		float area1 = box1.location.width * box1.location.height;
-
-		if (area0 <= 0.0f || area1 <= 0.0f)
-			return 0.0f;
-
-		float sx0 = box0.location.x - box0.location.width * 0.5f;
-		float sy0 = box0.location.y - box0.location.height * 0.5f;
-		float ex0 = box0.location.x + box0.location.width * 0.5f;
-		float ey0 = box0.location.y + box0.location.height * 0.5f;
-		float sx1 = box1.location.x - box1.location.width * 0.5f;
-		float sy1 = box1.location.y - box1.location.height * 0.5f;
-		float ex1 = box1.location.x + box1.location.width * 0.5f;
-		float ey1 = box1.location.y + box1.location.height * 0.5f;
-
-		float xmin0 = std::min (sx0, ex0);
-		float ymin0 = std::min (sy0, ey0);
-		float xmax0 = std::max (sx0, ex0);
-		float ymax0 = std::max (sy0, ey0);
-		float xmin1 = std::min (sx1, ex1);
-		float ymin1 = std::min (sy1, ey1);
-		float xmax1 = std::max (sx1, ex1);
-		float ymax1 = std::max (sy1, ey1);
-
-		float intersectXmin = std::max(xmin0, xmin1);
-		float intersectYmin = std::max(ymin0, ymin1);
-		float intersectXmax = std::min(xmax0, xmax1);
-		float intersectYmax = std::min(ymax0, ymax1);
-
-		float intersectArea = std::max((intersectYmax - intersectYmin), 0.0f) *
-							  std::max((intersectXmax - intersectXmin), 0.0f);
-		return intersectArea / (area0 + area1 - intersectArea);
+	if (mode != 0) {
+		LOGI("Skip Nms");
+		LOGI("LEAVE");
+		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	int PostProcess::Nms(BoxesList& boxeslist, int mode, float threshold, Boxes& nmsboxes)
-	{
-		LOGI("ENTER");
-
-		if (mode != 0) {
-			LOGI("Skip Nms");
-			LOGI("LEAVE");
-			return MEDIA_VISION_ERROR_NONE;
-		}
-
-		LOGI("threshold: %.3f", threshold);
-		bool isIgnore = false;
-		Boxes candidateBoxes;
-		for (auto& boxList : boxeslist) {
-			if (boxList.size() <=0 )
-				continue;
-
-			std::sort(boxList.begin(), boxList.end(), compareScore);
-			candidateBoxes.clear();
-			for (auto& decodedBox : boxList) {
-				isIgnore = false;
-				for (auto candidateBox = candidateBoxes.rbegin(); candidateBox != candidateBoxes.rend(); ++candidateBox) {
-					// compare decodedBox with previous one
-					float iouValue = calcIntersectionOverUnion(decodedBox, (*candidateBox));
-					LOGI("iouValue: %.3f", iouValue);
-					if (iouValue >= threshold) {
-						isIgnore = true;
-						break;
-					}
-				}
-				if (!isIgnore) {
-					candidateBoxes.push_back(decodedBox);
+	LOGI("threshold: %.3f", threshold);
+	bool isIgnore = false;
+	Boxes candidateBoxes;
+	for (auto &boxList : boxeslist) {
+		if (boxList.size() <= 0)
+			continue;
+
+		std::sort(boxList.begin(), boxList.end(), compareScore);
+		candidateBoxes.clear();
+		for (auto &decodedBox : boxList) {
+			isIgnore = false;
+			for (auto candidateBox = candidateBoxes.rbegin(); candidateBox != candidateBoxes.rend(); ++candidateBox) {
+				// compare decodedBox with previous one
+				float iouValue = calcIntersectionOverUnion(decodedBox, (*candidateBox));
+				LOGI("iouValue: %.3f", iouValue);
+				if (iouValue >= threshold) {
+					isIgnore = true;
+					break;
 				}
 			}
-			if (candidateBoxes.size() > 0) {
-				nmsboxes.insert(nmsboxes.begin(), candidateBoxes.begin(), candidateBoxes.end());
+			if (!isIgnore) {
+				candidateBoxes.push_back(decodedBox);
 			}
 		}
-		LOGI("LEAVE");
-
-		return MEDIA_VISION_ERROR_NONE;
+		if (candidateBoxes.size() > 0) {
+			nmsboxes.insert(nmsboxes.begin(), candidateBoxes.begin(), candidateBoxes.end());
+		}
 	}
+	LOGI("LEAVE");
+
+	return MEDIA_VISION_ERROR_NONE;
+}
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/src/Posture.cpp b/mv_machine_learning/inference/src/Posture.cpp
index 14c0cec..f9d237d 100644
--- a/mv_machine_learning/inference/src/Posture.cpp
+++ b/mv_machine_learning/inference/src/Posture.cpp
@@ -30,332 +30,319 @@ namespace mediavision
 {
 namespace inference
 {
-Posture::Posture() :
-    mBvhParser(),
-    mBvh(),
-    mPose()
+Posture::Posture() : mBvhParser(), mBvh(), mPose()
 {
-    LOGI("ENTER");
+	LOGI("ENTER");
 
-    mMotionToPoseMap.clear();
-    mPose.assign(HUMAN_POSE_MAX_LANDMARKS, std::make_pair(false, cv::Point(-1,-1)));
+	mMotionToPoseMap.clear();
+	mPose.assign(HUMAN_POSE_MAX_LANDMARKS, std::make_pair(false, cv::Point(-1, -1)));
 
-    mPoseParts.assign(HUMAN_POSE_MAX_PARTS, std::make_pair(false, std::vector<cv::Vec2f>()));
+	mPoseParts.assign(HUMAN_POSE_MAX_PARTS, std::make_pair(false, std::vector<cv::Vec2f>()));
 
-    LOGI("LEAVE");
+	LOGI("LEAVE");
 }
 
 Posture::~Posture()
 {
-    LOGI("ENTER");
+	LOGI("ENTER");
 
-    std::vector<std::pair<bool, cv::Point>>().swap(mPose);
+	std::vector<std::pair<bool, cv::Point> >().swap(mPose);
 
-    LOGI("LEAVE");
+	LOGI("LEAVE");
 }
 
-
-int Posture::getParts(int parts,
-                    std::vector<std::pair<bool, cv::Point>>& pose,
-                    std::vector<std::pair<bool, std::vector<cv::Vec2f>>>& posePart)
+int Posture::getParts(int parts, std::vector<std::pair<bool, cv::Point> > &pose,
+					  std::vector<std::pair<bool, std::vector<cv::Vec2f> > > &posePart)
 {
-    LOGI("ENTER");
-    // head
-    if (parts & MV_INFERENCE_HUMAN_BODY_PART_HEAD) {
-        LOGI("HEAD");
-        if (pose[0].first == false || pose[1].first == false || pose[2].first == false) {
-            posePart[0].first = false;
-        } else {
-            posePart[0].first = true;
-            posePart[0].second.push_back(getUnitVectors(pose[0].second, pose[1].second));
-            posePart[0].second.push_back(getUnitVectors(pose[1].second, pose[2].second));
-        }
-    }
-
-    // right arm
-    if (parts & MV_INFERENCE_HUMAN_BODY_PART_ARM_RIGHT) {
-        LOGI("ARM-R");
-        if (pose[3].first == false || pose[4].first == false || pose[5].first == false) {
-            posePart[1].first = false;
-        } else {
-            posePart[1].first = true;
-            posePart[1].second.push_back(getUnitVectors(pose[3].second, pose[4].second));
-            posePart[1].second.push_back(getUnitVectors(pose[4].second, pose[5].second));
-        }
-    }
-
-    // left arm
-    if (parts & MV_INFERENCE_HUMAN_BODY_PART_ARM_LEFT) {
-        LOGI("ARM-L");
-        if (pose[6].first == false || pose[7].first == false || pose[8].first == false) {
-            posePart[2].first = false;
-        } else {
-            posePart[2].first = true;
-            posePart[2].second.push_back(getUnitVectors(pose[6].second, pose[7].second));
-            posePart[2].second.push_back(getUnitVectors(pose[7].second, pose[8].second));
-        }
-    }
-
-    // right leg
-    if (parts & MV_INFERENCE_HUMAN_BODY_PART_LEG_RIGHT) {
-        LOGI("LEG-R");
-        if (pose[10].first == false || pose[11].first == false || pose[12].first == false) {
-            posePart[3].first = false;
-        } else {
-            posePart[3].first = true;
-            posePart[3].second.push_back(getUnitVectors(pose[10].second, pose[11].second));
-            posePart[3].second.push_back(getUnitVectors(pose[11].second, pose[12].second));
-        }
-    }
-
-    // left leg
-    if (parts & MV_INFERENCE_HUMAN_BODY_PART_LEG_LEFT) {
-        LOGI("LEG-L");
-        if (pose[13].first == false || pose[14].first == false || pose[15].first == false) {
-            posePart[4].first = false;
-        } else {
-            posePart[4].first = true;
-            posePart[4].second.push_back(getUnitVectors(pose[13].second, pose[14].second));
-            posePart[4].second.push_back(getUnitVectors(pose[14].second, pose[15].second));
-
-        }
-    }
-
-    // body
-    if (parts & MV_INFERENCE_HUMAN_BODY_PART_BODY) {
-        LOGI("BODY");
-        if (pose[2].first == false || pose[9].first == false ||
-            pose[10].first == false || pose[13].first == false) {
-            posePart[5].first = false;
-        } else {
-            posePart[5].first = true;
-            posePart[5].second.push_back(getUnitVectors(pose[2].second, pose[9].second));
-            posePart[5].second.push_back(getUnitVectors(pose[9].second, pose[10].second));
-            posePart[5].second.push_back(getUnitVectors(pose[9].second, pose[13].second));
-        }
-    }
-
-    LOGI("LEAVE");
-
-    return MEDIA_VISION_ERROR_NONE;
+	LOGI("ENTER");
+	// head
+	if (parts & MV_INFERENCE_HUMAN_BODY_PART_HEAD) {
+		LOGI("HEAD");
+		if (pose[0].first == false || pose[1].first == false || pose[2].first == false) {
+			posePart[0].first = false;
+		} else {
+			posePart[0].first = true;
+			posePart[0].second.push_back(getUnitVectors(pose[0].second, pose[1].second));
+			posePart[0].second.push_back(getUnitVectors(pose[1].second, pose[2].second));
+		}
+	}
+
+	// right arm
+	if (parts & MV_INFERENCE_HUMAN_BODY_PART_ARM_RIGHT) {
+		LOGI("ARM-R");
+		if (pose[3].first == false || pose[4].first == false || pose[5].first == false) {
+			posePart[1].first = false;
+		} else {
+			posePart[1].first = true;
+			posePart[1].second.push_back(getUnitVectors(pose[3].second, pose[4].second));
+			posePart[1].second.push_back(getUnitVectors(pose[4].second, pose[5].second));
+		}
+	}
+
+	// left arm
+	if (parts & MV_INFERENCE_HUMAN_BODY_PART_ARM_LEFT) {
+		LOGI("ARM-L");
+		if (pose[6].first == false || pose[7].first == false || pose[8].first == false) {
+			posePart[2].first = false;
+		} else {
+			posePart[2].first = true;
+			posePart[2].second.push_back(getUnitVectors(pose[6].second, pose[7].second));
+			posePart[2].second.push_back(getUnitVectors(pose[7].second, pose[8].second));
+		}
+	}
+
+	// right leg
+	if (parts & MV_INFERENCE_HUMAN_BODY_PART_LEG_RIGHT) {
+		LOGI("LEG-R");
+		if (pose[10].first == false || pose[11].first == false || pose[12].first == false) {
+			posePart[3].first = false;
+		} else {
+			posePart[3].first = true;
+			posePart[3].second.push_back(getUnitVectors(pose[10].second, pose[11].second));
+			posePart[3].second.push_back(getUnitVectors(pose[11].second, pose[12].second));
+		}
+	}
+
+	// left leg
+	if (parts & MV_INFERENCE_HUMAN_BODY_PART_LEG_LEFT) {
+		LOGI("LEG-L");
+		if (pose[13].first == false || pose[14].first == false || pose[15].first == false) {
+			posePart[4].first = false;
+		} else {
+			posePart[4].first = true;
+			posePart[4].second.push_back(getUnitVectors(pose[13].second, pose[14].second));
+			posePart[4].second.push_back(getUnitVectors(pose[14].second, pose[15].second));
+		}
+	}
+
+	// body
+	if (parts & MV_INFERENCE_HUMAN_BODY_PART_BODY) {
+		LOGI("BODY");
+		if (pose[2].first == false || pose[9].first == false || pose[10].first == false || pose[13].first == false) {
+			posePart[5].first = false;
+		} else {
+			posePart[5].first = true;
+			posePart[5].second.push_back(getUnitVectors(pose[2].second, pose[9].second));
+			posePart[5].second.push_back(getUnitVectors(pose[9].second, pose[10].second));
+			posePart[5].second.push_back(getUnitVectors(pose[9].second, pose[13].second));
+		}
+	}
+
+	LOGI("LEAVE");
+
+	return MEDIA_VISION_ERROR_NONE;
 }
 
 int Posture::setPoseFromFile(const std::string motionCaptureFilePath, const std::string motionMappingFilePath)
 {
-    LOGI("ENTER");
-
-    int ret = MEDIA_VISION_ERROR_NONE;
-
-    // parsing motion capture file
-    LOGD("%s", motionCaptureFilePath.c_str());
-    LOGD("%s", motionMappingFilePath.c_str());
-    ret = mBvhParser.parse(motionCaptureFilePath.c_str(), &mBvh);
-    LOGD("frames: %d",mBvh.num_frames());
-
-    if (ret != MEDIA_VISION_ERROR_NONE) {
-        LOGE("Fail to parse a file [%s]", motionCaptureFilePath.c_str());
-        return MEDIA_VISION_ERROR_INTERNAL;
-    }
-
-    mBvh.recalculate_joints_ltm();
-
-    LOGD("reading motion mapping....");
-    // read motion mapping file
-    std::ifstream fp(motionMappingFilePath.c_str());
-    if (!fp.is_open()) {
-        LOGE("Fail to open %s", motionMappingFilePath.c_str());
-        return MEDIA_VISION_ERROR_INVALID_PATH;
-    }
-
-    std::string line;
-    mMotionToPoseMap.clear();
-    while (!fp.eof()) {
-        std::getline(fp, line);
-
-        if (line.empty())
-            continue;
-
-        LOGD("%s", line.c_str());
-        std::istringstream lineStream(line);
-        std::string token;
-        std::vector<std::string> parsedString;
-        while(getline(lineStream, token, ',')) {
-            parsedString.push_back(token);
-        }
-        LOGD("name: %s, mapping index: %d", parsedString[0].c_str(), std::stoi(parsedString[1]));
-        mMotionToPoseMap.insert(make_pair(parsedString[0], std::stoi(parsedString[1])-1));
-    }
-
-    fp.close();
-    LOGD("mapping size is %zd", mMotionToPoseMap.size());
-
-    // convert bvh to pose
-    //convertBvhToPose();
-    //for (std::shared_ptr<Bvh::Joint>)
-
-    float pointX, pointY, minX, minY, maxX, maxY;
-    minX = minY = FLT_MAX;
-    maxX = maxY = FLT_MIN;
-    for (std::shared_ptr<Joint> joint : mBvh.joints()) {
-        std::map<std::string, int>::iterator it = mMotionToPoseMap.find(std::string(joint->name()));
-        if (it != mMotionToPoseMap.end()) {
-            pointX = joint->pos(0)[0];
-            pointY = joint->pos(0)[1];
-            if (pointX < minX)
-                minX = pointX;
-
-            if (pointY < minY)
-                minY = pointY;
-
-            if (pointX > maxX)
-                maxX = pointX;
-
-            if (pointY > maxY)
-                maxY = pointY;
-
-            mPose[it->second].first = true;
-            mPose[it->second].second = cv::Point(pointX, pointY);
-            LOGD("%d: (%f,%f)", it->second, pointX, pointY);
-        }
-    }
-
-    // add offset to make x > 0 and y > 0
-    int height = (int)maxY - (int)minY + POSE_OFFSET_VALUE;
-    for (std::vector<std::pair<bool, cv::Point>>::iterator iter = mPose.begin();
-        iter != mPose.end(); iter++) {
-        if (iter->first == false)
-            continue;
-
-        iter->second.x -= minX;
-        iter->second.y -= minY;
-
-        iter->second.x += POSE_OFFSET_VALUE;
-        iter->second.y += POSE_OFFSET_VALUE;
-
-        iter->second.y = height - iter->second.y;
-
-        LOGI("(%d, %d)", iter->second.x, iter->second.y);
-    }
-
-    ret = getParts((MV_INFERENCE_HUMAN_BODY_PART_HEAD |
-                    MV_INFERENCE_HUMAN_BODY_PART_ARM_RIGHT |
-                    MV_INFERENCE_HUMAN_BODY_PART_ARM_LEFT |
-                    MV_INFERENCE_HUMAN_BODY_PART_BODY |
-                    MV_INFERENCE_HUMAN_BODY_PART_LEG_RIGHT |
-                    MV_INFERENCE_HUMAN_BODY_PART_LEG_LEFT),
-                    mPose, mPoseParts);
-    if (ret != MEDIA_VISION_ERROR_NONE) {
-        LOGE("Fail to getPartse");
-        return ret;
-    }
-
-    LOGI("LEAVE");
-
-    return ret;
+	LOGI("ENTER");
+
+	int ret = MEDIA_VISION_ERROR_NONE;
+
+	// parsing motion capture file
+	LOGD("%s", motionCaptureFilePath.c_str());
+	LOGD("%s", motionMappingFilePath.c_str());
+	ret = mBvhParser.parse(motionCaptureFilePath.c_str(), &mBvh);
+	LOGD("frames: %d", mBvh.num_frames());
+
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to parse a file [%s]", motionCaptureFilePath.c_str());
+		return MEDIA_VISION_ERROR_INTERNAL;
+	}
+
+	mBvh.recalculate_joints_ltm();
+
+	LOGD("reading motion mapping....");
+	// read motion mapping file
+	std::ifstream fp(motionMappingFilePath.c_str());
+	if (!fp.is_open()) {
+		LOGE("Fail to open %s", motionMappingFilePath.c_str());
+		return MEDIA_VISION_ERROR_INVALID_PATH;
+	}
+
+	std::string line;
+	mMotionToPoseMap.clear();
+	while (!fp.eof()) {
+		std::getline(fp, line);
+
+		if (line.empty())
+			continue;
+
+		LOGD("%s", line.c_str());
+		std::istringstream lineStream(line);
+		std::string token;
+		std::vector<std::string> parsedString;
+		while (getline(lineStream, token, ',')) {
+			parsedString.push_back(token);
+		}
+		LOGD("name: %s, mapping index: %d", parsedString[0].c_str(), std::stoi(parsedString[1]));
+		mMotionToPoseMap.insert(make_pair(parsedString[0], std::stoi(parsedString[1]) - 1));
+	}
+
+	fp.close();
+	LOGD("mapping size is %zd", mMotionToPoseMap.size());
+
+	// convert bvh to pose
+	//convertBvhToPose();
+	//for (std::shared_ptr<Bvh::Joint>)
+
+	float pointX, pointY, minX, minY, maxX, maxY;
+	minX = minY = FLT_MAX;
+	maxX = maxY = FLT_MIN;
+	for (std::shared_ptr<Joint> joint : mBvh.joints()) {
+		std::map<std::string, int>::iterator it = mMotionToPoseMap.find(std::string(joint->name()));
+		if (it != mMotionToPoseMap.end()) {
+			pointX = joint->pos(0)[0];
+			pointY = joint->pos(0)[1];
+			if (pointX < minX)
+				minX = pointX;
+
+			if (pointY < minY)
+				minY = pointY;
+
+			if (pointX > maxX)
+				maxX = pointX;
+
+			if (pointY > maxY)
+				maxY = pointY;
+
+			mPose[it->second].first = true;
+			mPose[it->second].second = cv::Point(pointX, pointY);
+			LOGD("%d: (%f,%f)", it->second, pointX, pointY);
+		}
+	}
+
+	// add offset to make x > 0 and y > 0
+	int height = (int) maxY - (int) minY + POSE_OFFSET_VALUE;
+	for (std::vector<std::pair<bool, cv::Point> >::iterator iter = mPose.begin(); iter != mPose.end(); iter++) {
+		if (iter->first == false)
+			continue;
+
+		iter->second.x -= minX;
+		iter->second.y -= minY;
+
+		iter->second.x += POSE_OFFSET_VALUE;
+		iter->second.y += POSE_OFFSET_VALUE;
+
+		iter->second.y = height - iter->second.y;
+
+		LOGI("(%d, %d)", iter->second.x, iter->second.y);
+	}
+
+	ret = getParts((MV_INFERENCE_HUMAN_BODY_PART_HEAD | MV_INFERENCE_HUMAN_BODY_PART_ARM_RIGHT |
+					MV_INFERENCE_HUMAN_BODY_PART_ARM_LEFT | MV_INFERENCE_HUMAN_BODY_PART_BODY |
+					MV_INFERENCE_HUMAN_BODY_PART_LEG_RIGHT | MV_INFERENCE_HUMAN_BODY_PART_LEG_LEFT),
+				   mPose, mPoseParts);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to getPartse");
+		return ret;
+	}
+
+	LOGI("LEAVE");
+
+	return ret;
 }
 
 cv::Vec2f Posture::getUnitVectors(cv::Point point1, cv::Point point2)
 {
-    LOGI("ENTER");
+	LOGI("ENTER");
 
-    cv::Vec2i vec(point1.x - point2.x, point1.y - point2.y);
-    cv::Vec2f unitVec (vec[0]/cv::norm(vec, cv::NORM_L1), vec[1]/cv::norm(vec, cv::NORM_L1));
+	cv::Vec2i vec(point1.x - point2.x, point1.y - point2.y);
+	cv::Vec2f unitVec(vec[0] / cv::norm(vec, cv::NORM_L1), vec[1] / cv::norm(vec, cv::NORM_L1));
 
-    LOGI("LEAVE");
+	LOGI("LEAVE");
 
-    return unitVec;
+	return unitVec;
 }
 
 float Posture::cosineSimilarity(std::vector<cv::Vec2f> vec1, std::vector<cv::Vec2f> vec2, int size)
 {
-    float numer = 0.0f;
-    float denom1 = 0.0f;
-    float denom2 = 0.0f;
-
-    float value = 0.0f;
-
-    for (int k = 0; k < size; ++k) {
-        numer = denom1 = denom2 = 0.0f;
-        for (int dim = 0; dim <2; ++dim) {
-            numer += (vec1[k][dim] * vec2[k][dim]);
-            denom1 += (vec1[k][dim] * vec1[k][dim]);
-            denom2 += (vec2[k][dim] * vec2[k][dim]);
-        }
-        LOGI("similarity: %f", numer / sqrt( denom1 * denom2));
-        value += numer / sqrt( denom1 * denom2);
-
-    }
-
-    return value;
+	float numer = 0.0f;
+	float denom1 = 0.0f;
+	float denom2 = 0.0f;
+
+	float value = 0.0f;
+
+	for (int k = 0; k < size; ++k) {
+		numer = denom1 = denom2 = 0.0f;
+		for (int dim = 0; dim < 2; ++dim) {
+			numer += (vec1[k][dim] * vec2[k][dim]);
+			denom1 += (vec1[k][dim] * vec1[k][dim]);
+			denom2 += (vec2[k][dim] * vec2[k][dim]);
+		}
+		LOGI("similarity: %f", numer / sqrt(denom1 * denom2));
+		value += numer / sqrt(denom1 * denom2);
+	}
+
+	return value;
 }
 
-float Posture::getSimilarity(int parts,
-					std::vector<std::pair<bool, std::vector<cv::Vec2f>>>& posePart,
-					std::vector<std::pair<bool, std::vector<cv::Vec2f>>>& actionPart)
+float Posture::getSimilarity(int parts, std::vector<std::pair<bool, std::vector<cv::Vec2f> > > &posePart,
+							 std::vector<std::pair<bool, std::vector<cv::Vec2f> > > &actionPart)
 {
-    float score = 0.0f;
-    unsigned int bodyCount = 0;
-    std::vector<int> index;
+	float score = 0.0f;
+	unsigned int bodyCount = 0;
+	std::vector<int> index;
 
-    if (parts & MV_INFERENCE_HUMAN_BODY_PART_HEAD) {
-        index.push_back(0);
-    }
+	if (parts & MV_INFERENCE_HUMAN_BODY_PART_HEAD) {
+		index.push_back(0);
+	}
 
-    if (parts & MV_INFERENCE_HUMAN_BODY_PART_ARM_RIGHT) {
-        index.push_back(1);
-    }
+	if (parts & MV_INFERENCE_HUMAN_BODY_PART_ARM_RIGHT) {
+		index.push_back(1);
+	}
 
-    if (parts & MV_INFERENCE_HUMAN_BODY_PART_ARM_LEFT) {
-        index.push_back(2);
-    }
+	if (parts & MV_INFERENCE_HUMAN_BODY_PART_ARM_LEFT) {
+		index.push_back(2);
+	}
 
-    if (parts & MV_INFERENCE_HUMAN_BODY_PART_LEG_RIGHT) {
-        index.push_back(3);
-    }
+	if (parts & MV_INFERENCE_HUMAN_BODY_PART_LEG_RIGHT) {
+		index.push_back(3);
+	}
 
-    if (parts & MV_INFERENCE_HUMAN_BODY_PART_LEG_LEFT) {
-        index.push_back(4);
-    }
+	if (parts & MV_INFERENCE_HUMAN_BODY_PART_LEG_LEFT) {
+		index.push_back(4);
+	}
 
-    if (parts & MV_INFERENCE_HUMAN_BODY_PART_BODY) {
-        index.push_back(5);
-    }
+	if (parts & MV_INFERENCE_HUMAN_BODY_PART_BODY) {
+		index.push_back(5);
+	}
 
-    for (std::vector<int>::iterator it = index.begin(); it != index.end(); ++it) {
-        if (posePart[(*it)].first && actionPart[(*it)].first &&
-            (posePart[(*it)].second.size() == actionPart[(*it)].second.size())) {
-            score += cosineSimilarity(posePart[(*it)].second, actionPart[(*it)].second, posePart[(*it)].second.size());
+	for (std::vector<int>::iterator it = index.begin(); it != index.end(); ++it) {
+		if (posePart[(*it)].first && actionPart[(*it)].first &&
+			(posePart[(*it)].second.size() == actionPart[(*it)].second.size())) {
+			score += cosineSimilarity(posePart[(*it)].second, actionPart[(*it)].second, posePart[(*it)].second.size());
 
-            bodyCount += posePart[(*it)].second.size();
-            LOGI("body[%d], score[%f], count[%u]", (*it), score, bodyCount);
-        }
-    }
+			bodyCount += posePart[(*it)].second.size();
+			LOGI("body[%d], score[%f], count[%u]", (*it), score, bodyCount);
+		}
+	}
 
-    if (bodyCount > 0)
-        score /= (float)bodyCount;
+	if (bodyCount > 0)
+		score /= (float) bodyCount;
 
-    LOGD("score: %1.3f", score);
+	LOGD("score: %1.3f", score);
 
-    return score;
+	return score;
 }
 
-int Posture::compare(int parts, std::vector<std::pair<bool, cv::Point>> action, float* score)
+int Posture::compare(int parts, std::vector<std::pair<bool, cv::Point> > action, float *score)
 {
-    LOGI("ENTER");
+	LOGI("ENTER");
 
-    std::vector<std::pair<bool, std::vector<cv::Vec2f>>> actionParts;
-    actionParts.assign(6, std::make_pair(false, std::vector<cv::Vec2f>()));
-    int ret = getParts(parts, action, actionParts);
-    if (ret != MEDIA_VISION_ERROR_NONE) {
-        LOGE("Fail to getPartse");
-        return ret;
-    }
+	std::vector<std::pair<bool, std::vector<cv::Vec2f> > > actionParts;
+	actionParts.assign(6, std::make_pair(false, std::vector<cv::Vec2f>()));
+	int ret = getParts(parts, action, actionParts);
+	if (ret != MEDIA_VISION_ERROR_NONE) {
+		LOGE("Fail to getPartse");
+		return ret;
+	}
 
-    *score = getSimilarity(parts, mPoseParts, actionParts);
+	*score = getSimilarity(parts, mPoseParts, actionParts);
 
-    LOGI("LEAVE");
+	LOGI("LEAVE");
 
-    return MEDIA_VISION_ERROR_NONE;
+	return MEDIA_VISION_ERROR_NONE;
 }
 
 }
diff --git a/mv_machine_learning/inference/src/PreProcess.cpp b/mv_machine_learning/inference/src/PreProcess.cpp
index 0529124..475753b 100644
--- a/mv_machine_learning/inference/src/PreProcess.cpp
+++ b/mv_machine_learning/inference/src/PreProcess.cpp
@@ -24,131 +24,128 @@
 #include "PreProcess.h"
 
 const int colorConvertTable[][12] = {
-	{ 0,  0,                  0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
-	{ 0, -1,                  0, 0, 0, 0, 0, 0, 0, cv::COLOR_GRAY2BGR565, cv::COLOR_GRAY2RGB,     cv::COLOR_GRAY2RGBA },
-	{ 0, cv::COLOR_YUV2GRAY_I420, -1, 0, 0, 0, 0, 0, 0, 0,                cv::COLOR_RGBA2GRAY,    cv::COLOR_YUV2RGBA_I420 },
-	{ 0, cv::COLOR_YUV2GRAY_NV12, 0, -1, 0, 0, 0, 0, 0, 0,                cv::COLOR_YUV2RGB_NV12, cv::COLOR_YUV2RGBA_NV12 },
-	{ 0, cv::COLOR_YUV2GRAY_YV12, 0, 0, -1, 0, 0, 0, 0, 0,                cv::COLOR_YUV2RGB_YV12, cv::COLOR_YUV2RGBA_YV12 },
-	{ 0, cv::COLOR_YUV2GRAY_NV21, 0, 0, 0, -1, 0, 0, 0, 0,                cv::COLOR_YUV2RGB_NV21, cv::COLOR_YUV2RGBA_NV21 },
-	{ 0, cv::COLOR_YUV2GRAY_YUYV, 0, 0, 0, 0, -1, 0, 0, 0,                cv::COLOR_YUV2RGB_YUYV, cv::COLOR_YUV2RGBA_YUYV },
-	{ 0, cv::COLOR_YUV2GRAY_UYVY, 0, 0, 0, 0, 0, -1, 0, 0,                cv::COLOR_YUV2BGR_UYVY, cv::COLOR_YUV2BGRA_UYVY },
-	{ 0, cv::COLOR_YUV2GRAY_Y422, 0, 0, 0, 0, 0, 0, -1, 0,                cv::COLOR_YUV2RGB_Y422, cv::COLOR_YUV2RGBA_Y422 },
-	{ 0, cv::COLOR_BGR5652GRAY,   0, 0, 0, 0, 0, 0, 0, -1,                cv::COLOR_BGR5652BGR,   cv::COLOR_BGR5652BGRA   },
-	{ 0, cv::COLOR_RGB2GRAY,      0, 0, 0, 0, 0, 0, 0,  0,               -1,                      cv::COLOR_RGB2RGBA      },
-	{ 0, cv::COLOR_RGBA2GRAY,     0, 0, 0, 0, 0, 0, 0, cv::COLOR_BGRA2BGR565, cv::COLOR_RGBA2RGB,   -1}
+	{ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
+	{ 0, -1, 0, 0, 0, 0, 0, 0, 0, cv::COLOR_GRAY2BGR565, cv::COLOR_GRAY2RGB, cv::COLOR_GRAY2RGBA },
+	{ 0, cv::COLOR_YUV2GRAY_I420, -1, 0, 0, 0, 0, 0, 0, 0, cv::COLOR_RGBA2GRAY, cv::COLOR_YUV2RGBA_I420 },
+	{ 0, cv::COLOR_YUV2GRAY_NV12, 0, -1, 0, 0, 0, 0, 0, 0, cv::COLOR_YUV2RGB_NV12, cv::COLOR_YUV2RGBA_NV12 },
+	{ 0, cv::COLOR_YUV2GRAY_YV12, 0, 0, -1, 0, 0, 0, 0, 0, cv::COLOR_YUV2RGB_YV12, cv::COLOR_YUV2RGBA_YV12 },
+	{ 0, cv::COLOR_YUV2GRAY_NV21, 0, 0, 0, -1, 0, 0, 0, 0, cv::COLOR_YUV2RGB_NV21, cv::COLOR_YUV2RGBA_NV21 },
+	{ 0, cv::COLOR_YUV2GRAY_YUYV, 0, 0, 0, 0, -1, 0, 0, 0, cv::COLOR_YUV2RGB_YUYV, cv::COLOR_YUV2RGBA_YUYV },
+	{ 0, cv::COLOR_YUV2GRAY_UYVY, 0, 0, 0, 0, 0, -1, 0, 0, cv::COLOR_YUV2BGR_UYVY, cv::COLOR_YUV2BGRA_UYVY },
+	{ 0, cv::COLOR_YUV2GRAY_Y422, 0, 0, 0, 0, 0, 0, -1, 0, cv::COLOR_YUV2RGB_Y422, cv::COLOR_YUV2RGBA_Y422 },
+	{ 0, cv::COLOR_BGR5652GRAY, 0, 0, 0, 0, 0, 0, 0, -1, cv::COLOR_BGR5652BGR, cv::COLOR_BGR5652BGRA },
+	{ 0, cv::COLOR_RGB2GRAY, 0, 0, 0, 0, 0, 0, 0, 0, -1, cv::COLOR_RGB2RGBA },
+	{ 0, cv::COLOR_RGBA2GRAY, 0, 0, 0, 0, 0, 0, 0, cv::COLOR_BGRA2BGR565, cv::COLOR_RGBA2RGB, -1 }
 };
 
 namespace mediavision
 {
 namespace inference
 {
-	int PreProcess::Resize(cv::Mat& source, cv::Mat& dest, cv::Size size)
-	{
-		LOGI("ENTER");
-
-		try {
-			cv::resize(source, dest, size);
-		} catch (cv::Exception& e) {
-			LOGE("Fail to resize with msg: %s", e.what());
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
-
-		LOGI("LEAVE");
+int PreProcess::Resize(cv::Mat &source, cv::Mat &dest, cv::Size size)
+{
+	LOGI("ENTER");
 
-		return MEDIA_VISION_ERROR_NONE;
+	try {
+		cv::resize(source, dest, size);
+	} catch (cv::Exception &e) {
+		LOGE("Fail to resize with msg: %s", e.what());
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
+	LOGI("LEAVE");
 
-	int PreProcess::ColorConvert(cv::Mat& source, cv::Mat& dest, int sType, int dType)
-	{
-		LOGI("ENTER");
-
-		auto conversionColor = static_cast<int>(colorConvertTable[sType][dType]);
-		if (conversionColor == -1) {/* Don't need conversion */
-			dest = source;
-		} else if (conversionColor > 0) {
-			/* Class for representation the given image as cv::Mat before conversion */
-			cv::cvtColor(source, dest, conversionColor);
-		} else {
-			LOGE("Fail to ColorConvert");
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		LOGI("LEAVE");
-
-		return MEDIA_VISION_ERROR_NONE;
+int PreProcess::ColorConvert(cv::Mat &source, cv::Mat &dest, int sType, int dType)
+{
+	LOGI("ENTER");
+
+	auto conversionColor = static_cast<int>(colorConvertTable[sType][dType]);
+	if (conversionColor == -1) { /* Don't need conversion */
+		dest = source;
+	} else if (conversionColor > 0) {
+		/* Class for representation the given image as cv::Mat before conversion */
+		cv::cvtColor(source, dest, conversionColor);
+	} else {
+		LOGE("Fail to ColorConvert");
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
-	int PreProcess::Normalize(cv::Mat& source, cv::Mat& dest,
-							const std::vector<double>& mean, const std::vector<double>& std)
-	{
-		LOGI("ENTER");
-
-		try {
-			cv::subtract(source, cv::Scalar(mean[0], mean[1], mean[2]), dest);
-			source = dest;
-			cv::divide(source, cv::Scalar(std[0], std[1], std[2]), dest);
-		} catch (cv::Exception& e) {
-			LOGE("Fail to substract/divide with msg: %s", e.what());
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
+	LOGI("LEAVE");
 
-		LOGI("LEAVE");
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		return MEDIA_VISION_ERROR_NONE;
+int PreProcess::Normalize(cv::Mat &source, cv::Mat &dest, const std::vector<double> &mean,
+						  const std::vector<double> &std)
+{
+	LOGI("ENTER");
+
+	try {
+		cv::subtract(source, cv::Scalar(mean[0], mean[1], mean[2]), dest);
+		source = dest;
+		cv::divide(source, cv::Scalar(std[0], std[1], std[2]), dest);
+	} catch (cv::Exception &e) {
+		LOGE("Fail to substract/divide with msg: %s", e.what());
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
-	int PreProcess::Quantize(cv::Mat& source, cv::Mat& dest,
-							const std::vector<double>& scale, const std::vector<double>& zeropoint)
-	{
-		LOGI("ENTER");
-
-		try {
-			cv::subtract(source, cv::Scalar(zeropoint[0], zeropoint[1], zeropoint[2]), dest);
-			source = dest;
-			cv::multiply(source, cv::Scalar(scale[0], scale[1], scale[2]), dest);
-		} catch (cv::Exception& e) {
-			LOGE("Fail to subtract/multiply with msg: %s", e.what());
-			return MEDIA_VISION_ERROR_INVALID_OPERATION;
-		}
+	LOGI("LEAVE");
 
-		LOGI("LEAVE");
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		return MEDIA_VISION_ERROR_NONE;
+int PreProcess::Quantize(cv::Mat &source, cv::Mat &dest, const std::vector<double> &scale,
+						 const std::vector<double> &zeropoint)
+{
+	LOGI("ENTER");
+
+	try {
+		cv::subtract(source, cv::Scalar(zeropoint[0], zeropoint[1], zeropoint[2]), dest);
+		source = dest;
+		cv::multiply(source, cv::Scalar(scale[0], scale[1], scale[2]), dest);
+	} catch (cv::Exception &e) {
+		LOGE("Fail to subtract/multiply with msg: %s", e.what());
+		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
-	int PreProcess::Run(cv::Mat& source, const int colorSpace,
-							const int dataType, const LayerInfo& layerInfo,
-							const Options& options, void* buffer)
-	{
-		LOGI("ENTER");
+	LOGI("LEAVE");
 
-		// dest is a wrapper of the buffer
-		cv::Mat dest(cv::Size(layerInfo.getWidth(), layerInfo.getHeight()),
-					dataType, buffer);
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		cv::Mat cvSource, cvDest;
-		// cvSource has new allocation with dest.size()
-		Resize(source, cvSource, dest.size());
+int PreProcess::Run(cv::Mat &source, const int colorSpace, const int dataType, const LayerInfo &layerInfo,
+					const Options &options, void *buffer)
+{
+	LOGI("ENTER");
 
-		// cvDest has new allocation if it's colorSpace is not RGB888
-		// cvDest share the data with cvSource it's colorSpace is RGB888
-		ColorConvert(cvSource, cvDest, colorSpace, layerInfo.colorSpace);
+	// dest is a wrapper of the buffer
+	cv::Mat dest(cv::Size(layerInfo.getWidth(), layerInfo.getHeight()), dataType, buffer);
 
-		cvDest.convertTo(dest, dest.type());
+	cv::Mat cvSource, cvDest;
+	// cvSource has new allocation with dest.size()
+	Resize(source, cvSource, dest.size());
 
-		if (options.normalization.use) {
-			Normalize(dest, dest, options.normalization.mean, options.normalization.std);
-		}
+	// cvDest has new allocation if it's colorSpace is not RGB888
+	// cvDest share the data with cvSource it's colorSpace is RGB888
+	ColorConvert(cvSource, cvDest, colorSpace, layerInfo.colorSpace);
 
-		if (options.quantization.use) {
-			Quantize(dest, dest, options.quantization.scale, options.quantization.zeropoint);
-		}
+	cvDest.convertTo(dest, dest.type());
 
-		LOGI("LEAVE");
+	if (options.normalization.use) {
+		Normalize(dest, dest, options.normalization.mean, options.normalization.std);
+	}
 
-		return MEDIA_VISION_ERROR_NONE;
+	if (options.quantization.use) {
+		Quantize(dest, dest, options.quantization.scale, options.quantization.zeropoint);
 	}
 
+	LOGI("LEAVE");
+
+	return MEDIA_VISION_ERROR_NONE;
+}
+
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/src/TensorBuffer.cpp b/mv_machine_learning/inference/src/TensorBuffer.cpp
index 161f72f..2d48f52 100644
--- a/mv_machine_learning/inference/src/TensorBuffer.cpp
+++ b/mv_machine_learning/inference/src/TensorBuffer.cpp
@@ -28,200 +28,191 @@ namespace mediavision
 {
 namespace inference
 {
+bool TensorBuffer::empty()
+{
+	return _tensorBuffer.empty();
+}
 
-	bool TensorBuffer::empty()
-	{
-		return _tensorBuffer.empty();
-	}
+bool TensorBuffer::exist(std::string name)
+{
+	return getTensorBuffer(name) != nullptr;
+}
 
-	bool TensorBuffer::exist(std::string name)
-	{
-		return getTensorBuffer(name) != nullptr;
+int TensorBuffer::allocate(inference_engine_tensor_buffer &tensor_buffer,
+						   const inference_engine_tensor_info &tensor_info)
+{
+	if (tensor_info.data_type <= INFERENCE_TENSOR_DATA_TYPE_NONE ||
+		tensor_info.data_type >= INFERENCE_TENSOR_DATA_TYPE_MAX) {
+		LOGE("Invalid tensor data type.");
+		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	int TensorBuffer::allocate(inference_engine_tensor_buffer& tensor_buffer,
-							   const inference_engine_tensor_info& tensor_info)
-	{
-		if (tensor_info.data_type <= INFERENCE_TENSOR_DATA_TYPE_NONE ||
-				tensor_info.data_type >= INFERENCE_TENSOR_DATA_TYPE_MAX) {
-			LOGE("Invalid tensor data type.");
-			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
-		}
-
-		try {
-			if (tensor_info.data_type == INFERENCE_TENSOR_DATA_TYPE_FLOAT32)
-				tensor_buffer.buffer = new float[tensor_info.size];
-			else if (tensor_info.data_type == INFERENCE_TENSOR_DATA_TYPE_INT64)
-				tensor_buffer.buffer = new long long[tensor_info.size];
-			else if (tensor_info.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT64)
-				tensor_buffer.buffer = new unsigned long long[tensor_info.size];
-			else if (tensor_info.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT32)
-				tensor_buffer.buffer = new unsigned int[tensor_info.size];
-			else if (tensor_info.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT8)
-				tensor_buffer.buffer = new char[tensor_info.size];
-			else if (tensor_info.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT16)
-				tensor_buffer.buffer = new unsigned short[tensor_info.size];
-		}  catch (const std::bad_alloc& e) {
-			LOGE("Fail to allocate tensor buffer.(%s)", e.what());
-			return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
-		}
+	try {
+		if (tensor_info.data_type == INFERENCE_TENSOR_DATA_TYPE_FLOAT32)
+			tensor_buffer.buffer = new float[tensor_info.size];
+		else if (tensor_info.data_type == INFERENCE_TENSOR_DATA_TYPE_INT64)
+			tensor_buffer.buffer = new long long[tensor_info.size];
+		else if (tensor_info.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT64)
+			tensor_buffer.buffer = new unsigned long long[tensor_info.size];
+		else if (tensor_info.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT32)
+			tensor_buffer.buffer = new unsigned int[tensor_info.size];
+		else if (tensor_info.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT8)
+			tensor_buffer.buffer = new char[tensor_info.size];
+		else if (tensor_info.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT16)
+			tensor_buffer.buffer = new unsigned short[tensor_info.size];
+	} catch (const std::bad_alloc &e) {
+		LOGE("Fail to allocate tensor buffer.(%s)", e.what());
+		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
+	}
 
-		tensor_buffer.size = tensor_info.size;
+	tensor_buffer.size = tensor_info.size;
 
-		LOGI("Allocated tensor buffer(size = %zu, data type = %d)",
-				tensor_info.size, tensor_info.data_type);
-		tensor_buffer.owner_is_backend = 0;
-		tensor_buffer.data_type = tensor_info.data_type;
+	LOGI("Allocated tensor buffer(size = %zu, data type = %d)", tensor_info.size, tensor_info.data_type);
+	tensor_buffer.owner_is_backend = 0;
+	tensor_buffer.data_type = tensor_info.data_type;
 
-		return MEDIA_VISION_ERROR_NONE;
-	}
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-	void TensorBuffer::release()
-	{
-		for (auto& tensorBuffer : _tensorBuffer) {
-			auto& tBuffer = tensorBuffer.second;
-			if (tBuffer.owner_is_backend) {
-				continue;
-			}
-
-			if (tBuffer.data_type == INFERENCE_TENSOR_DATA_TYPE_FLOAT32) {
-				delete[] static_cast<float *>(tBuffer.buffer);
-			} else if (tBuffer.data_type == INFERENCE_TENSOR_DATA_TYPE_INT64) {
-				delete[] static_cast<long long *>(tBuffer.buffer);
-			} else if (tBuffer.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT32) {
-				delete[] static_cast<uint32_t *>(tBuffer.buffer);
-			} else if (tBuffer.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT16) {
-				delete[] static_cast<unsigned short *>(tBuffer.buffer);
-			} else {
-				delete[] static_cast<unsigned char *>(tBuffer.buffer);
-			}
+void TensorBuffer::release()
+{
+	for (auto &tensorBuffer : _tensorBuffer) {
+		auto &tBuffer = tensorBuffer.second;
+		if (tBuffer.owner_is_backend) {
+			continue;
 		}
 
-		LOGI("Tensor(%zu) have been released.", _tensorBuffer.size());
-		IETensorBuffer().swap(_tensorBuffer);
+		if (tBuffer.data_type == INFERENCE_TENSOR_DATA_TYPE_FLOAT32) {
+			delete[] static_cast<float *>(tBuffer.buffer);
+		} else if (tBuffer.data_type == INFERENCE_TENSOR_DATA_TYPE_INT64) {
+			delete[] static_cast<long long *>(tBuffer.buffer);
+		} else if (tBuffer.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT32) {
+			delete[] static_cast<uint32_t *>(tBuffer.buffer);
+		} else if (tBuffer.data_type == INFERENCE_TENSOR_DATA_TYPE_UINT16) {
+			delete[] static_cast<unsigned short *>(tBuffer.buffer);
+		} else {
+			delete[] static_cast<unsigned char *>(tBuffer.buffer);
+		}
 	}
 
-	size_t TensorBuffer::size()
-	{
-		return _tensorBuffer.size();
-	}
+	LOGI("Tensor(%zu) have been released.", _tensorBuffer.size());
+	IETensorBuffer().swap(_tensorBuffer);
+}
 
-	IETensorBuffer& TensorBuffer::getIETensorBuffer()
-	{
-		return _tensorBuffer;
-	}
+size_t TensorBuffer::size()
+{
+	return _tensorBuffer.size();
+}
 
-	inference_engine_tensor_buffer* TensorBuffer::getTensorBuffer(std::string name)
-	{
-		if (_tensorBuffer.find(name) == _tensorBuffer.end()){
-			return nullptr;
-		}
+IETensorBuffer &TensorBuffer::getIETensorBuffer()
+{
+	return _tensorBuffer;
+}
 
-		return &_tensorBuffer[name];
+inference_engine_tensor_buffer *TensorBuffer::getTensorBuffer(std::string name)
+{
+	if (_tensorBuffer.find(name) == _tensorBuffer.end()) {
+		return nullptr;
 	}
 
-	bool TensorBuffer::addTensorBuffer(std::string name, inference_engine_tensor_buffer& buffer)
-	{
-		if (name.empty() || buffer.buffer == nullptr) {
-			LOGE("Invalid parameters: %s, %p", name.c_str(), buffer.buffer);
-			return false;
-		}
+	return &_tensorBuffer[name];
+}
 
-		auto ret = _tensorBuffer.insert(std::make_pair(name, buffer));
-		if (ret.second == false) {
-			LOGE("Fail to insert %s with buffer %p", name.c_str(), buffer.buffer);
-			return false;
-		}
+bool TensorBuffer::addTensorBuffer(std::string name, inference_engine_tensor_buffer &buffer)
+{
+	if (name.empty() || buffer.buffer == nullptr) {
+		LOGE("Invalid parameters: %s, %p", name.c_str(), buffer.buffer);
+		return false;
+	}
 
-		return true;
+	auto ret = _tensorBuffer.insert(std::make_pair(name, buffer));
+	if (ret.second == false) {
+		LOGE("Fail to insert %s with buffer %p", name.c_str(), buffer.buffer);
+		return false;
 	}
 
-	int TensorBuffer::GetTensorInfo(inference_engine_layer_property& layerProperty, tensor_t& outputTensorInfo)
-	{
-		for (auto& layer : layerProperty.layers) {
-			const inference_engine_tensor_info& tensor_info = layer.second;
+	return true;
+}
 
-			std::vector<int> dimInfo;
+int TensorBuffer::GetTensorInfo(inference_engine_layer_property &layerProperty, tensor_t &outputTensorInfo)
+{
+	for (auto &layer : layerProperty.layers) {
+		const inference_engine_tensor_info &tensor_info = layer.second;
 
-			for (auto& dim : tensor_info.shape) {
-				dimInfo.push_back(dim);
-			}
+		std::vector<int> dimInfo;
 
-			outputTensorInfo.dimInfo.push_back(dimInfo);
+		for (auto &dim : tensor_info.shape) {
+			dimInfo.push_back(dim);
+		}
 
-			inference_engine_tensor_buffer* tensorBuffer = getTensorBuffer(layer.first);
-			if (tensorBuffer == NULL) {
-				LOGE("Fail to getTensorBuffer with name %s", layer.first.c_str());
-				return MEDIA_VISION_ERROR_INVALID_OPERATION;
-			}
+		outputTensorInfo.dimInfo.push_back(dimInfo);
 
-			outputTensorInfo.data.push_back(static_cast<void *>(tensorBuffer->buffer));
+		inference_engine_tensor_buffer *tensorBuffer = getTensorBuffer(layer.first);
+		if (tensorBuffer == NULL) {
+			LOGE("Fail to getTensorBuffer with name %s", layer.first.c_str());
+			return MEDIA_VISION_ERROR_INVALID_OPERATION;
 		}
 
-		return MEDIA_VISION_ERROR_NONE;
+		outputTensorInfo.data.push_back(static_cast<void *>(tensorBuffer->buffer));
 	}
 
-	template <typename T>
-	int TensorBuffer::convertToFloat(inference_engine_tensor_buffer *tensorBuffer)
-	{
-		float *new_buf = new(std::nothrow) float[tensorBuffer->size];
-		if (new_buf == NULL) {
-			LOGE("Fail to allocate a new output tensor buffer.");
-			return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
-		}
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		auto ori_buf = static_cast<T *>(tensorBuffer->buffer);
+template<typename T> int TensorBuffer::convertToFloat(inference_engine_tensor_buffer *tensorBuffer)
+{
+	float *new_buf = new (std::nothrow) float[tensorBuffer->size];
+	if (new_buf == NULL) {
+		LOGE("Fail to allocate a new output tensor buffer.");
+		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
+	}
 
-		for (size_t idx = 0; idx < tensorBuffer->size; idx++)
-			new_buf[idx] = static_cast<float>(ori_buf[idx]) / 255.0f;
+	auto ori_buf = static_cast<T *>(tensorBuffer->buffer);
 
-		// replace original buffer with new one, and release origin one.
-		tensorBuffer->buffer = new_buf;
+	for (size_t idx = 0; idx < tensorBuffer->size; idx++)
+		new_buf[idx] = static_cast<float>(ori_buf[idx]) / 255.0f;
 
-		if (!tensorBuffer->owner_is_backend)
-			delete[] ori_buf;
+	// replace original buffer with new one, and release origin one.
+	tensorBuffer->buffer = new_buf;
 
-		tensorBuffer->data_type = INFERENCE_TENSOR_DATA_TYPE_FLOAT32;
-		tensorBuffer->owner_is_backend = false;
+	if (!tensorBuffer->owner_is_backend)
+		delete[] ori_buf;
 
-		return MEDIA_VISION_ERROR_NONE;
-	}
+	tensorBuffer->data_type = INFERENCE_TENSOR_DATA_TYPE_FLOAT32;
+	tensorBuffer->owner_is_backend = false;
 
-	template <typename T>
-	T TensorBuffer::getValue(std::string name, int idx)
-	{
-		inference_engine_tensor_buffer* tBuffer =
-							getTensorBuffer(name);
-		if (tBuffer == nullptr) {
-			throw std::invalid_argument(name);
-		}
+	return MEDIA_VISION_ERROR_NONE;
+}
 
-		switch (tBuffer->data_type) {
-		case INFERENCE_TENSOR_DATA_TYPE_FLOAT32:
-			return static_cast<T>(static_cast<float*>(tBuffer->buffer)[idx]);
-		case INFERENCE_TENSOR_DATA_TYPE_INT64:
-			return static_cast<T>(
-					static_cast<long long*>(tBuffer->buffer)[idx]);
-		case INFERENCE_TENSOR_DATA_TYPE_UINT32:
-			return static_cast<T>(
-					static_cast<unsigned int*>(tBuffer->buffer)[idx]);
-		case INFERENCE_TENSOR_DATA_TYPE_UINT8:
-			return static_cast<T>(
-					static_cast<unsigned char*>(tBuffer->buffer)[idx]);
-		case INFERENCE_TENSOR_DATA_TYPE_UINT16:
-			return static_cast<T>(
-					static_cast<unsigned short*>(tBuffer->buffer)[idx]);
-		default:
-			break;
-		}
+template<typename T> T TensorBuffer::getValue(std::string name, int idx)
+{
+	inference_engine_tensor_buffer *tBuffer = getTensorBuffer(name);
+	if (tBuffer == nullptr) {
+		throw std::invalid_argument(name);
+	}
 
-		throw std::invalid_argument("Invalid data type");
+	switch (tBuffer->data_type) {
+	case INFERENCE_TENSOR_DATA_TYPE_FLOAT32:
+		return static_cast<T>(static_cast<float *>(tBuffer->buffer)[idx]);
+	case INFERENCE_TENSOR_DATA_TYPE_INT64:
+		return static_cast<T>(static_cast<long long *>(tBuffer->buffer)[idx]);
+	case INFERENCE_TENSOR_DATA_TYPE_UINT32:
+		return static_cast<T>(static_cast<unsigned int *>(tBuffer->buffer)[idx]);
+	case INFERENCE_TENSOR_DATA_TYPE_UINT8:
+		return static_cast<T>(static_cast<unsigned char *>(tBuffer->buffer)[idx]);
+	case INFERENCE_TENSOR_DATA_TYPE_UINT16:
+		return static_cast<T>(static_cast<unsigned short *>(tBuffer->buffer)[idx]);
+	default:
+		break;
 	}
 
-	template float TensorBuffer::getValue<float>(std::string, int);
-	template int TensorBuffer::getValue<int>(std::string, int);
-	template int TensorBuffer::convertToFloat<unsigned char>(_inference_engine_tensor_buffer*);
-	template int TensorBuffer::convertToFloat<unsigned short>(_inference_engine_tensor_buffer*);
+	throw std::invalid_argument("Invalid data type");
+}
+
+template float TensorBuffer::getValue<float>(std::string, int);
+template int TensorBuffer::getValue<int>(std::string, int);
+template int TensorBuffer::convertToFloat<unsigned char>(_inference_engine_tensor_buffer *);
+template int TensorBuffer::convertToFloat<unsigned short>(_inference_engine_tensor_buffer *);
 
 } /* Inference */
 } /* MediaVision */
diff --git a/mv_machine_learning/inference/src/mv_inference.c b/mv_machine_learning/inference/src/mv_inference.c
index bd14a88..f722cd9 100644
--- a/mv_machine_learning/inference/src/mv_inference.c
+++ b/mv_machine_learning/inference/src/mv_inference.c
@@ -25,8 +25,7 @@
 
 int mv_inference_create(mv_inference_h *infer)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(infer);
 
 	MEDIA_VISION_FUNCTION_ENTER();
@@ -41,8 +40,7 @@ int mv_inference_create(mv_inference_h *infer)
 
 int mv_inference_destroy(mv_inference_h infer)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(infer);
 
 	MEDIA_VISION_FUNCTION_ENTER();
@@ -55,11 +53,9 @@ int mv_inference_destroy(mv_inference_h infer)
 	return ret;
 }
 
-int mv_inference_configure(mv_inference_h infer,
-						   mv_engine_config_h engine_config)
+int mv_inference_configure(mv_inference_h infer, mv_engine_config_h engine_config)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(infer);
 	MEDIA_VISION_INSTANCE_CHECK(engine_config);
 
@@ -79,8 +75,7 @@ int mv_inference_configure(mv_inference_h infer,
 
 int mv_inference_prepare(mv_inference_h infer)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(infer);
 
 	MEDIA_VISION_FUNCTION_ENTER();
@@ -93,33 +88,27 @@ int mv_inference_prepare(mv_inference_h infer)
 	return ret;
 }
 
-int mv_inference_foreach_supported_engine(
-		mv_inference_h infer, mv_inference_supported_engine_cb callback,
-		void *user_data)
+int mv_inference_foreach_supported_engine(mv_inference_h infer, mv_inference_supported_engine_cb callback,
+										  void *user_data)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(infer);
 	MEDIA_VISION_NULL_ARG_CHECK(callback);
 	MEDIA_VISION_FUNCTION_ENTER();
 
 	int ret = MEDIA_VISION_ERROR_NONE;
 
-	ret = mv_inference_foreach_supported_engine_open(infer, callback,
-													 user_data);
+	ret = mv_inference_foreach_supported_engine_open(infer, callback, user_data);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_inference_image_classify(mv_source_h source, mv_inference_h infer,
-								mv_rectangle_s *roi,
-								mv_inference_image_classified_cb classified_cb,
-								void *user_data)
+int mv_inference_image_classify(mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
+								mv_inference_image_classified_cb classified_cb, void *user_data)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_image_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
 	MEDIA_VISION_INSTANCE_CHECK(infer);
 	MEDIA_VISION_NULL_ARG_CHECK(classified_cb);
@@ -128,20 +117,17 @@ int mv_inference_image_classify(mv_source_h source, mv_inference_h infer,
 
 	int ret = MEDIA_VISION_ERROR_NONE;
 
-	ret = mv_inference_image_classify_open(source, infer, roi, classified_cb,
-										   user_data);
+	ret = mv_inference_image_classify_open(source, infer, roi, classified_cb, user_data);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_inference_object_detect(mv_source_h source, mv_inference_h infer,
-							   mv_inference_object_detected_cb detected_cb,
+int mv_inference_object_detect(mv_source_h source, mv_inference_h infer, mv_inference_object_detected_cb detected_cb,
 							   void *user_data)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_image_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
 	MEDIA_VISION_INSTANCE_CHECK(infer);
 	MEDIA_VISION_NULL_ARG_CHECK(detected_cb);
@@ -150,20 +136,17 @@ int mv_inference_object_detect(mv_source_h source, mv_inference_h infer,
 
 	int ret = MEDIA_VISION_ERROR_NONE;
 
-	ret = mv_inference_object_detect_open(source, infer, detected_cb,
-										  user_data);
+	ret = mv_inference_object_detect_open(source, infer, detected_cb, user_data);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_inference_face_detect(mv_source_h source, mv_inference_h infer,
-							 mv_inference_face_detected_cb detected_cb,
+int mv_inference_face_detect(mv_source_h source, mv_inference_h infer, mv_inference_face_detected_cb detected_cb,
 							 void *user_data)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_face_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
 	MEDIA_VISION_INSTANCE_CHECK(infer);
 	MEDIA_VISION_NULL_ARG_CHECK(detected_cb);
@@ -179,12 +162,10 @@ int mv_inference_face_detect(mv_source_h source, mv_inference_h infer,
 	return ret;
 }
 
-int mv_inference_facial_landmark_detect(
-		mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
-		mv_inference_facial_landmark_detected_cb detected_cb, void *user_data)
+int mv_inference_facial_landmark_detect(mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
+										mv_inference_facial_landmark_detected_cb detected_cb, void *user_data)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_face_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
 	MEDIA_VISION_INSTANCE_CHECK(infer);
 	MEDIA_VISION_NULL_ARG_CHECK(detected_cb);
@@ -193,20 +174,17 @@ int mv_inference_facial_landmark_detect(
 
 	int ret = MEDIA_VISION_ERROR_NONE;
 
-	ret = mv_inference_facial_landmark_detect_open(source, infer, roi,
-												   detected_cb, user_data);
+	ret = mv_inference_facial_landmark_detect_open(source, infer, roi, detected_cb, user_data);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_inference_pose_landmark_detect(
-		mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
-		mv_inference_pose_landmark_detected_cb detected_cb, void *user_data)
+int mv_inference_pose_landmark_detect(mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
+									  mv_inference_pose_landmark_detected_cb detected_cb, void *user_data)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_face_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_face_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(source);
 	MEDIA_VISION_INSTANCE_CHECK(infer);
 	MEDIA_VISION_NULL_ARG_CHECK(detected_cb);
@@ -215,9 +193,7 @@ int mv_inference_pose_landmark_detect(
 
 	int ret = MEDIA_VISION_ERROR_NONE;
 
-
-	ret = mv_inference_pose_landmark_detect_open(source, infer, roi,
-												 detected_cb, user_data);
+	ret = mv_inference_pose_landmark_detect_open(source, infer, roi, detected_cb, user_data);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 
@@ -226,8 +202,7 @@ int mv_inference_pose_landmark_detect(
 
 int mv_inference_pose_get_number_of_poses(mv_inference_pose_result_h result, int *number_of_poses)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(result);
 
 	MEDIA_VISION_NULL_ARG_CHECK(number_of_poses);
@@ -243,11 +218,9 @@ int mv_inference_pose_get_number_of_poses(mv_inference_pose_result_h result, int
 	return ret;
 }
 
-
 int mv_inference_pose_get_number_of_landmarks(mv_inference_pose_result_h result, int *number_of_landmarks)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(result);
 
 	MEDIA_VISION_NULL_ARG_CHECK(number_of_landmarks);
@@ -263,11 +236,10 @@ int mv_inference_pose_get_number_of_landmarks(mv_inference_pose_result_h result,
 	return ret;
 }
 
-int mv_inference_pose_get_landmark(mv_inference_pose_result_h result,
-		int pose_index, int part_index, mv_point_s *location, float *score)
+int mv_inference_pose_get_landmark(mv_inference_pose_result_h result, int pose_index, int part_index,
+								   mv_point_s *location, float *score)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(result);
 
 	MEDIA_VISION_NULL_ARG_CHECK(location);
@@ -289,8 +261,7 @@ int mv_inference_pose_get_landmark(mv_inference_pose_result_h result,
 
 int mv_inference_pose_get_label(mv_inference_pose_result_h result, int pose_index, int *label)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(result);
 
 	MEDIA_VISION_NULL_ARG_CHECK(label);
@@ -309,11 +280,9 @@ int mv_inference_pose_get_label(mv_inference_pose_result_h result, int pose_inde
 	return ret;
 }
 
-
 int mv_pose_create(mv_pose_h *pose)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(pose);
 
 	MEDIA_VISION_FUNCTION_ENTER();
@@ -329,8 +298,7 @@ int mv_pose_create(mv_pose_h *pose)
 
 int mv_pose_destroy(mv_pose_h pose)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(pose);
 
 	MEDIA_VISION_FUNCTION_ENTER();
@@ -346,8 +314,7 @@ int mv_pose_destroy(mv_pose_h pose)
 
 int mv_pose_set_from_file(mv_pose_h pose, const char *motion_capture_file_path, const char *motion_mapping_file_path)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(pose);
 	MEDIA_VISION_NULL_ARG_CHECK(motion_capture_file_path);
 	MEDIA_VISION_NULL_ARG_CHECK(motion_mapping_file_path);
@@ -365,8 +332,7 @@ int mv_pose_set_from_file(mv_pose_h pose, const char *motion_capture_file_path,
 
 int mv_pose_compare(mv_pose_h pose, mv_inference_pose_result_h action, int parts, float *score)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_inference_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_inference_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(pose);
 	MEDIA_VISION_INSTANCE_CHECK(action);
 	MEDIA_VISION_NULL_ARG_CHECK(score);
diff --git a/mv_machine_learning/inference/src/mv_inference_open.cpp b/mv_machine_learning/inference/src/mv_inference_open.cpp
index da48ac8..28a052e 100644
--- a/mv_machine_learning/inference/src/mv_inference_open.cpp
+++ b/mv_machine_learning/inference/src/mv_inference_open.cpp
@@ -26,18 +26,15 @@
 
 using namespace mediavision::inference;
 
-static int check_mv_inference_engine_version(mv_engine_config_h engine_config,
-											 bool *is_new_version)
+static int check_mv_inference_engine_version(mv_engine_config_h engine_config, bool *is_new_version)
 {
 	int oldType = 0, newType = 0;
 
-	int ret = mv_engine_config_get_int_attribute(
-			engine_config, MV_INFERENCE_TARGET_TYPE, &oldType);
+	int ret = mv_engine_config_get_int_attribute(engine_config, MV_INFERENCE_TARGET_TYPE, &oldType);
 	if (ret != MEDIA_VISION_ERROR_NONE)
 		oldType = -1;
 
-	ret = mv_engine_config_get_int_attribute(
-			engine_config, MV_INFERENCE_TARGET_DEVICE_TYPE, &newType);
+	ret = mv_engine_config_get_int_attribute(engine_config, MV_INFERENCE_TARGET_DEVICE_TYPE, &newType);
 	if (ret != MEDIA_VISION_ERROR_NONE)
 		newType = -1;
 
@@ -48,8 +45,7 @@ static int check_mv_inference_engine_version(mv_engine_config_h engine_config,
 
 	// If values of both types are changed then return an error.
 	// only one of two types should be used.
-	if (oldType != MV_INFERENCE_TARGET_CPU &&
-		newType != MV_INFERENCE_TARGET_DEVICE_CPU) {
+	if (oldType != MV_INFERENCE_TARGET_CPU && newType != MV_INFERENCE_TARGET_DEVICE_CPU) {
 		LOGE("Please use only one of below two device types.");
 		LOGE("MV_INFERENCE_TARGET_TYPE(deprecated) or MV_INFERENCE_TARGET_DEVICE_TYPE(recommended).");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -63,8 +59,7 @@ static int check_mv_inference_engine_version(mv_engine_config_h engine_config,
 	//   (oldType == MV_INFERENCE_TARGET_CPU && newType == MV_INFERENCE_TARGET_DEVICE_CPU)
 	// - default value of only new type is changed.
 	//   (oldType == MV_INFERENCE_TARGET_CPU && (newType != -1 && newType != MV_INFERENCE_TARGET_DEVICE_CPU))
-	if ((oldType != -1 && oldType != MV_INFERENCE_TARGET_CPU) &&
-		newType == MV_INFERENCE_TARGET_DEVICE_CPU)
+	if ((oldType != -1 && oldType != MV_INFERENCE_TARGET_CPU) && newType == MV_INFERENCE_TARGET_DEVICE_CPU)
 		*is_new_version = false;
 	else
 		*is_new_version = true;
@@ -112,15 +107,14 @@ int mv_inference_destroy_open(mv_inference_h infer)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-static bool IsJsonFile(const std::string& fileName)
+static bool IsJsonFile(const std::string &fileName)
 {
 	return (!fileName.substr(fileName.find_last_of(".") + 1).compare("json"));
 }
 
 static bool IsValidBackendType(const int backend_type)
 {
-	return (backend_type > MV_INFERENCE_BACKEND_NONE &&
-			backend_type < MV_INFERENCE_BACKEND_MAX);
+	return (backend_type > MV_INFERENCE_BACKEND_NONE && backend_type < MV_INFERENCE_BACKEND_MAX);
 }
 
 static bool IsConfigFilePathRequired(const int target_device_type, const int backend_type)
@@ -128,8 +122,7 @@ static bool IsConfigFilePathRequired(const int target_device_type, const int bac
 	LOGW("DEPRECATION WARNING : MV_INFERENCE_BACKEND_MLAPI type is deprecated and will be removed from next release.");
 
 	// In case of MV_INFERENCE_TARGET_DEVICE_CUSTOM via MLAPI backend, config file path is required.
-	return (backend_type == MV_INFERENCE_BACKEND_MLAPI &&
-			target_device_type & MV_INFERENCE_TARGET_DEVICE_CUSTOM);
+	return (backend_type == MV_INFERENCE_BACKEND_MLAPI && target_device_type & MV_INFERENCE_TARGET_DEVICE_CUSTOM);
 }
 
 static int configure_model_open(Inference *pInfer, mv_engine_config_h engine_config)
@@ -143,32 +136,27 @@ static int configure_model_open(Inference *pInfer, mv_engine_config_h engine_con
 	int backendType = 0;
 	size_t userFileLength = 0;
 
-	int ret = mv_engine_config_get_string_attribute(
-			engine_config, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH,
-			&modelConfigFilePath);
+	int ret = mv_engine_config_get_string_attribute(engine_config, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH,
+													&modelConfigFilePath);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get model configuration file path");
 		goto out_of_function;
 	}
 
-	ret = mv_engine_config_get_string_attribute(
-			engine_config, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
-			&modelWeightFilePath);
+	ret = mv_engine_config_get_string_attribute(engine_config, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
+												&modelWeightFilePath);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get model weight file path");
 		goto release_model_config_file_path;
 	}
 
-	ret = mv_engine_config_get_string_attribute(
-			engine_config, MV_INFERENCE_MODEL_USER_FILE_PATH,
-			&modelUserFilePath);
+	ret = mv_engine_config_get_string_attribute(engine_config, MV_INFERENCE_MODEL_USER_FILE_PATH, &modelUserFilePath);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get model user file path");
 		goto release_model_weight_file_path;
 	}
 
-	ret = mv_engine_config_get_int_attribute(
-			engine_config, MV_INFERENCE_BACKEND_TYPE, &backendType);
+	ret = mv_engine_config_get_int_attribute(engine_config, MV_INFERENCE_BACKEND_TYPE, &backendType);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get inference backend type");
 		goto release_model_user_file_path;
@@ -202,13 +190,10 @@ static int configure_model_open(Inference *pInfer, mv_engine_config_h engine_con
 		goto release_model_user_file_path;
 	}
 
-	pInfer->ConfigureModelFiles(std::string(modelConfigFilePath),
-								std::string(modelWeightFilePath),
+	pInfer->ConfigureModelFiles(std::string(modelConfigFilePath), std::string(modelWeightFilePath),
 								std::string(modelUserFilePath));
 
-	ret = mv_engine_config_get_string_attribute(
-			engine_config, MV_INFERENCE_MODEL_META_FILE_PATH,
-			&modelMetaFilePath);
+	ret = mv_engine_config_get_string_attribute(engine_config, MV_INFERENCE_MODEL_META_FILE_PATH, &modelMetaFilePath);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get model meta file path");
 		goto release_model_user_file_path;
@@ -261,58 +246,50 @@ static int configure_input_info_open(Inference *pInfer, mv_engine_config_h engin
 	char *node_name = NULL;
 	int dataType = 0;
 
-	int ret = mv_engine_config_get_int_attribute(
-			engine_config, MV_INFERENCE_INPUT_TENSOR_WIDTH, &tensorWidth);
+	int ret = mv_engine_config_get_int_attribute(engine_config, MV_INFERENCE_INPUT_TENSOR_WIDTH, &tensorWidth);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get tensor width");
 		goto out_of_function;
 	}
 
-	ret = mv_engine_config_get_int_attribute(
-			engine_config, MV_INFERENCE_INPUT_TENSOR_HEIGHT, &tensorHeight);
+	ret = mv_engine_config_get_int_attribute(engine_config, MV_INFERENCE_INPUT_TENSOR_HEIGHT, &tensorHeight);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get tensor height");
 		goto out_of_function;
 	}
 
-	ret = mv_engine_config_get_int_attribute(
-			engine_config, MV_INFERENCE_INPUT_TENSOR_CHANNELS, &tensorCh);
+	ret = mv_engine_config_get_int_attribute(engine_config, MV_INFERENCE_INPUT_TENSOR_CHANNELS, &tensorCh);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get tensor channels");
 		goto out_of_function;
 	}
 
-	ret = mv_engine_config_get_double_attribute(
-			engine_config, MV_INFERENCE_MODEL_MEAN_VALUE, &meanValue);
+	ret = mv_engine_config_get_double_attribute(engine_config, MV_INFERENCE_MODEL_MEAN_VALUE, &meanValue);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get meanValue");
 		goto out_of_function;
 	}
 
-	ret = mv_engine_config_get_double_attribute(
-			engine_config, MV_INFERENCE_MODEL_STD_VALUE, &stdValue);
+	ret = mv_engine_config_get_double_attribute(engine_config, MV_INFERENCE_MODEL_STD_VALUE, &stdValue);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get stdValue");
 		goto out_of_function;
 	}
 
-	ret = mv_engine_config_get_int_attribute(
-			engine_config, MV_INFERENCE_INPUT_DATA_TYPE, &dataType);
+	ret = mv_engine_config_get_int_attribute(engine_config, MV_INFERENCE_INPUT_DATA_TYPE, &dataType);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get a input tensor data type");
 		goto out_of_function;
 	}
 
-	ret = mv_engine_config_get_string_attribute(
-			engine_config, MV_INFERENCE_INPUT_NODE_NAME, &node_name);
+	ret = mv_engine_config_get_string_attribute(engine_config, MV_INFERENCE_INPUT_NODE_NAME, &node_name);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get tensor width");
 		goto out_of_function;
 	}
 
-	pInfer->ConfigureInputInfo(
-			tensorWidth, tensorHeight, 1, tensorCh, stdValue, meanValue,
-			dataType, std::vector<std::string>(1, std::string(node_name)));
+	pInfer->ConfigureInputInfo(tensorWidth, tensorHeight, 1, tensorCh, stdValue, meanValue, dataType,
+							   std::vector<std::string>(1, std::string(node_name)));
 
 	if (node_name) {
 		free(node_name);
@@ -325,8 +302,7 @@ out_of_function:
 	return ret;
 }
 
-int mv_inference_configure_engine_open(mv_inference_h infer,
-									   mv_engine_config_h engine_config)
+int mv_inference_configure_engine_open(mv_inference_h infer, mv_engine_config_h engine_config)
 {
 	LOGI("ENTER");
 
@@ -336,15 +312,13 @@ int mv_inference_configure_engine_open(mv_inference_h infer,
 
 	pInfer->SetEngineConfig(engine_config);
 
-	int ret = mv_engine_config_get_int_attribute(
-			engine_config, MV_INFERENCE_BACKEND_TYPE, &backendType);
+	int ret = mv_engine_config_get_int_attribute(engine_config, MV_INFERENCE_BACKEND_TYPE, &backendType);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get inference backend type");
 		goto out_of_function;
 	}
 
-	ret = mv_engine_config_get_int_attribute(
-			engine_config, MV_INFERENCE_TARGET_DEVICE_TYPE, &targetTypes);
+	ret = mv_engine_config_get_int_attribute(engine_config, MV_INFERENCE_TARGET_DEVICE_TYPE, &targetTypes);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get inference target type");
 		goto out_of_function;
@@ -363,8 +337,7 @@ int mv_inference_configure_engine_open(mv_inference_h infer,
 		goto out_of_function;
 
 	// Convert old type to new one and then use it if is_new_version is false
-	if (pInfer->ConfigureTargetTypes(targetTypes, is_new_version) !=
-		MEDIA_VISION_ERROR_NONE) {
+	if (pInfer->ConfigureTargetTypes(targetTypes, is_new_version) != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Tried to configure invalid target types.");
 		goto out_of_function;
 	}
@@ -384,16 +357,14 @@ out_of_function:
 	return ret;
 }
 
-int mv_inference_configure_output_open(mv_inference_h infer,
-									   mv_engine_config_h engine_config)
+int mv_inference_configure_output_open(mv_inference_h infer, mv_engine_config_h engine_config)
 {
 	LOGI("ENTER");
 
 	Inference *pInfer = static_cast<Inference *>(infer);
 	int maxOutput = 0;
 
-	int ret = mv_engine_config_get_int_attribute(
-			engine_config, MV_INFERENCE_OUTPUT_MAX_NUMBER, &maxOutput);
+	int ret = mv_engine_config_get_int_attribute(engine_config, MV_INFERENCE_OUTPUT_MAX_NUMBER, &maxOutput);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get inference output maximum numbers");
 		goto out_of_function;
@@ -407,16 +378,14 @@ out_of_function:
 	return ret;
 }
 
-int mv_inference_configure_confidence_threshold_open(
-		mv_inference_h infer, mv_engine_config_h engine_config)
+int mv_inference_configure_confidence_threshold_open(mv_inference_h infer, mv_engine_config_h engine_config)
 {
 	LOGI("ENTER");
 
 	Inference *pInfer = static_cast<Inference *>(infer);
 	double threshold = 0;
 
-	int ret = mv_engine_config_get_double_attribute(
-			engine_config, MV_INFERENCE_CONFIDENCE_THRESHOLD, &threshold);
+	int ret = mv_engine_config_get_double_attribute(engine_config, MV_INFERENCE_CONFIDENCE_THRESHOLD, &threshold);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get inference confidence threshold value");
 		goto out_of_function;
@@ -437,8 +406,7 @@ static int configure_post_process_info_open(Inference *pInfer, mv_engine_config_
 	int maxOutput = 0;
 	double threshold = 0;
 
-	int ret = mv_engine_config_get_int_attribute(
-			engine_config, MV_INFERENCE_OUTPUT_MAX_NUMBER, &maxOutput);
+	int ret = mv_engine_config_get_int_attribute(engine_config, MV_INFERENCE_OUTPUT_MAX_NUMBER, &maxOutput);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get inference output maximum numbers");
 		goto out_of_function;
@@ -446,8 +414,7 @@ static int configure_post_process_info_open(Inference *pInfer, mv_engine_config_
 
 	pInfer->ConfigureOutput(maxOutput);
 
-	ret = mv_engine_config_get_double_attribute(
-			engine_config, MV_INFERENCE_CONFIDENCE_THRESHOLD, &threshold);
+	ret = mv_engine_config_get_double_attribute(engine_config, MV_INFERENCE_CONFIDENCE_THRESHOLD, &threshold);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get inference confidence threshold value");
 		goto out_of_function;
@@ -470,8 +437,8 @@ static int configure_output_info_open(Inference *pInfer, mv_engine_config_h engi
 	int size = 0;
 	std::vector<std::string> names;
 
-	int ret = mv_engine_config_get_array_string_attribute(
-			engine_config, MV_INFERENCE_OUTPUT_NODE_NAMES, &node_names, &size);
+	int ret = mv_engine_config_get_array_string_attribute(engine_config, MV_INFERENCE_OUTPUT_NODE_NAMES, &node_names,
+														  &size);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get _output_node_names");
 		return ret;
@@ -541,9 +508,8 @@ int mv_inference_prepare_open(mv_inference_h infer)
 	return ret;
 }
 
-int mv_inference_foreach_supported_engine_open(
-		mv_inference_h infer, mv_inference_supported_engine_cb callback,
-		void *user_data)
+int mv_inference_foreach_supported_engine_open(mv_inference_h infer, mv_inference_supported_engine_cb callback,
+											   void *user_data)
 {
 	LOGI("ENTER");
 
@@ -560,9 +526,8 @@ int mv_inference_foreach_supported_engine_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_inference_image_classify_open(
-		mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
-		mv_inference_image_classified_cb classified_cb, void *user_data)
+int mv_inference_image_classify_open(mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
+									 mv_inference_image_classified_cb classified_cb, void *user_data)
 {
 	Inference *pInfer = static_cast<Inference *>(infer);
 	std::vector<mv_source_h> sources;
@@ -610,8 +575,7 @@ int mv_inference_image_classify_open(
 }
 
 int mv_inference_object_detect_open(mv_source_h source, mv_inference_h infer,
-									mv_inference_object_detected_cb detected_cb,
-									void *user_data)
+									mv_inference_object_detected_cb detected_cb, void *user_data)
 {
 	Inference *pInfer = static_cast<Inference *>(infer);
 	std::vector<mv_source_h> sources;
@@ -650,23 +614,19 @@ int mv_inference_object_detect_open(mv_source_h source, mv_inference_h infer,
 		locations[output_idx].point.y = objectDetectionResults.locations[output_idx].y;
 		locations[output_idx].width = objectDetectionResults.locations[output_idx].width;
 		locations[output_idx].height = objectDetectionResults.locations[output_idx].height;
-		LOGI("%d, %d, %d, %d", locations[output_idx].point.x,
-								locations[output_idx].point.y,
-								locations[output_idx].width,
-								locations[output_idx].height);
+		LOGI("%d, %d, %d, %d", locations[output_idx].point.x, locations[output_idx].point.y,
+			 locations[output_idx].width, locations[output_idx].height);
 	}
 
 	int *indices = objectDetectionResults.indices.data();
 	float *confidences = objectDetectionResults.confidences.data();
 
-	detected_cb(source, numberOfOutputs, indices, names.data(), confidences,
-				locations.data(), user_data);
+	detected_cb(source, numberOfOutputs, indices, names.data(), confidences, locations.data(), user_data);
 
 	return ret;
 }
 
-int mv_inference_face_detect_open(mv_source_h source, mv_inference_h infer,
-								  mv_inference_face_detected_cb detected_cb,
+int mv_inference_face_detect_open(mv_source_h source, mv_inference_h infer, mv_inference_face_detected_cb detected_cb,
 								  void *user_data)
 {
 	Inference *pInfer = static_cast<Inference *>(infer);
@@ -701,15 +661,13 @@ int mv_inference_face_detect_open(mv_source_h source, mv_inference_h infer,
 
 	float *confidences = faceDetectionResults.confidences.data();
 
-	detected_cb(source, numberOfOutputs, confidences, locations.data(),
-				user_data);
+	detected_cb(source, numberOfOutputs, confidences, locations.data(), user_data);
 
 	return ret;
 }
 
-int mv_inference_facial_landmark_detect_open(
-		mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
-		mv_inference_facial_landmark_detected_cb detected_cb, void *user_data)
+int mv_inference_facial_landmark_detect_open(mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
+											 mv_inference_facial_landmark_detected_cb detected_cb, void *user_data)
 {
 	Inference *pInfer = static_cast<Inference *>(infer);
 	std::vector<mv_source_h> sources;
@@ -747,9 +705,8 @@ int mv_inference_facial_landmark_detect_open(
 	return ret;
 }
 
-int mv_inference_pose_landmark_detect_open(
-		mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
-		mv_inference_pose_landmark_detected_cb detected_cb, void *user_data)
+int mv_inference_pose_landmark_detect_open(mv_source_h source, mv_inference_h infer, mv_rectangle_s *roi,
+										   mv_inference_pose_landmark_detected_cb detected_cb, void *user_data)
 {
 	Inference *pInfer = static_cast<Inference *>(infer);
 	unsigned int width, height;
@@ -761,7 +718,7 @@ int mv_inference_pose_landmark_detect_open(
 	}
 
 	ret = mv_source_get_height(source, &height);
-		if (ret != MEDIA_VISION_ERROR_NONE) {
+	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get height");
 		return ret;
 	}
@@ -782,8 +739,7 @@ int mv_inference_pose_landmark_detect_open(
 
 	std::unique_ptr<mv_inference_pose_s> pose;
 
-	ret = pInfer->GetPoseLandmarkDetectionResults(
-			pose, width, height);
+	ret = pInfer->GetPoseLandmarkDetectionResults(pose, width, height);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to get inference results");
 		return ret;
@@ -792,9 +748,9 @@ int mv_inference_pose_landmark_detect_open(
 	for (int pose_index = 0; pose_index < pose->number_of_poses; ++pose_index) {
 		for (int landmark_index = 0; landmark_index < pose->number_of_landmarks_per_pose; ++landmark_index) {
 			LOGI("PoseIdx[%2d]: x[%d], y[%d], score[%.3f]", landmark_index,
-										pose->landmarks[pose_index][landmark_index].point.x,
-										pose->landmarks[pose_index][landmark_index].point.y,
-										pose->landmarks[pose_index][landmark_index].score);
+				 pose->landmarks[pose_index][landmark_index].point.x,
+				 pose->landmarks[pose_index][landmark_index].point.y,
+				 pose->landmarks[pose_index][landmark_index].score);
 		}
 	}
 
@@ -803,9 +759,7 @@ int mv_inference_pose_landmark_detect_open(
 	return ret;
 }
 
-int mv_inference_pose_get_number_of_poses_open(
-		mv_inference_pose_result_h result,
-		int *number_of_poses)
+int mv_inference_pose_get_number_of_poses_open(mv_inference_pose_result_h result, int *number_of_poses)
 {
 	mv_inference_pose_s *handle = static_cast<mv_inference_pose_s *>(result);
 	*number_of_poses = handle->number_of_poses;
@@ -814,9 +768,7 @@ int mv_inference_pose_get_number_of_poses_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_inference_pose_get_number_of_landmarks_open(
-		mv_inference_pose_result_h result,
-		int *number_of_landmarks)
+int mv_inference_pose_get_number_of_landmarks_open(mv_inference_pose_result_h result, int *number_of_landmarks)
 {
 	mv_inference_pose_s *handle = static_cast<mv_inference_pose_s *>(result);
 	*number_of_landmarks = handle->number_of_landmarks_per_pose;
@@ -825,12 +777,8 @@ int mv_inference_pose_get_number_of_landmarks_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_inference_pose_get_landmark_open(
-		mv_inference_pose_result_h result,
-		int pose_index,
-		int part_index,
-		mv_point_s *location,
-		float *score)
+int mv_inference_pose_get_landmark_open(mv_inference_pose_result_h result, int pose_index, int part_index,
+										mv_point_s *location, float *score)
 {
 	mv_inference_pose_s *pose_obj = static_cast<mv_inference_pose_s *>(result);
 
@@ -847,10 +795,7 @@ int mv_inference_pose_get_landmark_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_inference_pose_get_label_open(
-		mv_inference_pose_result_h result,
-		int pose_index,
-		int *label)
+int mv_inference_pose_get_label_open(mv_inference_pose_result_h result, int pose_index, int *label)
 {
 	mv_inference_pose_s *pose_obj = static_cast<mv_inference_pose_s *>(result);
 
@@ -896,22 +841,19 @@ int mv_pose_destroy_open(mv_pose_h pose)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_pose_set_from_file_open(mv_pose_h pose,
-		const char *motionCaptureFilePath,
-		const char *motionMappingFilePath)
+int mv_pose_set_from_file_open(mv_pose_h pose, const char *motionCaptureFilePath, const char *motionMappingFilePath)
 {
 	Posture *pPose = static_cast<Posture *>(pose);
 
 	// check file
 	if (access(motionCaptureFilePath, F_OK) || access(motionMappingFilePath, F_OK)) {
-        LOGE("Invalid Motion Capture file path [%s]", motionCaptureFilePath);
+		LOGE("Invalid Motion Capture file path [%s]", motionCaptureFilePath);
 		LOGE("Invalid Motion Mapping file path [%s]", motionMappingFilePath);
 
-        return MEDIA_VISION_ERROR_INVALID_PATH;
-    }
+		return MEDIA_VISION_ERROR_INVALID_PATH;
+	}
 
-	int ret = pPose->setPoseFromFile(std::string(motionCaptureFilePath),
-								std::string(motionMappingFilePath));
+	int ret = pPose->setPoseFromFile(std::string(motionCaptureFilePath), std::string(motionMappingFilePath));
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Fail to setPoseFromFile");
 		return ret;
@@ -923,18 +865,17 @@ int mv_pose_set_from_file_open(mv_pose_h pose,
 int mv_pose_compare_open(mv_pose_h pose, mv_inference_pose_result_h action, int parts, float *score)
 {
 	Posture *pPose = static_cast<Posture *>(pose);
-	std::vector<std::pair<bool, cv::Point>> actionParts;
+	std::vector<std::pair<bool, cv::Point> > actionParts;
 	mv_inference_pose_s *pAction = static_cast<mv_inference_pose_s *>(action);
 
 	for (int k = 0; k < HUMAN_POSE_MAX_LANDMARKS; ++k) {
 		if (pAction->landmarks[0][k].point.x == -1 || pAction->landmarks[0][k].point.y == -1) {
-			actionParts.push_back(std::make_pair(false, cv::Point(-1,-1)));
+			actionParts.push_back(std::make_pair(false, cv::Point(-1, -1)));
 			continue;
 		}
 
-		actionParts.push_back(std::make_pair(true, cv::Point(pAction->landmarks[0][k].point.x,
-															pAction->landmarks[0][k].point.y)));
-
+		actionParts.push_back(
+				std::make_pair(true, cv::Point(pAction->landmarks[0][k].point.x, pAction->landmarks[0][k].point.y)));
 	}
 
 	int ret = pPose->compare(parts, actionParts, score);
diff --git a/mv_machine_learning/training/include/data_augment.h b/mv_machine_learning/training/include/data_augment.h
index 58e1c46..3c5afa7 100644
--- a/mv_machine_learning/training/include/data_augment.h
+++ b/mv_machine_learning/training/include/data_augment.h
@@ -23,12 +23,13 @@
 #include <opencv2/opencv.hpp>
 #include <opencv2/imgproc/imgproc.hpp>
 
-class DataAugment {
+class DataAugment
+{
 public:
 	DataAugment();
 	virtual ~DataAugment();
 
-	virtual void Preprocess(std::vector<float>& in_vec, std::vector<float>& out_vec, int width, int height) = 0;
+	virtual void Preprocess(std::vector<float> &in_vec, std::vector<float> &out_vec, int width, int height) = 0;
 };
 
 #endif
\ No newline at end of file
diff --git a/mv_machine_learning/training/include/data_augment_default.h b/mv_machine_learning/training/include/data_augment_default.h
index 58e1597..5175ed1 100644
--- a/mv_machine_learning/training/include/data_augment_default.h
+++ b/mv_machine_learning/training/include/data_augment_default.h
@@ -22,12 +22,13 @@
 
 #include "data_augment.h"
 
-class DataAugmentDefault final : public DataAugment {
+class DataAugmentDefault final : public DataAugment
+{
 public:
 	DataAugmentDefault();
 	~DataAugmentDefault();
 
-	void Preprocess(std::vector<float>& in_vec, std::vector<float>& out_vec, int width, int height) final;
+	void Preprocess(std::vector<float> &in_vec, std::vector<float> &out_vec, int width, int height) final;
 };
 
 #endif
\ No newline at end of file
diff --git a/mv_machine_learning/training/include/data_augment_flip.h b/mv_machine_learning/training/include/data_augment_flip.h
index 153c49e..d7b53c7 100644
--- a/mv_machine_learning/training/include/data_augment_flip.h
+++ b/mv_machine_learning/training/include/data_augment_flip.h
@@ -22,12 +22,13 @@
 
 #include "data_augment.h"
 
-class DataAugmentFlip final : public DataAugment {
+class DataAugmentFlip final : public DataAugment
+{
 public:
 	DataAugmentFlip();
 	~DataAugmentFlip();
 
-	void Preprocess(std::vector<float>& in_vec, std::vector<float>& out_vec, int width, int height) final;
+	void Preprocess(std::vector<float> &in_vec, std::vector<float> &out_vec, int width, int height) final;
 };
 
 #endif
\ No newline at end of file
diff --git a/mv_machine_learning/training/include/data_augment_rotate.h b/mv_machine_learning/training/include/data_augment_rotate.h
index 43fec62..f727aec 100644
--- a/mv_machine_learning/training/include/data_augment_rotate.h
+++ b/mv_machine_learning/training/include/data_augment_rotate.h
@@ -22,7 +22,8 @@
 
 #include "data_augment.h"
 
-class DataAugmentRotate final : public DataAugment {
+class DataAugmentRotate final : public DataAugment
+{
 private:
 	unsigned int _degree;
 
@@ -30,7 +31,7 @@ public:
 	DataAugmentRotate(unsigned int degree = 90);
 	~DataAugmentRotate();
 
-	void Preprocess(std::vector<float>& in_vec, std::vector<float>& out_vec, int width, int height) final;
+	void Preprocess(std::vector<float> &in_vec, std::vector<float> &out_vec, int width, int height) final;
 };
 
 #endif
\ No newline at end of file
diff --git a/mv_machine_learning/training/include/data_set_manager.h b/mv_machine_learning/training/include/data_set_manager.h
index 56cbfd3..6e86b3b 100644
--- a/mv_machine_learning/training/include/data_set_manager.h
+++ b/mv_machine_learning/training/include/data_set_manager.h
@@ -23,10 +23,11 @@
 
 #include "feature_vector_manager.h"
 
-class DataSetManager {
+class DataSetManager
+{
 protected:
-	std::vector<std::vector<float>> _data;
-	std::vector<std::vector<float>> _labels;
+	std::vector<std::vector<float> > _data;
+	std::vector<std::vector<float> > _labels;
 	std::vector<unsigned int> _label_index;
 	size_t _feature_vector_size;
 	size_t _label_size;
@@ -37,13 +38,13 @@ public:
 	virtual ~DataSetManager();
 
 	void Clear();
-	bool IsFeatureVectorDuplicated(const std::vector<float>& vec);
-	std::vector<std::vector<float>>& GetData(void);
-	std::vector<std::vector<float>>& GetLabel(void);
+	bool IsFeatureVectorDuplicated(const std::vector<float> &vec);
+	std::vector<std::vector<float> > &GetData(void);
+	std::vector<std::vector<float> > &GetLabel(void);
 	size_t GetFeaVecSize(void);
 	size_t GetLabelSize(void);
 	size_t GetDataSetLen(void);
-	std::vector<unsigned int>& GetLabelIdx(void);
+	std::vector<unsigned int> &GetLabelIdx(void);
 
 	virtual void LoadDataSet(const std::string file_name) = 0;
 };
diff --git a/mv_machine_learning/training/include/feature_vector_manager.h b/mv_machine_learning/training/include/feature_vector_manager.h
index aeca7d9..f1ffc22 100644
--- a/mv_machine_learning/training/include/feature_vector_manager.h
+++ b/mv_machine_learning/training/include/feature_vector_manager.h
@@ -25,14 +25,16 @@
 
 #include "file_util.h"
 
-typedef struct {
+typedef struct
+{
 	unsigned int signature;
 	size_t feature_size;
 	size_t one_hot_table_size;
 	unsigned int data_set_cnt;
 } FeaVecHeader;
 
-class FeatureVectorManager {
+class FeatureVectorManager
+{
 protected:
 	std::string _feature_vector_file;
 
@@ -40,20 +42,18 @@ public:
 	FeatureVectorManager(const std::string feature_vector_file = "feature_vector_file.dat");
 	virtual ~FeatureVectorManager() = default;
 
-	const std::string& GetFileName();
+	const std::string &GetFileName();
 
-	static void GetVecFromImg(const std::string image_file, std::vector<float>& vec,
-							  unsigned int width, unsigned int height);
-	static void GetVecFromRGB(unsigned char *in_data, std::vector<float>& vec,
-							  unsigned int width, unsigned int height,
+	static void GetVecFromImg(const std::string image_file, std::vector<float> &vec, unsigned int width,
+							  unsigned int height);
+	static void GetVecFromRGB(unsigned char *in_data, std::vector<float> &vec, unsigned int width, unsigned int height,
 							  size_t re_width, size_t re_height);
-	static void GetVecFromXRGB(unsigned char *in_data, std::vector<float>& vec,
-							   unsigned int in_width, unsigned int in_height,
-							   unsigned int re_width, unsigned int re_height);
+	static void GetVecFromXRGB(unsigned char *in_data, std::vector<float> &vec, unsigned int in_width,
+							   unsigned int in_height, unsigned int re_width, unsigned int re_height);
 
-	virtual void WriteHeader(size_t feature_size, size_t one_hot_table_size, unsigned int  data_set_cnt) = 0;
-	virtual void ReadHeader(FeaVecHeader& header) = 0;
-	virtual void WriteFeatureVec(std::vector<float>& feature_vec, const int max_label, const int label_index) = 0;
+	virtual void WriteHeader(size_t feature_size, size_t one_hot_table_size, unsigned int data_set_cnt) = 0;
+	virtual void ReadHeader(FeaVecHeader &header) = 0;
+	virtual void WriteFeatureVec(std::vector<float> &feature_vec, const int max_label, const int label_index) = 0;
 	virtual void Remove() = 0;
 
 	static constexpr unsigned int feature_vector_signature = 0xFEA09841;
diff --git a/mv_machine_learning/training/include/file_util.h b/mv_machine_learning/training/include/file_util.h
index 5df0c9a..bcbe3ec 100644
--- a/mv_machine_learning/training/include/file_util.h
+++ b/mv_machine_learning/training/include/file_util.h
@@ -22,8 +22,8 @@
 
 namespace FaceRecogUtil
 {
-    bool IsFileExist(const std::string file_path);
-    bool IsImageFile(const std::string image_file);
+bool IsFileExist(const std::string file_path);
+bool IsImageFile(const std::string image_file);
 }
 
 #endif
\ No newline at end of file
diff --git a/mv_machine_learning/training/include/label_manager.h b/mv_machine_learning/training/include/label_manager.h
index 9c44f22..1902569 100644
--- a/mv_machine_learning/training/include/label_manager.h
+++ b/mv_machine_learning/training/include/label_manager.h
@@ -27,7 +27,8 @@
 
 #include "file_util.h"
 
-class LabelManager {
+class LabelManager
+{
 private:
 	std::map<std::string, std::string> _labels_and_files;
 	std::string _label_file;
@@ -43,13 +44,13 @@ public:
 	unsigned int GetLabelIndex(const std::string given_label);
 	bool IsExist(const std::string given_label);
 	unsigned int RemoveLabel(const std::string given_label);
-	int GetLabelString(std::string& label, const int idx);
+	int GetLabelString(std::string &label, const int idx);
 	unsigned int AddLabelToFile(std::string given_label);
 	int ImportLabel(void);
 	bool AddLabelToMap(const std::string given_label, const std::string image_file);
 	size_t GetMaxLabel(const std::string label_file);
 	size_t GetMaxLabel();
-	std::string GetLabelFromAnswer(const std::vector<float>& result);
+	std::string GetLabelFromAnswer(const std::vector<float> &result);
 	void Remove();
 };
 
diff --git a/mv_machine_learning/training/include/training_model.h b/mv_machine_learning/training/include/training_model.h
index 3667534..6bb0b20 100644
--- a/mv_machine_learning/training/include/training_model.h
+++ b/mv_machine_learning/training/include/training_model.h
@@ -28,7 +28,8 @@
 #include "data_set_manager.h"
 #include "feature_vector_manager.h"
 
-typedef struct {
+typedef struct
+{
 	int backend_type;
 	unsigned int target_device;
 	std::vector<std::string> input_layer_names;
@@ -39,29 +40,32 @@ typedef struct {
 	training_engine_compile_property compile_property;
 } TrainingEngineBackendInfo;
 
-class TrainingModel {
+class TrainingModel
+{
 private:
 	virtual void SaveModel(const std::string file_path) = 0;
 	virtual void RemoveModel(const std::string file_path) = 0;
+
 protected:
 	std::unique_ptr<TrainingEngineInterface::Common::TrainingEngineCommon> _training;
 	std::unique_ptr<training_engine_model> _model;
 	std::unique_ptr<training_engine_dataset> _data_set;
 	std::string _internal_model_file;
+
 public:
 	TrainingModel(const mv_inference_backend_type_e backend_type = MV_INFERENCE_BACKEND_NNTRAINER,
 				  const mv_inference_target_device_e target_type = MV_INFERENCE_TARGET_DEVICE_CPU,
 				  const std::string internal_model_file = "model_and_weights.ini");
 	virtual ~TrainingModel();
 
-	void ApplyDataSet(std::unique_ptr<DataSetManager>& data_set);
-	void ClearDataSet(std::unique_ptr<DataSetManager>& data_set);
+	void ApplyDataSet(std::unique_ptr<DataSetManager> &data_set);
+	void ClearDataSet(std::unique_ptr<DataSetManager> &data_set);
 	void Compile();
 	void Train();
 	void RemoveModel();
 
 	virtual void ConfigureModel(int num_of_class) = 0;
-	virtual TrainingEngineBackendInfo& GetTrainingEngineInfo() = 0;
+	virtual TrainingEngineBackendInfo &GetTrainingEngineInfo() = 0;
 };
 
 #endif
\ No newline at end of file
diff --git a/mv_machine_learning/training/src/data_augment.cpp b/mv_machine_learning/training/src/data_augment.cpp
index 01d2f49..aa3b4f8 100644
--- a/mv_machine_learning/training/src/data_augment.cpp
+++ b/mv_machine_learning/training/src/data_augment.cpp
@@ -19,11 +19,7 @@
 using namespace std;
 
 DataAugment::DataAugment()
-{
-
-}
+{}
 
 DataAugment::~DataAugment()
-{
-
-}
\ No newline at end of file
+{}
\ No newline at end of file
diff --git a/mv_machine_learning/training/src/data_augment_default.cpp b/mv_machine_learning/training/src/data_augment_default.cpp
index fdf7feb..26e7c98 100644
--- a/mv_machine_learning/training/src/data_augment_default.cpp
+++ b/mv_machine_learning/training/src/data_augment_default.cpp
@@ -19,18 +19,14 @@
 using namespace std;
 
 DataAugmentDefault::DataAugmentDefault() : DataAugment()
-{
-
-}
+{}
 
 DataAugmentDefault::~DataAugmentDefault()
-{
-
-}
+{}
 
-void DataAugmentDefault::Preprocess(vector<float>& in_vec, vector<float>& out_vec, int width, int height)
+void DataAugmentDefault::Preprocess(vector<float> &in_vec, vector<float> &out_vec, int width, int height)
 {
 	cv::Mat cvSrc = cv::Mat(cv::Size(width, height), CV_32FC3, in_vec.data()).clone();
 
-	out_vec.assign((float *)cvSrc.data, (float *)cvSrc.data + cvSrc.total() * cvSrc.channels());
+	out_vec.assign((float *) cvSrc.data, (float *) cvSrc.data + cvSrc.total() * cvSrc.channels());
 }
\ No newline at end of file
diff --git a/mv_machine_learning/training/src/data_augment_flip.cpp b/mv_machine_learning/training/src/data_augment_flip.cpp
index d7bca95..381751b 100644
--- a/mv_machine_learning/training/src/data_augment_flip.cpp
+++ b/mv_machine_learning/training/src/data_augment_flip.cpp
@@ -19,16 +19,12 @@
 using namespace std;
 
 DataAugmentFlip::DataAugmentFlip() : DataAugment()
-{
-
-}
+{}
 
 DataAugmentFlip::~DataAugmentFlip()
-{
-
-}
+{}
 
-void DataAugmentFlip::Preprocess(vector<float>& in_vec, vector<float>& out_vec, int width, int height)
+void DataAugmentFlip::Preprocess(vector<float> &in_vec, vector<float> &out_vec, int width, int height)
 {
 	cv::Mat cvSrc = cv::Mat(cv::Size(width, height), CV_32FC3, in_vec.data()).clone();
 
@@ -36,5 +32,5 @@ void DataAugmentFlip::Preprocess(vector<float>& in_vec, vector<float>& out_vec,
 
 	cv::flip(cvSrc, cvFlip, 1);
 
-	out_vec.assign((float *)cvFlip.data, (float *)cvFlip.data + cvFlip.total() * cvFlip.channels());
+	out_vec.assign((float *) cvFlip.data, (float *) cvFlip.data + cvFlip.total() * cvFlip.channels());
 }
\ No newline at end of file
diff --git a/mv_machine_learning/training/src/data_augment_rotate.cpp b/mv_machine_learning/training/src/data_augment_rotate.cpp
index 4b20623..2d82a5d 100644
--- a/mv_machine_learning/training/src/data_augment_rotate.cpp
+++ b/mv_machine_learning/training/src/data_augment_rotate.cpp
@@ -21,16 +21,12 @@ using namespace std;
 using namespace mediavision::machine_learning::exception;
 
 DataAugmentRotate::DataAugmentRotate(unsigned int degree) : _degree(degree)
-{
-
-}
+{}
 
 DataAugmentRotate::~DataAugmentRotate()
-{
-
-}
+{}
 
-void DataAugmentRotate::Preprocess(vector<float>& in_vec, vector<float>& out_vec, int width, int height)
+void DataAugmentRotate::Preprocess(vector<float> &in_vec, vector<float> &out_vec, int width, int height)
 {
 	cv::Mat cvSrc = cv::Mat(cv::Size(width, height), CV_32FC3, in_vec.data()).clone();
 
@@ -54,5 +50,5 @@ void DataAugmentRotate::Preprocess(vector<float>& in_vec, vector<float>& out_vec
 
 	cv::rotate(cvSrc, cvRotate, rotate_code);
 
-	out_vec.assign((float *)cvRotate.data, (float *)cvRotate.data + cvRotate.total() * cvRotate.channels());
+	out_vec.assign((float *) cvRotate.data, (float *) cvRotate.data + cvRotate.total() * cvRotate.channels());
 }
\ No newline at end of file
diff --git a/mv_machine_learning/training/src/data_set_manager.cpp b/mv_machine_learning/training/src/data_set_manager.cpp
index d661f31..e8952cc 100644
--- a/mv_machine_learning/training/src/data_set_manager.cpp
+++ b/mv_machine_learning/training/src/data_set_manager.cpp
@@ -18,10 +18,9 @@
 
 using namespace std;
 
-DataSetManager::DataSetManager() : _data(), _labels(), _label_index(), _feature_vector_size(), _label_size(), _data_set_length()
-{
-
-}
+DataSetManager::DataSetManager()
+		: _data(), _labels(), _label_index(), _feature_vector_size(), _label_size(), _data_set_length()
+{}
 
 DataSetManager::~DataSetManager()
 {
@@ -30,36 +29,36 @@ DataSetManager::~DataSetManager()
 
 void DataSetManager::Clear()
 {
-	for (auto& data : _data)
+	for (auto &data : _data)
 		data.clear();
 
 	_data.clear();
 
-	for (auto& label : _labels)
+	for (auto &label : _labels)
 		label.clear();
 
 	_labels.clear();
 	_label_index.clear();
 }
 
-bool DataSetManager::IsFeatureVectorDuplicated(const vector<float>& vec)
+bool DataSetManager::IsFeatureVectorDuplicated(const vector<float> &vec)
 {
 	if (_data.empty())
 		return false;
 
-	for (const auto& data : _data)
+	for (const auto &data : _data)
 		if (data == vec)
 			return true;
 
 	return false;
 }
 
-vector<vector<float>>& DataSetManager::GetData(void)
+vector<vector<float> > &DataSetManager::GetData(void)
 {
 	return _data;
 }
 
-vector<vector<float>>& DataSetManager::GetLabel(void)
+vector<vector<float> > &DataSetManager::GetLabel(void)
 {
 	return _labels;
 }
@@ -79,7 +78,7 @@ size_t DataSetManager::GetDataSetLen(void)
 	return _data_set_length;
 }
 
-vector<unsigned int>& DataSetManager::GetLabelIdx(void)
+vector<unsigned int> &DataSetManager::GetLabelIdx(void)
 {
 	return _label_index;
 }
\ No newline at end of file
diff --git a/mv_machine_learning/training/src/feature_vector_manager.cpp b/mv_machine_learning/training/src/feature_vector_manager.cpp
index 62d90a3..4de8a12 100644
--- a/mv_machine_learning/training/src/feature_vector_manager.cpp
+++ b/mv_machine_learning/training/src/feature_vector_manager.cpp
@@ -23,18 +23,16 @@
 using namespace std;
 using namespace mediavision::machine_learning::exception;
 
-FeatureVectorManager::FeatureVectorManager(const string feature_vector_file)
-	: _feature_vector_file(feature_vector_file)
-{
-}
+FeatureVectorManager::FeatureVectorManager(const string feature_vector_file) : _feature_vector_file(feature_vector_file)
+{}
 
-const string& FeatureVectorManager::GetFileName()
+const string &FeatureVectorManager::GetFileName()
 {
 	return _feature_vector_file;
 }
 
-void FeatureVectorManager::GetVecFromImg(const string image_file, vector<float>& vec,
-										 unsigned int width, unsigned int height)
+void FeatureVectorManager::GetVecFromImg(const string image_file, vector<float> &vec, unsigned int width,
+										 unsigned int height)
 {
 	cv::Mat src, dst;
 
@@ -61,12 +59,11 @@ void FeatureVectorManager::GetVecFromImg(const string image_file, vector<float>&
 	cv::subtract(floatSrc, meaned, dst);
 	dst /= 127.5f;
 
-	vec.assign((float *)dst.data, (float *)dst.data + dst.total() * dst.channels());
+	vec.assign((float *) dst.data, (float *) dst.data + dst.total() * dst.channels());
 }
 
-void FeatureVectorManager::GetVecFromRGB(unsigned char *in_data, vector<float>& vec,
-										 unsigned int width, unsigned int height,
-										 size_t re_width, size_t re_height)
+void FeatureVectorManager::GetVecFromRGB(unsigned char *in_data, vector<float> &vec, unsigned int width,
+										 unsigned int height, size_t re_width, size_t re_height)
 {
 	cv::Mat cvSrc = cv::Mat(cv::Size(width, height), CV_MAKETYPE(CV_8U, 3), in_data).clone();
 
@@ -84,18 +81,17 @@ void FeatureVectorManager::GetVecFromRGB(unsigned char *in_data, vector<float>&
 	cv::subtract(floatSrc, meaned, dst);
 	dst /= 127.5f;
 
-	vec.assign((float *)dst.data, (float *)dst.data + dst.total() * dst.channels());
+	vec.assign((float *) dst.data, (float *) dst.data + dst.total() * dst.channels());
 }
 
-void FeatureVectorManager::GetVecFromXRGB(unsigned char *in_data, vector<float>& vec,
-							unsigned int in_width, unsigned int in_height, unsigned int re_width,
-							unsigned int re_height)
+void FeatureVectorManager::GetVecFromXRGB(unsigned char *in_data, vector<float> &vec, unsigned int in_width,
+										  unsigned int in_height, unsigned int re_width, unsigned int re_height)
 {
 	cv::Mat argb(cv::Size(in_width, in_height), CV_8UC4, in_data);
 
 	cv::Mat split_rgbx[4];
-	cv::split (argb, split_rgbx);
-	cv::Mat splitted[] = {split_rgbx[0], split_rgbx[1], split_rgbx[2]};
+	cv::split(argb, split_rgbx);
+	cv::Mat splitted[] = { split_rgbx[0], split_rgbx[1], split_rgbx[2] };
 	cv::Mat rgb;
 	cv::merge(splitted, 3, rgb);
 
@@ -114,5 +110,5 @@ void FeatureVectorManager::GetVecFromXRGB(unsigned char *in_data, vector<float>&
 	cv::subtract(floatSrc, meaned, dst);
 	dst /= 127.5f;
 
-	vec.assign((float *)dst.data, (float *)dst.data + dst.total() * dst.channels());
+	vec.assign((float *) dst.data, (float *) dst.data + dst.total() * dst.channels());
 }
\ No newline at end of file
diff --git a/mv_machine_learning/training/src/file_util.cpp b/mv_machine_learning/training/src/file_util.cpp
index 72396df..482af4b 100644
--- a/mv_machine_learning/training/src/file_util.cpp
+++ b/mv_machine_learning/training/src/file_util.cpp
@@ -18,32 +18,31 @@
 
 namespace FaceRecogUtil
 {
-    bool IsFileExist(const std::string file_path)
-    {
-        struct stat fileStat;
-
-        if (stat(file_path.c_str(), &fileStat))
-            return false;
+bool IsFileExist(const std::string file_path)
+{
+	struct stat fileStat;
 
-        if (!S_ISREG(fileStat.st_mode))
-            return false;
+	if (stat(file_path.c_str(), &fileStat))
+		return false;
 
-        return true;
-    }
+	if (!S_ISREG(fileStat.st_mode))
+		return false;
 
-    bool IsImageFile(const std::string image_file)
-	{
+	return true;
+}
 
-		size_t size = image_file.size();
+bool IsImageFile(const std::string image_file)
+{
+	size_t size = image_file.size();
 
-		// At least, the length of a image file name should be more then 5. i.e., a.bmp, a.jpg, a.png, ...
-		if (size < 5)
-			return false;
+	// At least, the length of a image file name should be more then 5. i.e., a.bmp, a.jpg, a.png, ...
+	if (size < 5)
+		return false;
 
-		std::string ext = image_file.substr(size - 3);
-		if (ext.compare("bmp") != 0 && ext.compare("jpg") != 0 && ext.compare("png") != 0)
-			return false;
+	std::string ext = image_file.substr(size - 3);
+	if (ext.compare("bmp") != 0 && ext.compare("jpg") != 0 && ext.compare("png") != 0)
+		return false;
 
-		return true;
-	}
+	return true;
+}
 }
\ No newline at end of file
diff --git a/mv_machine_learning/training/src/label_manager.cpp b/mv_machine_learning/training/src/label_manager.cpp
index 3e03a57..feee3bb 100644
--- a/mv_machine_learning/training/src/label_manager.cpp
+++ b/mv_machine_learning/training/src/label_manager.cpp
@@ -31,17 +31,21 @@ LabelManager::LabelManager(string label_file, double decision_threshold) : _labe
 	LOGD("decision_threshold value is %lf", _decision_threshold);
 }
 
-LabelManager::~LabelManager() { }
+LabelManager::~LabelManager()
+{}
 
-void LabelManager::Clear() {
+void LabelManager::Clear()
+{
 	_labels_and_files.clear();
 }
 
-float LabelManager::GetDecisionThreshold() {
+float LabelManager::GetDecisionThreshold()
+{
 	return _decision_threshold;
 }
 
-float LabelManager::GetDecisionWeight() {
+float LabelManager::GetDecisionWeight()
+{
 	return _decision_weight;
 }
 
@@ -148,7 +152,7 @@ unsigned int LabelManager::RemoveLabel(const string given_label)
 	return label_index;
 }
 
-int LabelManager::GetLabelString(string& label, const int idx)
+int LabelManager::GetLabelString(string &label, const int idx)
 {
 	ifstream readFile;
 
@@ -223,7 +227,6 @@ int LabelManager::ImportLabel(void)
 	return label_cnt;
 }
 
-
 bool LabelManager::AddLabelToMap(const string given_label, const string image_file)
 {
 	// Find same one if not empty. If same one exists in the map then skip.
@@ -240,7 +243,6 @@ bool LabelManager::AddLabelToMap(const string given_label, const string image_fi
 
 size_t LabelManager::GetMaxLabel(const string label_file)
 {
-
 	// label count is 0 if lael file doesn't exist.
 	if (!FaceRecogUtil::IsFileExist(label_file))
 		return 0;
@@ -269,7 +271,7 @@ size_t LabelManager::GetMaxLabel()
 	return GetMaxLabel(_label_file);
 }
 
-string LabelManager::GetLabelFromAnswer(const vector<float>& result)
+string LabelManager::GetLabelFromAnswer(const vector<float> &result)
 {
 	if (result.empty())
 		throw InvalidParameter("result vector is empty.");
diff --git a/mv_machine_learning/training/src/training_model.cpp b/mv_machine_learning/training/src/training_model.cpp
index 5229b6b..ee022ed 100644
--- a/mv_machine_learning/training/src/training_model.cpp
+++ b/mv_machine_learning/training/src/training_model.cpp
@@ -34,8 +34,7 @@ using namespace TrainingEngineInterface::Common;
 using namespace mediavision::machine_learning::exception;
 
 TrainingModel::TrainingModel(const mv_inference_backend_type_e backend_type,
-							 const mv_inference_target_device_e target_type,
-							 const string internal_model_file)
+							 const mv_inference_target_device_e target_type, const string internal_model_file)
 {
 	_internal_model_file = internal_model_file;
 	_training = make_unique<TrainingEngineInterface::Common::TrainingEngineCommon>();
@@ -52,16 +51,16 @@ TrainingModel::TrainingModel(const mv_inference_backend_type_e backend_type,
 		throw InvalidOperation("Fail to get backend capacity.");
 }
 
-TrainingModel::~ TrainingModel()
+TrainingModel::~TrainingModel()
 {
 	if (_training)
 		_training->UnbindBackend();
 }
 
-void TrainingModel::ApplyDataSet(unique_ptr<DataSetManager>& data_set)
+void TrainingModel::ApplyDataSet(unique_ptr<DataSetManager> &data_set)
 {
-	auto& values = data_set->GetData();
-	auto& labels = data_set->GetLabel();
+	auto &values = data_set->GetData();
+	auto &labels = data_set->GetLabel();
 
 	LOGD("Generating feature vectors for training");
 
@@ -84,7 +83,7 @@ void TrainingModel::ApplyDataSet(unique_ptr<DataSetManager>& data_set)
 		throw InvalidOperation("Fail to set dataset to model.", ret);
 }
 
-void TrainingModel::ClearDataSet(unique_ptr<DataSetManager>& data_set)
+void TrainingModel::ClearDataSet(unique_ptr<DataSetManager> &data_set)
 {
 	data_set->Clear();
 	_training->DestroyDataset(_data_set.get());
diff --git a/mv_roi_tracker/roi_tracker/include/ROITracker.h b/mv_roi_tracker/roi_tracker/include/ROITracker.h
index 3b6d6fd..edd7b49 100644
--- a/mv_roi_tracker/roi_tracker/include/ROITracker.h
+++ b/mv_roi_tracker/roi_tracker/include/ROITracker.h
@@ -25,24 +25,26 @@
 #include <opencv2/tracking.hpp>
 #include <opencv2/tracking/tracking_legacy.hpp>
 
-namespace MediaVision {
-namespace ROITracker {
-
+namespace MediaVision
+{
+namespace ROITracker
+{
 using TrackerResult = std::tuple<int, int, int, int>;
 
-class ROITracker {
+class ROITracker
+{
 public:
 	ROITracker() = default;
 	virtual ~ROITracker() = default;
 
 	void setType(mv_roi_tracker_type_e type) noexcept;
 	void setRoi(int x, int y, int width, int height) noexcept;
-	void perform(cv::Mat& frame);
+	void perform(cv::Mat &frame);
 	TrackerResult result();
 
 private:
-	void initialize(cv::Mat& frame);
-	void update(cv::Mat& frame);
+	void initialize(cv::Mat &frame);
+	void update(cv::Mat &frame);
 
 	cv::Ptr<cv::Tracker> __cvTracker;
 	cv::Rect __boundingBox;
diff --git a/mv_roi_tracker/roi_tracker/include/ROITrackerUtil.h b/mv_roi_tracker/roi_tracker/include/ROITrackerUtil.h
index 6bc90b9..8807236 100644
--- a/mv_roi_tracker/roi_tracker/include/ROITrackerUtil.h
+++ b/mv_roi_tracker/roi_tracker/include/ROITrackerUtil.h
@@ -19,9 +19,11 @@
 #ifndef __MEDIA_VISION_ROITRACKERUTIL_H__
 #define __MEDIA_VISION_ROITRACKERUTIL_H__
 
-namespace MediaVision {
-namespace ROITracker {
-    cv::Ptr<cv::Tracker> createTrackerByName(mv_roi_tracker_type_e type);
+namespace MediaVision
+{
+namespace ROITracker
+{
+cv::Ptr<cv::Tracker> createTrackerByName(mv_roi_tracker_type_e type);
 
 } /* ROITracker */
 } /* MediaVision */
diff --git a/mv_roi_tracker/roi_tracker/include/mv_roi_tracker_open.h b/mv_roi_tracker/roi_tracker/include/mv_roi_tracker_open.h
index 3100f56..b2f5738 100644
--- a/mv_roi_tracker/roi_tracker/include/mv_roi_tracker_open.h
+++ b/mv_roi_tracker/roi_tracker/include/mv_roi_tracker_open.h
@@ -23,8 +23,7 @@
 #include "mv_roi_tracker_type.h"
 
 #ifdef __cplusplus
-extern "C"
-{
+extern "C" {
 #endif /* __cplusplus */
 
 /**
@@ -86,8 +85,7 @@ int mv_roi_tracker_destroy_open(mv_roi_tracker_h handle);
  * @retval #MEDIA_VISION_ERROR_OUT_OF_MEMORY Out of memory
  * @retval #MEDIA_VISION_ERROR_NOT_SUPPORTED Not supported
  */
-int mv_roi_tracker_configure_engine_open(mv_roi_tracker_h handle,
-                                        mv_engine_config_h engine_config);
+int mv_roi_tracker_configure_engine_open(mv_roi_tracker_h handle, mv_engine_config_h engine_config);
 
 /**
  * @brief Prepare roi tracker.
@@ -133,7 +131,8 @@ int mv_roi_tracker_prepare_open(mv_roi_tracker_h handle, int x, int y, int width
  * @pre Create a source handle by calling @ref mv_create_source()
  * @pre Create an tracker handle by calling @ref mv_roi_tracker_create_open()
  */
-int mv_roi_tracker_perform_open(mv_roi_tracker_h handle, mv_source_h source, mv_roi_tracker_tracked_cb tracked_cb, void *user_data);
+int mv_roi_tracker_perform_open(mv_roi_tracker_h handle, mv_source_h source, mv_roi_tracker_tracked_cb tracked_cb,
+								void *user_data);
 
 #ifdef __cplusplus
 }
diff --git a/mv_roi_tracker/roi_tracker/src/ROITracker.cpp b/mv_roi_tracker/roi_tracker/src/ROITracker.cpp
index c473865..52e8aae 100644
--- a/mv_roi_tracker/roi_tracker/src/ROITracker.cpp
+++ b/mv_roi_tracker/roi_tracker/src/ROITracker.cpp
@@ -35,18 +35,19 @@
 #include "ROITracker.h"
 #include "ROITrackerUtil.h"
 
-namespace MediaVision {
-namespace ROITracker {
-
-void ROITracker::initialize(cv::Mat& frame)
+namespace MediaVision
+{
+namespace ROITracker
+{
+void ROITracker::initialize(cv::Mat &frame)
 {
 	if (__cvTracker) {
 		LOGE("cvTracker already exists. 'mv_roi_tracker_destroy' should be called for removing cvTracker.");
 		throw std::runtime_error("tracker Initialize failed.");
 	}
 
-	LOGD("Init pos : x:%d, y:%d, w:%d, h:%d is set.",
-		__boundingBox.x, __boundingBox.y, __boundingBox.width, __boundingBox.height);
+	LOGD("Init pos : x:%d, y:%d, w:%d, h:%d is set.", __boundingBox.x, __boundingBox.y, __boundingBox.width,
+		 __boundingBox.height);
 
 	__cvTracker = createTrackerByName(__type);
 	__cvTracker->init(frame, __boundingBox);
@@ -56,7 +57,7 @@ void ROITracker::initialize(cv::Mat& frame)
 	LOGI("Initialized done");
 }
 
-void ROITracker::update(cv::Mat& frame)
+void ROITracker::update(cv::Mat &frame)
 {
 	if (!__cvTracker->update(frame, __boundingBox)) {
 		LOGE("update failed.");
@@ -64,11 +65,11 @@ void ROITracker::update(cv::Mat& frame)
 		throw std::runtime_error("tracker update failed.");
 	}
 
-	LOGD(" Updated: x: %d, y: %d, w: %d, h: %d",
-		__boundingBox.x, __boundingBox.y, __boundingBox.width, __boundingBox.height);
+	LOGD(" Updated: x: %d, y: %d, w: %d, h: %d", __boundingBox.x, __boundingBox.y, __boundingBox.width,
+		 __boundingBox.height);
 }
 
-void ROITracker::perform(cv::Mat& frame)
+void ROITracker::perform(cv::Mat &frame)
 {
 	if (!__initialized)
 		initialize(frame);
@@ -95,8 +96,8 @@ void ROITracker::setRoi(int x, int y, int width, int height) noexcept
 {
 	__boundingBox = { x, y, width, height };
 
-	LOGD("ROI : x:%d, y:%d, w:%d, h:%d is set.",
-			__boundingBox.x, __boundingBox.y, __boundingBox.width, __boundingBox.height);
+	LOGD("ROI : x:%d, y:%d, w:%d, h:%d is set.", __boundingBox.x, __boundingBox.y, __boundingBox.width,
+		 __boundingBox.height);
 }
 
 } /* ROITracker */
diff --git a/mv_roi_tracker/roi_tracker/src/ROITrackerUtil.cpp b/mv_roi_tracker/roi_tracker/src/ROITrackerUtil.cpp
index 6732bb7..5493738 100644
--- a/mv_roi_tracker/roi_tracker/src/ROITrackerUtil.cpp
+++ b/mv_roi_tracker/roi_tracker/src/ROITrackerUtil.cpp
@@ -20,20 +20,22 @@
 #include <opencv2/tracking/tracking_legacy.hpp>
 #include <iostream>
 
-namespace MediaVision {
-namespace ROITracker {
-    cv::Ptr<cv::Tracker> createTrackerByName(mv_roi_tracker_type_e type)
-    {
-        switch (type) {
-        case MV_ROI_TRACKER_TYPE_BALANCE:
-            return cv::TrackerKCF::create();
-        case MV_ROI_TRACKER_TYPE_SPEED:
-            return cv::legacy::upgradeTrackingAPI(cv::legacy::TrackerMedianFlow::create());
-        case MV_ROI_TRACKER_TYPE_ACCURACY:
-            return cv::TrackerCSRT::create();
-        default:
-            throw std::runtime_error("Unexpected type");
-        }
-    }
+namespace MediaVision
+{
+namespace ROITracker
+{
+cv::Ptr<cv::Tracker> createTrackerByName(mv_roi_tracker_type_e type)
+{
+	switch (type) {
+	case MV_ROI_TRACKER_TYPE_BALANCE:
+		return cv::TrackerKCF::create();
+	case MV_ROI_TRACKER_TYPE_SPEED:
+		return cv::legacy::upgradeTrackingAPI(cv::legacy::TrackerMedianFlow::create());
+	case MV_ROI_TRACKER_TYPE_ACCURACY:
+		return cv::TrackerCSRT::create();
+	default:
+		throw std::runtime_error("Unexpected type");
+	}
+}
 } /* ROITracker */
 } /* MediaVision */
\ No newline at end of file
diff --git a/mv_roi_tracker/roi_tracker/src/mv_roi_tracker.c b/mv_roi_tracker/roi_tracker/src/mv_roi_tracker.c
index 12cefe2..6b8b650 100644
--- a/mv_roi_tracker/roi_tracker/src/mv_roi_tracker.c
+++ b/mv_roi_tracker/roi_tracker/src/mv_roi_tracker.c
@@ -20,8 +20,7 @@
 
 int mv_roi_tracker_create(mv_roi_tracker_h *handle)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-		_mv_roi_tracking_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_roi_tracking_check_system_info_feature_supported());
 
 	MEDIA_VISION_NULL_ARG_CHECK(handle);
 
@@ -36,8 +35,7 @@ int mv_roi_tracker_create(mv_roi_tracker_h *handle)
 
 int mv_roi_tracker_destroy(mv_roi_tracker_h handle)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-		_mv_roi_tracking_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_roi_tracking_check_system_info_feature_supported());
 
 	MEDIA_VISION_INSTANCE_CHECK(handle);
 
@@ -50,11 +48,9 @@ int mv_roi_tracker_destroy(mv_roi_tracker_h handle)
 	return ret;
 }
 
-int mv_roi_tracker_configure(mv_roi_tracker_h handle,
-						   mv_engine_config_h engine_config)
+int mv_roi_tracker_configure(mv_roi_tracker_h handle, mv_engine_config_h engine_config)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_roi_tracking_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_roi_tracking_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(handle);
 	MEDIA_VISION_INSTANCE_CHECK(engine_config);
 
@@ -74,8 +70,7 @@ int mv_roi_tracker_configure(mv_roi_tracker_h handle,
 
 int mv_roi_tracker_prepare(mv_roi_tracker_h handle, int x, int y, int width, int height)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-			_mv_roi_tracking_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_roi_tracking_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(handle);
 	MEDIA_VISION_NULL_ARG_CHECK(x);
 	MEDIA_VISION_NULL_ARG_CHECK(y);
@@ -92,10 +87,10 @@ int mv_roi_tracker_prepare(mv_roi_tracker_h handle, int x, int y, int width, int
 	return ret;
 }
 
-int mv_roi_tracker_perform(mv_roi_tracker_h handle, mv_source_h source, mv_roi_tracker_tracked_cb tracked_cb, void *user_data)
+int mv_roi_tracker_perform(mv_roi_tracker_h handle, mv_source_h source, mv_roi_tracker_tracked_cb tracked_cb,
+						   void *user_data)
 {
-	MEDIA_VISION_SUPPORT_CHECK(
-		_mv_roi_tracking_check_system_info_feature_supported());
+	MEDIA_VISION_SUPPORT_CHECK(_mv_roi_tracking_check_system_info_feature_supported());
 
 	MEDIA_VISION_INSTANCE_CHECK(handle);
 	MEDIA_VISION_INSTANCE_CHECK(source);
diff --git a/mv_roi_tracker/roi_tracker/src/mv_roi_tracker_open.cpp b/mv_roi_tracker/roi_tracker/src/mv_roi_tracker_open.cpp
index 5fe8f0b..32b3488 100644
--- a/mv_roi_tracker/roi_tracker/src/mv_roi_tracker_open.cpp
+++ b/mv_roi_tracker/roi_tracker/src/mv_roi_tracker_open.cpp
@@ -23,7 +23,8 @@
 using namespace std;
 using namespace MediaVision::ROITracker;
 
-static cv::Mat getTrackerFrame(mv_colorspace_e colorspace, unsigned int width, unsigned int height, unsigned char* buffer)
+static cv::Mat getTrackerFrame(mv_colorspace_e colorspace, unsigned int width, unsigned int height,
+							   unsigned char *buffer)
 {
 	switch (colorspace) {
 	case MEDIA_VISION_COLORSPACE_Y800:
@@ -32,7 +33,7 @@ static cv::Mat getTrackerFrame(mv_colorspace_e colorspace, unsigned int width, u
 	case MEDIA_VISION_COLORSPACE_NV12:
 	case MEDIA_VISION_COLORSPACE_NV21:
 	case MEDIA_VISION_COLORSPACE_YV12:
-		return cv::Mat(width, height * 3/2, CV_8UC1, buffer).clone();
+		return cv::Mat(width, height * 3 / 2, CV_8UC1, buffer).clone();
 	case MEDIA_VISION_COLORSPACE_YUYV:
 	case MEDIA_VISION_COLORSPACE_UYVY:
 	case MEDIA_VISION_COLORSPACE_422P:
@@ -52,7 +53,7 @@ int mv_roi_tracker_create_open(mv_roi_tracker_h *handle)
 {
 	LOGD("ENTER");
 
-	ROITracker *pTracker = new (std::nothrow)ROITracker;
+	ROITracker *pTracker = new (std::nothrow) ROITracker;
 	if (!pTracker) {
 		LOGE("Failed to create tracker");
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
@@ -82,8 +83,7 @@ int mv_roi_tracker_destroy_open(mv_roi_tracker_h handle)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_roi_tracker_configure_engine_open(mv_roi_tracker_h handle,
-									   mv_engine_config_h engine_config)
+int mv_roi_tracker_configure_engine_open(mv_roi_tracker_h handle, mv_engine_config_h engine_config)
 {
 	LOGI("ENTER");
 
@@ -93,8 +93,8 @@ int mv_roi_tracker_configure_engine_open(mv_roi_tracker_h handle,
 	}
 
 	int tracker_type;
-	if (mv_engine_config_get_int_attribute(engine_config,
-			MV_ROI_TRACKER_TYPE, &tracker_type) != MEDIA_VISION_ERROR_NONE)
+	if (mv_engine_config_get_int_attribute(engine_config, MV_ROI_TRACKER_TYPE, &tracker_type) !=
+		MEDIA_VISION_ERROR_NONE)
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 
 	auto pTracker = static_cast<ROITracker *>(handle);
@@ -120,7 +120,8 @@ int mv_roi_tracker_prepare_open(mv_roi_tracker_h handle, int x, int y, int width
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_roi_tracker_perform_open(mv_roi_tracker_h handle, mv_source_h source, mv_roi_tracker_tracked_cb tracked_cb, void *user_data)
+int mv_roi_tracker_perform_open(mv_roi_tracker_h handle, mv_source_h source, mv_roi_tracker_tracked_cb tracked_cb,
+								void *user_data)
 {
 	LOGD("ENTER");
 
@@ -135,14 +136,10 @@ int mv_roi_tracker_perform_open(mv_roi_tracker_h handle, mv_source_h source, mv_
 	unsigned char *buffer = NULL;
 	mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
 
-	MEDIA_VISION_ASSERT(mv_source_get_width(source, &width),
-			"Failed to get the width.");
-	MEDIA_VISION_ASSERT(mv_source_get_height(source, &height),
-			"Failed to get the height.");
-	MEDIA_VISION_ASSERT(mv_source_get_colorspace(source, &colorspace),
-			"Failed to get the colorspace.");
-	MEDIA_VISION_ASSERT(mv_source_get_buffer(source, &buffer, &bufferSize),
-			"Failed to get the buffer size.");
+	MEDIA_VISION_ASSERT(mv_source_get_width(source, &width), "Failed to get the width.");
+	MEDIA_VISION_ASSERT(mv_source_get_height(source, &height), "Failed to get the height.");
+	MEDIA_VISION_ASSERT(mv_source_get_colorspace(source, &colorspace), "Failed to get the colorspace.");
+	MEDIA_VISION_ASSERT(mv_source_get_buffer(source, &buffer, &bufferSize), "Failed to get the buffer size.");
 
 	LOGD(" w: %d, h: %d, c: %d", width, height, channels);
 	try {
diff --git a/mv_surveillance/surveillance/include/EventDefs.h b/mv_surveillance/surveillance/include/EventDefs.h
index 9d92ade..0fd812e 100644
--- a/mv_surveillance/surveillance/include/EventDefs.h
+++ b/mv_surveillance/surveillance/include/EventDefs.h
@@ -31,9 +31,10 @@
 
 #include <opencv2/opencv.hpp>
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 typedef std::map<std::string, std::vector<std::string> > EventTypesMap;
 typedef EventTypesMap::iterator EventTypesMapIter;
 typedef EventTypesMap::const_iterator EventTypesMapConstIter;
diff --git a/mv_surveillance/surveillance/include/EventManager.h b/mv_surveillance/surveillance/include/EventManager.h
index dc802a7..8bb4011 100644
--- a/mv_surveillance/surveillance/include/EventManager.h
+++ b/mv_surveillance/surveillance/include/EventManager.h
@@ -25,9 +25,10 @@
 #include "EventTrigger.h"
 #include "EventDefs.h"
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 class EventManager;
 
 /**
@@ -36,9 +37,9 @@ class EventManager;
  *
  * @since_tizen 3.0
  */
-class EventManagerDestroyer {
+class EventManagerDestroyer
+{
 public:
-
 	/**
 	 * @brief Default destructor.
 	 *
@@ -55,7 +56,6 @@ public:
 	void initialize(EventManager *pointer);
 
 private:
-
 	EventManager *__pInstance;
 };
 
@@ -66,15 +66,15 @@ private:
  * @since_tizen 3.0
  */
 
-class EventManager {
+class EventManager
+{
 public:
-
 	/**
 	 * @brief Gets EventManager instance.
 	 *
 	 * @since_tizen 3.0
 	 */
-	static EventManager& getInstance();
+	static EventManager &getInstance();
 
 	/**
 	 * @brief Registers event.
@@ -92,19 +92,11 @@ public:
 	 * @param [in] isInternal        Interpretation event as internal in surveillance
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	int registerEvent(
-		mv_surveillance_event_trigger_h eventTrigger,
-		long int triggerId,
-		const char *eventType,
-		int videoStreamId,
-		mv_engine_config_h engineCfg,
-		mv_surveillance_event_occurred_cb callback,
-		void *user_data,
-		int numberOfPoints,
-		mv_point_s *roi,
-		bool isInternal);
-
-    /**
+	int registerEvent(mv_surveillance_event_trigger_h eventTrigger, long int triggerId, const char *eventType,
+					  int videoStreamId, mv_engine_config_h engineCfg, mv_surveillance_event_occurred_cb callback,
+					  void *user_data, int numberOfPoints, mv_point_s *roi, bool isInternal);
+
+	/**
      * @brief Unregisters event.
      *
      * @since_tizen 3.0
@@ -114,7 +106,7 @@ public:
      *                             will be unregistered
      * @return @c 0 on success, otherwise a negative error value
      */
-    int unregisterEvent(long int triggerId, int videoStreamId);
+	int unregisterEvent(long int triggerId, int videoStreamId);
 
 	/**
 	 * @brief Pushes media source to run event triggers.
@@ -133,7 +125,7 @@ public:
 	 * @param [out] eventTypes    The supported event types
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	static int getSupportedEventTypes(StringVector& eventTypes);
+	static int getSupportedEventTypes(StringVector &eventTypes);
 
 	/**
 	 * @brief Gets all supported event result value names.
@@ -142,7 +134,7 @@ public:
 	 * @param [out] eventResValNames    The supported event result value names
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	static int getSupportedEventResultValueNames(StringVector& eventResValNames);
+	static int getSupportedEventResultValueNames(StringVector &eventResValNames);
 
 	/**
 	 * @brief Gets supported event result value names for an event type.
@@ -153,28 +145,24 @@ public:
 	 * @param [out] eventResValNames    The supported event result value names
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	static int getSupportedEventResultValueNames(
-		const std::string& eventTypeName,
-		StringVector& eventResValNames);
+	static int getSupportedEventResultValueNames(const std::string &eventTypeName, StringVector &eventResValNames);
 
 private:
-
 	EventManager();
 
-	EventManager(const EventManager&);
+	EventManager(const EventManager &);
 
-	EventManager& operator=(EventManager&);
+	EventManager &operator=(EventManager &);
 
 	~EventManager();
 
 	static void setSupportedEventTypes();
 
-    EventTriggersIter isTriggerExists(EventTrigger *trigger, int videoStreamId);
+	EventTriggersIter isTriggerExists(EventTrigger *trigger, int videoStreamId);
 
 	friend class EventManagerDestroyer;
 
 private:
-
 	static EventManager *__pInstance;
 
 	static EventManagerDestroyer Destroyer;
@@ -182,7 +170,6 @@ private:
 	static EventTypesMap SupportedEventTypes;
 
 private:
-
 	EventTriggersMap __eventTriggers;
 };
 
diff --git a/mv_surveillance/surveillance/include/EventResult.h b/mv_surveillance/surveillance/include/EventResult.h
index 7ce8f45..495100f 100644
--- a/mv_surveillance/surveillance/include/EventResult.h
+++ b/mv_surveillance/surveillance/include/EventResult.h
@@ -22,23 +22,26 @@
  * @brief This file contains interface for event trigger.
  */
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 /**
  * @class    EventResult
  * @brief    This class contains event result interface.
  *
  * @since_tizen 3.0
  */
-class EventResult {
+class EventResult
+{
 public:
 	/**
 	 * @brief Default destructor.
 	 *
 	 * @since_tizen 3.0
 	 */
-	virtual ~EventResult() {}
+	virtual ~EventResult()
+	{}
 
 	/**
 	 * @brief Gets result value.
@@ -52,7 +55,6 @@ public:
 	virtual int getResultValue(const char *valueName, void *value) const = 0;
 };
 
-
 } /* surveillance */
 } /* mediavision */
 
diff --git a/mv_surveillance/surveillance/include/EventTrigger.h b/mv_surveillance/surveillance/include/EventTrigger.h
index f2fbd2d..014a200 100644
--- a/mv_surveillance/surveillance/include/EventTrigger.h
+++ b/mv_surveillance/surveillance/include/EventTrigger.h
@@ -31,16 +31,18 @@
 #include <map>
 #include <list>
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 /**
  * @class    EventTrigger
  * @brief    This class contains event trigger interface.
  *
  * @since_tizen 3.0
  */
-class EventTrigger {
+class EventTrigger
+{
 public:
 	/**
 	 * @brief Default constructor.
@@ -55,15 +57,9 @@ public:
 	 * @param [in] roi               The intput array with ROI points
 	 * @param [in] isInternal        Interpretation event as internal in surveillance
 	 */
-	EventTrigger(
-		mv_surveillance_event_trigger_h eventTrigger,
-		long int triggerId,
-		int videoStreamId,
-		mv_surveillance_event_occurred_cb callback,
-		void *userData,
-		int numberOfPoints,
-		mv_point_s *roi,
-		bool isInternal);
+	EventTrigger(mv_surveillance_event_trigger_h eventTrigger, long int triggerId, int videoStreamId,
+				 mv_surveillance_event_occurred_cb callback, void *userData, int numberOfPoints, mv_point_s *roi,
+				 bool isInternal);
 
 	/**
 	 * @brief Default destructor.
@@ -90,10 +86,7 @@ public:
 	 * @param [in] grayImage     The converted to gray scale source
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	virtual int pushSource(
-					mv_source_h source,
-					mv_source_h graySource,
-					const cv::Mat& grayImage) = 0;
+	virtual int pushSource(mv_source_h source, mv_source_h graySource, const cv::Mat &grayImage) = 0;
 
 	/**
 	 * @brief Gets event type.
@@ -132,14 +125,9 @@ public:
 	 * @param [in] isInternal        Interpretation event as internal in surveillance
 	 * @return @c true on success, false otherwise
 	 */
-	bool subscribeCallback(
-			mv_surveillance_event_trigger_h eventTrigger,
-			long int triggerId,
-			mv_surveillance_event_occurred_cb callback,
-			void *userData,
-			int numberOfPoints,
-			mv_point_s *roi,
-			bool isInternal);
+	bool subscribeCallback(mv_surveillance_event_trigger_h eventTrigger, long int triggerId,
+						   mv_surveillance_event_occurred_cb callback, void *userData, int numberOfPoints,
+						   mv_point_s *roi, bool isInternal);
 
 	/**
 	 * @brief Unsubscibes callback with unique identifier.
@@ -170,13 +158,8 @@ public:
 	 * @param [in] scaleY         The scale for Y ROI point coordinate
 	 * @return @c true on success, false otherwise
 	 */
-	int applyROIToImage(
-			unsigned char *image,
-			int imageWidth,
-			int imageHeight,
-			bool scalePoints = false,
-			int scaleX = 1,
-			int scaleY = 1);
+	int applyROIToImage(unsigned char *image, int imageWidth, int imageHeight, bool scalePoints = false, int scaleX = 1,
+						int scaleY = 1);
 
 	/**
 	 * @brief Comparison operator for equal case.
@@ -184,7 +167,7 @@ public:
 	 * @since_tizen 3.0
 	 * @return true if event trigger is equal to other, false otherwise
 	 */
-	virtual bool operator==(const EventTrigger& other) const;
+	virtual bool operator==(const EventTrigger &other) const;
 
 	/**
 	 * @brief Comparison operator for not equal case.
@@ -192,10 +175,11 @@ public:
 	 * @since_tizen 3.0
 	 * @return true if event trigger is not equal to other, false otherwise
 	 */
-	virtual bool operator!=(const EventTrigger& other) const;
+	virtual bool operator!=(const EventTrigger &other) const;
 
 protected:
-	struct CallbackData {
+	struct CallbackData
+	{
 		mv_surveillance_event_trigger_h eventTrigger;
 
 		mv_surveillance_event_occurred_cb callback;
@@ -222,7 +206,7 @@ protected:
 	CallbackDataMap __callbackDataMap;
 };
 
-typedef std::list<EventTrigger*> EventTriggers;
+typedef std::list<EventTrigger *> EventTriggers;
 typedef std::map<int, EventTriggers> EventTriggersMap;
 typedef EventTriggers::const_iterator EventTriggersConstIter;
 typedef EventTriggers::iterator EventTriggersIter;
diff --git a/mv_surveillance/surveillance/include/EventTriggerMovementDetection.h b/mv_surveillance/surveillance/include/EventTriggerMovementDetection.h
index e775446..f593f68 100644
--- a/mv_surveillance/surveillance/include/EventTriggerMovementDetection.h
+++ b/mv_surveillance/surveillance/include/EventTriggerMovementDetection.h
@@ -27,16 +27,18 @@
 #include "EventResult.h"
 #include "EventDefs.h"
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 /**
  * @class EventResultMovementDetection
  * @brief This class contains movement detection event results.
  *
  * @since_tizen 3.0
  */
-class EventResultMovementDetection : public EventResult {
+class EventResultMovementDetection : public EventResult
+{
 public:
 	/**
 	 * @brief Gets result value.
@@ -61,7 +63,8 @@ public:
  *
  * @since_tizen 3.0
  */
-class EventTriggerMovementDetection : public EventTrigger {
+class EventTriggerMovementDetection : public EventTrigger
+{
 public:
 	/**
 	 * @brief Default constructor.
@@ -76,15 +79,9 @@ public:
 	 * @param [in] roi               The intput array with ROI points
 	 * @param [in] isInternal        Interpretation event as internal in surveillance
 	 */
-	EventTriggerMovementDetection(
-		mv_surveillance_event_trigger_h eventTrigger,
-		long int triggerId,
-		int videoStreamId,
-		mv_surveillance_event_occurred_cb callback,
-		void *userData,
-		int numberOfPoints,
-		mv_point_s *roi,
-		bool isInternal);
+	EventTriggerMovementDetection(mv_surveillance_event_trigger_h eventTrigger, long int triggerId, int videoStreamId,
+								  mv_surveillance_event_occurred_cb callback, void *userData, int numberOfPoints,
+								  mv_point_s *roi, bool isInternal);
 
 	/**
 	 * @brief Default destructor.
@@ -111,10 +108,7 @@ public:
 	 * @param [in] grayImage     The converted to gray scale source
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	virtual int pushSource(
-					mv_source_h source,
-					mv_source_h graySource,
-					const cv::Mat& grayImage);
+	virtual int pushSource(mv_source_h source, mv_source_h graySource, const cv::Mat &grayImage);
 
 	/**
 	 * @brief Gets event type.
diff --git a/mv_surveillance/surveillance/include/EventTriggerPersonAppearance.h b/mv_surveillance/surveillance/include/EventTriggerPersonAppearance.h
index 4355107..3e9d947 100644
--- a/mv_surveillance/surveillance/include/EventTriggerPersonAppearance.h
+++ b/mv_surveillance/surveillance/include/EventTriggerPersonAppearance.h
@@ -33,16 +33,18 @@
 
 #include <sys/time.h>
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 /**
  * @class EventResultPersonAppearance
  * @brief This class contains person appeared / disapeared event results.
  *
  * @since_tizen 3.0
  */
-class EventResultPersonAppearance : public EventResult {
+class EventResultPersonAppearance : public EventResult
+{
 public:
 	/**
 	 * @brief Gets result value.
@@ -72,7 +74,8 @@ public:
  *
  * @since_tizen 3.0
  */
-class EventTriggerPersonAppearance : public EventTrigger {
+class EventTriggerPersonAppearance : public EventTrigger
+{
 public:
 	/**
 	 * @brief Default constructor.
@@ -87,15 +90,9 @@ public:
 	 * @param [in] roi               The intput array with ROI points
 	 * @param [in] isInternal        Interpretation event as internal in surveillance
 	 */
-	EventTriggerPersonAppearance(
-		mv_surveillance_event_trigger_h eventTrigger,
-		long int triggerId,
-		int videoStreamId,
-		mv_surveillance_event_occurred_cb callback,
-		void *userData,
-		int numberOfPoints,
-		mv_point_s *roi,
-		bool isInternal);
+	EventTriggerPersonAppearance(mv_surveillance_event_trigger_h eventTrigger, long int triggerId, int videoStreamId,
+								 mv_surveillance_event_occurred_cb callback, void *userData, int numberOfPoints,
+								 mv_point_s *roi, bool isInternal);
 
 	/**
 	 * @brief Default destructor.
@@ -122,10 +119,7 @@ public:
 	 * @param [in] grayImage     The converted to gray scale source
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	virtual int pushSource(
-					mv_source_h source,
-					mv_source_h graySource,
-					const cv::Mat& grayImage);
+	virtual int pushSource(mv_source_h source, mv_source_h graySource, const cv::Mat &grayImage);
 
 	/**
 	 * @brief Gets event type.
@@ -136,22 +130,17 @@ public:
 	virtual std::string getEventType() const;
 
 private:
-	static void movementDetectedCB(
-		mv_surveillance_event_trigger_h event_trigger,
-		mv_source_h source,
-		int video_stream_id,
-		mv_surveillance_result_h event_result,
-		void *user_data);
+	static void movementDetectedCB(mv_surveillance_event_trigger_h event_trigger, mv_source_h source,
+								   int video_stream_id, mv_surveillance_result_h event_result, void *user_data);
 
 private:
-
 	void runCallbacks(mv_source_h source);
 
-	std::vector<bool> reinforceTrackedPersons(const CVRectangles& appearedPersons);
+	std::vector<bool> reinforceTrackedPersons(const CVRectangles &appearedPersons);
 
 private:
-
-	class TrackedRectangle {
+	class TrackedRectangle
+	{
 	public:
 		TrackedRectangle(cv::Rect _rect, struct timeval _appearanceTime);
 
diff --git a/mv_surveillance/surveillance/include/EventTriggerPersonRecognition.h b/mv_surveillance/surveillance/include/EventTriggerPersonRecognition.h
index bcfce95..57f9aea 100644
--- a/mv_surveillance/surveillance/include/EventTriggerPersonRecognition.h
+++ b/mv_surveillance/surveillance/include/EventTriggerPersonRecognition.h
@@ -31,16 +31,18 @@
 
 #include "EventTriggerPersonAppearance.h"
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 /**
  * @class EventResultPersonRecogniton
  * @brief This class contains person recognized event results.
  *
  * @since_tizen 3.0
  */
-class EventResultPersonRecognition : public EventResult {
+class EventResultPersonRecognition : public EventResult
+{
 public:
 	/**
 	 * @brief Gets result value.
@@ -67,7 +69,8 @@ public:
  *
  * @since_tizen 3.0
  */
-class EventTriggerPersonRecognition : public EventTrigger {
+class EventTriggerPersonRecognition : public EventTrigger
+{
 public:
 	/**
 	 * @brief Default constructor.
@@ -82,15 +85,9 @@ public:
 	 * @param [in] roi               The intput array with ROI points
 	 * @param [in] isInternal        Interpretation event as internal in surveillance
 	 */
-	EventTriggerPersonRecognition(
-		mv_surveillance_event_trigger_h eventTrigger,
-		long int triggerId,
-		int videoStreamId,
-		mv_surveillance_event_occurred_cb callback,
-		void *userData,
-		int numberOfPoints,
-		mv_point_s *roi,
-		bool isInternal);
+	EventTriggerPersonRecognition(mv_surveillance_event_trigger_h eventTrigger, long int triggerId, int videoStreamId,
+								  mv_surveillance_event_occurred_cb callback, void *userData, int numberOfPoints,
+								  mv_point_s *roi, bool isInternal);
 
 	/**
 	 * @brief Default destructor.
@@ -117,10 +114,7 @@ public:
 	 * @param [in] grayImage     The converted to gray scale source
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	virtual int pushSource(
-					mv_source_h source,
-					mv_source_h graySource,
-					const cv::Mat& grayImage);
+	virtual int pushSource(mv_source_h source, mv_source_h graySource, const cv::Mat &grayImage);
 
 	/**
 	 * @brief Gets event type.
@@ -142,10 +136,7 @@ public:
 	 *                             (value from 0.0 to 1.0).
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	void setEventResults(
-		mv_rectangle_s faceLocation,
-		int faceLabel,
-		double confidence);
+	void setEventResults(mv_rectangle_s faceLocation, int faceLabel, double confidence);
 
 private:
 	mv_face_recognition_model_h __faceRecognitionModel;
@@ -155,21 +146,12 @@ private:
 	EventResultPersonRecognition *__eventResult;
 
 private:
-	static void faceDetectedCB(
-					mv_source_h source,
-					mv_engine_config_h engine_cfg,
-					mv_rectangle_s *faces_locations,
-					int number_of_faces,
-					void *user_data);
-
-	static void faceRecognizedCB(
-					mv_source_h source,
-					mv_face_recognition_model_h recognition_model,
-					mv_engine_config_h engine_cfg,
-					mv_rectangle_s *face_location,
-					const int *face_label,
-					double confidence,
-					void *user_data);
+	static void faceDetectedCB(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s *faces_locations,
+							   int number_of_faces, void *user_data);
+
+	static void faceRecognizedCB(mv_source_h source, mv_face_recognition_model_h recognition_model,
+								 mv_engine_config_h engine_cfg, mv_rectangle_s *face_location, const int *face_label,
+								 double confidence, void *user_data);
 };
 
 } /* surveillance */
diff --git a/mv_surveillance/surveillance/include/MFTracker.h b/mv_surveillance/surveillance/include/MFTracker.h
index b93267a..4ca2804 100644
--- a/mv_surveillance/surveillance/include/MFTracker.h
+++ b/mv_surveillance/surveillance/include/MFTracker.h
@@ -20,18 +20,21 @@
 #include <opencv2/core.hpp>
 #include <opencv2/tracking.hpp>
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 /**
  * @class    MFTracker
  * @brief    Median Flow tracker implementation.
  *
  * @since_tizen 3.0
  */
-class MFTracker {
+class MFTracker
+{
 public:
-	struct Params {
+	struct Params
+	{
 		/**
 		 * @brief TrackerMedianFlow algorithm parameters constructor
 		 */
@@ -66,7 +69,7 @@ public:
 	 * @param [out]  result   Result contour
 	 * @return true if object is tracked, otherwise return false
 	 */
-	bool track(const cv::Mat& frame, cv::Rect_<float>& result);
+	bool track(const cv::Mat &frame, cv::Rect_<float> &result);
 
 	/**
 	 * @brief Provides the current location of a target.
@@ -74,60 +77,50 @@ public:
 	 * @since_tizen 3.0
 	 * @param [in] location  Current location of a target
 	 */
-	void reinforcement(const cv::Rect_<float>& location);
+	void reinforcement(const cv::Rect_<float> &location);
 
 private:
 	bool isInited() const;
 
-	bool init(const cv::Mat& image);
+	bool init(const cv::Mat &image);
 
-	bool update(const cv::Mat& image);
+	bool update(const cv::Mat &image);
 
 	float getLastConfidence() const;
 
 	cv::Rect_<float> getLastBoundingBox() const;
 
-	bool medianFlowImpl(cv::Mat oldImage, cv::Mat newImage, cv::Rect_<float>& oldBox);
+	bool medianFlowImpl(cv::Mat oldImage, cv::Mat newImage, cv::Rect_<float> &oldBox);
 
-	cv::Rect_<float> vote(
-		const std::vector<cv::Point2f>& oldPoints,
-		const std::vector<cv::Point2f>& newPoints,
-		const cv::Rect_<float>& oldRect,
-		cv::Point2f& mD);
+	cv::Rect_<float> vote(const std::vector<cv::Point2f> &oldPoints, const std::vector<cv::Point2f> &newPoints,
+						  const cv::Rect_<float> &oldRect, cv::Point2f &mD);
 
-	void check_FB(
-		std::vector<cv::Mat> newPyramid,
-		const std::vector<cv::Point2f>& oldPoints,
-		const std::vector<cv::Point2f>& newPoints,
-		std::vector<bool>& status);
+	void check_FB(std::vector<cv::Mat> newPyramid, const std::vector<cv::Point2f> &oldPoints,
+				  const std::vector<cv::Point2f> &newPoints, std::vector<bool> &status);
 
-	void check_NCC(
-		const cv::Mat& oldImage,
-		const cv::Mat& newImage,
-		const std::vector<cv::Point2f>& oldPoints,
-		const std::vector<cv::Point2f>& newPoints,
-		std::vector<bool>& status);
+	void check_NCC(const cv::Mat &oldImage, const cv::Mat &newImage, const std::vector<cv::Point2f> &oldPoints,
+				   const std::vector<cv::Point2f> &newPoints, std::vector<bool> &status);
 
 private:
-	bool __isInit;                /**< Flag is used to determine the model
+	bool __isInit; /**< Flag is used to determine the model
                                        initialization */
 
-	Params __params;              /**< Parameters used during tracking, see
+	Params __params; /**< Parameters used during tracking, see
                                        @ref TrackerMedianFlow::Params */
 
-	cv::TermCriteria __termcrit;  /**< Terminating criteria for OpenCV
+	cv::TermCriteria __termcrit; /**< Terminating criteria for OpenCV
                                        Lucas–Kanade optical flow algorithm used
                                        during tracking */
 
-	cv::Rect_<float> __boundingBox;  /**< Tracking object bounding box */
+	cv::Rect_<float> __boundingBox; /**< Tracking object bounding box */
 
-	float __confidence;              /**< Confidence that object was tracked
+	float __confidence; /**< Confidence that object was tracked
                                           correctly at the last tracking iteration */
 
-	cv::Mat __image;                 /**< Last image for which tracking was
+	cv::Mat __image; /**< Last image for which tracking was
                                           performed */
 
-	std::vector<cv::Mat> __pyramid;  /**< The pyramid had been calculated for
+	std::vector<cv::Mat> __pyramid; /**< The pyramid had been calculated for
                                           the previous frame(or when
                                           initialize the model) */
 };
diff --git a/mv_surveillance/surveillance/include/SurveillanceHelper.h b/mv_surveillance/surveillance/include/SurveillanceHelper.h
index 62fb5b7..d884805 100644
--- a/mv_surveillance/surveillance/include/SurveillanceHelper.h
+++ b/mv_surveillance/surveillance/include/SurveillanceHelper.h
@@ -26,9 +26,10 @@
 
 #include <opencv2/core.hpp>
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 /**
  * @class    SurveillanceHelper
  * @brief    This class contains surveillance helper interface (common class for
@@ -36,9 +37,9 @@ namespace surveillance {
  *
  * @since_tizen 3.0
  */
-class SurveillanceHelper {
+class SurveillanceHelper
+{
 public:
-
 #ifdef ENABLE_NEON
 	/**
 	 * @brief Converts mediavision source to cv::Mat in gray scale with NEON.
@@ -49,11 +50,10 @@ public:
 	 * @param [out] cvSource    The outut matrix with gray scaled image
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	static int convertSourceMVRGB2GrayCVNeon(mv_source_h mvSource, cv::Mat& cvSource);
+	static int convertSourceMVRGB2GrayCVNeon(mv_source_h mvSource, cv::Mat &cvSource);
 #endif
 };
 
-
 } /* surveillance */
 } /* mediavision */
 
diff --git a/mv_surveillance/surveillance/include/mv_absdiff.h b/mv_surveillance/surveillance/include/mv_absdiff.h
index 1ad0a8a..b6afffa 100644
--- a/mv_surveillance/surveillance/include/mv_absdiff.h
+++ b/mv_surveillance/surveillance/include/mv_absdiff.h
@@ -40,17 +40,11 @@ extern "C" {
  * @retval #MEDIA_VISION_ERROR_NONE Successful
  * @retval #MEDIA_VISION_ERROR_INVALID_PARAMETER Invalid parameter
  */
-int mv_absdiff(
-		uint8_t *__restrict__ src1,
-		uint8_t *__restrict__ src2,
-		int width,
-		int height,
-		int stride,
-		uint8_t *__restrict__ dst);
+int mv_absdiff(uint8_t *__restrict__ src1, uint8_t *__restrict__ src2, int width, int height, int stride,
+			   uint8_t *__restrict__ dst);
 
 #ifdef __cplusplus
 }
 #endif /* __cplusplus */
 
 #endif /* __MEDIA_VISION_MV_ABSDIFF_H__ */
-
diff --git a/mv_surveillance/surveillance/include/mv_apply_mask.h b/mv_surveillance/surveillance/include/mv_apply_mask.h
index a639c03..d45cc42 100644
--- a/mv_surveillance/surveillance/include/mv_apply_mask.h
+++ b/mv_surveillance/surveillance/include/mv_apply_mask.h
@@ -40,17 +40,11 @@ extern "C" {
  * @retval #MEDIA_VISION_ERROR_NONE Successful
  * @retval #MEDIA_VISION_ERROR_INVALID_PARAMETER Invalid parameter
  */
-int mv_apply_mask(
-		uint8_t *src_buffer,
-		uint8_t *__restrict mask,
-		int width,
-		int height,
-		int stride,
-		uint8_t *dst_buffer);
+int mv_apply_mask(uint8_t *src_buffer, uint8_t *__restrict mask, int width, int height, int stride,
+				  uint8_t *dst_buffer);
 
 #ifdef __cplusplus
 }
 #endif /* __cplusplus */
 
 #endif /* __MEDIA_VISION_MV_APPLY_MASK_H__ */
-
diff --git a/mv_surveillance/surveillance/include/mv_mask_buffer.h b/mv_surveillance/surveillance/include/mv_mask_buffer.h
index abc690f..9207316 100644
--- a/mv_surveillance/surveillance/include/mv_mask_buffer.h
+++ b/mv_surveillance/surveillance/include/mv_mask_buffer.h
@@ -40,16 +40,11 @@ extern "C" {
  *
  * @post Free memory for mask_buffer.
  */
-int mv_get_mask_buffer(
-		unsigned int buffer_width,
-		unsigned int buffer_height,
-		mv_point_s *polygon,
-		unsigned int points_number,
-		unsigned char **mask_buffer);
+int mv_get_mask_buffer(unsigned int buffer_width, unsigned int buffer_height, mv_point_s *polygon,
+					   unsigned int points_number, unsigned char **mask_buffer);
 
 #ifdef __cplusplus
 }
 #endif /* __cplusplus */
 
 #endif /* __MEDIA_VISION_MV_MASK_BUFFER_H__ */
-
diff --git a/mv_surveillance/surveillance/include/mv_surveillance_open.h b/mv_surveillance/surveillance/include/mv_surveillance_open.h
index 3f7cfd1..734237a 100644
--- a/mv_surveillance/surveillance/include/mv_surveillance_open.h
+++ b/mv_surveillance/surveillance/include/mv_surveillance_open.h
@@ -55,12 +55,9 @@ extern "C" {
  * @see mv_surveillance_event_trigger_s
  * @see mv_surveillance_unsubscribe_event_trigger_open()
  */
-int mv_surveillance_subscribe_event_trigger_open(
-		mv_surveillance_event_trigger_h event_trigger,
-		int video_stream_id,
-		mv_engine_config_h engine_cfg,
-		mv_surveillance_event_occurred_cb callback,
-		void *user_data);
+int mv_surveillance_subscribe_event_trigger_open(mv_surveillance_event_trigger_h event_trigger, int video_stream_id,
+												 mv_engine_config_h engine_cfg,
+												 mv_surveillance_event_occurred_cb callback, void *user_data);
 
 /**
  * @brief Allows to unsubscribe from the event and stop calling @a callback.
@@ -82,9 +79,7 @@ int mv_surveillance_subscribe_event_trigger_open(
  * @see mv_surveillance_event_trigger_s
  * @see mv_surveillance_subscribe_event_trigger_open()
  */
-int mv_surveillance_unsubscribe_event_trigger_open(
-		mv_surveillance_event_trigger_h event_trigger,
-		int video_stream_id);
+int mv_surveillance_unsubscribe_event_trigger_open(mv_surveillance_event_trigger_h event_trigger, int video_stream_id);
 
 /**
  * @brief Allows to push source to the event trigger and start calling @a callback.
@@ -102,9 +97,7 @@ int mv_surveillance_unsubscribe_event_trigger_open(
  * @see mv_surveillance_subscribe_event_trigger_open()
  * @see mv_surveillance_unsubscribe_event_trigger_open()
  */
-int mv_surveillance_push_source_open(
-		mv_source_h source,
-		int video_stream_id);
+int mv_surveillance_push_source_open(mv_source_h source, int video_stream_id);
 
 /**
  * @brief Starts traversing through list of supported event types.
@@ -125,9 +118,7 @@ int mv_surveillance_push_source_open(
  * @see mv_surveillance_event_type_cb
  * @see mv_surveillance_foreach_event_result_value_name_open()
  */
-int mv_surveillance_foreach_event_type_open(
-		mv_surveillance_event_type_cb callback,
-		void *user_data);
+int mv_surveillance_foreach_event_type_open(mv_surveillance_event_type_cb callback, void *user_data);
 
 /**
  * @brief Starts traversing through list of supported event result value names.
@@ -154,10 +145,9 @@ int mv_surveillance_foreach_event_type_open(
  * @see mv_surveillance_foreach_event_type_open()
  * @see mv_surveillance_get_result_value_open()
  */
-int mv_surveillance_foreach_event_result_value_name_open(
-		const char *event_type,
-		mv_surveillance_event_result_name_cb callback,
-		void *user_data);
+int mv_surveillance_foreach_event_result_value_name_open(const char *event_type,
+														 mv_surveillance_event_result_name_cb callback,
+														 void *user_data);
 
 /**
  * @brief Gets result value.
@@ -182,10 +172,7 @@ int mv_surveillance_foreach_event_result_value_name_open(
  * @see mv_surveillance_unsubscribe_event_trigger_open()
  * @see mv_surveillance_query_events_open()
  */
-int mv_surveillance_get_result_value_open(
-		mv_surveillance_result_h result,
-		const char *value_name,
-		void *value);
+int mv_surveillance_get_result_value_open(mv_surveillance_result_h result, const char *value_name, void *value);
 
 #ifdef __cplusplus
 }
diff --git a/mv_surveillance/surveillance/src/EventManager.cpp b/mv_surveillance/surveillance/src/EventManager.cpp
index d6879f4..4948cf3 100644
--- a/mv_surveillance/surveillance/src/EventManager.cpp
+++ b/mv_surveillance/surveillance/src/EventManager.cpp
@@ -25,9 +25,10 @@
 #include "mv_private.h"
 #include <CommonUtils.h>
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 static const int MAX_VALUE_NAME_LENGTH = 255;
 
 EventManager *EventManager::__pInstance = 0;
@@ -39,14 +40,14 @@ EventManagerDestroyer::~EventManagerDestroyer()
 	delete __pInstance;
 }
 
-void EventManagerDestroyer::initialize(EventManager* pointer)
+void EventManagerDestroyer::initialize(EventManager *pointer)
 {
 	__pInstance = pointer;
 }
 
-EventManager& EventManager::getInstance()
+EventManager &EventManager::getInstance()
 {
-	if(!__pInstance) {
+	if (!__pInstance) {
 		__pInstance = new EventManager();
 		Destroyer.initialize(__pInstance);
 		setSupportedEventTypes();
@@ -58,32 +59,31 @@ EventManager& EventManager::getInstance()
 void EventManager::setSupportedEventTypes()
 {
 	/* Add supported event types here */
-	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED]
-		.push_back(MV_SURVEILLANCE_MOVEMENT_NUMBER_OF_REGIONS);
-	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED]
-		.push_back(MV_SURVEILLANCE_MOVEMENT_REGIONS);
-
-	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED]
-		.push_back(MV_SURVEILLANCE_PERSONS_APPEARED_NUMBER);
-	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED]
-		.push_back(MV_SURVEILLANCE_PERSONS_DISAPPEARED_NUMBER);
-	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED]
-		.push_back(MV_SURVEILLANCE_PERSONS_TRACKED_NUMBER);
-	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED]
-		.push_back(MV_SURVEILLANCE_PERSONS_APPEARED_LOCATIONS);
-	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED]
-		.push_back(MV_SURVEILLANCE_PERSONS_DISAPPEARED_LOCATIONS);
-	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED]
-		.push_back(MV_SURVEILLANCE_PERSONS_TRACKED_LOCATIONS);
-
-	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED]
-		.push_back(MV_SURVEILLANCE_PERSONS_RECOGNIZED_NUMBER);
-	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED]
-		.push_back(MV_SURVEILLANCE_PERSONS_RECOGNIZED_LOCATIONS);
-	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED]
-		.push_back(MV_SURVEILLANCE_PERSONS_RECOGNIZED_LABELS);
-	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED]
-		.push_back(MV_SURVEILLANCE_PERSONS_RECOGNIZED_CONFIDENCES);
+	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED].push_back(
+			MV_SURVEILLANCE_MOVEMENT_NUMBER_OF_REGIONS);
+	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED].push_back(MV_SURVEILLANCE_MOVEMENT_REGIONS);
+
+	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED].push_back(
+			MV_SURVEILLANCE_PERSONS_APPEARED_NUMBER);
+	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED].push_back(
+			MV_SURVEILLANCE_PERSONS_DISAPPEARED_NUMBER);
+	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED].push_back(
+			MV_SURVEILLANCE_PERSONS_TRACKED_NUMBER);
+	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED].push_back(
+			MV_SURVEILLANCE_PERSONS_APPEARED_LOCATIONS);
+	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED].push_back(
+			MV_SURVEILLANCE_PERSONS_DISAPPEARED_LOCATIONS);
+	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED].push_back(
+			MV_SURVEILLANCE_PERSONS_TRACKED_LOCATIONS);
+
+	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED].push_back(
+			MV_SURVEILLANCE_PERSONS_RECOGNIZED_NUMBER);
+	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED].push_back(
+			MV_SURVEILLANCE_PERSONS_RECOGNIZED_LOCATIONS);
+	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED].push_back(
+			MV_SURVEILLANCE_PERSONS_RECOGNIZED_LABELS);
+	SupportedEventTypes[MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED].push_back(
+			MV_SURVEILLANCE_PERSONS_RECOGNIZED_CONFIDENCES);
 }
 
 EventManager::EventManager()
@@ -96,17 +96,10 @@ EventManager::~EventManager()
 	; /* NULL */
 }
 
-int EventManager::registerEvent(
-					mv_surveillance_event_trigger_h eventTrigger,
-					long int triggerId,
-					const char *eventType,
-					int videoStreamId,
-					mv_engine_config_h engineCfg,
-					mv_surveillance_event_occurred_cb callback,
-					void *user_data,
-					int numberOfPoints,
-					mv_point_s *roi,
-					bool isInternal)
+int EventManager::registerEvent(mv_surveillance_event_trigger_h eventTrigger, long int triggerId, const char *eventType,
+								int videoStreamId, mv_engine_config_h engineCfg,
+								mv_surveillance_event_occurred_cb callback, void *user_data, int numberOfPoints,
+								mv_point_s *roi, bool isInternal)
 {
 	if (NULL == callback || NULL == eventType) {
 		LOGE("Input event trigger or callback is NULL. Event registering failed.");
@@ -118,24 +111,16 @@ int EventManager::registerEvent(
 	for (; iter != __eventTriggers[videoStreamId].end(); ++iter) {
 		if ((*iter)->isCallbackSubscribed(triggerId)) {
 			LOGE("Callback with id %ld is already subscribed. "
-					"Event registering failed.", triggerId);
+				 "Event registering failed.",
+				 triggerId);
 			return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 		}
 	}
 
 	/* Add appropriate event trigger here */
-	if (strncmp(eventType, MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED,
-				MAX_VALUE_NAME_LENGTH) == 0) {
-		EventTriggerPersonAppearance* trigger =
-			new EventTriggerPersonAppearance(
-					eventTrigger,
-					triggerId,
-					videoStreamId,
-					callback,
-					user_data,
-					numberOfPoints,
-					roi,
-					isInternal);
+	if (strncmp(eventType, MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED, MAX_VALUE_NAME_LENGTH) == 0) {
+		EventTriggerPersonAppearance *trigger = new EventTriggerPersonAppearance(
+				eventTrigger, triggerId, videoStreamId, callback, user_data, numberOfPoints, roi, isInternal);
 		const int error = trigger->parseEngineConfig(engineCfg);
 
 		if (error != MEDIA_VISION_ERROR_NONE) {
@@ -148,31 +133,15 @@ int EventManager::registerEvent(
 		EventTriggersIter iter2 = isTriggerExists(trigger, videoStreamId);
 
 		if (iter2 != __eventTriggers[videoStreamId].end()) {
-			(*iter2)->subscribeCallback(
-						eventTrigger,
-						triggerId,
-						callback,
-						user_data,
-						numberOfPoints,
-						roi,
-						isInternal);
-
-						delete trigger;
+			(*iter2)->subscribeCallback(eventTrigger, triggerId, callback, user_data, numberOfPoints, roi, isInternal);
+
+			delete trigger;
 		} else {
 			__eventTriggers[videoStreamId].push_back(trigger);
 		}
-	} else if (strncmp(eventType, MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED,
-						MAX_VALUE_NAME_LENGTH) == 0) {
-		EventTriggerPersonRecognition* trigger =
-						new EventTriggerPersonRecognition(
-										eventTrigger,
-										triggerId,
-										videoStreamId,
-										callback,
-										user_data,
-										numberOfPoints,
-										roi,
-										isInternal);
+	} else if (strncmp(eventType, MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED, MAX_VALUE_NAME_LENGTH) == 0) {
+		EventTriggerPersonRecognition *trigger = new EventTriggerPersonRecognition(
+				eventTrigger, triggerId, videoStreamId, callback, user_data, numberOfPoints, roi, isInternal);
 
 		const int error = trigger->parseEngineConfig(engineCfg);
 		if (error != MEDIA_VISION_ERROR_NONE) {
@@ -185,31 +154,15 @@ int EventManager::registerEvent(
 		EventTriggersIter iter2 = isTriggerExists(trigger, videoStreamId);
 
 		if (iter2 != __eventTriggers[videoStreamId].end()) {
-			(*iter2)->subscribeCallback(
-						eventTrigger,
-						triggerId,
-						callback,
-						user_data,
-						numberOfPoints,
-						roi,
-						isInternal);
+			(*iter2)->subscribeCallback(eventTrigger, triggerId, callback, user_data, numberOfPoints, roi, isInternal);
 
 			delete trigger;
 		} else {
 			__eventTriggers[videoStreamId].push_back(trigger);
 		}
-	} else if (strncmp(eventType, MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED,
-				MAX_VALUE_NAME_LENGTH) == 0) {
-			EventTriggerMovementDetection* trigger =
-						new EventTriggerMovementDetection(
-									eventTrigger,
-									triggerId,
-									videoStreamId,
-									callback,
-									user_data,
-									numberOfPoints,
-									roi,
-									isInternal);
+	} else if (strncmp(eventType, MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED, MAX_VALUE_NAME_LENGTH) == 0) {
+		EventTriggerMovementDetection *trigger = new EventTriggerMovementDetection(
+				eventTrigger, triggerId, videoStreamId, callback, user_data, numberOfPoints, roi, isInternal);
 
 		const int error = trigger->parseEngineConfig(engineCfg);
 
@@ -223,14 +176,7 @@ int EventManager::registerEvent(
 		EventTriggersIter iter2 = isTriggerExists(trigger, videoStreamId);
 
 		if (iter2 != __eventTriggers[videoStreamId].end()) {
-			(*iter2)->subscribeCallback(
-						eventTrigger,
-						triggerId,
-						callback,
-						user_data,
-						numberOfPoints,
-						roi,
-						isInternal);
+			(*iter2)->subscribeCallback(eventTrigger, triggerId, callback, user_data, numberOfPoints, roi, isInternal);
 
 			delete trigger;
 		} else {
@@ -285,12 +231,9 @@ int EventManager::pushSource(mv_source_h source, int videoStreamId)
 	unsigned int height = 0;
 	mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
 
-	MEDIA_VISION_ASSERT(mv_source_get_width(source, &width),
-						"Failed to get the width.");
-	MEDIA_VISION_ASSERT(mv_source_get_height(source, &height),
-						"Failed to get the height.");
-	MEDIA_VISION_ASSERT(mv_source_get_colorspace(source, &colorspace),
-						"Failed to get the colorspace.");
+	MEDIA_VISION_ASSERT(mv_source_get_width(source, &width), "Failed to get the width.");
+	MEDIA_VISION_ASSERT(mv_source_get_height(source, &height), "Failed to get the height.");
+	MEDIA_VISION_ASSERT(mv_source_get_colorspace(source, &colorspace), "Failed to get the colorspace.");
 
 	cv::Mat grayImage;
 
@@ -315,13 +258,8 @@ int EventManager::pushSource(mv_source_h source, int videoStreamId)
 		return error;
 	}
 
-	error = mv_source_fill_by_buffer(
-				graySource,
-				grayImage.data,
-				grayImage.cols * grayImage.rows,
-				grayImage.cols,
-				grayImage.rows,
-				MEDIA_VISION_COLORSPACE_Y800);
+	error = mv_source_fill_by_buffer(graySource, grayImage.data, grayImage.cols * grayImage.rows, grayImage.cols,
+									 grayImage.rows, MEDIA_VISION_COLORSPACE_Y800);
 
 	if (MEDIA_VISION_ERROR_NONE != error) {
 		mv_destroy_source(graySource);
@@ -346,7 +284,7 @@ int EventManager::pushSource(mv_source_h source, int videoStreamId)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int EventManager::getSupportedEventTypes(StringVector& eventTypes)
+int EventManager::getSupportedEventTypes(StringVector &eventTypes)
 {
 	eventTypes.clear();
 
@@ -363,8 +301,7 @@ int EventManager::getSupportedEventTypes(StringVector& eventTypes)
 }
 
 // LCOV_EXCL_START
-int EventManager::getSupportedEventResultValueNames(
-	StringVector& eventResValNames)
+int EventManager::getSupportedEventResultValueNames(StringVector &eventResValNames)
 {
 	eventResValNames.clear();
 
@@ -373,10 +310,7 @@ int EventManager::getSupportedEventResultValueNames(
 
 	EventTypesMapConstIter etIter = SupportedEventTypes.begin();
 	while (etIter != SupportedEventTypes.end()) {
-		eventResValNames.insert(
-					eventResValNames.end(),
-					etIter->second.begin(),
-					etIter->second.end());
+		eventResValNames.insert(eventResValNames.end(), etIter->second.begin(), etIter->second.end());
 		++etIter;
 	}
 
@@ -384,9 +318,7 @@ int EventManager::getSupportedEventResultValueNames(
 }
 // LCOV_EXCL_STOP
 
-int EventManager::getSupportedEventResultValueNames(
-	const std::string& eventTypeName,
-	StringVector& eventResValNames)
+int EventManager::getSupportedEventResultValueNames(const std::string &eventTypeName, StringVector &eventResValNames)
 {
 	eventResValNames.clear();
 
@@ -402,9 +334,7 @@ int EventManager::getSupportedEventResultValueNames(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-EventTriggersIter EventManager::isTriggerExists(
-		EventTrigger* trigger,
-		int videoStreamId)
+EventTriggersIter EventManager::isTriggerExists(EventTrigger *trigger, int videoStreamId)
 {
 	EventTriggersIter iter = __eventTriggers[videoStreamId].begin();
 
@@ -417,4 +347,3 @@ EventTriggersIter EventManager::isTriggerExists(
 
 } /* surveillance */
 } /* mediavision */
-
diff --git a/mv_surveillance/surveillance/src/EventTrigger.cpp b/mv_surveillance/surveillance/src/EventTrigger.cpp
index e9968fc..94642de 100644
--- a/mv_surveillance/surveillance/src/EventTrigger.cpp
+++ b/mv_surveillance/surveillance/src/EventTrigger.cpp
@@ -20,22 +20,16 @@
 #include <mv_mask_buffer.h>
 #include <mv_apply_mask.h>
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 long int EventTrigger::InternalTriggersCounter = -1l;
 
-EventTrigger::EventTrigger(
-		mv_surveillance_event_trigger_h eventTrigger,
-		long int triggerId,
-		int videoStreamId,
-		mv_surveillance_event_occurred_cb callback,
-		void *userData,
-		int numberOfPoints,
-		mv_point_s *roi,
-		bool isInternal):
-	__videoStreamId(videoStreamId),
-	__roi(numberOfPoints)
+EventTrigger::EventTrigger(mv_surveillance_event_trigger_h eventTrigger, long int triggerId, int videoStreamId,
+						   mv_surveillance_event_occurred_cb callback, void *userData, int numberOfPoints,
+						   mv_point_s *roi, bool isInternal)
+		: __videoStreamId(videoStreamId), __roi(numberOfPoints)
 {
 	CallbackData callbackData;
 	callbackData.eventTrigger = eventTrigger;
@@ -64,18 +58,14 @@ bool EventTrigger::isCallbackSubscribed(long int triggerId) const
 	return __callbackDataMap.find(triggerId) != __callbackDataMap.end();
 }
 
-bool EventTrigger::subscribeCallback(
-		mv_surveillance_event_trigger_h eventTrigger,
-		long int triggerId,
-		mv_surveillance_event_occurred_cb callback,
-		void *userData,
-		int numberOfPoints,
-		mv_point_s *roi,
-		bool isInternal)
+bool EventTrigger::subscribeCallback(mv_surveillance_event_trigger_h eventTrigger, long int triggerId,
+									 mv_surveillance_event_occurred_cb callback, void *userData, int numberOfPoints,
+									 mv_point_s *roi, bool isInternal)
 {
 	if (isCallbackSubscribed(triggerId)) {
 		LOGE("Callback with id %ld is already subscribed. "
-			"Callback subscribing failed.", triggerId);
+			 "Callback subscribing failed.",
+			 triggerId);
 		return false;
 	}
 
@@ -103,7 +93,8 @@ bool EventTrigger::unsubscribeCallback(long int triggerId)
 
 	if (iter == __callbackDataMap.end()) {
 		LOGE("Callback with id %ld was not subscribed. "
-			"Callback unsubscribing failed.", triggerId);
+			 "Callback unsubscribing failed.",
+			 triggerId);
 		return false;
 	}
 
@@ -120,13 +111,8 @@ bool EventTrigger::isCallbacksEmpty() const
 }
 
 // LCOV_EXCL_START
-int EventTrigger::applyROIToImage(
-					unsigned char *image,
-					int imageWidth,
-					int imageHeight,
-					bool scalePoints,
-					int scaleX,
-					int scaleY)
+int EventTrigger::applyROIToImage(unsigned char *image, int imageWidth, int imageHeight, bool scalePoints, int scaleX,
+								  int scaleY)
 {
 	const size_t roiSize = __roi.size();
 
@@ -141,12 +127,7 @@ int EventTrigger::applyROIToImage(
 
 		unsigned char *maskBuffer = NULL;
 
-		int error = mv_get_mask_buffer(
-						imageWidth,
-						imageHeight,
-						scaledPoints.data(),
-						(int) roiSize,
-						&maskBuffer);
+		int error = mv_get_mask_buffer(imageWidth, imageHeight, scaledPoints.data(), (int) roiSize, &maskBuffer);
 
 		if (error != MEDIA_VISION_ERROR_NONE || maskBuffer == NULL) {
 			if (maskBuffer != NULL) {
@@ -158,13 +139,7 @@ int EventTrigger::applyROIToImage(
 			return error;
 		}
 
-		error = mv_apply_mask(
-					image,
-					maskBuffer,
-					imageWidth / 16 * 16,
-					imageHeight,
-					imageWidth,
-					image);
+		error = mv_apply_mask(image, maskBuffer, imageWidth / 16 * 16, imageHeight, imageWidth, image);
 
 		free(maskBuffer);
 		maskBuffer = NULL;
@@ -179,14 +154,13 @@ int EventTrigger::applyROIToImage(
 }
 // LCOV_EXCL_STOP
 
-bool EventTrigger::operator==(const EventTrigger& other) const
+bool EventTrigger::operator==(const EventTrigger &other) const
 {
 	const std::string currentEventType = this->getEventType();
 	const std::string otherEventType = other.getEventType();
 
-	if (__videoStreamId != other.__videoStreamId ||
-			currentEventType.compare(otherEventType) != 0 ||
-			__roi.size() != other.__roi.size())
+	if (__videoStreamId != other.__videoStreamId || currentEventType.compare(otherEventType) != 0 ||
+		__roi.size() != other.__roi.size())
 		return false;
 
 	size_t size = __roi.size();
@@ -197,7 +171,7 @@ bool EventTrigger::operator==(const EventTrigger& other) const
 	return true;
 }
 
-bool EventTrigger::operator!=(const EventTrigger& other) const
+bool EventTrigger::operator!=(const EventTrigger &other) const
 {
 	return !(*this == other);
 }
diff --git a/mv_surveillance/surveillance/src/EventTriggerMovementDetection.cpp b/mv_surveillance/surveillance/src/EventTriggerMovementDetection.cpp
index 72c387b..d880e8c 100644
--- a/mv_surveillance/surveillance/src/EventTriggerMovementDetection.cpp
+++ b/mv_surveillance/surveillance/src/EventTriggerMovementDetection.cpp
@@ -25,24 +25,24 @@
 #include "opencv2/highgui.hpp"
 #include "opencv2/imgproc/imgproc_c.h"
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 static const int DEFAULT_DIFF_THRESHOLD = 10;
 
 static const int MAX_VALUE_NAME_LENGTH = 255;
 
-const cv::Mat EventTriggerMovementDetection::__ERODE_KERNEL =
-	cv::getStructuringElement(cv::MORPH_RECT, cv::Size(4, 4));
+const cv::Mat EventTriggerMovementDetection::__ERODE_KERNEL = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(4, 4));
 
 const cv::Mat EventTriggerMovementDetection::__DILATE_KERNEL =
-	cv::getStructuringElement(cv::MORPH_RECT, cv::Size(24, 24));
+		cv::getStructuringElement(cv::MORPH_RECT, cv::Size(24, 24));
 
 static const cv::Rect DEFAULT_RECT = cv::Rect(0, 0, 0, 0);
 
-namespace {
-
-inline void convertRectCV2MV(const cv::Rect& src, mv_rectangle_s& dst)
+namespace
+{
+inline void convertRectCV2MV(const cv::Rect &src, mv_rectangle_s &dst)
 {
 	dst.point.x = src.x;
 	dst.point.y = src.y;
@@ -50,7 +50,7 @@ inline void convertRectCV2MV(const cv::Rect& src, mv_rectangle_s& dst)
 	dst.height = src.height;
 }
 
-void mergeOverlappedRects(CVRectangles& rects)
+void mergeOverlappedRects(CVRectangles &rects)
 {
 	const size_t rectsSize = rects.size();
 
@@ -61,8 +61,7 @@ void mergeOverlappedRects(CVRectangles& rects)
 			const int area2 = rects[j].area();
 			const int intersectionArea = (rects[i] & rects[j]).area();
 
-			if (intersectionArea != 0 &&
-				intersectionArea > std::min(area1, area2) / 2) {
+			if (intersectionArea != 0 && intersectionArea > std::min(area1, area2) / 2) {
 				rects[j] |= rects[i];
 				rects[i] = DEFAULT_RECT;
 				break;
@@ -73,9 +72,7 @@ void mergeOverlappedRects(CVRectangles& rects)
 
 } /* anonymous namespace */
 
-int EventResultMovementDetection::getResultValue(
-	const char *valueName,
-	void *value) const
+int EventResultMovementDetection::getResultValue(const char *valueName, void *value) const
 {
 	if (valueName == NULL) {
 		LOGE("Invalid pointer for value name. Getting result value failed.");
@@ -87,13 +84,11 @@ int EventResultMovementDetection::getResultValue(
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	if (strncmp(valueName, MV_SURVEILLANCE_MOVEMENT_NUMBER_OF_REGIONS,
-				MAX_VALUE_NAME_LENGTH) == 0) {
-		size_t *const numberOfDetectedMovements = (size_t*) value;
+	if (strncmp(valueName, MV_SURVEILLANCE_MOVEMENT_NUMBER_OF_REGIONS, MAX_VALUE_NAME_LENGTH) == 0) {
+		size_t *const numberOfDetectedMovements = (size_t *) value;
 		*numberOfDetectedMovements = __movementRegions.size();
-	} else if (strncmp(valueName, MV_SURVEILLANCE_MOVEMENT_REGIONS,
-				MAX_VALUE_NAME_LENGTH) == 0) {
-		mv_rectangle_s *const movementsRegions = (mv_rectangle_s*) value;
+	} else if (strncmp(valueName, MV_SURVEILLANCE_MOVEMENT_REGIONS, MAX_VALUE_NAME_LENGTH) == 0) {
+		mv_rectangle_s *const movementsRegions = (mv_rectangle_s *) value;
 
 		const size_t numberOfDetectedMovements = __movementRegions.size();
 
@@ -108,26 +103,14 @@ int EventResultMovementDetection::getResultValue(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-EventTriggerMovementDetection::EventTriggerMovementDetection(
-		mv_surveillance_event_trigger_h eventTrigger,
-		long int triggerId,
-		int videoStreamId,
-		mv_surveillance_event_occurred_cb callback,
-		void *userData,
-		int numberOfPoints,
-		mv_point_s *roi,
-		bool isInternal) : EventTrigger(
-								eventTrigger,
-								triggerId,
-								videoStreamId,
-								callback,
-								userData,
-								numberOfPoints,
-								roi,
-								isInternal),
-		__previousImage(),
-		__eventResult(new EventResultMovementDetection()),
-		__diffThreshold(DEFAULT_DIFF_THRESHOLD)
+EventTriggerMovementDetection::EventTriggerMovementDetection(mv_surveillance_event_trigger_h eventTrigger,
+															 long int triggerId, int videoStreamId,
+															 mv_surveillance_event_occurred_cb callback, void *userData,
+															 int numberOfPoints, mv_point_s *roi, bool isInternal)
+		: EventTrigger(eventTrigger, triggerId, videoStreamId, callback, userData, numberOfPoints, roi, isInternal)
+		, __previousImage()
+		, __eventResult(new EventResultMovementDetection())
+		, __diffThreshold(DEFAULT_DIFF_THRESHOLD)
 {
 	; /* NULL */
 }
@@ -144,10 +127,8 @@ int EventTriggerMovementDetection::parseEngineConfig(mv_engine_config_h engineCo
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	const int error = mv_engine_config_get_int_attribute(
-			engineConfig,
-			MV_SURVEILLANCE_MOVEMENT_DETECTION_THRESHOLD,
-			&__diffThreshold);
+	const int error = mv_engine_config_get_int_attribute(engineConfig, MV_SURVEILLANCE_MOVEMENT_DETECTION_THRESHOLD,
+														 &__diffThreshold);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Getting movement detection threshold from engine configuration failed.");
@@ -157,10 +138,7 @@ int EventTriggerMovementDetection::parseEngineConfig(mv_engine_config_h engineCo
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int EventTriggerMovementDetection::pushSource(
-		mv_source_h source,
-		mv_source_h graySource,
-		const cv::Mat& grayImage)
+int EventTriggerMovementDetection::pushSource(mv_source_h source, mv_source_h graySource, const cv::Mat &grayImage)
 {
 	if (source == NULL || graySource == NULL || grayImage.empty()) {
 		LOGE("Media source is NULL. Pushing source failed.");
@@ -181,18 +159,12 @@ int EventTriggerMovementDetection::pushSource(
 	cv::Mat image = grayImage.clone();
 
 	const int bufSize = image.cols * image.rows * sizeof(uint8_t);
-	uint8_t *diffBuffer = (uint8_t*) malloc(bufSize * sizeof(uint8_t));
+	uint8_t *diffBuffer = (uint8_t *) malloc(bufSize * sizeof(uint8_t));
 	if (diffBuffer != NULL) {
 		memset(diffBuffer, 0, bufSize);
 	}
 
-	error = mv_absdiff(
-			image.data,
-			__previousImage.data,
-			image.cols,
-			image.rows,
-			image.cols,
-			diffBuffer);
+	error = mv_absdiff(image.data, __previousImage.data, image.cols, image.rows, image.cols, diffBuffer);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		free(diffBuffer);
@@ -208,8 +180,7 @@ int EventTriggerMovementDetection::pushSource(
 		return error;
 	}
 
-	cv::Mat imgDiff = cv::Mat(cv::Size(image.cols, image.rows),
-			CV_8UC1, diffBuffer);
+	cv::Mat imgDiff = cv::Mat(cv::Size(image.cols, image.rows), CV_8UC1, diffBuffer);
 
 	cv::erode(imgDiff, imgDiff, __ERODE_KERNEL);
 	cv::dilate(imgDiff, imgDiff, __DILATE_KERNEL);
@@ -250,12 +221,7 @@ int EventTriggerMovementDetection::pushSource(
 		mv_surveillance_event_occurred_cb callback = iter->second.callback;
 
 		if (__eventResult->__movementRegions.size() > 0 || iter->second.isInternal)
-			callback(
-				iter->second.eventTrigger,
-				source,
-				__videoStreamId,
-				__eventResult,
-				iter->second.userData);
+			callback(iter->second.eventTrigger, source, __videoStreamId, __eventResult, iter->second.userData);
 	}
 
 	return MEDIA_VISION_ERROR_NONE;
diff --git a/mv_surveillance/surveillance/src/EventTriggerPersonAppearance.cpp b/mv_surveillance/surveillance/src/EventTriggerPersonAppearance.cpp
index bcd9f31..e8781e9 100644
--- a/mv_surveillance/surveillance/src/EventTriggerPersonAppearance.cpp
+++ b/mv_surveillance/surveillance/src/EventTriggerPersonAppearance.cpp
@@ -27,9 +27,10 @@
 #include <sys/time.h>
 #include <unistd.h>
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 // LCOV_EXCL_START
 using namespace cv;
 
@@ -55,26 +56,25 @@ static const float MINIMAL_INTERSECTION = 0.1f;
 
 static const float TRACKING_MARGIN = 0.2f;
 
-static const std::vector<float> DEFAULT_SVM_PEOPLE_DETECTOR =
-		cv::HOGDescriptor::getDefaultPeopleDetector();
-
-namespace {
+static const std::vector<float> DEFAULT_SVM_PEOPLE_DETECTOR = cv::HOGDescriptor::getDefaultPeopleDetector();
 
+namespace
+{
 cv::Rect operator&(cv::Rect r1, cv::Rect_<float> r2)
 {
-	cv::Rect r2int((int)r2.x, (int)r2.y, (int)r2.width, (int)r2.height);
+	cv::Rect r2int((int) r2.x, (int) r2.y, (int) r2.width, (int) r2.height);
 
 	return r1 & r2int;
 }
 
 cv::Rect operator|=(cv::Rect r1, cv::Rect_<float> r2)
 {
-	cv::Rect r2int((int)r2.x, (int)r2.y, (int)r2.width, (int)r2.height);
+	cv::Rect r2int((int) r2.x, (int) r2.y, (int) r2.width, (int) r2.height);
 
 	return r1 |= r2int;
 }
 
-cv::Rect_<float> cutRectForTracking(const cv::Rect_<float>& rect)
+cv::Rect_<float> cutRectForTracking(const cv::Rect_<float> &rect)
 {
 	cv::Rect_<float> res;
 
@@ -89,7 +89,7 @@ cv::Rect_<float> cutRectForTracking(const cv::Rect_<float>& rect)
 	return res;
 }
 
-cv::Rect_<float> supplementRectAfterTracking(const cv::Rect_<float>& rect)
+cv::Rect_<float> supplementRectAfterTracking(const cv::Rect_<float> &rect)
 {
 	cv::Rect_<float> res;
 
@@ -101,28 +101,26 @@ cv::Rect_<float> supplementRectAfterTracking(const cv::Rect_<float>& rect)
 	return res;
 }
 
-float sizeDifferenceFactor(const cv::Rect& r1, const cv::Rect& r2)
+float sizeDifferenceFactor(const cv::Rect &r1, const cv::Rect &r2)
 {
-	float widthDiffFactor = r1.width / (float)r2.width;
-	float heightDiffFactor = r1.height / (float)r2.height;
+	float widthDiffFactor = r1.width / (float) r2.width;
+	float heightDiffFactor = r1.height / (float) r2.height;
 
 	if (widthDiffFactor > 1.f)
 		widthDiffFactor = 1.f / widthDiffFactor;
 	if (heightDiffFactor > 1.f)
 		heightDiffFactor = 1.f / heightDiffFactor;
 
-	return widthDiffFactor * heightDiffFactor *
-			(1.f - fabs(widthDiffFactor - heightDiffFactor));
+	return widthDiffFactor * heightDiffFactor * (1.f - fabs(widthDiffFactor - heightDiffFactor));
 }
 
-bool isPossibleToMerge(const cv::Rect& r1, const cv::Rect& r2)
+bool isPossibleToMerge(const cv::Rect &r1, const cv::Rect &r2)
 {
 	return sizeDifferenceFactor(r1, r2) > POSSIBLE_SIZE_DIFFERENCE &&
-			((r1.area() + r2.area()) * MINIMAL_INTERSECTION / 2.f) <
-			(r1 & r2).area();
+		   ((r1.area() + r2.area()) * MINIMAL_INTERSECTION / 2.f) < (r1 & r2).area();
 }
 
-inline void convertRectMV2CV(const mv_rectangle_s& src, cv::Rect& dst)
+inline void convertRectMV2CV(const mv_rectangle_s &src, cv::Rect &dst)
 {
 	dst.x = src.point.x;
 	dst.y = src.point.y;
@@ -130,7 +128,7 @@ inline void convertRectMV2CV(const mv_rectangle_s& src, cv::Rect& dst)
 	dst.height = src.height;
 }
 
-inline void convertRectCV2MV(const cv::Rect& src, mv_rectangle_s& dst)
+inline void convertRectCV2MV(const cv::Rect &src, mv_rectangle_s &dst)
 {
 	dst.point.x = src.x;
 	dst.point.y = src.y;
@@ -140,16 +138,14 @@ inline void convertRectCV2MV(const cv::Rect& src, mv_rectangle_s& dst)
 
 } /* Anonymous namespace*/
 
-EventTriggerPersonAppearance::TrackedRectangle::TrackedRectangle(cv::Rect _rect,
-		struct timeval _appearanceTime)
+EventTriggerPersonAppearance::TrackedRectangle::TrackedRectangle(cv::Rect _rect, struct timeval _appearanceTime)
 {
 	rect = _rect;
 	appearanceTime = _appearanceTime;
 	tracker.reinforcement(cutRectForTracking(rect));
 }
 
-int EventResultPersonAppearance::getResultValue(const char *valueName,
-		void *value) const
+int EventResultPersonAppearance::getResultValue(const char *valueName, void *value) const
 {
 	if (valueName == NULL) {
 		LOGE("Invalid pointer for value name. Getting result value failed.");
@@ -161,37 +157,31 @@ int EventResultPersonAppearance::getResultValue(const char *valueName,
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_APPEARED_NUMBER,
-			MAX_VALUE_NAME_LENGHT) == 0) {
-		size_t * const numberOfAppearedPersons = (size_t*) value;
+	if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_APPEARED_NUMBER, MAX_VALUE_NAME_LENGHT) == 0) {
+		size_t *const numberOfAppearedPersons = (size_t *) value;
 		*numberOfAppearedPersons = __appearedLocations.size();
-	} else if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_APPEARED_LOCATIONS,
-			MAX_VALUE_NAME_LENGHT) == 0) {
-		mv_rectangle_s * const appearedLocations = (mv_rectangle_s*) value;
+	} else if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_APPEARED_LOCATIONS, MAX_VALUE_NAME_LENGHT) == 0) {
+		mv_rectangle_s *const appearedLocations = (mv_rectangle_s *) value;
 
 		const size_t numberOfAppearedPersons = __appearedLocations.size();
 
 		for (size_t i = 0u; i < numberOfAppearedPersons; ++i)
 			appearedLocations[i] = __appearedLocations[i];
-	} else if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_TRACKED_NUMBER,
-			MAX_VALUE_NAME_LENGHT) == 0) {
-		size_t * const numberOfTrackedPersons = (size_t*) value;
+	} else if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_TRACKED_NUMBER, MAX_VALUE_NAME_LENGHT) == 0) {
+		size_t *const numberOfTrackedPersons = (size_t *) value;
 		*numberOfTrackedPersons = __trackedLocations.size();
-	} else if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_TRACKED_LOCATIONS,
-			MAX_VALUE_NAME_LENGHT) == 0) {
-		mv_rectangle_s * const trackedLocations = (mv_rectangle_s*) value;
+	} else if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_TRACKED_LOCATIONS, MAX_VALUE_NAME_LENGHT) == 0) {
+		mv_rectangle_s *const trackedLocations = (mv_rectangle_s *) value;
 
 		const size_t numberOfTrackedPersons = __trackedLocations.size();
 
 		for (size_t i = 0u; i < numberOfTrackedPersons; ++i)
 			trackedLocations[i] = __trackedLocations[i];
-	} else if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_DISAPPEARED_NUMBER,
-			MAX_VALUE_NAME_LENGHT) == 0) {
-		size_t * const numberOfDisappearedPersons = (size_t*) value;
+	} else if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_DISAPPEARED_NUMBER, MAX_VALUE_NAME_LENGHT) == 0) {
+		size_t *const numberOfDisappearedPersons = (size_t *) value;
 		*numberOfDisappearedPersons = __disappearedLocations.size();
-	} else if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_DISAPPEARED_LOCATIONS,
-			MAX_VALUE_NAME_LENGHT) == 0) {
-		mv_rectangle_s * const disappearedLocations = (mv_rectangle_s*) value;
+	} else if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_DISAPPEARED_LOCATIONS, MAX_VALUE_NAME_LENGHT) == 0) {
+		mv_rectangle_s *const disappearedLocations = (mv_rectangle_s *) value;
 
 		const size_t numberOfDisappearedPersons = __disappearedLocations.size();
 
@@ -205,44 +195,47 @@ int EventResultPersonAppearance::getResultValue(const char *valueName,
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-EventTriggerPersonAppearance::EventTriggerPersonAppearance(
-		mv_surveillance_event_trigger_h eventTrigger, long int triggerId,
-		int videoStreamId, mv_surveillance_event_occurred_cb callback,
-		void *userData, int numberOfPoints, mv_point_s *roi, bool isInternal) :
-				EventTrigger(eventTrigger, triggerId, videoStreamId, callback, userData,
-				numberOfPoints, roi, isInternal),
-				__skipFramesCount(DEFAULT_SKIP_FRAMES_COUNT),
-				__frameCounter(0), __movementDetectedEventId(InternalTriggersCounter--),
-				__factorX(1.f), __factorY(1.f), __rectToDetect(ALL_IMAGE_RECT),
-				__rectToDetectPrevious(ALL_IMAGE_RECT), __trackedRects(),
-				__appearedRects(), __disappearedRects(), __hogClassifier(),
-				__eventResult(new EventResultPersonAppearance())
+EventTriggerPersonAppearance::EventTriggerPersonAppearance(mv_surveillance_event_trigger_h eventTrigger,
+														   long int triggerId, int videoStreamId,
+														   mv_surveillance_event_occurred_cb callback, void *userData,
+														   int numberOfPoints, mv_point_s *roi, bool isInternal)
+		: EventTrigger(eventTrigger, triggerId, videoStreamId, callback, userData, numberOfPoints, roi, isInternal)
+		, __skipFramesCount(DEFAULT_SKIP_FRAMES_COUNT)
+		, __frameCounter(0)
+		, __movementDetectedEventId(InternalTriggersCounter--)
+		, __factorX(1.f)
+		, __factorY(1.f)
+		, __rectToDetect(ALL_IMAGE_RECT)
+		, __rectToDetectPrevious(ALL_IMAGE_RECT)
+		, __trackedRects()
+		, __appearedRects()
+		, __disappearedRects()
+		, __hogClassifier()
+		, __eventResult(new EventResultPersonAppearance())
 {
 	__hogClassifier.setSVMDetector(DEFAULT_SVM_PEOPLE_DETECTOR);
 
 	EventManager::getInstance().registerEvent(NULL, __movementDetectedEventId,
-		MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED, videoStreamId, NULL,
-		movementDetectedCB, this, numberOfPoints, roi, true);
+											  MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED, videoStreamId, NULL,
+											  movementDetectedCB, this, numberOfPoints, roi, true);
 }
 
 EventTriggerPersonAppearance::~EventTriggerPersonAppearance()
 {
-	EventManager::getInstance().unregisterEvent(__movementDetectedEventId,
-			__videoStreamId);
+	EventManager::getInstance().unregisterEvent(__movementDetectedEventId, __videoStreamId);
 
 	delete __eventResult;
 }
 
-int EventTriggerPersonAppearance::parseEngineConfig(
-		mv_engine_config_h engineConfig)
+int EventTriggerPersonAppearance::parseEngineConfig(mv_engine_config_h engineConfig)
 {
 	if (NULL == engineConfig) {
 		LOGI("Default value for frame skip count was set.");
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	const int error = mv_engine_config_get_int_attribute(engineConfig,
-	MV_SURVEILLANCE_SKIP_FRAMES_COUNT, &__skipFramesCount);
+	const int error =
+			mv_engine_config_get_int_attribute(engineConfig, MV_SURVEILLANCE_SKIP_FRAMES_COUNT, &__skipFramesCount);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Getting frame skip count from engine configuration failed.");
@@ -252,8 +245,7 @@ int EventTriggerPersonAppearance::parseEngineConfig(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int EventTriggerPersonAppearance::pushSource(mv_source_h source,
-		mv_source_h graySource, const cv::Mat& grayImage)
+int EventTriggerPersonAppearance::pushSource(mv_source_h source, mv_source_h graySource, const cv::Mat &grayImage)
 {
 	if (source == NULL || graySource == NULL || grayImage.empty()) {
 		LOGE("Media source is NULL. Pushing source failed.");
@@ -268,23 +260,20 @@ std::string EventTriggerPersonAppearance::getEventType() const
 	return MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED;
 }
 
-void EventTriggerPersonAppearance::movementDetectedCB(
-		mv_surveillance_event_trigger_h /*event_trigger*/, mv_source_h source,
-		int /*video_stream_id*/, mv_surveillance_result_h event_result,
-		void *user_data)
+void EventTriggerPersonAppearance::movementDetectedCB(mv_surveillance_event_trigger_h /*event_trigger*/,
+													  mv_source_h source, int /*video_stream_id*/,
+													  mv_surveillance_result_h event_result, void *user_data)
 {
-	EventTriggerPersonAppearance *trigger =
-			(EventTriggerPersonAppearance*) user_data;
+	EventTriggerPersonAppearance *trigger = (EventTriggerPersonAppearance *) user_data;
 
 	/* 1. Get input image in grayscale and resize it */
-	EventResultMovementDetection *result =
-			static_cast<EventResultMovementDetection*>(event_result);
+	EventResultMovementDetection *result = static_cast<EventResultMovementDetection *>(event_result);
 
 	cv::Mat resizedImage;
 	cv::resize(result->__grayImage, resizedImage, DEFAULT_FRAME_SIZE);
 
-	int error = trigger->applyROIToImage(resizedImage.data, resizedImage.cols,
-			resizedImage.rows, true, DEFAULT_FRAME_WIDTH, DEFAULT_FRAME_HEIGHT);
+	int error = trigger->applyROIToImage(resizedImage.data, resizedImage.cols, resizedImage.rows, true,
+										 DEFAULT_FRAME_WIDTH, DEFAULT_FRAME_HEIGHT);
 
 	if (error != MEDIA_VISION_ERROR_NONE || resizedImage.empty()) {
 		trigger->runCallbacks(source);
@@ -317,7 +306,7 @@ void EventTriggerPersonAppearance::movementDetectedCB(
 			trigger->__rectToDetect |= movementRegions[j];
 
 		if (trigger->__rectToDetect.width < trigger->__hogClassifier.winSize.width ||
-				trigger->__rectToDetect.height < trigger->__hogClassifier.winSize.height)
+			trigger->__rectToDetect.height < trigger->__hogClassifier.winSize.height)
 			trigger->__rectToDetect |= trigger->__rectToDetectPrevious;
 	}
 
@@ -349,9 +338,8 @@ void EventTriggerPersonAppearance::movementDetectedCB(
 
 		CVRectangles hogRects;
 
-		trigger->__hogClassifier.detectMultiScale(
-				resizedImage(trigger->__rectToDetect), hogRects, 0,
-				DEFAULT_DETECTION_STEPS, cv::Size(32, 32), 1.059, 5);
+		trigger->__hogClassifier.detectMultiScale(resizedImage(trigger->__rectToDetect), hogRects, 0,
+												  DEFAULT_DETECTION_STEPS, cv::Size(32, 32), 1.059, 5);
 
 		const size_t hogRectsSize = hogRects.size();
 
@@ -361,8 +349,7 @@ void EventTriggerPersonAppearance::movementDetectedCB(
 		}
 
 		/* Merge appearance and tracked rectangles */
-		std::vector<bool> appearedBusyRects =
-				trigger->reinforceTrackedPersons(hogRects);
+		std::vector<bool> appearedBusyRects = trigger->reinforceTrackedPersons(hogRects);
 
 		/* Person appearance */
 		trigger->__appearedRects.clear();
@@ -375,9 +362,8 @@ void EventTriggerPersonAppearance::movementDetectedCB(
 		gettimeofday(&time, NULL);
 		TrackedRectanglesIter trackRectIter = trigger->__trackedRects.begin();
 		for (; trackRectIter != trigger->__trackedRects.end(); ++trackRectIter) {
-			time_t currentLifetime = 1000000 *
-					(time.tv_sec - trackRectIter->appearanceTime.tv_sec) +
-					(time.tv_usec - trackRectIter->appearanceTime.tv_usec);
+			time_t currentLifetime = 1000000 * (time.tv_sec - trackRectIter->appearanceTime.tv_sec) +
+									 (time.tv_usec - trackRectIter->appearanceTime.tv_usec);
 
 			if (currentLifetime > PERSON_LIFETIME) {
 				trigger->__disappearedRects.push_back(trackRectIter->rect);
@@ -408,42 +394,33 @@ void EventTriggerPersonAppearance::movementDetectedCB(
 
 	CVRectanglesConstIter appearedIter = trigger->__appearedRects.begin();
 	for (; appearedIter != trigger->__appearedRects.end(); ++appearedIter)
-		trigger->__trackedRects.push_back(
-				TrackedRectangle(*appearedIter, time));
+		trigger->__trackedRects.push_back(TrackedRectangle(*appearedIter, time));
 	trigger->__appearedRects.clear();
 
 	/* 7. Clear array of disappeared persons */
 	trigger->__disappearedRects.clear();
 }
 
-std::vector<bool> EventTriggerPersonAppearance::reinforceTrackedPersons(
-		const CVRectangles& appearedPersons)
+std::vector<bool> EventTriggerPersonAppearance::reinforceTrackedPersons(const CVRectangles &appearedPersons)
 {
 	const size_t hogRectsSize = appearedPersons.size();
 	std::vector<bool> appearedBusyRects(hogRectsSize, false);
 	if (__trackedRects.size() > 0u && hogRectsSize > 0u) {
 		TrackedRectanglesIter trackRectIter = __trackedRects.begin();
-		std::vector<std::vector<size_t> > intersectionAreas(
-				__trackedRects.size(), std::vector<size_t>(hogRectsSize, 0u));
-		std::vector<std::vector<size_t> > confidence(
-				__trackedRects.size(), std::vector<size_t>(hogRectsSize, 0u));
+		std::vector<std::vector<size_t> > intersectionAreas(__trackedRects.size(),
+															std::vector<size_t>(hogRectsSize, 0u));
+		std::vector<std::vector<size_t> > confidence(__trackedRects.size(), std::vector<size_t>(hogRectsSize, 0u));
 
 		/* Merge tracked -> appearance */
-		for (size_t trIdx = 0u; trackRectIter != __trackedRects.end();
-				++trackRectIter, ++trIdx) {
+		for (size_t trIdx = 0u; trackRectIter != __trackedRects.end(); ++trackRectIter, ++trIdx) {
 			size_t bestIdx = 0u;
 			bool haveRes = false;
 			for (size_t apIdx = 0u; apIdx < hogRectsSize; ++apIdx) {
-				intersectionAreas[trIdx][apIdx] =
-					static_cast<size_t>(
-						static_cast<unsigned int>(
-							(appearedPersons[apIdx] & trackRectIter->rect).area()
-						)
-					);
+				intersectionAreas[trIdx][apIdx] = static_cast<size_t>(
+						static_cast<unsigned int>((appearedPersons[apIdx] & trackRectIter->rect).area()));
 
 				if (intersectionAreas[trIdx][apIdx] > 0 &&
-						(intersectionAreas[trIdx][apIdx] >
-						intersectionAreas[trIdx][bestIdx] || !haveRes)) {
+					(intersectionAreas[trIdx][apIdx] > intersectionAreas[trIdx][bestIdx] || !haveRes)) {
 					bestIdx = apIdx;
 					haveRes = true;
 				}
@@ -451,7 +428,7 @@ std::vector<bool> EventTriggerPersonAppearance::reinforceTrackedPersons(
 
 			if (haveRes)
 				confidence[trIdx][bestIdx] += intersectionAreas[trIdx][bestIdx] *
-					sizeDifferenceFactor(trackRectIter->rect, appearedPersons[bestIdx]);
+											  sizeDifferenceFactor(trackRectIter->rect, appearedPersons[bestIdx]);
 		}
 
 		/* Merge appearance -> tracked */
@@ -461,11 +438,9 @@ std::vector<bool> EventTriggerPersonAppearance::reinforceTrackedPersons(
 			bool haveRes = false;
 			cv::Rect bestTrackedRect = trackRectIter->rect;
 
-			for (size_t trIdx = 0u; trackRectIter != __trackedRects.end();
-					++trackRectIter, ++trIdx) {
+			for (size_t trIdx = 0u; trackRectIter != __trackedRects.end(); ++trackRectIter, ++trIdx) {
 				if (intersectionAreas[trIdx][apIdx] > 0 &&
-						(intersectionAreas[trIdx][apIdx] >
-						intersectionAreas[bestIdx][apIdx] || !haveRes)) {
+					(intersectionAreas[trIdx][apIdx] > intersectionAreas[bestIdx][apIdx] || !haveRes)) {
 					bestIdx = trIdx;
 					bestTrackedRect = trackRectIter->rect;
 					haveRes = true;
@@ -474,26 +449,23 @@ std::vector<bool> EventTriggerPersonAppearance::reinforceTrackedPersons(
 
 			if (haveRes)
 				confidence[bestIdx][apIdx] += intersectionAreas[bestIdx][apIdx] *
-					sizeDifferenceFactor(bestTrackedRect, appearedPersons[apIdx]);
+											  sizeDifferenceFactor(bestTrackedRect, appearedPersons[apIdx]);
 		}
 
 		/* Final merge */
 		trackRectIter = __trackedRects.begin();
-		for (size_t trIdx = 0u; trackRectIter != __trackedRects.end();
-				++trackRectIter, ++trIdx) {
+		for (size_t trIdx = 0u; trackRectIter != __trackedRects.end(); ++trackRectIter, ++trIdx) {
 			bool haveRes = false;
 			size_t bestIdx = 0u;
 
 			for (size_t apIdx = 0u; apIdx < hogRectsSize; ++apIdx) {
-				if (!appearedBusyRects[apIdx] && (!haveRes ||
-						confidence[trIdx][apIdx] > confidence[trIdx][bestIdx])) {
+				if (!appearedBusyRects[apIdx] && (!haveRes || confidence[trIdx][apIdx] > confidence[trIdx][bestIdx])) {
 					bestIdx = apIdx;
 					haveRes = true;
 				}
 			}
 
-			if (isPossibleToMerge(trackRectIter->rect, appearedPersons[bestIdx]) &&
-					haveRes) {
+			if (isPossibleToMerge(trackRectIter->rect, appearedPersons[bestIdx]) && haveRes) {
 				appearedBusyRects[bestIdx] = true;
 
 				struct timeval time;
@@ -501,19 +473,16 @@ std::vector<bool> EventTriggerPersonAppearance::reinforceTrackedPersons(
 
 				trackRectIter->appearanceTime = time;
 				trackRectIter->rect = appearedPersons[bestIdx];
-				trackRectIter->tracker.reinforcement(
-						cutRectForTracking(trackRectIter->rect));
+				trackRectIter->tracker.reinforcement(cutRectForTracking(trackRectIter->rect));
 			}
 		}
 
 		for (size_t apIdx = 0u; apIdx < hogRectsSize; ++apIdx) {
 			if (!appearedBusyRects[apIdx]) {
 				trackRectIter = __trackedRects.begin();
-				for (;trackRectIter != __trackedRects.end();
-						++trackRectIter) {
-					if (isPossibleToMerge(trackRectIter->rect,
-							appearedPersons[apIdx]) && (appearedPersons[apIdx].area() / 2.f) <
-							(appearedPersons[apIdx] & trackRectIter->rect).area()) {
+				for (; trackRectIter != __trackedRects.end(); ++trackRectIter) {
+					if (isPossibleToMerge(trackRectIter->rect, appearedPersons[apIdx]) &&
+						(appearedPersons[apIdx].area() / 2.f) < (appearedPersons[apIdx] & trackRectIter->rect).area()) {
 						appearedBusyRects[apIdx] = true;
 						break;
 					}
@@ -535,8 +504,7 @@ void EventTriggerPersonAppearance::runCallbacks(mv_source_h source)
 	__eventResult->__appearedLocations.resize(appearedLocationsSize);
 
 	for (size_t i = 0u; i < appearedLocationsSize; ++i) {
-		convertRectCV2MV(__appearedRects[i],
-				__eventResult->__appearedLocations[i]);
+		convertRectCV2MV(__appearedRects[i], __eventResult->__appearedLocations[i]);
 		__eventResult->__appearedLocations[i].point.x /= __factorX;
 		__eventResult->__appearedLocations[i].point.y /= __factorY;
 		__eventResult->__appearedLocations[i].width /= __factorX;
@@ -547,8 +515,7 @@ void EventTriggerPersonAppearance::runCallbacks(mv_source_h source)
 	__eventResult->__disappearedLocations.resize(disappearedLocationsSize);
 
 	for (size_t i = 0u; i < disappearedLocationsSize; ++i) {
-		convertRectCV2MV(__disappearedRects[i],
-				__eventResult->__disappearedLocations[i]);
+		convertRectCV2MV(__disappearedRects[i], __eventResult->__disappearedLocations[i]);
 		__eventResult->__disappearedLocations[i].point.x /= __factorX;
 		__eventResult->__disappearedLocations[i].point.y /= __factorY;
 		__eventResult->__disappearedLocations[i].width /= __factorX;
@@ -560,8 +527,7 @@ void EventTriggerPersonAppearance::runCallbacks(mv_source_h source)
 
 	TrackedRectanglesConstIter trackedIter = __trackedRects.begin();
 	for (size_t i = 0u; i < trackedLocationsSize; ++i, ++trackedIter) {
-		convertRectCV2MV(trackedIter->rect,
-				__eventResult->__trackedLocations[i]);
+		convertRectCV2MV(trackedIter->rect, __eventResult->__trackedLocations[i]);
 		__eventResult->__trackedLocations[i].point.x /= __factorX;
 		__eventResult->__trackedLocations[i].point.y /= __factorY;
 		__eventResult->__trackedLocations[i].width /= __factorX;
@@ -574,11 +540,9 @@ void EventTriggerPersonAppearance::runCallbacks(mv_source_h source)
 	for (; iter != __callbackDataMap.end(); ++iter) {
 		mv_surveillance_event_occurred_cb callback = iter->second.callback;
 
-
-		if (appearedLocationsSize > 0 || disappearedLocationsSize > 0
-				|| trackedLocationsSize > 0 || iter->second.isInternal)
-			callback(iter->second.eventTrigger, source, __videoStreamId,
-					__eventResult, iter->second.userData);
+		if (appearedLocationsSize > 0 || disappearedLocationsSize > 0 || trackedLocationsSize > 0 ||
+			iter->second.isInternal)
+			callback(iter->second.eventTrigger, source, __videoStreamId, __eventResult, iter->second.userData);
 	}
 }
 // LCOV_EXCL_STOP
diff --git a/mv_surveillance/surveillance/src/EventTriggerPersonRecognition.cpp b/mv_surveillance/surveillance/src/EventTriggerPersonRecognition.cpp
index c367082..7a23796 100644
--- a/mv_surveillance/surveillance/src/EventTriggerPersonRecognition.cpp
+++ b/mv_surveillance/surveillance/src/EventTriggerPersonRecognition.cpp
@@ -23,15 +23,15 @@
 
 #include <sstream>
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 static const int MAX_VALUE_NAME_LENGHT = 255;
 
-namespace {
-
-template <typename T>
-std::string numberToString(T Number)
+namespace
+{
+template<typename T> std::string numberToString(T Number)
 {
 	std::ostringstream ss;
 	ss << Number;
@@ -40,9 +40,7 @@ std::string numberToString(T Number)
 
 } /* Anonymous namespace*/
 
-int EventResultPersonRecognition::getResultValue(
-	const char *valueName,
-	void *value) const
+int EventResultPersonRecognition::getResultValue(const char *valueName, void *value) const
 {
 	if (valueName == NULL) {
 		LOGE("Invalid pointer for value name. Getting result value failed.");
@@ -56,29 +54,21 @@ int EventResultPersonRecognition::getResultValue(
 
 	const size_t numberOfPersons = __locations.size();
 
-	if (strncmp(valueName,
-				MV_SURVEILLANCE_PERSONS_RECOGNIZED_NUMBER,
-				MAX_VALUE_NAME_LENGHT) == 0) {
-		size_t *outNumberOfPersons = (size_t*) value;
+	if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_RECOGNIZED_NUMBER, MAX_VALUE_NAME_LENGHT) == 0) {
+		size_t *outNumberOfPersons = (size_t *) value;
 		*outNumberOfPersons = numberOfPersons;
-	} else if (strncmp(valueName,
-						MV_SURVEILLANCE_PERSONS_RECOGNIZED_LOCATIONS,
-						MAX_VALUE_NAME_LENGHT) == 0) {
-		mv_rectangle_s *locations = (mv_rectangle_s*) value;
+	} else if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_RECOGNIZED_LOCATIONS, MAX_VALUE_NAME_LENGHT) == 0) {
+		mv_rectangle_s *locations = (mv_rectangle_s *) value;
 
 		for (size_t i = 0; i < numberOfPersons; ++i)
 			locations[i] = __locations[i];
-	} else if (strncmp(valueName,
-						MV_SURVEILLANCE_PERSONS_RECOGNIZED_LABELS,
-						MAX_VALUE_NAME_LENGHT) == 0) {
-		int *labels = (int*) value;
+	} else if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_RECOGNIZED_LABELS, MAX_VALUE_NAME_LENGHT) == 0) {
+		int *labels = (int *) value;
 
 		for (size_t i = 0; i < numberOfPersons; ++i)
 			labels[i] = __faceLabels[i];
-	} else if (strncmp(valueName,
-						MV_SURVEILLANCE_PERSONS_RECOGNIZED_CONFIDENCES,
-						MAX_VALUE_NAME_LENGHT) == 0) {
-		double *confidences = (double*) value;
+	} else if (strncmp(valueName, MV_SURVEILLANCE_PERSONS_RECOGNIZED_CONFIDENCES, MAX_VALUE_NAME_LENGHT) == 0) {
+		double *confidences = (double *) value;
 
 		for (size_t i = 0; i < numberOfPersons; ++i)
 			confidences[i] = __confidences[i];
@@ -90,25 +80,14 @@ int EventResultPersonRecognition::getResultValue(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-EventTriggerPersonRecognition::EventTriggerPersonRecognition(
-		mv_surveillance_event_trigger_h eventTrigger,
-		long int triggerId,
-		int videoStreamId,
-		mv_surveillance_event_occurred_cb callback,
-		void *userData,
-		int numberOfPoints,
-		mv_point_s *roi,
-		bool isInternal) : EventTrigger(eventTrigger,
-										triggerId,
-										videoStreamId,
-										callback,
-										userData,
-										numberOfPoints,
-										roi,
-										isInternal),
-	__faceRecognitionModel(NULL),
-	__lastFrame(NULL),
-	__eventResult(new EventResultPersonRecognition())
+EventTriggerPersonRecognition::EventTriggerPersonRecognition(mv_surveillance_event_trigger_h eventTrigger,
+															 long int triggerId, int videoStreamId,
+															 mv_surveillance_event_occurred_cb callback, void *userData,
+															 int numberOfPoints, mv_point_s *roi, bool isInternal)
+		: EventTrigger(eventTrigger, triggerId, videoStreamId, callback, userData, numberOfPoints, roi, isInternal)
+		, __faceRecognitionModel(NULL)
+		, __lastFrame(NULL)
+		, __eventResult(new EventResultPersonRecognition())
 {
 	; /* NULL */
 }
@@ -119,7 +98,8 @@ EventTriggerPersonRecognition::~EventTriggerPersonRecognition()
 		const int err = mv_face_recognition_model_destroy(__faceRecognitionModel);
 		if (MEDIA_VISION_ERROR_NONE != err)
 			LOGE("Error while trying to delete face recognition model when "
-					"event trigger had been destroyed. Error code: %i.", err);
+				 "event trigger had been destroyed. Error code: %i.",
+				 err);
 	}
 
 	delete __eventResult;
@@ -134,10 +114,8 @@ int EventTriggerPersonRecognition::parseEngineConfig(mv_engine_config_h engineCo
 
 	char *modelPath = NULL;
 
-	int error = mv_engine_config_get_string_attribute(
-			engineConfig,
-			MV_SURVEILLANCE_FACE_RECOGNITION_MODEL_FILE_PATH,
-			&modelPath);
+	int error = mv_engine_config_get_string_attribute(engineConfig, MV_SURVEILLANCE_FACE_RECOGNITION_MODEL_FILE_PATH,
+													  &modelPath);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		if (modelPath != NULL) {
@@ -155,8 +133,7 @@ int EventTriggerPersonRecognition::parseEngineConfig(mv_engine_config_h engineCo
 	error = mv_face_recognition_model_load(modelPath, &recognitionModel);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
-		LOGE("Loading recognition model from file %s failed.",
-				modelPath);
+		LOGE("Loading recognition model from file %s failed.", modelPath);
 
 		if (modelPath != NULL) {
 			free(modelPath);
@@ -166,7 +143,8 @@ int EventTriggerPersonRecognition::parseEngineConfig(mv_engine_config_h engineCo
 		const int err = mv_face_recognition_model_destroy(recognitionModel);
 		if (MEDIA_VISION_ERROR_NONE != err) {
 			LOGE("Error while trying to delete face recognition model."
-					" Error code: %i.", err);
+				 " Error code: %i.",
+				 err);
 		}
 
 		return error;
@@ -176,7 +154,8 @@ int EventTriggerPersonRecognition::parseEngineConfig(mv_engine_config_h engineCo
 		error = mv_face_recognition_model_destroy(__faceRecognitionModel);
 		if (MEDIA_VISION_ERROR_NONE != error) {
 			LOGE("Error while trying to delete old face recognition model when "
-					"new model is trying to be loaded. Error code: %i.", error);
+				 "new model is trying to be loaded. Error code: %i.",
+				 error);
 		}
 	}
 
@@ -184,7 +163,8 @@ int EventTriggerPersonRecognition::parseEngineConfig(mv_engine_config_h engineCo
 
 	if (NULL == __faceRecognitionModel) {
 		LOGE("Failed to load face recognition model. Check %s attribute of the "
-				"engine config.", MV_SURVEILLANCE_FACE_RECOGNITION_MODEL_FILE_PATH);
+			 "engine config.",
+			 MV_SURVEILLANCE_FACE_RECOGNITION_MODEL_FILE_PATH);
 
 		if (modelPath != NULL) {
 			free(modelPath);
@@ -202,10 +182,7 @@ int EventTriggerPersonRecognition::parseEngineConfig(mv_engine_config_h engineCo
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int EventTriggerPersonRecognition::pushSource(
-		mv_source_h source,
-		mv_source_h graySource,
-		const cv::Mat& grayImage)
+int EventTriggerPersonRecognition::pushSource(mv_source_h source, mv_source_h graySource, const cv::Mat &grayImage)
 {
 	if (source == NULL || graySource == NULL || grayImage.empty()) {
 		LOGE("Media source is NULL. Pushing source failed.");
@@ -267,8 +244,7 @@ int EventTriggerPersonRecognition::pushSource(
 		return error;
 	}
 
-	error = mv_source_fill_by_buffer(sourceCopy, data_buffer, buffer_size,
-			width, height, colorspace);
+	error = mv_source_fill_by_buffer(sourceCopy, data_buffer, buffer_size, width, height, colorspace);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		mv_destroy_source(sourceCopy);
@@ -315,42 +291,30 @@ std::string EventTriggerPersonRecognition::getEventType() const
 	return MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED;
 }
 
-void EventTriggerPersonRecognition::setEventResults(
-		mv_rectangle_s faceLocation,
-		int faceLabel,
-		double confidence)
+void EventTriggerPersonRecognition::setEventResults(mv_rectangle_s faceLocation, int faceLabel, double confidence)
 {
 	__eventResult->__locations.push_back(faceLocation);
 	__eventResult->__faceLabels.push_back(faceLabel);
 	__eventResult->__confidences.push_back(confidence);
 }
 
-void EventTriggerPersonRecognition::faceDetectedCB(
-		mv_source_h source,
-		mv_engine_config_h /*engine_cfg*/,
-		mv_rectangle_s *faces_locations,
-		int number_of_faces,
-		void *user_data)
+void EventTriggerPersonRecognition::faceDetectedCB(mv_source_h source, mv_engine_config_h /*engine_cfg*/,
+												   mv_rectangle_s *faces_locations, int number_of_faces,
+												   void *user_data)
 {
 	if (NULL == user_data) {
 		LOGE("Invalid user data passed");
 		return;
 	}
 
-	EventTriggerPersonRecognition *trigger =
-		(EventTriggerPersonRecognition*)user_data;
+	EventTriggerPersonRecognition *trigger = (EventTriggerPersonRecognition *) user_data;
 
 	int location_idx = 0;
 	for (; location_idx < number_of_faces; ++location_idx) {
 		LOGI("Start surveillance face recognition");
 
-		const int error = mv_face_recognize(
-				source,
-				trigger->__faceRecognitionModel,
-				NULL,
-				&faces_locations[location_idx],
-				faceRecognizedCB,
-				trigger);
+		const int error = mv_face_recognize(source, trigger->__faceRecognitionModel, NULL,
+											&faces_locations[location_idx], faceRecognizedCB, trigger);
 
 		if (error != MEDIA_VISION_ERROR_NONE) {
 			LOGW("Face recognition for one model failed. Continue");
@@ -366,31 +330,22 @@ void EventTriggerPersonRecognition::faceDetectedCB(
 		mv_surveillance_event_occurred_cb callback = iter->second.callback;
 
 		if (trigger->__eventResult->__locations.size() > 0 || iter->second.isInternal)
-			callback(
-				iter->second.eventTrigger,
-				trigger->__lastFrame,
-				trigger->__videoStreamId,
-				trigger->__eventResult,
-				iter->second.userData);
+			callback(iter->second.eventTrigger, trigger->__lastFrame, trigger->__videoStreamId, trigger->__eventResult,
+					 iter->second.userData);
 	}
 }
 
-void EventTriggerPersonRecognition::faceRecognizedCB(
-		mv_source_h source,
-		mv_face_recognition_model_h /*recognition_model*/,
-		mv_engine_config_h /*engine_cfg*/,
-		mv_rectangle_s *face_location,
-		const int *face_label,
-		double confidence,
-		void *user_data)
+void EventTriggerPersonRecognition::faceRecognizedCB(mv_source_h source,
+													 mv_face_recognition_model_h /*recognition_model*/,
+													 mv_engine_config_h /*engine_cfg*/, mv_rectangle_s *face_location,
+													 const int *face_label, double confidence, void *user_data)
 {
 	if (source == NULL || face_location == NULL || face_label == NULL) {
 		LOGI("Face wasn't recognized");
 		return;
 	}
 
-	EventTriggerPersonRecognition *trigger =
-		(EventTriggerPersonRecognition*) user_data;
+	EventTriggerPersonRecognition *trigger = (EventTriggerPersonRecognition *) user_data;
 
 	trigger->setEventResults(*face_location, *face_label, confidence);
 }
diff --git a/mv_surveillance/surveillance/src/MFTracker.cpp b/mv_surveillance/surveillance/src/MFTracker.cpp
index 32179ff..c7d19a8 100644
--- a/mv_surveillance/surveillance/src/MFTracker.cpp
+++ b/mv_surveillance/surveillance/src/MFTracker.cpp
@@ -19,23 +19,24 @@
 #include "opencv2/video/tracking.hpp"
 #include "opencv2/imgproc.hpp"
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 // LCOV_EXCL_START
-namespace {
+namespace
+{
 const float FLOATEPS = 10e-6f;
 
-template<typename T>
-T getMedian(std::vector<T>& values, int size = -1)
+template<typename T> T getMedian(std::vector<T> &values, int size = -1)
 {
 	if (size == -1)
-		size = (int)values.size();
+		size = (int) values.size();
 
 	std::vector<T> copy(values.begin(), values.begin() + size);
 	std::sort(copy.begin(), copy.end());
-	if (size%2 == 0) {
-		return (copy[size / 2 - 1] + copy[size/2]) / ((T)2.0);
+	if (size % 2 == 0) {
+		return (copy[size / 2 - 1] + copy[size / 2]) / ((T) 2.0);
 	} else {
 		return copy[(size - 1) / 2];
 	}
@@ -56,15 +57,14 @@ MFTracker::Params::Params()
 	mPyrMaxLevel = 5;
 }
 
-MFTracker::MFTracker(Params params) :
-	__isInit(false),
-	__params(params),
-	__termcrit(cv::TermCriteria::COUNT | cv::TermCriteria::EPS, 20, 0.3),
-	__confidence(0.0f)
-{
-}
+MFTracker::MFTracker(Params params)
+		: __isInit(false)
+		, __params(params)
+		, __termcrit(cv::TermCriteria::COUNT | cv::TermCriteria::EPS, 20, 0.3)
+		, __confidence(0.0f)
+{}
 
-bool MFTracker::track(const cv::Mat& frame, cv::Rect_<float>& result)
+bool MFTracker::track(const cv::Mat &frame, cv::Rect_<float> &result)
 {
 	if (!__isInit) {
 		if (__boundingBox.width <= 0 || __boundingBox.height <= 0)
@@ -83,30 +83,26 @@ bool MFTracker::track(const cv::Mat& frame, cv::Rect_<float>& result)
 	return true;
 }
 
-void MFTracker::reinforcement(const cv::Rect_<float>& location)
+void MFTracker::reinforcement(const cv::Rect_<float> &location)
 {
 	__isInit = false;
 
 	__boundingBox = location;
 }
 
-bool MFTracker::init(const cv::Mat& image)
+bool MFTracker::init(const cv::Mat &image)
 {
 	if (image.empty())
 		return false;
 
 	image.copyTo(__image);
-	buildOpticalFlowPyramid(
-		__image,
-		__pyramid,
-		__params.mWindowSize,
-		__params.mPyrMaxLevel);
+	buildOpticalFlowPyramid(__image, __pyramid, __params.mWindowSize, __params.mPyrMaxLevel);
 
 	__isInit = true;
 	return __isInit;
 }
 
-bool MFTracker::update(const cv::Mat& image)
+bool MFTracker::update(const cv::Mat &image)
 {
 	if (!__isInit || image.empty())
 		return false;
@@ -129,7 +125,7 @@ bool MFTracker::update(const cv::Mat& image)
 	cv::Mat oldImage = __image;
 
 	cv::Rect_<float> oldBox = __boundingBox;
-	if(!medianFlowImpl(oldImage, image, oldBox))
+	if (!medianFlowImpl(oldImage, image, oldBox))
 		return false;
 
 	image.copyTo(__image);
@@ -152,8 +148,7 @@ cv::Rect_<float> MFTracker::getLastBoundingBox() const
 	return __boundingBox;
 }
 
-bool MFTracker::medianFlowImpl(
-	cv::Mat oldImage_gray, cv::Mat newImage_gray, cv::Rect_<float>& oldBox)
+bool MFTracker::medianFlowImpl(cv::Mat oldImage_gray, cv::Mat newImage_gray, cv::Rect_<float> &oldBox)
 {
 	std::vector<cv::Point2f> pointsToTrackOld, pointsToTrackNew;
 
@@ -161,9 +156,8 @@ bool MFTracker::medianFlowImpl(
 	const float gridYStep = oldBox.height / __params.mPointsInGrid;
 	for (int i = 0; i < __params.mPointsInGrid; i++)
 		for (int j = 0; j < __params.mPointsInGrid; j++) {
-			pointsToTrackOld.push_back(
-				cv::Point2f(oldBox.x + .5f*gridXStep + 1.f*gridXStep*j,
-							oldBox.y + .5f*gridYStep + 1.f*gridYStep*i));
+			pointsToTrackOld.push_back(cv::Point2f(oldBox.x + .5f * gridXStep + 1.f * gridXStep * j,
+												   oldBox.y + .5f * gridYStep + 1.f * gridYStep * i));
 		}
 
 	const size_t numberOfPointsToTrackOld = pointsToTrackOld.size();
@@ -171,21 +165,10 @@ bool MFTracker::medianFlowImpl(
 	std::vector<float> errors(numberOfPointsToTrackOld);
 
 	std::vector<cv::Mat> tempPyramid;
-	buildOpticalFlowPyramid(
-		newImage_gray,
-		tempPyramid,
-		__params.mWindowSize,
-		__params.mPyrMaxLevel);
-
-	calcOpticalFlowPyrLK(__pyramid,
-			tempPyramid,
-			pointsToTrackOld,
-			pointsToTrackNew,
-			status,
-			errors,
-			__params.mWindowSize,
-			__params.mPyrMaxLevel,
-			__termcrit);
+	buildOpticalFlowPyramid(newImage_gray, tempPyramid, __params.mWindowSize, __params.mPyrMaxLevel);
+
+	calcOpticalFlowPyrLK(__pyramid, tempPyramid, pointsToTrackOld, pointsToTrackNew, status, errors,
+						 __params.mWindowSize, __params.mPyrMaxLevel, __termcrit);
 
 	std::vector<cv::Point2f> di;
 	for (size_t idx = 0u; idx < numberOfPointsToTrackOld; idx++)
@@ -193,15 +176,8 @@ bool MFTracker::medianFlowImpl(
 			di.push_back(pointsToTrackNew[idx] - pointsToTrackOld[idx]);
 
 	std::vector<bool> filter_status;
-	check_FB(tempPyramid,
-			pointsToTrackOld,
-			pointsToTrackNew,
-			filter_status);
-	check_NCC(oldImage_gray,
-			newImage_gray,
-			pointsToTrackOld,
-			pointsToTrackNew,
-			filter_status);
+	check_FB(tempPyramid, pointsToTrackOld, pointsToTrackNew, filter_status);
+	check_NCC(oldImage_gray, newImage_gray, pointsToTrackOld, pointsToTrackNew, filter_status);
 
 	for (size_t idx = 0u; idx < pointsToTrackOld.size(); idx++)
 		if (!filter_status[idx]) {
@@ -215,8 +191,7 @@ bool MFTracker::medianFlowImpl(
 		return false;
 
 	cv::Point2f mDisplacement;
-	cv::Rect_<float> boxCandidate =
-		vote(pointsToTrackOld, pointsToTrackNew, oldBox, mDisplacement);
+	cv::Rect_<float> boxCandidate = vote(pointsToTrackOld, pointsToTrackNew, oldBox, mDisplacement);
 
 	std::vector<float> displacements;
 	for (size_t idx = 0u; idx < di.size(); idx++) {
@@ -224,8 +199,7 @@ bool MFTracker::medianFlowImpl(
 		displacements.push_back(sqrt(di[idx].ddot(di[idx])));
 	}
 
-	__confidence =
-		(10.f - getMedian(displacements, static_cast<int>(displacements.size()))) / 10.f;
+	__confidence = (10.f - getMedian(displacements, static_cast<int>(displacements.size()))) / 10.f;
 
 	if (__confidence < 0.f) {
 		__confidence = 0.f;
@@ -237,23 +211,18 @@ bool MFTracker::medianFlowImpl(
 	return true;
 }
 
-cv::Rect_<float> MFTracker::vote(
-	const std::vector<cv::Point2f>& oldPoints,
-	const std::vector<cv::Point2f>& newPoints,
-	const cv::Rect_<float>& oldRect,
-	cv::Point2f& mD)
+cv::Rect_<float> MFTracker::vote(const std::vector<cv::Point2f> &oldPoints, const std::vector<cv::Point2f> &newPoints,
+								 const cv::Rect_<float> &oldRect, cv::Point2f &mD)
 {
 	cv::Rect_<float> newRect;
-	cv::Point2f newCenter(
-		oldRect.x + oldRect.width / 2.f,
-		oldRect.y + oldRect.height / 2.f);
+	cv::Point2f newCenter(oldRect.x + oldRect.width / 2.f, oldRect.y + oldRect.height / 2.f);
 
-	const int n = (int)oldPoints.size();
-	std::vector<float> buf(std::max(n*(n-1) / 2, 3), 0.f);
+	const int n = (int) oldPoints.size();
+	std::vector<float> buf(std::max(n * (n - 1) / 2, 3), 0.f);
 
-	if(oldPoints.size() == 1) {
-		newRect.x = oldRect.x+newPoints[0].x-oldPoints[0].x;
-		newRect.y = oldRect.y+newPoints[0].y-oldPoints[0].y;
+	if (oldPoints.size() == 1) {
+		newRect.x = oldRect.x + newPoints[0].x - oldPoints[0].x;
+		newRect.y = oldRect.y + newPoints[0].y - oldPoints[0].y;
 		newRect.width = oldRect.width;
 		newRect.height = oldRect.height;
 
@@ -293,20 +262,17 @@ cv::Rect_<float> MFTracker::vote(
 			ctr++;
 		}
 
-	float scale = getMedian(buf, n*(n-1) / 2);
+	float scale = getMedian(buf, n * (n - 1) / 2);
 	newRect.x = newCenter.x - scale * oldRect.width / 2.f;
-	newRect.y = newCenter.y-scale * oldRect.height / 2.f;
+	newRect.y = newCenter.y - scale * oldRect.height / 2.f;
 	newRect.width = scale * oldRect.width;
 	newRect.height = scale * oldRect.height;
 
 	return newRect;
 }
 
-void MFTracker::check_FB(
-	std::vector<cv::Mat> newPyramid,
-	const std::vector<cv::Point2f>& oldPoints,
-	const std::vector<cv::Point2f>& newPoints,
-	std::vector<bool>& status)
+void MFTracker::check_FB(std::vector<cv::Mat> newPyramid, const std::vector<cv::Point2f> &oldPoints,
+						 const std::vector<cv::Point2f> &newPoints, std::vector<bool> &status)
 {
 	const size_t numberOfOldPoints = oldPoints.size();
 
@@ -318,15 +284,8 @@ void MFTracker::check_FB(
 	std::vector<float> FBerror(numberOfOldPoints);
 	std::vector<cv::Point2f> pointsToTrackReprojection;
 
-	calcOpticalFlowPyrLK(newPyramid,
-			__pyramid,
-			newPoints,
-			pointsToTrackReprojection,
-			LKstatus,
-			errors,
-			__params.mWindowSize,
-			__params.mPyrMaxLevel,
-			__termcrit);
+	calcOpticalFlowPyrLK(newPyramid, __pyramid, newPoints, pointsToTrackReprojection, LKstatus, errors,
+						 __params.mWindowSize, __params.mPyrMaxLevel, __termcrit);
 
 	for (size_t idx = 0u; idx < numberOfOldPoints; idx++)
 		FBerror[idx] = l2distance(oldPoints[idx], pointsToTrackReprojection[idx]);
@@ -336,12 +295,8 @@ void MFTracker::check_FB(
 		status[idx] = (FBerror[idx] < FBerrorMedian);
 }
 
-void MFTracker::check_NCC(
-	const cv::Mat& oldImage,
-	const cv::Mat& newImage,
-	const std::vector<cv::Point2f>& oldPoints,
-	const std::vector<cv::Point2f>& newPoints,
-	std::vector<bool>& status)
+void MFTracker::check_NCC(const cv::Mat &oldImage, const cv::Mat &newImage, const std::vector<cv::Point2f> &oldPoints,
+						  const std::vector<cv::Point2f> &newPoints, std::vector<bool> &status)
 {
 	std::vector<float> NCC(oldPoints.size(), 0.f);
 	cv::Size patch(30, 30);
@@ -360,12 +315,11 @@ void MFTracker::check_NCC(
 		const float prod = p1.dot(p2);
 		const float sq1 = sqrt(n1 * n1 - s1 * s1 / N);
 		const float sq2 = sqrt(n2 * n2 - s2 * s2 / N);
-		NCC[idx] = (sq2 == 0 ? sq1 / std::abs(sq1)
-					: (prod - s1 * s2 / N) / sq1 / sq2);
+		NCC[idx] = (sq2 == 0 ? sq1 / std::abs(sq1) : (prod - s1 * s2 / N) / sq1 / sq2);
 	}
 
 	float median = getMedian(NCC) - FLOATEPS;
-	for(size_t idx = 0u; idx < oldPoints.size(); idx++)
+	for (size_t idx = 0u; idx < oldPoints.size(); idx++)
 		status[idx] = status[idx] && (NCC[idx] > median);
 }
 
diff --git a/mv_surveillance/surveillance/src/SurveillanceHelper.cpp b/mv_surveillance/surveillance/src/SurveillanceHelper.cpp
index 98e2360..f1351db 100644
--- a/mv_surveillance/surveillance/src/SurveillanceHelper.cpp
+++ b/mv_surveillance/surveillance/src/SurveillanceHelper.cpp
@@ -22,13 +22,12 @@
 #include "opencv2/highgui.hpp"
 #include "opencv2/imgproc/imgproc_c.h"
 
-namespace mediavision {
-namespace surveillance {
-
+namespace mediavision
+{
+namespace surveillance
+{
 #ifdef ENABLE_NEON
-int SurveillanceHelper::convertSourceMVRGB2GrayCVNeon(
-		mv_source_h mvSource,
-		cv::Mat& cvSource)
+int SurveillanceHelper::convertSourceMVRGB2GrayCVNeon(mv_source_h mvSource, cv::Mat &cvSource)
 {
 	MEDIA_VISION_INSTANCE_CHECK(mvSource);
 
@@ -39,14 +38,10 @@ int SurveillanceHelper::convertSourceMVRGB2GrayCVNeon(
 
 	mv_colorspace_e colorspace = MEDIA_VISION_COLORSPACE_INVALID;
 
-	MEDIA_VISION_ASSERT(mv_source_get_width(mvSource, &width),
-						"Failed to get the width.");
-	MEDIA_VISION_ASSERT(mv_source_get_height(mvSource, &height),
-						"Failed to get the height.");
-	MEDIA_VISION_ASSERT(mv_source_get_colorspace(mvSource, &colorspace),
-						"Failed to get the colorspace.");
-	MEDIA_VISION_ASSERT(mv_source_get_buffer(mvSource, &src, &bufferSize),
-						"Failed to get the buffer size.");
+	MEDIA_VISION_ASSERT(mv_source_get_width(mvSource, &width), "Failed to get the width.");
+	MEDIA_VISION_ASSERT(mv_source_get_height(mvSource, &height), "Failed to get the height.");
+	MEDIA_VISION_ASSERT(mv_source_get_colorspace(mvSource, &colorspace), "Failed to get the colorspace.");
+	MEDIA_VISION_ASSERT(mv_source_get_buffer(mvSource, &src, &bufferSize), "Failed to get the buffer size.");
 
 	if (colorspace != MEDIA_VISION_COLORSPACE_RGB888) {
 		LOGE("Error: mv_source has unsupported colorspace.");
@@ -57,49 +52,51 @@ int SurveillanceHelper::convertSourceMVRGB2GrayCVNeon(
 	const unsigned int cvSourceSize = width * height;
 
 #if defined(__aarch64__)
-	asm volatile ("lsr  %2, %2, #3     \n"
-		"# channel multimpliers:       \n"
-		"mov         w4, #28           \n"
-		"mov         w5, #151          \n"
-		"mov         w6, #77           \n"
-		"dup         v3.8b, w4         \n"
-		"dup         v4.8b, w5         \n"
-		"dup         v5.8b, w6         \n"
-		".loop:                        \n"
-		"# load 8 pixels:              \n"
-		"ld3         {v0.8b,v1.8b,v2.8b}, [%0],#24 \n"
-		"# conversion:                             \n"
-		"umull       v7.8h, v0.8b, v3.8b           \n"
-		"umlal       v7.8h, v1.8b, v4.8b           \n"
-		"umlal       v7.8h, v2.8b, v5.8b           \n"
-		"# shift and store:                        \n"
-		"shrn        v6.8b, v7.8h, #8              \n"
-		"st1         {v6.8b}, [%1],#8              \n"
-		"subs        %2, %2, #1                    \n"
-		"bne         .loop             \n"::"r" (src), "r" (cvSource.data), "r" (cvSourceSize)
-		:"memory", "w4", "w5", "w6");
+	asm volatile("lsr  %2, %2, #3     \n"
+				 "# channel multimpliers:       \n"
+				 "mov         w4, #28           \n"
+				 "mov         w5, #151          \n"
+				 "mov         w6, #77           \n"
+				 "dup         v3.8b, w4         \n"
+				 "dup         v4.8b, w5         \n"
+				 "dup         v5.8b, w6         \n"
+				 ".loop:                        \n"
+				 "# load 8 pixels:              \n"
+				 "ld3         {v0.8b,v1.8b,v2.8b}, [%0],#24 \n"
+				 "# conversion:                             \n"
+				 "umull       v7.8h, v0.8b, v3.8b           \n"
+				 "umlal       v7.8h, v1.8b, v4.8b           \n"
+				 "umlal       v7.8h, v2.8b, v5.8b           \n"
+				 "# shift and store:                        \n"
+				 "shrn        v6.8b, v7.8h, #8              \n"
+				 "st1         {v6.8b}, [%1],#8              \n"
+				 "subs        %2, %2, #1                    \n"
+				 "bne         .loop             \n" ::"r"(src),
+				 "r"(cvSource.data), "r"(cvSourceSize)
+				 : "memory", "w4", "w5", "w6");
 #else
-	asm volatile ("lsr  %2, %2, #3     \n"
-		"# channel multimpliers:       \n"
-		"mov         r4, #77           \n"
-		"mov         r5, #151          \n"
-		"mov         r6, #28           \n"
-		"vdup.8      d3, r4            \n"
-		"vdup.8      d4, r5            \n"
-		"vdup.8      d5, r6            \n"
-		".loop:                        \n"
-		"# load 8 pixels:              \n"
-		"vld3.8      {d0-d2}, [%0]!    \n"
-		"# conversion:                 \n"
-		"vmull.u8    q7, d0, d3        \n"
-		"vmlal.u8    q7, d1, d4        \n"
-		"vmlal.u8    q7, d2, d5        \n"
-		"# shift and store:            \n"
-		"vshrn.u16   d6, q7, #8        \n"
-		"vst1.8      {d6}, [%1]!       \n"
-		"subs        %2, %2, #1        \n"
-		"bne         .loop             \n"::"r" (src), "r" (cvSource.data), "r" (cvSourceSize)
-		:"memory", "r4", "r5", "r6");
+	asm volatile("lsr  %2, %2, #3     \n"
+				 "# channel multimpliers:       \n"
+				 "mov         r4, #77           \n"
+				 "mov         r5, #151          \n"
+				 "mov         r6, #28           \n"
+				 "vdup.8      d3, r4            \n"
+				 "vdup.8      d4, r5            \n"
+				 "vdup.8      d5, r6            \n"
+				 ".loop:                        \n"
+				 "# load 8 pixels:              \n"
+				 "vld3.8      {d0-d2}, [%0]!    \n"
+				 "# conversion:                 \n"
+				 "vmull.u8    q7, d0, d3        \n"
+				 "vmlal.u8    q7, d1, d4        \n"
+				 "vmlal.u8    q7, d2, d5        \n"
+				 "# shift and store:            \n"
+				 "vshrn.u16   d6, q7, #8        \n"
+				 "vst1.8      {d6}, [%1]!       \n"
+				 "subs        %2, %2, #1        \n"
+				 "bne         .loop             \n" ::"r"(src),
+				 "r"(cvSource.data), "r"(cvSourceSize)
+				 : "memory", "r4", "r5", "r6");
 #endif
 
 	return MEDIA_VISION_ERROR_NONE;
diff --git a/mv_surveillance/surveillance/src/mv_absdiff.c b/mv_surveillance/surveillance/src/mv_absdiff.c
index 416016a..c740598 100644
--- a/mv_surveillance/surveillance/src/mv_absdiff.c
+++ b/mv_surveillance/surveillance/src/mv_absdiff.c
@@ -24,16 +24,10 @@
 #include <arm_neon.h>
 #endif
 
-int mv_absdiff(
-		uint8_t *__restrict__ src1,
-		uint8_t *__restrict__ src2,
-		int width,
-		int height,
-		int stride,
-		uint8_t *__restrict__ dst)
+int mv_absdiff(uint8_t *__restrict__ src1, uint8_t *__restrict__ src2, int width, int height, int stride,
+			   uint8_t *__restrict__ dst)
 {
-	if (src1 == NULL || src2 == NULL || width <= 0 || height <= 0 ||
-			stride <= 0 || dst == NULL) {
+	if (src1 == NULL || src2 == NULL || width <= 0 || height <= 0 || stride <= 0 || dst == NULL) {
 		LOGE("Wrong input parameter. Aplpying mask failed.");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
@@ -50,12 +44,12 @@ int mv_absdiff(
 	for (; row < height; ++row) {
 #ifdef ENABLE_NEON
 		for (column = 0; column < batch_columns_count; ++column) {
-			uint8x16_t gray1 = vld1q_u8 (src1);
-			uint8x16_t gray2 = vld1q_u8 (src2);
+			uint8x16_t gray1 = vld1q_u8(src1);
+			uint8x16_t gray2 = vld1q_u8(src2);
 
 			uint8x16_t dst_temp = vabdq_u8(gray1, gray2);
 
-			vst1q_u8 (dst, dst_temp);
+			vst1q_u8(dst, dst_temp);
 
 			src1 += batch_size;
 			src2 += batch_size;
diff --git a/mv_surveillance/surveillance/src/mv_apply_mask.c b/mv_surveillance/surveillance/src/mv_apply_mask.c
index f156d07..f6c0103 100644
--- a/mv_surveillance/surveillance/src/mv_apply_mask.c
+++ b/mv_surveillance/surveillance/src/mv_apply_mask.c
@@ -23,16 +23,9 @@
 #include <arm_neon.h>
 #endif
 
-int mv_apply_mask(
-	uint8_t *src_buffer,
-	uint8_t *__restrict mask,
-	int width,
-	int height,
-	int stride,
-	uint8_t *dst_buffer)
+int mv_apply_mask(uint8_t *src_buffer, uint8_t *__restrict mask, int width, int height, int stride, uint8_t *dst_buffer)
 {
-	if (src_buffer == NULL || mask == NULL || width <= 0 || height <= 0 ||
-			stride <= 0 || dst_buffer == NULL) {
+	if (src_buffer == NULL || mask == NULL || width <= 0 || height <= 0 || stride <= 0 || dst_buffer == NULL) {
 		LOGE("Wrong input parameter. Aplpying mask failed.");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
diff --git a/mv_surveillance/surveillance/src/mv_mask_buffer.c b/mv_surveillance/surveillance/src/mv_mask_buffer.c
index 98d252b..45bf8d7 100644
--- a/mv_surveillance/surveillance/src/mv_mask_buffer.c
+++ b/mv_surveillance/surveillance/src/mv_mask_buffer.c
@@ -22,21 +22,16 @@
 #include <stdio.h>
 #include <stdlib.h>
 
-int mv_get_mask_buffer(
-	unsigned int buffer_width,
-	unsigned int buffer_height,
-	mv_point_s *polygon,
-	unsigned int points_number,
-	unsigned char **mask_buffer)
+int mv_get_mask_buffer(unsigned int buffer_width, unsigned int buffer_height, mv_point_s *polygon,
+					   unsigned int points_number, unsigned char **mask_buffer)
 {
-	if (buffer_width == 0u || buffer_height == 0u ||
-			polygon == NULL || points_number == 0u || mask_buffer == NULL) {
+	if (buffer_width == 0u || buffer_height == 0u || polygon == NULL || points_number == 0u || mask_buffer == NULL) {
 		LOGE("Wrong input parameter. Getting mask buffer failed.");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
 	const unsigned int buffer_size = buffer_width * buffer_height;
-	unsigned char* buffer = (unsigned char*) malloc(sizeof(unsigned char) * buffer_size);
+	unsigned char *buffer = (unsigned char *) malloc(sizeof(unsigned char) * buffer_size);
 	if (buffer == NULL) {
 		LOGE("*buffer is null");
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
@@ -63,7 +58,6 @@ int mv_get_mask_buffer(
 			min_y = polygon[k].y;
 	}
 
-
 	for (k = 0u; k < buffer_size; ++k) {
 		bool inside_polygon = false;
 
@@ -77,10 +71,9 @@ int mv_get_mask_buffer(
 
 		for (i = 0u, j = points_number - 1; i < points_number; j = i++) {
 			if (((polygon[i].y > test_y) != (polygon[j].y > test_y)) &&
-					((float) test_x < (float) (polygon[j].x - polygon[i].x) *
-					(test_y - polygon[i].y) /
-					(polygon[j].y - polygon[i].y) +
-					polygon[i].x)) {
+				((float) test_x <
+				 (float) (polygon[j].x - polygon[i].x) * (test_y - polygon[i].y) / (polygon[j].y - polygon[i].y) +
+						 polygon[i].x)) {
 				inside_polygon = !inside_polygon;
 			}
 		}
diff --git a/mv_surveillance/surveillance/src/mv_surveillance.c b/mv_surveillance/surveillance/src/mv_surveillance.c
index e01b76a..45b9cf1 100644
--- a/mv_surveillance/surveillance/src/mv_surveillance.c
+++ b/mv_surveillance/surveillance/src/mv_surveillance.c
@@ -28,9 +28,7 @@
 
 static size_t __mv_surveillance_id_counter = 0;
 
-int mv_surveillance_event_trigger_create(
-		const char *event_type,
-		mv_surveillance_event_trigger_h * trigger)
+int mv_surveillance_event_trigger_create(const char *event_type, mv_surveillance_event_trigger_h *trigger)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
@@ -39,8 +37,7 @@ int mv_surveillance_event_trigger_create(
 	MEDIA_VISION_FUNCTION_ENTER();
 
 	mv_surveillance_event_trigger_s *handle =
-			(mv_surveillance_event_trigger_s *) malloc(
-					sizeof(mv_surveillance_event_trigger_s));
+			(mv_surveillance_event_trigger_s *) malloc(sizeof(mv_surveillance_event_trigger_s));
 	if (NULL == handle) {
 		LOGE("[%s] malloc fail", __func__);
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
@@ -60,16 +57,14 @@ int mv_surveillance_event_trigger_create(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_surveillance_event_trigger_destroy(
-		mv_surveillance_event_trigger_h trigger)
+int mv_surveillance_event_trigger_destroy(mv_surveillance_event_trigger_h trigger)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(trigger);
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	mv_surveillance_event_trigger_s *handle =
-			(mv_surveillance_event_trigger_s *) trigger;
+	mv_surveillance_event_trigger_s *handle = (mv_surveillance_event_trigger_s *) trigger;
 	free(handle->event_type);
 	free(handle->roi);
 	free((mv_surveillance_event_trigger_s *) trigger);
@@ -78,9 +73,7 @@ int mv_surveillance_event_trigger_destroy(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_surveillance_get_event_trigger_type(
-		mv_surveillance_event_trigger_h trigger,
-		char **event_type)
+int mv_surveillance_get_event_trigger_type(mv_surveillance_event_trigger_h trigger, char **event_type)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
@@ -88,18 +81,15 @@ int mv_surveillance_get_event_trigger_type(
 	MEDIA_VISION_NULL_ARG_CHECK(event_type);
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	mv_surveillance_event_trigger_s *handle =
-			(mv_surveillance_event_trigger_s *)trigger;
+	mv_surveillance_event_trigger_s *handle = (mv_surveillance_event_trigger_s *) trigger;
 	*event_type = strndup(handle->event_type, 255);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_surveillance_set_event_trigger_roi(
-		mv_surveillance_event_trigger_h trigger,
-		int number_of_points,
-		mv_point_s *roi)
+int mv_surveillance_set_event_trigger_roi(mv_surveillance_event_trigger_h trigger, int number_of_points,
+										  mv_point_s *roi)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
@@ -112,8 +102,7 @@ int mv_surveillance_set_event_trigger_roi(
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
 
-	mv_surveillance_event_trigger_s *handle =
-			(mv_surveillance_event_trigger_s *)trigger;
+	mv_surveillance_event_trigger_s *handle = (mv_surveillance_event_trigger_s *) trigger;
 
 	if (handle->roi) {
 		free(handle->roi);
@@ -121,7 +110,7 @@ int mv_surveillance_set_event_trigger_roi(
 	}
 
 	handle->number_of_roi_points = number_of_points;
-	handle->roi = (mv_point_s*) malloc(sizeof(mv_point_s) * number_of_points);
+	handle->roi = (mv_point_s *) malloc(sizeof(mv_point_s) * number_of_points);
 
 	if (NULL == handle->roi) {
 		LOGE("[%s] malloc fail", __func__);
@@ -138,10 +127,8 @@ int mv_surveillance_set_event_trigger_roi(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_surveillance_get_event_trigger_roi(
-		mv_surveillance_event_trigger_h trigger,
-		int *number_of_points,
-		mv_point_s ** roi)
+int mv_surveillance_get_event_trigger_roi(mv_surveillance_event_trigger_h trigger, int *number_of_points,
+										  mv_point_s **roi)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
@@ -150,8 +137,7 @@ int mv_surveillance_get_event_trigger_roi(
 	MEDIA_VISION_NULL_ARG_CHECK(roi);
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	mv_surveillance_event_trigger_s *handle =
-			(mv_surveillance_event_trigger_s *) trigger;
+	mv_surveillance_event_trigger_s *handle = (mv_surveillance_event_trigger_s *) trigger;
 
 	*number_of_points = handle->number_of_roi_points;
 	if (0 == *number_of_points) {
@@ -159,8 +145,7 @@ int mv_surveillance_get_event_trigger_roi(
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	*roi = (mv_point_s *) malloc(
-					sizeof(mv_point_s) * handle->number_of_roi_points);
+	*roi = (mv_point_s *) malloc(sizeof(mv_point_s) * handle->number_of_roi_points);
 	if (*roi == NULL) {
 		LOGE("*roi is null");
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
@@ -176,12 +161,9 @@ int mv_surveillance_get_event_trigger_roi(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_surveillance_subscribe_event_trigger(
-		mv_surveillance_event_trigger_h event_trigger,
-		int video_stream_id,
-		mv_engine_config_h engine_cfg,
-		mv_surveillance_event_occurred_cb callback,
-		void *user_data)
+int mv_surveillance_subscribe_event_trigger(mv_surveillance_event_trigger_h event_trigger, int video_stream_id,
+											mv_engine_config_h engine_cfg, mv_surveillance_event_occurred_cb callback,
+											void *user_data)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
@@ -189,37 +171,27 @@ int mv_surveillance_subscribe_event_trigger(
 	MEDIA_VISION_NULL_ARG_CHECK(callback);
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	const int ret = mv_surveillance_subscribe_event_trigger_open(
-					event_trigger,
-					video_stream_id,
-					engine_cfg,
-					callback,
-					user_data);
+	const int ret = mv_surveillance_subscribe_event_trigger_open(event_trigger, video_stream_id, engine_cfg, callback,
+																 user_data);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_surveillance_unsubscribe_event_trigger(
-		mv_surveillance_event_trigger_h event_trigger,
-		int video_stream_id)
+int mv_surveillance_unsubscribe_event_trigger(mv_surveillance_event_trigger_h event_trigger, int video_stream_id)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_INSTANCE_CHECK(event_trigger);
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	const int ret = mv_surveillance_unsubscribe_event_trigger_open(
-					event_trigger,
-					video_stream_id);
+	const int ret = mv_surveillance_unsubscribe_event_trigger_open(event_trigger, video_stream_id);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_surveillance_push_source(
-		mv_source_h source,
-		int video_stream_id)
+int mv_surveillance_push_source(mv_source_h source, int video_stream_id)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
@@ -232,27 +204,21 @@ int mv_surveillance_push_source(
 	return ret;
 }
 
-int mv_surveillance_foreach_supported_event_type(
-		mv_surveillance_event_type_cb callback,
-		void *user_data)
+int mv_surveillance_foreach_supported_event_type(mv_surveillance_event_type_cb callback, void *user_data)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
 	MEDIA_VISION_NULL_ARG_CHECK(callback);
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	const int ret = mv_surveillance_foreach_event_type_open(
-					callback,
-					user_data);
+	const int ret = mv_surveillance_foreach_event_type_open(callback, user_data);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
 }
 
-int mv_surveillance_foreach_event_result_name(
-		const char *event_type,
-		mv_surveillance_event_result_name_cb callback,
-		void *user_data)
+int mv_surveillance_foreach_event_result_name(const char *event_type, mv_surveillance_event_result_name_cb callback,
+											  void *user_data)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
@@ -260,20 +226,14 @@ int mv_surveillance_foreach_event_result_name(
 	MEDIA_VISION_NULL_ARG_CHECK(callback);
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	const int ret = mv_surveillance_foreach_event_result_value_name_open(
-					event_type,
-					callback,
-					user_data);
+	const int ret = mv_surveillance_foreach_event_result_value_name_open(event_type, callback, user_data);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 
 	return ret;
 }
 
-int mv_surveillance_get_result_value(
-		mv_surveillance_result_h result,
-		const char *value_name,
-		void *value)
+int mv_surveillance_get_result_value(mv_surveillance_result_h result, const char *value_name, void *value)
 {
 	MEDIA_VISION_SUPPORT_CHECK(_mv_face_check_system_info_feature_supported());
 	MEDIA_VISION_SUPPORT_CHECK(_mv_image_check_system_info_feature_supported());
@@ -282,10 +242,7 @@ int mv_surveillance_get_result_value(
 	MEDIA_VISION_NULL_ARG_CHECK(value);
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	const int ret = mv_surveillance_get_result_value_open(
-					result,
-					value_name,
-					value);
+	const int ret = mv_surveillance_get_result_value_open(result, value_name, value);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return ret;
diff --git a/mv_surveillance/surveillance/src/mv_surveillance_open.cpp b/mv_surveillance/surveillance/src/mv_surveillance_open.cpp
index 0f303e4..11872ab 100644
--- a/mv_surveillance/surveillance/src/mv_surveillance_open.cpp
+++ b/mv_surveillance/surveillance/src/mv_surveillance_open.cpp
@@ -23,60 +23,38 @@
 
 using namespace mediavision::surveillance;
 
-int mv_surveillance_subscribe_event_trigger_open(
-	mv_surveillance_event_trigger_h event_trigger,
-	int video_stream_id,
-	mv_engine_config_h engine_cfg,
-	mv_surveillance_event_occurred_cb callback,
-	void *user_data)
+int mv_surveillance_subscribe_event_trigger_open(mv_surveillance_event_trigger_h event_trigger, int video_stream_id,
+												 mv_engine_config_h engine_cfg,
+												 mv_surveillance_event_occurred_cb callback, void *user_data)
 {
-	mv_surveillance_event_trigger_s *handle =
-		(mv_surveillance_event_trigger_s *)event_trigger;
-
-	return EventManager::getInstance().registerEvent(
-			event_trigger,
-			static_cast<long int>(handle->trigger_id),
-			handle->event_type,
-			video_stream_id,
-			engine_cfg,
-			callback,
-			user_data,
-			handle->number_of_roi_points,
-			handle->roi,
-			false);
+	mv_surveillance_event_trigger_s *handle = (mv_surveillance_event_trigger_s *) event_trigger;
+
+	return EventManager::getInstance().registerEvent(event_trigger, static_cast<long int>(handle->trigger_id),
+													 handle->event_type, video_stream_id, engine_cfg, callback,
+													 user_data, handle->number_of_roi_points, handle->roi, false);
 }
 
-int mv_surveillance_unsubscribe_event_trigger_open(
-	mv_surveillance_event_trigger_h event_trigger,
-	int video_stream_id)
+int mv_surveillance_unsubscribe_event_trigger_open(mv_surveillance_event_trigger_h event_trigger, int video_stream_id)
 {
-	mv_surveillance_event_trigger_s *handle =
-		(mv_surveillance_event_trigger_s *)event_trigger;
+	mv_surveillance_event_trigger_s *handle = (mv_surveillance_event_trigger_s *) event_trigger;
 
-	return EventManager::getInstance().unregisterEvent(
-			static_cast<long int>(handle->trigger_id),
-			video_stream_id);
+	return EventManager::getInstance().unregisterEvent(static_cast<long int>(handle->trigger_id), video_stream_id);
 }
 
-int mv_surveillance_push_source_open(
-		mv_source_h source,
-		int video_stream_id)
+int mv_surveillance_push_source_open(mv_source_h source, int video_stream_id)
 {
 	MEDIA_VISION_INSTANCE_CHECK(source);
 
 	return EventManager::getInstance().pushSource(source, video_stream_id);
 }
 
-int mv_surveillance_foreach_event_type_open(
-		mv_surveillance_event_type_cb callback,
-		void *user_data)
+int mv_surveillance_foreach_event_type_open(mv_surveillance_event_type_cb callback, void *user_data)
 {
 	StringVector eventTypes;
 	const int error = EventManager::getInstance().getSupportedEventTypes(eventTypes);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
-		LOGE("Query events failed due to internal issues. Error code: %i",
-				error);
+		LOGE("Query events failed due to internal issues. Error code: %i", error);
 		return error;
 	}
 
@@ -91,27 +69,23 @@ int mv_surveillance_foreach_event_type_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_surveillance_foreach_event_result_value_name_open(
-	const char *event_type,
-	mv_surveillance_event_result_name_cb callback,
-	void *user_data)
+int mv_surveillance_foreach_event_result_value_name_open(const char *event_type,
+														 mv_surveillance_event_result_name_cb callback, void *user_data)
 {
 	StringVector eventResultValueNames;
 
 	int error = MEDIA_VISION_ERROR_NONE;
 
 	if (NULL == event_type) {
-		error = EventManager::getInstance().getSupportedEventResultValueNames(
-					eventResultValueNames);
+		error = EventManager::getInstance().getSupportedEventResultValueNames(eventResultValueNames);
 	} else {
-		error = EventManager::getInstance().getSupportedEventResultValueNames(
-					event_type,
-					eventResultValueNames);
+		error = EventManager::getInstance().getSupportedEventResultValueNames(event_type, eventResultValueNames);
 	}
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Query result value names failed due to internal issues. "
-				"Error code: %i", error);
+			 "Error code: %i",
+			 error);
 		return error;
 	}
 
@@ -126,16 +100,13 @@ int mv_surveillance_foreach_event_result_value_name_open(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_surveillance_get_result_value_open(
-	mv_surveillance_result_h result,
-	const char *value_name,
-	void *value)
+int mv_surveillance_get_result_value_open(mv_surveillance_result_h result, const char *value_name, void *value)
 {
 	MEDIA_VISION_INSTANCE_CHECK(result);
 	MEDIA_VISION_NULL_ARG_CHECK(value_name);
 	MEDIA_VISION_NULL_ARG_CHECK(value);
 
-	EventResult *eventResult = (EventResult*) result;
+	EventResult *eventResult = (EventResult *) result;
 
 	return eventResult->getResultValue(value_name, value);
 }
diff --git a/packaging/capi-media-vision.spec b/packaging/capi-media-vision.spec
index 76f5f5b..ba8863e 100644
--- a/packaging/capi-media-vision.spec
+++ b/packaging/capi-media-vision.spec
@@ -1,6 +1,6 @@
 Name:        capi-media-vision
 Summary:     Media Vision library for Tizen Native API
-Version:     0.23.22
+Version:     0.23.23
 Release:     0
 Group:       Multimedia/Framework
 License:     Apache-2.0 and BSD-3-Clause
diff --git a/test/assessment/barcode/assessment_barcode.cpp b/test/assessment/barcode/assessment_barcode.cpp
index 47b80d1..b023750 100644
--- a/test/assessment/barcode/assessment_barcode.cpp
+++ b/test/assessment/barcode/assessment_barcode.cpp
@@ -42,11 +42,8 @@ struct arguments
 	char *source;
 };
 
-int load_image_to_buffer(char *source,
-		unsigned char **buffer,
-		unsigned long *size,
-		unsigned int *width,
-		unsigned int *height)
+int load_image_to_buffer(char *source, unsigned char **buffer, unsigned long *size, unsigned int *width,
+						 unsigned int *height)
 {
 	cv::Mat image;
 	image = cv::imread(source);
@@ -70,14 +67,9 @@ int load_image_to_buffer(char *source,
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-void barcode_detected_cb(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		const mv_quadrangle_s *barcodes_locations,
-		const char *messages[],
-		const mv_barcode_type_e *types,
-		int number_of_barcodes,
-		void *user_data)
+void barcode_detected_cb(mv_source_h source, mv_engine_config_h engine_cfg, const mv_quadrangle_s *barcodes_locations,
+						 const char *messages[], const mv_barcode_type_e *types, int number_of_barcodes,
+						 void *user_data)
 {
 	MEDIA_VISION_FUNCTION_ENTER();
 
@@ -102,11 +94,10 @@ int perform_detect(struct arguments *arguments)
 	unsigned int image_width = 0;
 	unsigned int image_height = 0;
 	int int_value = MV_BARCODE_DETECT_ATTR_TARGET_ALL;
-	mv_rectangle_s roi = { {0, 0}, 0, 0 };
+	mv_rectangle_s roi = { { 0, 0 }, 0, 0 };
 	int err = MEDIA_VISION_ERROR_NONE;
 
-	err = load_image_to_buffer(arguments->source,
-			&data_buffer, &buffer_size, &image_width, &image_height);
+	err = load_image_to_buffer(arguments->source, &data_buffer, &buffer_size, &image_width, &image_height);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		LOGE("Errors were occurred during opening the file!!! code : %i", err);
@@ -120,10 +111,10 @@ int perform_detect(struct arguments *arguments)
 	}
 
 	if (MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE ==
-		mv_engine_config_get_int_attribute(
-					mv_engine_config, MV_BARCODE_DETECT_ATTR_TARGET, &int_value)) {
+		mv_engine_config_get_int_attribute(mv_engine_config, MV_BARCODE_DETECT_ATTR_TARGET, &int_value)) {
 		LOGE("Errors were occurred during target attribute"
-				"configuration : %i", err);
+			 "configuration : %i",
+			 err);
 		goto out;
 	}
 
@@ -133,8 +124,8 @@ int perform_detect(struct arguments *arguments)
 		goto out;
 	}
 
-	err = mv_source_fill_by_buffer(source, data_buffer, buffer_size,
-			image_width, image_height, MEDIA_VISION_COLORSPACE_Y800);
+	err = mv_source_fill_by_buffer(source, data_buffer, buffer_size, image_width, image_height,
+								   MEDIA_VISION_COLORSPACE_Y800);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		LOGE("Errors were occurred during filling the source!!! code : %i", err);
 		goto out;
@@ -150,7 +141,7 @@ out:
 		printf("-1\n");
 
 	if (data_buffer != NULL) {
-		delete [] data_buffer;
+		delete[] data_buffer;
 		data_buffer = NULL;
 	}
 
@@ -172,9 +163,9 @@ out:
 	return err;
 }
 
-static error_t parse_opt (int key, char *arg, struct argp_state *state)
+static error_t parse_opt(int key, char *arg, struct argp_state *state)
 {
-	struct arguments *arguments = (struct arguments *)state->input;
+	struct arguments *arguments = (struct arguments *) state->input;
 
 	switch (key) {
 	case ARGP_KEY_NO_ARGS:
@@ -201,11 +192,12 @@ int main(int argc, char *argv[])
 	LOGI("Media Vision Assessment-Barcode is launched.");
 
 	struct arguments arguments;
-	argp_parse (&argp, argc, argv, 0, 0, &arguments);
+	argp_parse(&argp, argc, argv, 0, 0, &arguments);
 
 	std::chrono::system_clock::time_point StartTime = std::chrono::system_clock::now();
 	int err = perform_detect(&arguments);
-	std::chrono::milliseconds ms = std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::system_clock::now() - StartTime);
+	std::chrono::milliseconds ms =
+			std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::system_clock::now() - StartTime);
 	std::cout << ms.count() << "ms" << std::endl;
 
 	if (err != MEDIA_VISION_ERROR_NONE)
diff --git a/test/assessment/face/assessment_face.cpp b/test/assessment/face/assessment_face.cpp
index 56a97c4..8d4fb07 100644
--- a/test/assessment/face/assessment_face.cpp
+++ b/test/assessment/face/assessment_face.cpp
@@ -45,16 +45,12 @@ struct arguments
 	int model_type;
 };
 
-const char *model_names[3] = {"/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt.xml",
-							"/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt2.xml",
-							"/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt_tree.xml"};
-
-void on_face_detected_cb(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s *faces_locations,
-		int number_of_faces,
-		void *user_data)
+const char *model_names[3] = { "/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt.xml",
+							   "/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt2.xml",
+							   "/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt_tree.xml" };
+
+void on_face_detected_cb(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s *faces_locations,
+						 int number_of_faces, void *user_data)
 {
 	MEDIA_VISION_FUNCTION_ENTER();
 
@@ -62,20 +58,16 @@ void on_face_detected_cb(
 	printf("%i\n", number_of_faces);
 	if (number_of_faces > 0) {
 		for (i = 0; i < number_of_faces; ++i) {
-			printf("%i %i %i %i\n",
-					faces_locations[i].point.x, faces_locations[i].point.y,
-					faces_locations[i].width, faces_locations[i].height);
+			printf("%i %i %i %i\n", faces_locations[i].point.x, faces_locations[i].point.y, faces_locations[i].width,
+				   faces_locations[i].height);
 		}
 	}
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 }
 
-int load_image_to_buffer(char *source,
-		unsigned char **buffer,
-		unsigned long *size,
-		unsigned int *width,
-		unsigned int *height)
+int load_image_to_buffer(char *source, unsigned char **buffer, unsigned long *size, unsigned int *width,
+						 unsigned int *height)
 {
 	cv::Mat image;
 	image = cv::imread(source);
@@ -110,8 +102,7 @@ int perform_detect(struct arguments *arguments)
 	unsigned int image_width = 0;
 	unsigned int image_height = 0;
 
-	int err = load_image_to_buffer(arguments->source,
-			&data_buffer, &buffer_size, &image_width, &image_height);
+	int err = load_image_to_buffer(arguments->source, &data_buffer, &buffer_size, &image_width, &image_height);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		LOGE("Errors were occurred during opening the file!!! code : %i", err);
@@ -124,10 +115,8 @@ int perform_detect(struct arguments *arguments)
 		goto out;
 	}
 
-	mv_engine_config_set_string_attribute(
-				mv_engine_config,
-				MV_FACE_DETECTION_MODEL_FILE_PATH,
-				model_names[arguments->model_type]);
+	mv_engine_config_set_string_attribute(mv_engine_config, MV_FACE_DETECTION_MODEL_FILE_PATH,
+										  model_names[arguments->model_type]);
 
 	err = mv_create_source(&source);
 	if (MEDIA_VISION_ERROR_NONE != err) {
@@ -135,8 +124,8 @@ int perform_detect(struct arguments *arguments)
 		goto out;
 	}
 
-	err = mv_source_fill_by_buffer(source, data_buffer, buffer_size,
-			image_width, image_height, MEDIA_VISION_COLORSPACE_Y800);
+	err = mv_source_fill_by_buffer(source, data_buffer, buffer_size, image_width, image_height,
+								   MEDIA_VISION_COLORSPACE_Y800);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		LOGE("Errors were occurred during filling the source!!! code : %i", err);
 		goto out;
@@ -168,9 +157,9 @@ out:
 	return err;
 }
 
-static error_t parse_opt (int key, char *arg, struct argp_state *state)
+static error_t parse_opt(int key, char *arg, struct argp_state *state)
 {
-	struct arguments *arguments = (struct arguments *)state->input;
+	struct arguments *arguments = (struct arguments *) state->input;
 
 	switch (key) {
 	case ARGP_KEY_NO_ARGS:
@@ -202,11 +191,12 @@ int main(int argc, char *argv[])
 	LOGI("Media Vision Assessment-Face is launched.");
 
 	struct arguments arguments;
-	argp_parse (&argp, argc, argv, 0, 0, &arguments);
+	argp_parse(&argp, argc, argv, 0, 0, &arguments);
 
 	std::chrono::system_clock::time_point StartTime = std::chrono::system_clock::now();
 	int err = perform_detect(&arguments);
-	std::chrono::milliseconds ms = std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::system_clock::now() - StartTime);
+	std::chrono::milliseconds ms =
+			std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::system_clock::now() - StartTime);
 	std::cout << ms.count() << "ms" << std::endl;
 
 	if (err != MEDIA_VISION_ERROR_NONE)
diff --git a/test/assessment/surveillance/assessment_surveillance.cpp b/test/assessment/surveillance/assessment_surveillance.cpp
index 861ae3f..7bf5220 100644
--- a/test/assessment/surveillance/assessment_surveillance.cpp
+++ b/test/assessment/surveillance/assessment_surveillance.cpp
@@ -42,43 +42,33 @@ struct arguments
 	int threshold;
 };
 
-void movement_detected_cb(
-	mv_surveillance_event_trigger_h event_trigger,
-	mv_source_h source,
-	int video_stream_id,
-	mv_surveillance_result_h event_result,
-	void *user_data)
+void movement_detected_cb(mv_surveillance_event_trigger_h event_trigger, mv_source_h source, int video_stream_id,
+						  mv_surveillance_result_h event_result, void *user_data)
 {
 	MEDIA_VISION_FUNCTION_ENTER();
 
 	int number_of_movement_regions = 0;
-	int error = mv_surveillance_get_result_value(
-					event_result,
-					MV_SURVEILLANCE_MOVEMENT_NUMBER_OF_REGIONS,
-					&number_of_movement_regions);
+	int error = mv_surveillance_get_result_value(event_result, MV_SURVEILLANCE_MOVEMENT_NUMBER_OF_REGIONS,
+												 &number_of_movement_regions);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		LOGE("Error with code %d was occurred in getting number of "
-				"movement regions.", error);
+			 "movement regions.",
+			 error);
 		return;
 	}
 
-	mv_rectangle_s *movement_regions = (mv_rectangle_s *)
-		malloc(sizeof(mv_rectangle_s) * number_of_movement_regions);
+	mv_rectangle_s *movement_regions = (mv_rectangle_s *) malloc(sizeof(mv_rectangle_s) * number_of_movement_regions);
 
 	if (movement_regions == NULL) {
 		LOGE("Failed to malloc movement_regions");
 		return;
 	}
 
-	error = mv_surveillance_get_result_value(
-				event_result,
-				MV_SURVEILLANCE_MOVEMENT_REGIONS,
-				movement_regions);
+	error = mv_surveillance_get_result_value(event_result, MV_SURVEILLANCE_MOVEMENT_REGIONS, movement_regions);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
-		LOGE("Error with code %d was occurred in getting movement regions.",
-				error);
+		LOGE("Error with code %d was occurred in getting movement regions.", error);
 		if (movement_regions != NULL)
 			free(movement_regions);
 		return;
@@ -90,7 +80,6 @@ void movement_detected_cb(
 	cv::Scalar color(0, 0, 255);
 	static unsigned int findex = 0;
 
-
 	mv_source_get_width(source, &image_width);
 	mv_source_get_height(source, &image_height);
 	mv_source_get_colorspace(source, &image_colorspace);
@@ -111,22 +100,15 @@ void movement_detected_cb(
 #endif
 
 	for (int i = 0; i < number_of_movement_regions; ++i) {
-		printf("%d:%d:%d-%d:%d\n",
-				findex,
-				movement_regions[i].point.x,
-				movement_regions[i].point.y,
-				movement_regions[i].width,
-				movement_regions[i].height);
+		printf("%d:%d:%d-%d:%d\n", findex, movement_regions[i].point.x, movement_regions[i].point.y,
+			   movement_regions[i].width, movement_regions[i].height);
 #if DUMP_JPEG
 		char buf[256];
 		cv::Mat cvImage(image_width, image_height, CV_8UC(3), out_buffer_copy);
-		cv::rectangle(
-			cvImage,
-			cv::Point(movement_regions[i].point.x, movement_regions[i].point.y),
-			cv::Point((movement_regions[i].width - movement_regions[i].point.x),
-					(movement_regions[i].height - movement_regions[i].point.y)),
-			color,
-			3);
+		cv::rectangle(cvImage, cv::Point(movement_regions[i].point.x, movement_regions[i].point.y),
+					  cv::Point((movement_regions[i].width - movement_regions[i].point.x),
+								(movement_regions[i].height - movement_regions[i].point.y)),
+					  color, 3);
 		sprintf(buf, "%d.jpg", findex);
 		if (!cv::imwrite(buf, cvImage))
 			LOGE("Failed to write image");
@@ -153,11 +135,11 @@ int perform_detect(struct arguments *arguments)
 	mv_engine_config_h engine_cfg = NULL;
 	int err = MEDIA_VISION_ERROR_NONE;
 
-	err = mv_surveillance_event_trigger_create(
-					MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED, &event_trigger);
+	err = mv_surveillance_event_trigger_create(MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED, &event_trigger);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		LOGE("mv_surveillance_event_trigger_create() error!\n"
-				"Error code: %i\n", err);
+			 "Error code: %i\n",
+			 err);
 		goto out;
 	}
 
@@ -167,19 +149,14 @@ int perform_detect(struct arguments *arguments)
 		goto out;
 	}
 
-	err = mv_engine_config_set_int_attribute(engine_cfg,
-					MV_SURVEILLANCE_MOVEMENT_DETECTION_THRESHOLD, arguments->threshold);
+	err = mv_engine_config_set_int_attribute(engine_cfg, MV_SURVEILLANCE_MOVEMENT_DETECTION_THRESHOLD,
+											 arguments->threshold);
 	if (err != MEDIA_VISION_ERROR_NONE) {
-			LOGE("Setting frame detection threshold from engine configuration failed.");
-			goto out;
+		LOGE("Setting frame detection threshold from engine configuration failed.");
+		goto out;
 	}
 
-	err = mv_surveillance_subscribe_event_trigger(
-					event_trigger,
-					0,
-					engine_cfg,
-					movement_detected_cb,
-					NULL);
+	err = mv_surveillance_subscribe_event_trigger(event_trigger, 0, engine_cfg, movement_detected_cb, NULL);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		LOGE("Error with code %d was occurred in subscribe event.", err);
@@ -189,7 +166,7 @@ int perform_detect(struct arguments *arguments)
 out:
 	if (MEDIA_VISION_ERROR_NONE == err) {
 		cv::VideoCapture cap(arguments->source);
-		if(!cap.isOpened())
+		if (!cap.isOpened())
 			LOGE("Can not open Video file");
 
 		int rows = cap.get(cv::CAP_PROP_FRAME_WIDTH);
@@ -199,7 +176,7 @@ out:
 		if (MEDIA_VISION_ERROR_NONE != err) {
 			LOGE("Errors were occurred during source creating!!! Code %i", err);
 		} else {
-			for(int frame = 0; frame < cap.get(cv::CAP_PROP_FRAME_COUNT); frame++) {
+			for (int frame = 0; frame < cap.get(cv::CAP_PROP_FRAME_COUNT); frame++) {
 				cv::Mat f, rgb;
 				cap >> f;
 				if (f.empty())
@@ -209,13 +186,7 @@ out:
 				int size = rgb.total() * rgb.elemSize();
 				unsigned char *data = rgb.data;
 
-
-				err = mv_source_fill_by_buffer(
-						source, data,
-						size,
-						cols,
-						rows ,
-						MEDIA_VISION_COLORSPACE_RGB888);
+				err = mv_source_fill_by_buffer(source, data, size, cols, rows, MEDIA_VISION_COLORSPACE_RGB888);
 
 				err = mv_surveillance_push_source(source, 0);
 				if (MEDIA_VISION_ERROR_NONE != err) {
@@ -235,14 +206,16 @@ out:
 		err = mv_destroy_engine_config(engine_cfg);
 		if (err != MEDIA_VISION_ERROR_NONE)
 			LOGE("Failed to destroy engine configuration for event trigger."
-					"Error code: %i", err);
+				 "Error code: %i",
+				 err);
 	}
 
 	if (event_trigger != NULL) {
 		err = mv_surveillance_event_trigger_destroy(event_trigger);
 		if (MEDIA_VISION_ERROR_NONE != err) {
 			LOGE("Error with code %d was occurred when try to destroy "
-					"event trigger.", err);
+				 "event trigger.",
+				 err);
 		}
 	}
 
@@ -251,9 +224,9 @@ out:
 	return err;
 }
 
-static error_t parse_opt (int key, char *arg, struct argp_state *state)
+static error_t parse_opt(int key, char *arg, struct argp_state *state)
 {
-	struct arguments *arguments = (struct arguments *)state->input;
+	struct arguments *arguments = (struct arguments *) state->input;
 
 	switch (key) {
 	case ARGP_KEY_NO_ARGS:
@@ -287,11 +260,12 @@ int main(int argc, char *argv[])
 	LOGI("Media Vision Assessment-Surveillance is launched.");
 
 	struct arguments arguments;
-	argp_parse (&argp, argc, argv, 0, 0, &arguments);
+	argp_parse(&argp, argc, argv, 0, 0, &arguments);
 
 	std::chrono::system_clock::time_point StartTime = std::chrono::system_clock::now();
 	err = perform_detect(&arguments);
-	std::chrono::milliseconds ms = std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::system_clock::now() - StartTime);
+	std::chrono::milliseconds ms =
+			std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::system_clock::now() - StartTime);
 	std::cout << ms.count() << "ms" << std::endl;
 
 	if (err != MEDIA_VISION_ERROR_NONE)
diff --git a/test/testsuites/barcode/barcode_test_suite.c b/test/testsuites/barcode/barcode_test_suite.c
index f89ff3d..517c64c 100644
--- a/test/testsuites/barcode/barcode_test_suite.c
+++ b/test/testsuites/barcode/barcode_test_suite.c
@@ -42,7 +42,8 @@
 
 #define ARRAY_SIZE(x) (sizeof((x)) / sizeof((x)[0]))
 
-typedef struct {
+typedef struct
+{
 	mv_barcode_type_e type;
 	mv_barcode_qr_ecc_e ecc;
 	mv_barcode_qr_mode_e mode;
@@ -60,7 +61,8 @@ typedef struct {
 	char *back_color;
 } barcode_model_s;
 
-typedef enum {
+typedef enum
+{
 	MV_TS_GENERATE_TO_IMAGE_FCN,
 	MV_TS_GENERATE_TO_SOURCE_FCN
 } generation_fcn_e;
@@ -73,8 +75,8 @@ static const char doc[] = "mv_barcode_test -- mediavision barcode test";
 static const char args_doc[] = "";
 
 static struct argp_option arg_options[] = {
-	{"mode", 'm', "MODE", OPTION_ARG_OPTIONAL, "Run test by MODE [0=manual|1=auto] (default 0)"},
-	{"interval", 'i', "TIME", OPTION_ARG_OPTIONAL, "Run test by TIME (default 0 sec, maximum 9 sec) interval"},
+	{ "mode", 'm', "MODE", OPTION_ARG_OPTIONAL, "Run test by MODE [0=manual|1=auto] (default 0)" },
+	{ "interval", 'i', "TIME", OPTION_ARG_OPTIONAL, "Run test by TIME (default 0 sec, maximum 9 sec) interval" },
 	{ 0 }
 };
 
@@ -84,9 +86,8 @@ struct arguments
 	int interval;
 };
 
-int convert_rgb_to(unsigned char *src_buffer, unsigned char **dst_buffer,
-		image_data_s image_data, mv_colorspace_e dst_colorspace,
-		unsigned long *cvt_buffer_size)
+int convert_rgb_to(unsigned char *src_buffer, unsigned char **dst_buffer, image_data_s image_data,
+				   mv_colorspace_e dst_colorspace, unsigned long *cvt_buffer_size)
 {
 	enum AVPixelFormat pixel_format = AV_PIX_FMT_NONE;
 
@@ -126,7 +127,7 @@ int convert_rgb_to(unsigned char *src_buffer, unsigned char **dst_buffer,
 		break;
 	case MEDIA_VISION_COLORSPACE_RGB888:
 		*cvt_buffer_size = image_data.image_width * image_data.image_height * 3;
-		(*dst_buffer) = (unsigned char*)malloc(*cvt_buffer_size);
+		(*dst_buffer) = (unsigned char *) malloc(*cvt_buffer_size);
 		memcpy(*dst_buffer, src_buffer, *cvt_buffer_size);
 
 		MEDIA_VISION_FUNCTION_LEAVE();
@@ -139,31 +140,27 @@ int convert_rgb_to(unsigned char *src_buffer, unsigned char **dst_buffer,
 	AVPicture src_picture;
 	AVPicture dst_picture;
 
-	avpicture_fill(&src_picture, (uint8_t*)src_buffer, AV_PIX_FMT_RGB24,
-			image_data.image_width, image_data.image_height);
+	avpicture_fill(&src_picture, (uint8_t *) src_buffer, AV_PIX_FMT_RGB24, image_data.image_width,
+				   image_data.image_height);
 
-	avpicture_alloc(&dst_picture, pixel_format,
-			image_data.image_width, image_data.image_height);
+	avpicture_alloc(&dst_picture, pixel_format, image_data.image_width, image_data.image_height);
 
-	struct SwsContext *context = sws_getContext(
-			image_data.image_width, image_data.image_height, AV_PIX_FMT_RGB24,
-			image_data.image_width, image_data.image_height, pixel_format,
-			SWS_FAST_BILINEAR, 0, 0, 0);
+	struct SwsContext *context = sws_getContext(image_data.image_width, image_data.image_height, AV_PIX_FMT_RGB24,
+												image_data.image_width, image_data.image_height, pixel_format,
+												SWS_FAST_BILINEAR, 0, 0, 0);
 
-	sws_scale(context, (const uint8_t * const *)src_picture.data,
-			src_picture.linesize, 0, image_data.image_height,
-			dst_picture.data, dst_picture.linesize);
+	sws_scale(context, (const uint8_t *const *) src_picture.data, src_picture.linesize, 0, image_data.image_height,
+			  dst_picture.data, dst_picture.linesize);
 
-	int picture_size = avpicture_get_size(pixel_format,
-			image_data.image_width, image_data.image_height);
+	int picture_size = avpicture_get_size(pixel_format, image_data.image_width, image_data.image_height);
 	if (picture_size < 0) {
 		avpicture_free(&dst_picture);
 		MEDIA_VISION_FUNCTION_LEAVE();
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 	}
-	*cvt_buffer_size = (unsigned long)picture_size;
+	*cvt_buffer_size = (unsigned long) picture_size;
 
-	(*dst_buffer) = (unsigned char*)malloc(*cvt_buffer_size);
+	(*dst_buffer) = (unsigned char *) malloc(*cvt_buffer_size);
 	memcpy(*dst_buffer, dst_picture.data[0], *cvt_buffer_size);
 
 	avpicture_free(&dst_picture);
@@ -249,15 +246,15 @@ int find_max_y(const mv_quadrangle_s *quadrangle, int *maxY)
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-bool _mv_engine_config_supported_attribute(mv_config_attribute_type_e attribute_type,
-		const char *attribute_name, void *user_data)
+bool _mv_engine_config_supported_attribute(mv_config_attribute_type_e attribute_type, const char *attribute_name,
+										   void *user_data)
 {
 	mvprintw(current_y++, MINX, "Callback call for engine configuration attribute");
 
 	if (user_data == NULL)
 		return false;
 
-	mv_engine_config_h mv_engine_config = (mv_engine_config_h *)user_data;
+	mv_engine_config_h mv_engine_config = (mv_engine_config_h *) user_data;
 
 	int int_value = 0;
 	double double_value = 0.0;
@@ -266,47 +263,37 @@ bool _mv_engine_config_supported_attribute(mv_config_attribute_type_e attribute_
 	switch (attribute_type) {
 	case MV_ENGINE_CONFIG_ATTR_TYPE_DOUBLE:
 		if (MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE ==
-			mv_engine_config_get_double_attribute(
-						mv_engine_config, attribute_name, &double_value)) {
-			mvprintw(current_y++, MINX, "Default double attribute %s wasn't set in engine",
-					attribute_name);
+			mv_engine_config_get_double_attribute(mv_engine_config, attribute_name, &double_value)) {
+			mvprintw(current_y++, MINX, "Default double attribute %s wasn't set in engine", attribute_name);
 			return false;
 		}
-		mvprintw(current_y++, MINX, "Default double attribute %s was set to %f in engine",
-					attribute_name, double_value);
+		mvprintw(current_y++, MINX, "Default double attribute %s was set to %f in engine", attribute_name,
+				 double_value);
 		break;
 	case MV_ENGINE_CONFIG_ATTR_TYPE_INTEGER:
 		if (MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE ==
-			mv_engine_config_get_int_attribute(
-						mv_engine_config, attribute_name, &int_value)) {
-			mvprintw(current_y++, MINX, "Default integer attribute %s wasn't set in engine",
-					attribute_name);
+			mv_engine_config_get_int_attribute(mv_engine_config, attribute_name, &int_value)) {
+			mvprintw(current_y++, MINX, "Default integer attribute %s wasn't set in engine", attribute_name);
 			return false;
 		}
-		mvprintw(current_y++, MINX, "Default integer attribute %s was set to %d in engine",
-				attribute_name, int_value);
+		mvprintw(current_y++, MINX, "Default integer attribute %s was set to %d in engine", attribute_name, int_value);
 		break;
 	case MV_ENGINE_CONFIG_ATTR_TYPE_BOOLEAN:
 		if (MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE ==
-			mv_engine_config_get_bool_attribute(
-						mv_engine_config, attribute_name, &bool_value)) {
-			mvprintw(current_y++, MINX, "Default bool attribute %s wasn't set in engine",
-					attribute_name);
+			mv_engine_config_get_bool_attribute(mv_engine_config, attribute_name, &bool_value)) {
+			mvprintw(current_y++, MINX, "Default bool attribute %s wasn't set in engine", attribute_name);
 			return false;
 		}
-		mvprintw(current_y++, MINX, "Default bool attribute %s was set to %s in engine",
-					attribute_name,  bool_value ? "TRUE" : "FALSE");
+		mvprintw(current_y++, MINX, "Default bool attribute %s was set to %s in engine", attribute_name,
+				 bool_value ? "TRUE" : "FALSE");
 		break;
 	case MV_ENGINE_CONFIG_ATTR_TYPE_STRING:
 		if (MEDIA_VISION_ERROR_KEY_NOT_AVAILABLE ==
-			mv_engine_config_get_string_attribute(
-						mv_engine_config, attribute_name, &str_value)) {
-			mvprintw(current_y++, MINX, "Default string attribute %s wasn't set in engine",
-					attribute_name);
+			mv_engine_config_get_string_attribute(mv_engine_config, attribute_name, &str_value)) {
+			mvprintw(current_y++, MINX, "Default string attribute %s wasn't set in engine", attribute_name);
 			return false;
 		}
-		mvprintw(current_y++, MINX, "Default string attribute %s was set to %s in engine",
-				attribute_name, str_value);
+		mvprintw(current_y++, MINX, "Default string attribute %s was set to %s in engine", attribute_name, str_value);
 		if (str_value != NULL) {
 			free(str_value);
 			str_value = NULL;
@@ -320,14 +307,9 @@ bool _mv_engine_config_supported_attribute(mv_config_attribute_type_e attribute_
 	return true;
 }
 
-void barcode_detected_cb(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		const mv_quadrangle_s *barcodes_locations,
-		const char *messages[],
-		const mv_barcode_type_e *types,
-		int number_of_barcodes,
-		void *user_data)
+void barcode_detected_cb(mv_source_h source, mv_engine_config_h engine_cfg, const mv_quadrangle_s *barcodes_locations,
+						 const char *messages[], const mv_barcode_type_e *types, int number_of_barcodes,
+						 void *user_data)
 {
 	MEDIA_VISION_FUNCTION_ENTER();
 
@@ -348,8 +330,8 @@ void barcode_detected_cb(
 			user_data == NULL) {
 			mvprintw(current_y++, MINX, "ERROR : Creating out image is impossible.");
 		} else {
-			file_name = ((barcode_model_s *)user_data)->out_file_name;
-			draw_buffer = ((barcode_model_s *)user_data)->out_buffer_ptr;
+			file_name = ((barcode_model_s *) user_data)->out_file_name;
+			draw_buffer = ((barcode_model_s *) user_data)->out_buffer_ptr;
 			image_data.image_colorspace = MEDIA_VISION_COLORSPACE_RGB888;
 			is_source_data_loaded = 1;
 		}
@@ -422,17 +404,10 @@ void barcode_detected_cb(
 					continue;
 				}
 
-				const int drawing_color[] = {255, 0, 0};
-
-				if (MEDIA_VISION_ERROR_NONE != draw_rectangle_on_buffer(
-							minX,
-							minY,
-							maxX,
-							maxY,
-							6,
-							drawing_color,
-							&image_data,
-							draw_buffer))
+				const int drawing_color[] = { 255, 0, 0 };
+
+				if (MEDIA_VISION_ERROR_NONE !=
+					draw_rectangle_on_buffer(minX, minY, maxX, maxY, 6, drawing_color, &image_data, draw_buffer))
 					continue;
 			}
 		}
@@ -454,8 +429,7 @@ int generate_barcode_to_image(barcode_model_s model)
 {
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	if (model.message   == NULL ||
-			model.file_name == NULL) {
+	if (model.message == NULL || model.file_name == NULL) {
 		MEDIA_VISION_FUNCTION_LEAVE();
 
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -467,58 +441,59 @@ int generate_barcode_to_image(barcode_model_s model)
 	int err = mv_create_engine_config(&mv_engine_config);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Errors were occurred during creating the media engine "
-				"config : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Errors were occurred during creating the media engine "
+				 "config : %i",
+				 err);
 		MEDIA_VISION_FUNCTION_LEAVE();
 
 		return err;
 	}
 
-	err = mv_engine_config_set_int_attribute(mv_engine_config,
-											MV_BARCODE_GENERATE_ATTR_TEXT,
-											model.is_hrt);
+	err = mv_engine_config_set_int_attribute(mv_engine_config, MV_BARCODE_GENERATE_ATTR_TEXT, model.is_hrt);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Errors were occurred during set integer attribute to "
-				"media engine config : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Errors were occurred during set integer attribute to "
+				 "media engine config : %i",
+				 err);
 		goto cleanup;
 	}
 
-	err = mv_engine_config_set_string_attribute(mv_engine_config,
-											MV_BARCODE_GENERATE_ATTR_COLOR_FRONT,
-											model.front_color);
+	err = mv_engine_config_set_string_attribute(mv_engine_config, MV_BARCODE_GENERATE_ATTR_COLOR_FRONT,
+												model.front_color);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Errors were occurred during set string attribute to "
-				"media engine config : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Errors were occurred during set string attribute to "
+				 "media engine config : %i",
+				 err);
 		goto cleanup;
 	}
 
-	err = mv_engine_config_set_string_attribute(mv_engine_config,
-											MV_BARCODE_GENERATE_ATTR_COLOR_BACK,
-											model.back_color);
+	err = mv_engine_config_set_string_attribute(mv_engine_config, MV_BARCODE_GENERATE_ATTR_COLOR_BACK,
+												model.back_color);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Errors were occurred during set string attribute to "
-				"media engine config : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Errors were occurred during set string attribute to "
+				 "media engine config : %i",
+				 err);
 		goto cleanup;
 	}
-	err = mv_barcode_generate_image(mv_engine_config, model.message,
-									model.width, model.height, model.type,
-									model.mode, model.ecc, model.version,
-									model.file_name, model.out_image_format);
+	err = mv_barcode_generate_image(mv_engine_config, model.message, model.width, model.height, model.type, model.mode,
+									model.ecc, model.version, model.file_name, model.out_image_format);
 	if (MEDIA_VISION_ERROR_NONE != err)
-		mvprintw(current_y++, MINX, "ERROR : Errors were occurred during generate image error : %i",
-			   err);
+		mvprintw(current_y++, MINX, "ERROR : Errors were occurred during generate image error : %i", err);
 cleanup:
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		int err2 = mv_destroy_engine_config(mv_engine_config);
 		if (MEDIA_VISION_ERROR_NONE != err2)
 			mvprintw(current_y++, MINX, "ERROR : Errors were occurred during destroying the media engine config : %i",
-				   err2);
+					 err2);
 
 	} else {
 		err = mv_destroy_engine_config(mv_engine_config);
 		if (MEDIA_VISION_ERROR_NONE != err)
 			mvprintw(current_y++, MINX, "ERROR : Errors were occurred during destroying the media engine config : %i",
-				   err);
+					 err);
 	}
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return err;
@@ -527,8 +502,7 @@ int generate_barcode_to_source(barcode_model_s model)
 {
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	if (model.message   == NULL ||
-		model.file_name == NULL) {
+	if (model.message == NULL || model.file_name == NULL) {
 		MEDIA_VISION_FUNCTION_LEAVE();
 
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -539,8 +513,10 @@ int generate_barcode_to_source(barcode_model_s model)
 	mv_source_h source = NULL;
 	int err = mv_create_source(&source);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Error occurred when trying to create Media Vision "
-				"source. Error code : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Error occurred when trying to create Media Vision "
+				 "source. Error code : %i",
+				 err);
 
 		MEDIA_VISION_FUNCTION_LEAVE();
 
@@ -554,41 +530,41 @@ int generate_barcode_to_source(barcode_model_s model)
 	mv_engine_config_h mv_engine_config;
 	err = mv_create_engine_config(&mv_engine_config);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Errors were occurred during creating the media engine "
-				"config : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Errors were occurred during creating the media engine "
+				 "config : %i",
+				 err);
 		goto clean_source;
 	}
 
-	err = mv_engine_config_set_string_attribute(mv_engine_config,
-											MV_BARCODE_GENERATE_ATTR_COLOR_FRONT,
-											model.front_color);
+	err = mv_engine_config_set_string_attribute(mv_engine_config, MV_BARCODE_GENERATE_ATTR_COLOR_FRONT,
+												model.front_color);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Errors were occurred during set string attribute to "
-				"media engine config : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Errors were occurred during set string attribute to "
+				 "media engine config : %i",
+				 err);
 		goto clean_all;
 	}
 
-	err = mv_engine_config_set_string_attribute(mv_engine_config,
-											MV_BARCODE_GENERATE_ATTR_COLOR_BACK,
-											model.back_color);
+	err = mv_engine_config_set_string_attribute(mv_engine_config, MV_BARCODE_GENERATE_ATTR_COLOR_BACK,
+												model.back_color);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Errors were occurred during set string attribute to "
-				"media engine config : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Errors were occurred during set string attribute to "
+				 "media engine config : %i",
+				 err);
 		goto clean_all;
 	}
 
-	err = mv_barcode_generate_source(
-			mv_engine_config,
-			model.message,
-			model.type,
-			model.mode,
-			model.ecc,
-			model.version,
-			source);
+	err = mv_barcode_generate_source(mv_engine_config, model.message, model.type, model.mode, model.ecc, model.version,
+									 source);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Error occurred during generation barcode to the "
-				"Media Vision source. Error code : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Error occurred during generation barcode to the "
+				 "Media Vision source. Error code : %i",
+				 err);
 		goto clean_all;
 	}
 
@@ -600,29 +576,37 @@ int generate_barcode_to_source(barcode_model_s model)
 
 	err = mv_source_get_buffer(source, &data_buffer, &buffer_size);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Error occurred when trying to get buffer from "
-				"Media Vision source. Error code : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Error occurred when trying to get buffer from "
+				 "Media Vision source. Error code : %i",
+				 err);
 		goto clean_all;
 	}
 
 	err = mv_source_get_width(source, &image_width);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Error occurred when trying to get width of "
-				"Media Vision source. Error code : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Error occurred when trying to get width of "
+				 "Media Vision source. Error code : %i",
+				 err);
 		goto clean_all;
 	}
 
 	err = mv_source_get_height(source, &image_height);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Error occurred when trying to get height of "
-				"Media Vision source. Error code : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Error occurred when trying to get height of "
+				 "Media Vision source. Error code : %i",
+				 err);
 		goto clean_all;
 	}
 
 	err = mv_source_get_colorspace(source, &image_colorspace);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Error occurred when trying to get colorspace of "
-				"Media Vision source. Error code : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Error occurred when trying to get colorspace of "
+				 "Media Vision source. Error code : %i",
+				 err);
 		goto clean_all;
 	}
 
@@ -638,7 +622,7 @@ int generate_barcode_to_source(barcode_model_s model)
 		}
 	} else {
 		size_t size = strlen(model.file_name);
-		jpeg_file_name = (char*)malloc(size + 5);
+		jpeg_file_name = (char *) malloc(size + 5);
 		if (jpeg_file_name == NULL) {
 			err = MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 			goto clean_all;
@@ -648,8 +632,10 @@ int generate_barcode_to_source(barcode_model_s model)
 	}
 	err = save_image_from_buffer(jpeg_file_name, data_buffer, &image_data, 100);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Error occurred when try to save image from buffer."
-				"Error code : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Error occurred when try to save image from buffer."
+				 "Error code : %i",
+				 err);
 	}
 	free(jpeg_file_name);
 clean_all:
@@ -657,24 +643,24 @@ clean_all:
 		int err2 = mv_destroy_engine_config(mv_engine_config);
 		if (MEDIA_VISION_ERROR_NONE != err2)
 			mvprintw(current_y++, MINX, "ERROR : Errors were occurred during destroying the media engine config : %i",
-				   err2);
+					 err2);
 	} else {
 		err = mv_destroy_engine_config(mv_engine_config);
 		if (MEDIA_VISION_ERROR_NONE != err)
 			mvprintw(current_y++, MINX, "ERROR : Errors were occurred during destroying the media engine config : %i",
-				   err);
+					 err);
 	}
 clean_source:
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2)
-			mvprintw(current_y++, MINX, "ERROR : Error occurred when try to destroy Media Vision source. Error code : %i",
-				   err2);
+			mvprintw(current_y++, MINX,
+					 "ERROR : Error occurred when try to destroy Media Vision source. Error code : %i", err2);
 	} else {
 		err = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err)
-			mvprintw(current_y++, MINX, "ERROR : Error occurred when try to destroy Media Vision source. Error code : %i",
-				   err);
+			mvprintw(current_y++, MINX,
+					 "ERROR : Error occurred when try to destroy Media Vision source. Error code : %i", err);
 	}
 	MEDIA_VISION_FUNCTION_LEAVE();
 	return err;
@@ -688,8 +674,7 @@ int detect_barcode(barcode_model_s model, mv_rectangle_s roi)
 	unsigned long buffer_size = 0;
 	image_data_s image_data;
 
-	int err = load_image_to_buffer(
-			model.file_name, &data_buffer, &buffer_size, &image_data);
+	int err = load_image_to_buffer(model.file_name, &data_buffer, &buffer_size, &image_data);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		mvprintw(current_y++, MINX, "ERROR : Errors were occurred during opening the file!!! code : %i", err);
 
@@ -727,13 +712,13 @@ int detect_barcode(barcode_model_s model, mv_rectangle_s roi)
 
 	mv_engine_config_foreach_supported_attribute(_mv_engine_config_supported_attribute, mv_engine_config);
 
-	err = mv_engine_config_set_int_attribute(
-			mv_engine_config,
-			MV_BARCODE_DETECT_ATTR_TARGET,
-			MV_BARCODE_DETECT_ATTR_TARGET_ALL);
+	err = mv_engine_config_set_int_attribute(mv_engine_config, MV_BARCODE_DETECT_ATTR_TARGET,
+											 MV_BARCODE_DETECT_ATTR_TARGET_ALL);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		mvprintw(current_y++, MINX, "ERROR : Errors were occurred during target attribute"
-				"configuration : %i", err);
+		mvprintw(current_y++, MINX,
+				 "ERROR : Errors were occurred during target attribute"
+				 "configuration : %i",
+				 err);
 	}
 
 	mv_source_h source;
@@ -755,8 +740,8 @@ int detect_barcode(barcode_model_s model, mv_rectangle_s roi)
 		return err;
 	}
 
-	err = mv_source_fill_by_buffer(source, converted_buffer, converted_buffer_size,
-			image_data.image_width, image_data.image_height, model.colorspace);
+	err = mv_source_fill_by_buffer(source, converted_buffer, converted_buffer_size, image_data.image_width,
+								   image_data.image_height, model.colorspace);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		mvprintw(current_y++, MINX, "ERROR : Errors were occurred during filling the source!!! code : %i", err);
 
@@ -816,7 +801,7 @@ int input_string(const char *prompt, size_t max_len, char **string)
 	size_t string_len = strlen(buffer);
 	buffer[string_len] = '\0';
 	size_t real_string_len = string_len + 1;
-	*string = (char*)malloc(real_string_len * sizeof(char));
+	*string = (char *) malloc(real_string_len * sizeof(char));
 	if (*string == NULL) {
 		MEDIA_VISION_FUNCTION_LEAVE();
 		return -1;
@@ -826,7 +811,7 @@ int input_string(const char *prompt, size_t max_len, char **string)
 	size_t str_len = strlen(*string);
 
 	if (test_interval > 0)
-		 sleep(test_interval);
+		sleep(test_interval);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 
@@ -850,7 +835,7 @@ int input_size(const char *prompt, size_t max_size, size_t *size)
 	int ret = (*size > max_size ? -1 : 0);
 
 	if (test_interval > 0)
-		 sleep(test_interval);
+		sleep(test_interval);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 
@@ -874,7 +859,7 @@ int input_int(const char *prompt, int min_value, int max_value, int *value)
 	int ret = (*value < min_value || *value > max_value ? -1 : 0);
 
 	if (test_interval > 0)
-		 sleep(test_interval);
+		sleep(test_interval);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 
@@ -906,7 +891,7 @@ int show_menu(const char *title, const int *options, const char **names, int cnt
 		mvaddstr(current_y++, MINX, "Your Choice : ");
 		getstr(&buf);
 		selection = atoi(buf);
-		condition = selection > options[cnt-1];
+		condition = selection > options[cnt - 1];
 		if (condition)
 			mvprintw(current_y++, MINX, "You pressed invalid menu, try again");
 
@@ -914,7 +899,7 @@ int show_menu(const char *title, const int *options, const char **names, int cnt
 	} while (condition);
 
 	if (test_interval > 0)
-		 sleep(test_interval);
+		sleep(test_interval);
 
 	MEDIA_VISION_FUNCTION_LEAVE();
 
@@ -926,8 +911,8 @@ mv_barcode_type_e select_type(void)
 	mv_barcode_type_e selected_type = MV_BARCODE_UNKNOWN;
 	int sel_opt = 0;
 	const int options[] = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 };
-	const char *names[] = { "qr", "upca", "upce", "ean8", "ean13", "code39", "code128", "interleave25",
-								"ean2", "ean5", "code93", "codabar", "databar", "databarExpand" };
+	const char *names[] = { "qr",			"upca", "upce", "ean8",	  "ean13",	 "code39",	"code128",
+							"interleave25", "ean2", "ean5", "code93", "codabar", "databar", "databarExpand" };
 
 	MEDIA_VISION_FUNCTION_ENTER();
 
@@ -1093,7 +1078,7 @@ int select_version(void)
 
 	int sel_opt = 0;
 	while (sel_opt == 0) {
-		const int options[] = {1, 40};
+		const int options[] = { 1, 40 };
 		const char *names[] = { "1..", "..40" };
 		sel_opt = show_menu("Select QR version : ", options, names, ARRAY_SIZE(options));
 		if (sel_opt < 1 || sel_opt > 40)
@@ -1170,22 +1155,28 @@ int perform_detect()
 {
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	barcode_model_s detect_model = {
-		MV_BARCODE_UNKNOWN,
-		MV_BARCODE_QR_ECC_UNAVAILABLE,
-		MV_BARCODE_QR_MODE_UNAVAILABLE,
-		0,
-		0, 0, 0,
-		MV_BARCODE_IMAGE_FORMAT_PNG,
-		MEDIA_VISION_COLORSPACE_INVALID,
-		NULL, NULL, NULL, NULL, NULL, NULL };
+	barcode_model_s detect_model = { MV_BARCODE_UNKNOWN,
+									 MV_BARCODE_QR_ECC_UNAVAILABLE,
+									 MV_BARCODE_QR_MODE_UNAVAILABLE,
+									 0,
+									 0,
+									 0,
+									 0,
+									 MV_BARCODE_IMAGE_FORMAT_PNG,
+									 MEDIA_VISION_COLORSPACE_INVALID,
+									 NULL,
+									 NULL,
+									 NULL,
+									 NULL,
+									 NULL,
+									 NULL };
 
 	while (input_string("Input file name to be analyzed : ", 1024, &(detect_model.file_name)) == -1)
 		mvprintw(current_y++, MINX, "Incorrect input! Try again.");
 
 	LOGI("Barcode input image has been specified");
 
-	mv_rectangle_s roi = { {0, 0}, 0, 0 };
+	mv_rectangle_s roi = { { 0, 0 }, 0, 0 };
 
 	while (input_int("Input x coordinate for ROI top left vertex : ", 0, 10000, &(roi.point.x)) == -1)
 		mvprintw(current_y++, MINX, "Incorrect input! Try again.");
@@ -1206,28 +1197,20 @@ int perform_detect()
 
 	LOGI("Barcode output image has been specified");
 
-	const int options[] = { MEDIA_VISION_COLORSPACE_Y800,
-								MEDIA_VISION_COLORSPACE_I420,
-								MEDIA_VISION_COLORSPACE_NV12,
-								MEDIA_VISION_COLORSPACE_YV12,
-								MEDIA_VISION_COLORSPACE_NV21,
-								MEDIA_VISION_COLORSPACE_YUYV,
-								MEDIA_VISION_COLORSPACE_UYVY,
-								MEDIA_VISION_COLORSPACE_422P,
-								MEDIA_VISION_COLORSPACE_RGB565,
-								MEDIA_VISION_COLORSPACE_RGB888,
-								MEDIA_VISION_COLORSPACE_RGBA };
-	const char *names[] = { "Y800", "I420", "NV12", "YV12", "NV21",
-								"YUYV", "UYVY", "422P", "RGB565",
-								"RGB888", "RGBA" };
+	const int options[] = { MEDIA_VISION_COLORSPACE_Y800,	MEDIA_VISION_COLORSPACE_I420,
+							MEDIA_VISION_COLORSPACE_NV12,	MEDIA_VISION_COLORSPACE_YV12,
+							MEDIA_VISION_COLORSPACE_NV21,	MEDIA_VISION_COLORSPACE_YUYV,
+							MEDIA_VISION_COLORSPACE_UYVY,	MEDIA_VISION_COLORSPACE_422P,
+							MEDIA_VISION_COLORSPACE_RGB565, MEDIA_VISION_COLORSPACE_RGB888,
+							MEDIA_VISION_COLORSPACE_RGBA };
+	const char *names[] = { "Y800", "I420", "NV12", "YV12", "NV21", "YUYV", "UYVY", "422P", "RGB565", "RGB888", "RGBA" };
 
 	while (true) {
 		int sel_opt = show_menu("Select colorspace to test detector on : ", options, names, ARRAY_SIZE(options));
-		if (sel_opt < MEDIA_VISION_COLORSPACE_Y800 ||
-			sel_opt > MEDIA_VISION_COLORSPACE_RGBA)
+		if (sel_opt < MEDIA_VISION_COLORSPACE_Y800 || sel_opt > MEDIA_VISION_COLORSPACE_RGBA)
 			continue;
 
-		detect_model.colorspace = (mv_colorspace_e)sel_opt;
+		detect_model.colorspace = (mv_colorspace_e) sel_opt;
 		LOGI("User selection is %i", sel_opt);
 		break;
 	}
@@ -1252,15 +1235,21 @@ int perform_generate(void)
 {
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	barcode_model_s generate_model = {
-			MV_BARCODE_UNKNOWN,
-			MV_BARCODE_QR_ECC_UNAVAILABLE,
-			MV_BARCODE_QR_MODE_UNAVAILABLE,
-			0,
-			0, 0, 0,
-			MV_BARCODE_IMAGE_FORMAT_PNG,
-			MEDIA_VISION_COLORSPACE_INVALID,
-			NULL, NULL, NULL, NULL, NULL, NULL };
+	barcode_model_s generate_model = { MV_BARCODE_UNKNOWN,
+									   MV_BARCODE_QR_ECC_UNAVAILABLE,
+									   MV_BARCODE_QR_MODE_UNAVAILABLE,
+									   0,
+									   0,
+									   0,
+									   0,
+									   MV_BARCODE_IMAGE_FORMAT_PNG,
+									   MEDIA_VISION_COLORSPACE_INVALID,
+									   NULL,
+									   NULL,
+									   NULL,
+									   NULL,
+									   NULL,
+									   NULL };
 
 	generation_fcn_e gen_fcn = select_gen_function();
 	generate_model.type = select_type();
@@ -1317,10 +1306,8 @@ int perform_generate(void)
 		LOGI("Barcode output file height has been specified");
 	}
 
-	const int err =
-			gen_fcn == MV_TS_GENERATE_TO_IMAGE_FCN ?
-			generate_barcode_to_image(generate_model) :
-			generate_barcode_to_source(generate_model);
+	const int err = gen_fcn == MV_TS_GENERATE_TO_IMAGE_FCN ? generate_barcode_to_image(generate_model) :
+															 generate_barcode_to_source(generate_model);
 
 	if (generate_model.message != NULL)
 		free(generate_model.message);
@@ -1353,16 +1340,16 @@ int perform_generate(void)
 	return 0;
 }
 
-static error_t parse_opt (int key, char *arg, struct argp_state *state)
+static error_t parse_opt(int key, char *arg, struct argp_state *state)
 {
 	struct arguments *arguments = state->input;
 
 	switch (key) {
-    case 'm':
-		arguments->mode = arg ? atoi (arg) : 0;
-      break;
-    case 'i':
-		arguments->interval = arg ? atoi (arg) : 0;
+	case 'm':
+		arguments->mode = arg ? atoi(arg) : 0;
+		break;
+	case 'i':
+		arguments->interval = arg ? atoi(arg) : 0;
 		if (arguments->interval > MAXINTERVAL) {
 			printf("WARN : value is out of range, reset to max value.\n");
 			arguments->interval = MAXINTERVAL;
@@ -1370,13 +1357,13 @@ static error_t parse_opt (int key, char *arg, struct argp_state *state)
 			printf("WARN : value is out of range, reset to min value.\n");
 			arguments->interval = MININTERVAL;
 		}
-      break;
+		break;
 	case ARGP_KEY_NO_ARGS:
 		/* do nothing */
-    break;
-    default:
+		break;
+	default:
 		return ARGP_ERR_UNKNOWN;
-    }
+	}
 	return 0;
 }
 
@@ -1396,7 +1383,7 @@ int main(int argc, char *argv[])
 	arguments.mode = 0;
 	arguments.interval = 0;
 
-	argp_parse (&argp, argc, argv, 0, 0, &arguments);
+	argp_parse(&argp, argc, argv, 0, 0, &arguments);
 	mode = arguments.mode;
 	test_interval = arguments.interval;
 
diff --git a/test/testsuites/barcode/test_barcode.cpp b/test/testsuites/barcode/test_barcode.cpp
index a4247dc..7dc302a 100644
--- a/test/testsuites/barcode/test_barcode.cpp
+++ b/test/testsuites/barcode/test_barcode.cpp
@@ -17,10 +17,9 @@ using TestParams = tuple<string, string>;
 	MV_CONFIG_PATH   \
 	"/res/media-vision-barcodes.json"
 
-void barcode_detected_cb(mv_source_h source, mv_engine_config_h engine_cfg,
-						 const mv_quadrangle_s *barcodes_locations,
-						 const char *messages[], const mv_barcode_type_e *types,
-						 int number_of_barcodes, void *user_data)
+void barcode_detected_cb(mv_source_h source, mv_engine_config_h engine_cfg, const mv_quadrangle_s *barcodes_locations,
+						 const char *messages[], const mv_barcode_type_e *types, int number_of_barcodes,
+						 void *user_data)
 {
 	EXPECT_EQ(number_of_barcodes, 1);
 	EXPECT_STREQ(messages[0], (const char *) user_data);
@@ -66,15 +65,13 @@ class TestBarcode : public testing::TestWithParam<TestParams>
 public:
 	TestBarcode()
 	{
-		EXPECT_EQ(mv_create_engine_config(&engine_cfg),
-				  MEDIA_VISION_ERROR_NONE);
+		EXPECT_EQ(mv_create_engine_config(&engine_cfg), MEDIA_VISION_ERROR_NONE);
 		EXPECT_EQ(mv_create_source(&mv_source), MEDIA_VISION_ERROR_NONE);
 	}
 	~TestBarcode()
 	{
 		EXPECT_EQ(mv_destroy_source(mv_source), MEDIA_VISION_ERROR_NONE);
-		EXPECT_EQ(mv_destroy_engine_config(engine_cfg),
-				  MEDIA_VISION_ERROR_NONE);
+		EXPECT_EQ(mv_destroy_engine_config(engine_cfg), MEDIA_VISION_ERROR_NONE);
 	}
 	mv_engine_config_h engine_cfg;
 	mv_source_h mv_source;
@@ -85,21 +82,16 @@ TEST_P(TestBarcode, Detection)
 	auto image_name = BARCODE_IMG_PREFIX + get<0>(GetParam());
 	auto message = get<1>(GetParam());
 
-	EXPECT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(
-					  image_name.c_str(), mv_source),
+	EXPECT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(image_name.c_str(), mv_source),
 			  MEDIA_VISION_ERROR_NONE);
 
 	mv_rectangle_s roi = { { 0, 0 }, 0, 0 };
 	mv_source_get_width(mv_source, (unsigned int *) &(roi.width));
 	mv_source_get_width(mv_source, (unsigned int *) &(roi.height));
-	mv_engine_config_set_int_attribute(engine_cfg,
-									   MV_BARCODE_DETECT_ATTR_TARGET,
-									   MV_BARCODE_DETECT_ATTR_TARGET_ALL);
+	mv_engine_config_set_int_attribute(engine_cfg, MV_BARCODE_DETECT_ATTR_TARGET, MV_BARCODE_DETECT_ATTR_TARGET_ALL);
 
-	EXPECT_EQ(mv_barcode_detect(mv_source, engine_cfg, roi, barcode_detected_cb,
-								(void *) message.c_str()),
+	EXPECT_EQ(mv_barcode_detect(mv_source, engine_cfg, roi, barcode_detected_cb, (void *) message.c_str()),
 			  MEDIA_VISION_ERROR_NONE);
 }
 
-INSTANTIATE_TEST_CASE_P(GeneralAndSpecial, TestBarcode,
-						testing::ValuesIn(ReadDetPositive1()));
\ No newline at end of file
+INSTANTIATE_TEST_CASE_P(GeneralAndSpecial, TestBarcode, testing::ValuesIn(ReadDetPositive1()));
\ No newline at end of file
diff --git a/test/testsuites/common/image_helper/include/ImageHelper.h b/test/testsuites/common/image_helper/include/ImageHelper.h
index a2e01bd..f5e562d 100644
--- a/test/testsuites/common/image_helper/include/ImageHelper.h
+++ b/test/testsuites/common/image_helper/include/ImageHelper.h
@@ -27,31 +27,35 @@
  * @brief  ImageHelper class definition.
  */
 
-namespace cv {
-	template<typename _Tp> class Scalar_;
-	typedef Scalar_<double> Scalar;
+namespace cv
+{
+template<typename _Tp> class Scalar_;
+typedef Scalar_<double> Scalar;
 
-	class VideoCapture;
-	class VideoWriter;
+class VideoCapture;
+class VideoWriter;
 }
 
-namespace MediaVision {
-namespace Common {
-
+namespace MediaVision
+{
+namespace Common
+{
 /**
  * @class ImageHelper
  * @brief Helper class that provides set of useful methods
  *        for image management.
  */
-class ImageHelper {
+class ImageHelper
+{
 public:
 	/**
 	 * @brief Structure to keep information about width, height and colorspace of an image.
 	 */
-	struct ImageData {
-		unsigned int imageWidth;                 /**< Image width */
-		unsigned int imageHeight;                /**< Image height */
-		mv_colorspace_e imageColorspace;         /**< Image colorspace */
+	struct ImageData
+	{
+		unsigned int imageWidth; /**< Image width */
+		unsigned int imageHeight; /**< Image height */
+		mv_colorspace_e imageColorspace; /**< Image colorspace */
 	};
 
 	/**
@@ -71,11 +75,8 @@ public:
 	  * @see ImageHelper::saveImageFromBuffer()
 	  * @see ImageHelper::destroyLoadedBuffer()
 	  */
-	static int loadImageToBuffer(
-			const char *filePath,
-			unsigned char **pDataBuffer,
-			unsigned long *pBufferSize,
-			ImageData *pImageData);
+	static int loadImageToBuffer(const char *filePath, unsigned char **pDataBuffer, unsigned long *pBufferSize,
+								 ImageData *pImageData);
 
 	static int loadImageToSource(const char *filePath, mv_source_h source);
 
@@ -93,11 +94,8 @@ public:
 	 *
 	 * @see ImageHelper::loadImageToBuffer()
 	 */
-	static int saveImageFromBuffer(
-			const char *filePath,
-			unsigned char *pDataBuffer,
-			const ImageData& imageData,
-			int quality = 100);
+	static int saveImageFromBuffer(const char *filePath, unsigned char *pDataBuffer, const ImageData &imageData,
+								   int quality = 100);
 
 	/**
 	 * @brief Destroys loaded buffer by loadImageToBuffer().
@@ -134,15 +132,9 @@ public:
 	 *                                    which will be used for rectangle drawing
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	static int drawRectangleOnBuffer(
-			int topLeftVertexX,
-			int topLeftVertexY,
-			int bottomRightVertexX,
-			int bottomRightVertexY,
-			int thickness,
-			const cv::Scalar& color,
-			const ImageData& imageData,
-			unsigned char *pDataBuffer);
+	static int drawRectangleOnBuffer(int topLeftVertexX, int topLeftVertexY, int bottomRightVertexX,
+									 int bottomRightVertexY, int thickness, const cv::Scalar &color,
+									 const ImageData &imageData, unsigned char *pDataBuffer);
 
 	/**
 	 * @brief Draws the quadrangle of specified size on the image data buffer.
@@ -159,12 +151,8 @@ public:
 	 *                                    which will be used for quadrangle drawing
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	static int drawQuadrangleOnBuffer(
-			mv_quadrangle_s location,
-			int thickness,
-			const cv::Scalar& color,
-			const ImageData& imageData,
-			unsigned char *pDataBuffer);
+	static int drawQuadrangleOnBuffer(mv_quadrangle_s location, int thickness, const cv::Scalar &color,
+									  const ImageData &imageData, unsigned char *pDataBuffer);
 
 	/**
 	 * @brief Converts image data to the image data of RGB888 colorspace.
@@ -179,10 +167,8 @@ public:
 	 *                            a result of the conversion
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	static int convertBufferToRGB888(
-			const unsigned char *pInBuffer,
-			const ImageData& imageData,
-			unsigned char **pOutBuffer);
+	static int convertBufferToRGB888(const unsigned char *pInBuffer, const ImageData &imageData,
+									 unsigned char **pOutBuffer);
 
 	/**
 	 * @brief Determines number of channels (components) for the colorspace.
@@ -193,9 +179,7 @@ public:
 	 * @param [out] pComponentsNumber    Number of components to be determined
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	static int getNumberOfComponents(
-			mv_colorspace_e colorspace,
-			int *pComponentsNumber);
+	static int getNumberOfComponents(mv_colorspace_e colorspace, int *pComponentsNumber);
 
 private:
 	/**
@@ -211,10 +195,7 @@ private:
 	 *                            data in RGB888 colorspace format
 	 * @return @c 0 on success, otherwise a negative error value
 	 */
-	static int convertY800ToRGB(
-			const unsigned char *pInBuffer,
-			const ImageData& imageData,
-			unsigned char **pOutBuffer);
+	static int convertY800ToRGB(const unsigned char *pInBuffer, const ImageData &imageData, unsigned char **pOutBuffer);
 };
 
 } /* Common */
diff --git a/test/testsuites/common/image_helper/include/image_helper.h b/test/testsuites/common/image_helper/include/image_helper.h
index fe4ce92..16869f2 100644
--- a/test/testsuites/common/image_helper/include/image_helper.h
+++ b/test/testsuites/common/image_helper/include/image_helper.h
@@ -42,10 +42,11 @@ extern "C" {
  *
  * @since_tizen 3.0
  */
-typedef struct {
-	unsigned int image_width;                 /**< Image width */
-	unsigned int image_height;                /**< Image height */
-	mv_colorspace_e image_colorspace;         /**< Image colorspace */
+typedef struct
+{
+	unsigned int image_width; /**< Image width */
+	unsigned int image_height; /**< Image height */
+	mv_colorspace_e image_colorspace; /**< Image colorspace */
 } image_data_s;
 
 /**
@@ -65,11 +66,8 @@ typedef struct {
  * @see save_image_from_buffer()
  * @see destroy_loaded_buffer()
  */
-int load_image_to_buffer(
-		const char *file_path,
-		unsigned char **data_buffer,
-		unsigned long *buffer_size,
-		image_data_s *image_data);
+int load_image_to_buffer(const char *file_path, unsigned char **data_buffer, unsigned long *buffer_size,
+						 image_data_s *image_data);
 
 /**
  * @brief Saves image stored into @a pDataBuffer to the file in jpeg format.
@@ -85,11 +83,8 @@ int load_image_to_buffer(
  *
  * @see load_image_to_buffer()
  */
-int save_image_from_buffer(
-		const char *file_path,
-		unsigned char *data_buffer,
-		const image_data_s *image_data,
-		int quality);
+int save_image_from_buffer(const char *file_path, unsigned char *data_buffer, const image_data_s *image_data,
+						   int quality);
 
 /**
  * @brief Destroys loaded buffer by load_image_to_buffer().
@@ -120,15 +115,8 @@ int destroy_loaded_buffer(unsigned char *data_buffer);
  *                             be used for rectangle drawing
  * @return @c 0 on success, otherwise a negative error value
  */
-int draw_rectangle_on_buffer(
-		int tl_vertex_x,
-		int tl_vertex_y,
-		int br_vertex_x,
-		int br_vertex_y,
-		int thickness,
-		const int rgb_color[3],
-		const image_data_s *image_data,
-		unsigned char *data_buffer);
+int draw_rectangle_on_buffer(int tl_vertex_x, int tl_vertex_y, int br_vertex_x, int br_vertex_y, int thickness,
+							 const int rgb_color[3], const image_data_s *image_data, unsigned char *data_buffer);
 
 /**
  * @brief Draws the quadrangle of specified size on the image data buffer.
@@ -144,12 +132,8 @@ int draw_rectangle_on_buffer(
  *                                be used for quadrangle drawing
  * @return @c 0 on success, otherwise a negative error value
  */
-int draw_quadrangle_on_buffer(
-		mv_quadrangle_s location,
-		int thickness,
-		const int rgb_color[3],
-		const image_data_s *image_data,
-		unsigned char *data_buffer);
+int draw_quadrangle_on_buffer(mv_quadrangle_s location, int thickness, const int rgb_color[3],
+							  const image_data_s *image_data, unsigned char *data_buffer);
 
 /**
  * @brief Converts image data to the image data of RGB888 colorspace.
@@ -164,10 +148,8 @@ int draw_quadrangle_on_buffer(
  *                            a result of the conversion
  * @return @c 0 on success, otherwise a negative error value
  */
-int convert_buffer_to_RGB888(
-		const unsigned char *in_buffer,
-		const image_data_s *image_data,
-		unsigned char **out_buffer);
+int convert_buffer_to_RGB888(const unsigned char *in_buffer, const image_data_s *image_data,
+							 unsigned char **out_buffer);
 
 /**
  * @brief Determines number of channels (components) for the colorspace.
@@ -178,9 +160,7 @@ int convert_buffer_to_RGB888(
  * @param [out] components_number    Number of components to be determined
  * @return @c 0 on success, otherwise a negative error value
  */
-int get_number_of_components(
-		mv_colorspace_e colorspace,
-		int *components_number);
+int get_number_of_components(mv_colorspace_e colorspace, int *components_number);
 
 #ifdef __cplusplus
 }
diff --git a/test/testsuites/common/image_helper/src/ImageHelper.cpp b/test/testsuites/common/image_helper/src/ImageHelper.cpp
index 66c164f..b3f8550 100644
--- a/test/testsuites/common/image_helper/src/ImageHelper.cpp
+++ b/test/testsuites/common/image_helper/src/ImageHelper.cpp
@@ -34,11 +34,12 @@
  * @brief  The ImageHelper class methods implementation.
  */
 
-namespace MediaVision {
-namespace Common {
-
-namespace {
-
+namespace MediaVision
+{
+namespace Common
+{
+namespace
+{
 const int OPEN_CV_CHANNELS = 3;
 const mv_colorspace_e OPEN_CV_COLOR = MEDIA_VISION_COLORSPACE_RGB888;
 const int QUADRANGLE_VERTICES = 4;
@@ -54,14 +55,10 @@ std::vector<std::string> getJPGExtensions()
 
 } /* anonymous namespace */
 
-int ImageHelper::loadImageToBuffer(
-		const char *filePath,
-		unsigned char **pDataBuffer,
-		unsigned long *pBufferSize,
-		ImageData *pImageData)
+int ImageHelper::loadImageToBuffer(const char *filePath, unsigned char **pDataBuffer, unsigned long *pBufferSize,
+								   ImageData *pImageData)
 {
-	if (filePath == NULL || pDataBuffer == NULL ||
-		pBufferSize == NULL || pImageData == NULL)
+	if (filePath == NULL || pDataBuffer == NULL || pBufferSize == NULL || pImageData == NULL)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 
 	cv::Mat image;
@@ -96,18 +93,14 @@ int ImageHelper::loadImageToSource(const char *filePath, mv_source_h source)
 	cv::Mat image = cv::imread(filePath);
 	cv::cvtColor(image, image, CV_BGR2RGB);
 
-	if (!(mediaSource->fill(image.data, image.total() * image.elemSize(),
-							image.cols, image.rows, OPEN_CV_COLOR)))
+	if (!(mediaSource->fill(image.data, image.total() * image.elemSize(), image.cols, image.rows, OPEN_CV_COLOR)))
 		return MEDIA_VISION_ERROR_OUT_OF_MEMORY;
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int ImageHelper::saveImageFromBuffer(
-		const char *filePath,
-		unsigned char *pDataBuffer,
-		const ImageData& imageData,
-		int quality)
+int ImageHelper::saveImageFromBuffer(const char *filePath, unsigned char *pDataBuffer, const ImageData &imageData,
+									 int quality)
 {
 	if (filePath == NULL || pDataBuffer == NULL)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -124,12 +117,9 @@ int ImageHelper::saveImageFromBuffer(
 		for (size_t extNum = 0; extNum < JPG_EXTENSIONS.size(); ++extNum) {
 			if (resultFilePath.size() >= JPG_EXTENSIONS[extNum].size()) {
 				std::string givenExtension = resultFilePath.substr(
-						resultFilePath.length() - JPG_EXTENSIONS[extNum].size(),
-						JPG_EXTENSIONS[extNum].size());
+						resultFilePath.length() - JPG_EXTENSIONS[extNum].size(), JPG_EXTENSIONS[extNum].size());
 
-				std::transform(
-					givenExtension.begin(), givenExtension.end(),
-					givenExtension.begin(), ::tolower);
+				std::transform(givenExtension.begin(), givenExtension.end(), givenExtension.begin(), ::tolower);
 
 				if (givenExtension == JPG_EXTENSIONS[extNum]) {
 					rightExtensionFlag = true;
@@ -205,8 +195,7 @@ int ImageHelper::saveImageFromBuffer(
 	}
 
 	const int depth = CV_8U;
-	cv::Mat cvImage(cv::Size(width, height),
-					CV_MAKETYPE(depth, channelsNumber), pDataBuffer);
+	cv::Mat cvImage(cv::Size(width, height), CV_MAKETYPE(depth, channelsNumber), pDataBuffer);
 	cv::Mat cvBGRImage;
 	cv::cvtColor(cvImage, cvBGRImage, conversionType);
 
@@ -226,75 +215,53 @@ int ImageHelper::destroyLoadedBuffer(unsigned char *pDataBuffer)
 		return MEDIA_VISION_ERROR_NONE;
 	}
 
-	delete [] pDataBuffer;
+	delete[] pDataBuffer;
 	pDataBuffer = NULL;
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int ImageHelper::drawRectangleOnBuffer(
-		int topLeftVertexX,
-		int topLeftVertexY,
-		int bottomRightVertexX,
-		int bottomRightVertexY,
-		int thickness,
-		const cv::Scalar& color,
-		const ImageData& imageData,
-		unsigned char *pDataBuffer)
+int ImageHelper::drawRectangleOnBuffer(int topLeftVertexX, int topLeftVertexY, int bottomRightVertexX,
+									   int bottomRightVertexY, int thickness, const cv::Scalar &color,
+									   const ImageData &imageData, unsigned char *pDataBuffer)
 {
 	if (NULL == pDataBuffer)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 
 	cv::Mat cvImage(imageData.imageHeight, imageData.imageWidth, CV_8UC(OPEN_CV_CHANNELS), pDataBuffer);
-	cv::rectangle(
-		cvImage,
-		cv::Point(topLeftVertexX, topLeftVertexY),
-		cv::Point(bottomRightVertexX, bottomRightVertexY),
-		color,
-		thickness);
+	cv::rectangle(cvImage, cv::Point(topLeftVertexX, topLeftVertexY), cv::Point(bottomRightVertexX, bottomRightVertexY),
+				  color, thickness);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int ImageHelper::drawQuadrangleOnBuffer(
-		mv_quadrangle_s location,
-		int thickness,
-		const cv::Scalar& color,
-		const ImageData& imageData,
-		unsigned char *pDataBuffer)
+int ImageHelper::drawQuadrangleOnBuffer(mv_quadrangle_s location, int thickness, const cv::Scalar &color,
+										const ImageData &imageData, unsigned char *pDataBuffer)
 {
 	if (NULL == pDataBuffer)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 
 	cv::Mat cvImage(imageData.imageHeight, imageData.imageWidth, CV_8UC(OPEN_CV_CHANNELS), pDataBuffer);
 	for (int i = 0; i < QUADRANGLE_VERTICES; ++i) {
-		cv::line(
-			cvImage,
-			cv::Point(location.points[i].x, location.points[i].y),
-			cv::Point(location.points[(i + 1) % QUADRANGLE_VERTICES].x,
-				location.points[(i + 1) % QUADRANGLE_VERTICES].y),
-			color,
-			thickness);
+		cv::line(cvImage, cv::Point(location.points[i].x, location.points[i].y),
+				 cv::Point(location.points[(i + 1) % QUADRANGLE_VERTICES].x,
+						   location.points[(i + 1) % QUADRANGLE_VERTICES].y),
+				 color, thickness);
 	}
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int ImageHelper::convertBufferToRGB888(
-		const unsigned char *pInBuffer,
-		const ImageData& imageData,
-		unsigned char **pOutBuffer)
+int ImageHelper::convertBufferToRGB888(const unsigned char *pInBuffer, const ImageData &imageData,
+									   unsigned char **pOutBuffer)
 {
 	/* todo: support more colorspaces: */
 	switch (imageData.imageColorspace) {
 	case MEDIA_VISION_COLORSPACE_Y800:
 		return convertY800ToRGB(pInBuffer, imageData, pOutBuffer);
-	case MEDIA_VISION_COLORSPACE_RGB888:
-	{
+	case MEDIA_VISION_COLORSPACE_RGB888: {
 		int numberOfComponents = 0;
-		getNumberOfComponents(
-			MEDIA_VISION_COLORSPACE_RGB888, &numberOfComponents);
-		const int dataSize =
-			imageData.imageHeight * imageData.imageWidth * numberOfComponents;
+		getNumberOfComponents(MEDIA_VISION_COLORSPACE_RGB888, &numberOfComponents);
+		const int dataSize = imageData.imageHeight * imageData.imageWidth * numberOfComponents;
 		(*pOutBuffer) = new unsigned char[dataSize];
 		std::memcpy(*pOutBuffer, pInBuffer, dataSize);
 		return MEDIA_VISION_ERROR_NONE;
@@ -306,9 +273,7 @@ int ImageHelper::convertBufferToRGB888(
 	return MEDIA_VISION_ERROR_NOT_SUPPORTED;
 }
 
-int ImageHelper::getNumberOfComponents(
-		mv_colorspace_e colorspace,
-		int *pComponentsNumber)
+int ImageHelper::getNumberOfComponents(mv_colorspace_e colorspace, int *pComponentsNumber)
 {
 	/* todo: support more colorspaces: */
 	switch (colorspace) {
@@ -325,10 +290,8 @@ int ImageHelper::getNumberOfComponents(
 	return MEDIA_VISION_ERROR_NOT_SUPPORTED;
 }
 
-int ImageHelper::convertY800ToRGB(
-		const unsigned char *pInBuffer,
-		const ImageData& imageData,
-		unsigned char **pOutBuffer)
+int ImageHelper::convertY800ToRGB(const unsigned char *pInBuffer, const ImageData &imageData,
+								  unsigned char **pOutBuffer)
 {
 	if (imageData.imageColorspace != MEDIA_VISION_COLORSPACE_Y800)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -339,10 +302,10 @@ int ImageHelper::convertY800ToRGB(
 	const int dataSize = inDataSize * numberOfComponents;
 	(*pOutBuffer) = new unsigned char[dataSize];
 	for (int i = 0; i < inDataSize; ++i) {
-		int pixelStartIndex = i*numberOfComponents;
-		(*pOutBuffer)[pixelStartIndex]   = pInBuffer[i];
-		(*pOutBuffer)[pixelStartIndex+1] = pInBuffer[i];
-		(*pOutBuffer)[pixelStartIndex+2] = pInBuffer[i];
+		int pixelStartIndex = i * numberOfComponents;
+		(*pOutBuffer)[pixelStartIndex] = pInBuffer[i];
+		(*pOutBuffer)[pixelStartIndex + 1] = pInBuffer[i];
+		(*pOutBuffer)[pixelStartIndex + 2] = pInBuffer[i];
 	}
 	return MEDIA_VISION_ERROR_NONE;
 }
diff --git a/test/testsuites/common/image_helper/src/image_helper.cpp b/test/testsuites/common/image_helper/src/image_helper.cpp
index c4d9698..0b4db2a 100644
--- a/test/testsuites/common/image_helper/src/image_helper.cpp
+++ b/test/testsuites/common/image_helper/src/image_helper.cpp
@@ -46,12 +46,8 @@ ImageHelper::ImageData convertToCppData(image_data_s data)
 	return ret;
 }
 
-
-int load_image_to_buffer(
-	const char *file_path,
-	unsigned char **data_buffer,
-	unsigned long *buffer_size,
-	image_data_s *image_data)
+int load_image_to_buffer(const char *file_path, unsigned char **data_buffer, unsigned long *buffer_size,
+						 image_data_s *image_data)
 {
 	if (image_data == NULL)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -66,11 +62,8 @@ int load_image_to_buffer(
 	return err;
 }
 
-int save_image_from_buffer(
-	const char *file_path,
-	unsigned char *data_buffer,
-	const image_data_s *image_data,
-	int quality)
+int save_image_from_buffer(const char *file_path, unsigned char *data_buffer, const image_data_s *image_data,
+						   int quality)
 {
 	if (image_data == NULL)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -84,15 +77,8 @@ int destroy_loaded_buffer(unsigned char *data_buffer)
 	return ImageHelper::destroyLoadedBuffer(data_buffer);
 }
 
-int draw_rectangle_on_buffer(
-	int tl_vertex_x,
-	int tl_vertex_y,
-	int br_vertex_x,
-	int br_vertex_y,
-	int thickness,
-	const int rgb_color[3],
-	const image_data_s *image_data,
-	unsigned char *data_buffer)
+int draw_rectangle_on_buffer(int tl_vertex_x, int tl_vertex_y, int br_vertex_x, int br_vertex_y, int thickness,
+							 const int rgb_color[3], const image_data_s *image_data, unsigned char *data_buffer)
 {
 	if (image_data == NULL)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -101,20 +87,12 @@ int draw_rectangle_on_buffer(
 
 	cv::Scalar color(rgb_color[2], rgb_color[1], rgb_color[0]);
 
-	return ImageHelper::drawRectangleOnBuffer(
-			tl_vertex_x, tl_vertex_y,
-			br_vertex_x, br_vertex_y,
-			thickness,
-			color,
-			imageData, data_buffer);
+	return ImageHelper::drawRectangleOnBuffer(tl_vertex_x, tl_vertex_y, br_vertex_x, br_vertex_y, thickness, color,
+											  imageData, data_buffer);
 }
 
-int draw_quadrangle_on_buffer(
-		mv_quadrangle_s location,
-		int thickness,
-		const int rgb_color[3],
-		const image_data_s *image_data,
-		unsigned char *data_buffer)
+int draw_quadrangle_on_buffer(mv_quadrangle_s location, int thickness, const int rgb_color[3],
+							  const image_data_s *image_data, unsigned char *data_buffer)
 {
 	if (image_data == NULL)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -123,18 +101,10 @@ int draw_quadrangle_on_buffer(
 
 	cv::Scalar color(rgb_color[2], rgb_color[1], rgb_color[0]);
 
-	return ImageHelper::drawQuadrangleOnBuffer(
-			location,
-			thickness,
-			color,
-			imageData,
-			data_buffer);
+	return ImageHelper::drawQuadrangleOnBuffer(location, thickness, color, imageData, data_buffer);
 }
 
-int convert_buffer_to_RGB888(
-		const unsigned char *in_buffer,
-		const image_data_s *image_data,
-		unsigned char **out_buffer)
+int convert_buffer_to_RGB888(const unsigned char *in_buffer, const image_data_s *image_data, unsigned char **out_buffer)
 {
 	if (image_data == NULL)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -143,9 +113,7 @@ int convert_buffer_to_RGB888(
 	return ImageHelper::convertBufferToRGB888(in_buffer, imageData, out_buffer);
 }
 
-int get_number_of_components(
-		mv_colorspace_e colorspace,
-		int *components_number)
+int get_number_of_components(mv_colorspace_e colorspace, int *components_number)
 {
 	return ImageHelper::getNumberOfComponents(colorspace, components_number);
 }
diff --git a/test/testsuites/common/testsuite_common/mv_testsuite_common.c b/test/testsuites/common/testsuite_common/mv_testsuite_common.c
index 29a1385..44d87a0 100644
--- a/test/testsuites/common/testsuite_common/mv_testsuite_common.c
+++ b/test/testsuites/common/testsuite_common/mv_testsuite_common.c
@@ -23,37 +23,23 @@
 #include <stdio.h>
 #include <stdlib.h>
 
-void print_fail_result(
-		const char *action_name,
-		int action_return_value)
+void print_fail_result(const char *action_name, int action_return_value)
 {
-	printf(TEXT_RED
-			"Error with code %i was occurred during action '%s'"
-			TEXT_RESET "\n",
-			action_return_value,
-			action_name);
+	printf(TEXT_RED "Error with code %i was occurred during action '%s'" TEXT_RESET "\n", action_return_value,
+		   action_name);
 }
 
 void print_done_result(const char *action_name)
 {
-	printf(TEXT_YELLOW
-			"Action '%s' was finished"
-			TEXT_RESET "\n",
-			action_name);
+	printf(TEXT_YELLOW "Action '%s' was finished" TEXT_RESET "\n", action_name);
 }
 
 void print_success_result(const char *action_name)
 {
-	printf(TEXT_GREEN
-			"Action '%s' was finished successfully"
-			TEXT_RESET
-			"\n", action_name);
+	printf(TEXT_GREEN "Action '%s' was finished successfully" TEXT_RESET "\n", action_name);
 }
 
-void print_action_result(
-		const char *action_name,
-		int action_return_value,
-		notification_type_e notification_type_e)
+void print_action_result(const char *action_name, int action_return_value, notification_type_e notification_type_e)
 {
 	switch (notification_type_e) {
 	case FAIL_OR_SUCCESSS:
@@ -132,11 +118,7 @@ int input_int(const char *prompt, int min_value, int max_value, int *value)
 	return (*value < min_value || *value > max_value ? -1 : 0);
 }
 
-int input_double(
-		const char *prompt,
-		double min_value,
-		double max_value,
-		double *value)
+int input_double(const char *prompt, double min_value, double max_value, double *value)
 {
 	printf("\n");
 	printf("%s ", prompt);
@@ -154,7 +136,7 @@ int input_double(
 
 bool show_confirm_dialog(const char *title)
 {
-	const int options[2] = {1, 2};
+	const int options[2] = { 1, 2 };
 	const char *names[2] = { "No", "Yes" };
 
 	bool answer = false;
@@ -179,11 +161,7 @@ bool show_confirm_dialog(const char *title)
 	return answer;
 }
 
-int show_menu(
-		const char *title,
-		const int *options,
-		const char **names,
-		int number_of_option)
+int show_menu(const char *title, const int *options, const char **names, int number_of_option)
 {
 	if (NULL == title || NULL == options || NULL == names || 0 >= number_of_option)
 		return -1;
@@ -237,35 +215,26 @@ int show_menu(
 	return selection;
 }
 
-int load_mv_source_from_file(
-		const char *path_to_image,
-		mv_source_h source)
+int load_mv_source_from_file(const char *path_to_image, mv_source_h source)
 {
 	unsigned char *data_buffer = NULL;
 	unsigned long buffer_size = 0;
 	image_data_s image_data;
 
-	int err = load_image_to_buffer(path_to_image, &data_buffer,
-									&buffer_size, &image_data);
+	int err = load_image_to_buffer(path_to_image, &data_buffer, &buffer_size, &image_data);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf("ERROR: Errors were occurred during opening file!!! code: %i\n",
-			err);
+		printf("ERROR: Errors were occurred during opening file!!! code: %i\n", err);
 		if (NULL != data_buffer)
 			destroy_loaded_buffer(data_buffer);
 
 		return err;
 	}
 
-	err = mv_source_fill_by_buffer(
-			source, data_buffer,
-			buffer_size,
-			image_data.image_width,
-			image_data.image_height,
-			image_data.image_colorspace);
+	err = mv_source_fill_by_buffer(source, data_buffer, buffer_size, image_data.image_width, image_data.image_height,
+								   image_data.image_colorspace);
 
 	if (MEDIA_VISION_ERROR_NONE != err)
-		printf("ERROR: Errors were occurred during filling source!!! code %i\n",
-			err);
+		printf("ERROR: Errors were occurred during filling source!!! code %i\n", err);
 
 	if (NULL != data_buffer)
 		destroy_loaded_buffer(data_buffer);
diff --git a/test/testsuites/common/testsuite_common/mv_testsuite_common.h b/test/testsuites/common/testsuite_common/mv_testsuite_common.h
index 66876e0..5b0bc7c 100644
--- a/test/testsuites/common/testsuite_common/mv_testsuite_common.h
+++ b/test/testsuites/common/testsuite_common/mv_testsuite_common.h
@@ -21,7 +21,8 @@
 
 #include <stddef.h>
 
-typedef enum {
+typedef enum
+{
 	FAIL_OR_SUCCESSS,
 	FAIL_OR_DONE
 } notification_type_e;
@@ -33,9 +34,7 @@ typedef enum {
  * @param [in] action_name           Name of action which result will be printed
  * @param [in] action_return_value   Return value of action
  */
-void print_fail_result(
-		const char *action_name,
-		int action_return_value);
+void print_fail_result(const char *action_name, int action_return_value);
 
 /**
  * @brief Prints success result of action.
@@ -61,10 +60,7 @@ void print_success_result(const char *action_name);
  * @param [in] action_return_value   Return value of action
  * @param [in] notification_type_e   Type of notification
  */
-void print_action_result(
-		const char *action_name,
-		int action_return_value,
-		notification_type_e notification_type_e);
+void print_action_result(const char *action_name, int action_return_value, notification_type_e notification_type_e);
 
 /**
  * @brief Gets string from console.
@@ -136,16 +132,9 @@ bool show_confirm_dialog(const char *title);
  * @return The selected item positive number from options array on success,
  *         otherwise a negative error value
  */
-int show_menu(
-		const char *title,
-		const int *options,
-		const char **names,
-		int number_of_option);
+int show_menu(const char *title, const int *options, const char **names, int number_of_option);
 
-int show_menu_linear(
-		const char *title,
-		const char **menu,
-		size_t len_menu);
+int show_menu_linear(const char *title, const char **menu, size_t len_menu);
 
 int show_menu_yes_or_no(const char *title);
 
@@ -157,8 +146,6 @@ int show_menu_yes_or_no(const char *title);
  * @param [in/out] source       The handler to media source which will be filled
  * @return @c 0 on success, otherwise a negative error value
  */
-int load_mv_source_from_file(
-		const char *path_to_image,
-		mv_source_h source);
+int load_mv_source_from_file(const char *path_to_image, mv_source_h source);
 
 #endif /* __MEDIA_VISION_MV_TESTSUITE_COMMON_H__ */
diff --git a/test/testsuites/common/video_helper/mv_log_cfg.h b/test/testsuites/common/video_helper/mv_log_cfg.h
index 2af638b..31aa0e4 100644
--- a/test/testsuites/common/video_helper/mv_log_cfg.h
+++ b/test/testsuites/common/video_helper/mv_log_cfg.h
@@ -21,47 +21,47 @@
 
 /* #define ROOTSTRAP_OUT // enables logs to console */
 
-#define TEXT_RED     "\x1b[31m"
-#define TEXT_GREEN   "\x1b[32m"
-#define TEXT_YELLOW  "\x1b[33m"
-#define TEXT_BLUE    "\x1b[34m"
+#define TEXT_RED "\x1b[31m"
+#define TEXT_GREEN "\x1b[32m"
+#define TEXT_YELLOW "\x1b[33m"
+#define TEXT_BLUE "\x1b[34m"
 #define TEXT_MAGENTA "\x1b[35m"
-#define TEXT_CYAN    "\x1b[36m"
-#define TEXT_RESET   "\x1b[0m"
+#define TEXT_CYAN "\x1b[36m"
+#define TEXT_RESET "\x1b[0m"
 
 #ifdef ROOTSTRAP_OUT
 
-#define LOGD(...)                                 \
-do {                                              \
-	printf("<%s:%d>", __FUNCTION__, __LINE__);    \
-	printf(TEXT_CYAN);                            \
-	printf(__VA_ARGS__);                          \
-	printf(TEXT_RESET "\n");                      \
-} while (0)
+#define LOGD(...)                                  \
+	do {                                           \
+		printf("<%s:%d>", __FUNCTION__, __LINE__); \
+		printf(TEXT_CYAN);                         \
+		printf(__VA_ARGS__);                       \
+		printf(TEXT_RESET "\n");                   \
+	} while (0)
 
-#define LOGI(...)                                 \
-do  {                                             \
-	printf("<%s:%d>", __FUNCTION__, __LINE__);    \
-	printf(TEXT_GREEN);                           \
-	printf(__VA_ARGS__);                          \
-	printf(TEXT_RESET "\n");                      \
-} while (0)
+#define LOGI(...)                                  \
+	do {                                           \
+		printf("<%s:%d>", __FUNCTION__, __LINE__); \
+		printf(TEXT_GREEN);                        \
+		printf(__VA_ARGS__);                       \
+		printf(TEXT_RESET "\n");                   \
+	} while (0)
 
-#define LOGW(...)                                 \
-do {                                              \
-	printf("<%s:%d>", __FUNCTION__, __LINE__);    \
-	printf(TEXT_YELLOW);                          \
-	printf(__VA_ARGS__);                          \
-	printf(TEXT_RESET "\n");                      \
-} while (0)
+#define LOGW(...)                                  \
+	do {                                           \
+		printf("<%s:%d>", __FUNCTION__, __LINE__); \
+		printf(TEXT_YELLOW);                       \
+		printf(__VA_ARGS__);                       \
+		printf(TEXT_RESET "\n");                   \
+	} while (0)
 
-#define LOGE(...)                                 \
-do {                                              \
-	printf("<%s:%d>", __FUNCTION__, __LINE__);    \
-	printf(TEXT_RED);                             \
-	printf(__VA_ARGS__);                          \
-	printf(TEXT_RESET "\n");                      \
-} while (0)
+#define LOGE(...)                                  \
+	do {                                           \
+		printf("<%s:%d>", __FUNCTION__, __LINE__); \
+		printf(TEXT_RED);                          \
+		printf(__VA_ARGS__);                       \
+		printf(TEXT_RESET "\n");                   \
+	} while (0)
 
 #endif
 
diff --git a/test/testsuites/common/video_helper/mv_video_helper.c b/test/testsuites/common/video_helper/mv_video_helper.c
index 2eb7448..f95409c 100644
--- a/test/testsuites/common/video_helper/mv_video_helper.c
+++ b/test/testsuites/common/video_helper/mv_video_helper.c
@@ -29,7 +29,8 @@
 
 #include <pthread.h>
 
-typedef struct _mv_video_reader_s {
+typedef struct _mv_video_reader_s
+{
 	/* Main bin */
 	GstElement *pl;
 
@@ -53,7 +54,8 @@ typedef struct _mv_video_reader_s {
 	mv_video_reader_eos_cb eos_cb;
 } mv_video_reader_s;
 
-typedef struct _mv_video_writer_s {
+typedef struct _mv_video_writer_s
+{
 	/* Main bin */
 	GstElement *pl;
 
@@ -88,8 +90,7 @@ static void cb_newpad(GstElement *decodebin, GstPad *new_pad, gpointer user_data
 static GstPadProbeReturn pad_probe_data_cb(GstPad *pad, GstPadProbeInfo *info, gpointer user_data);
 
 /* video reader */
-int mv_create_video_reader(
-		mv_video_reader_h *reader)
+int mv_create_video_reader(mv_video_reader_h *reader)
 {
 	mv_video_reader_s *handle = NULL;
 	int err = MEDIA_VISION_ERROR_NONE;
@@ -127,8 +128,7 @@ int mv_create_video_reader(
 	return err;
 }
 
-int mv_destroy_video_reader(
-		mv_video_reader_h reader)
+int mv_destroy_video_reader(mv_video_reader_h reader)
 {
 	mv_video_reader_s *handle = NULL;
 
@@ -157,17 +157,12 @@ int mv_destroy_video_reader(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_video_reader_load(
-		mv_video_reader_h reader,
-		const char *path,
-		image_data_s *image_data,
-		unsigned int *fps)
+int mv_video_reader_load(mv_video_reader_h reader, const char *path, image_data_s *image_data, unsigned int *fps)
 {
 	mv_video_reader_s *handle = NULL;
 	GstVideoInfo info;
 
-	if (reader == NULL || path == NULL ||
-			image_data == NULL || fps == NULL) {
+	if (reader == NULL || path == NULL || image_data == NULL || fps == NULL) {
 		LOGE("NULL pointer passed");
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 	}
@@ -175,9 +170,7 @@ int mv_video_reader_load(
 	handle = (mv_video_reader_s *) reader;
 
 	/* Set input file location from path */
-	g_object_set(G_OBJECT(handle->filesrc),
-			"location", path,
-			NULL);
+	g_object_set(G_OBJECT(handle->filesrc), "location", path, NULL);
 
 	/* Start playback */
 	if (_mv_video_reader_state_change(handle, GST_STATE_PLAYING)) {
@@ -199,7 +192,7 @@ int mv_video_reader_load(
 
 	gst_caps_unref(handle->caps);
 
-	*fps = info.fps_n/info.fps_d;
+	*fps = info.fps_n / info.fps_d;
 
 	/* Fill image data */
 	image_data->image_width = info.width;
@@ -241,8 +234,7 @@ int mv_video_reader_load(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_video_reader_start(
-		mv_video_reader_h reader)
+int mv_video_reader_start(mv_video_reader_h reader)
 {
 	mv_video_reader_s *handle = NULL;
 
@@ -262,8 +254,7 @@ int mv_video_reader_start(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_video_reader_stop(
-		mv_video_reader_h reader)
+int mv_video_reader_stop(mv_video_reader_h reader)
 {
 	mv_video_reader_s *handle = NULL;
 
@@ -283,10 +274,7 @@ int mv_video_reader_stop(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_video_reader_set_new_sample_cb(
-		mv_video_reader_h reader,
-		mv_video_reader_new_sample_cb callback,
-		void *user_data)
+int mv_video_reader_set_new_sample_cb(mv_video_reader_h reader, mv_video_reader_new_sample_cb callback, void *user_data)
 {
 	mv_video_reader_s *handle = NULL;
 
@@ -305,10 +293,7 @@ int mv_video_reader_set_new_sample_cb(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_video_reader_set_eos_cb(
-		mv_video_reader_h reader,
-		mv_video_reader_eos_cb callback,
-		void *user_data)
+int mv_video_reader_set_eos_cb(mv_video_reader_h reader, mv_video_reader_eos_cb callback, void *user_data)
 {
 	mv_video_reader_s *handle = NULL;
 
@@ -328,8 +313,7 @@ int mv_video_reader_set_eos_cb(
 }
 
 /* Video Writer */
-int mv_create_video_writer(
-		mv_video_writer_h *writer)
+int mv_create_video_writer(mv_video_writer_h *writer)
 {
 	mv_video_writer_s *handle = NULL;
 	int err = MEDIA_VISION_ERROR_NONE;
@@ -360,8 +344,7 @@ int mv_create_video_writer(
 	return err;
 }
 
-int mv_destroy_video_writer(
-		mv_video_writer_h writer)
+int mv_destroy_video_writer(mv_video_writer_h writer)
 {
 	mv_video_writer_s *handle = NULL;
 
@@ -386,11 +369,7 @@ int mv_destroy_video_writer(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int mv_video_writer_init(
-		mv_video_writer_h writer,
-		const char *path,
-		image_data_s image_data,
-		unsigned int fps)
+int mv_video_writer_init(mv_video_writer_h writer, const char *path, image_data_s image_data, unsigned int fps)
 {
 	mv_video_writer_s *handle = NULL;
 	unsigned int err = MEDIA_VISION_ERROR_NONE;
@@ -408,9 +387,7 @@ int mv_video_writer_init(
 
 	handle->fps = fps;
 
-	g_object_set(G_OBJECT(handle->filesink),
-			"location", path,
-			NULL);
+	g_object_set(G_OBJECT(handle->filesink), "location", path, NULL);
 
 	err = _mv_video_writer_link_internals(handle);
 	if (MEDIA_VISION_ERROR_NONE != err) {
@@ -421,9 +398,7 @@ int mv_video_writer_init(
 	return err;
 }
 
-int mv_video_writer_write_frame(
-		mv_video_writer_h writer,
-		unsigned char *frame)
+int mv_video_writer_write_frame(mv_video_writer_h writer, unsigned char *frame)
 {
 	mv_video_writer_s *handle = NULL;
 	GstMapInfo info;
@@ -436,7 +411,7 @@ int mv_video_writer_write_frame(
 
 	handle = (mv_video_writer_s *) writer;
 
-	buffer =  gst_buffer_new_allocate(NULL, handle->buffer_size, NULL);
+	buffer = gst_buffer_new_allocate(NULL, handle->buffer_size, NULL);
 	if (!buffer) {
 		LOGE("Unable to allocate buffer for frame");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
@@ -447,8 +422,7 @@ int mv_video_writer_write_frame(
 	memcpy(info.data, frame, info.size);
 	gst_buffer_unmap(buffer, &info);
 
-	if (GST_FLOW_OK !=
-			gst_app_src_push_buffer((GstAppSrc*)(handle->appsrc), buffer)) {
+	if (GST_FLOW_OK != gst_app_src_push_buffer((GstAppSrc *) (handle->appsrc), buffer)) {
 		LOGE("Failed to push buffer to appsrc");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
@@ -457,8 +431,7 @@ int mv_video_writer_write_frame(
 }
 
 /* Internal functions */
-static int _mv_video_reader_create_internals(
-		mv_video_reader_s *reader)
+static int _mv_video_reader_create_internals(mv_video_reader_s *reader)
 {
 	pthread_spin_init(&(reader->new_sample_cb_guard), PTHREAD_PROCESS_SHARED);
 	pthread_spin_init(&(reader->eos_cb_guard), PTHREAD_PROCESS_SHARED);
@@ -471,110 +444,72 @@ static int _mv_video_reader_create_internals(
 	reader->queue = gst_element_factory_make("queue", "queue");
 	reader->appsink = gst_element_factory_make("appsink", "appsink");
 
-	if ((!reader->pl) ||
-			(!reader->filesrc) ||
-			(!reader->decodebin) ||
-			(!reader->videoconvert) ||
-			(!reader->queue) ||
-			(!reader->appsink)) {
+	if ((!reader->pl) || (!reader->filesrc) || (!reader->decodebin) || (!reader->videoconvert) || (!reader->queue) ||
+		(!reader->appsink)) {
 		LOGE("Unable to create video read pipeline elements");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
-	gst_bin_add_many(GST_BIN(reader->pl),
-			reader->filesrc,
-			reader->decodebin,
-			reader->videoconvert,
-			reader->queue,
-			reader->appsink,
-			NULL);
+	gst_bin_add_many(GST_BIN(reader->pl), reader->filesrc, reader->decodebin, reader->videoconvert, reader->queue,
+					 reader->appsink, NULL);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-static int _mv_video_reader_link_internals(
-		mv_video_reader_s *reader)
+static int _mv_video_reader_link_internals(mv_video_reader_s *reader)
 {
 	GstCaps *caps = NULL;
 	GstPad *pad = NULL;
 
-	if (!gst_element_link_many(reader->filesrc,
-				reader->decodebin,
-				NULL)) {
+	if (!gst_element_link_many(reader->filesrc, reader->decodebin, NULL)) {
 		LOGE("Unable to link filesrc to decodebin");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
 	/* Decodebin pad will be linked during state change */
-	g_signal_connect(reader->decodebin,
-			"pad-added",
-			G_CALLBACK(cb_newpad),
-			reader);
-
-	if (!gst_element_link_many(reader->videoconvert,
-			reader->queue, reader->appsink, NULL)) {
+	g_signal_connect(reader->decodebin, "pad-added", G_CALLBACK(cb_newpad), reader);
 
+	if (!gst_element_link_many(reader->videoconvert, reader->queue, reader->appsink, NULL)) {
 		LOGE("Unable to link videocovnert-queue-appsink");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
-	caps = gst_caps_new_simple("video/x-raw",
-			"format", G_TYPE_STRING, "RGB",
-			NULL);
+	caps = gst_caps_new_simple("video/x-raw", "format", G_TYPE_STRING, "RGB", NULL);
 
 	gst_app_sink_set_caps(GST_APP_SINK(reader->appsink), caps);
 	gst_caps_unref(caps);
 
 	/* Configure appsink */
 	gst_app_sink_set_emit_signals(GST_APP_SINK(reader->appsink), TRUE);
-	g_signal_connect(reader->appsink,
-			"new-sample",
-			G_CALLBACK(appsink_newsample),
-			reader);
-	g_signal_connect(reader->appsink,
-			"eos",
-			G_CALLBACK(appsink_eos),
-			reader);
-	g_object_set(G_OBJECT(reader->appsink),
-			"drop", TRUE,
-			"enable-last-sample", TRUE,
-			"sync", FALSE,
-			NULL);
-
+	g_signal_connect(reader->appsink, "new-sample", G_CALLBACK(appsink_newsample), reader);
+	g_signal_connect(reader->appsink, "eos", G_CALLBACK(appsink_eos), reader);
+	g_object_set(G_OBJECT(reader->appsink), "drop", TRUE, "enable-last-sample", TRUE, "sync", FALSE, NULL);
 
 	/* pad probe */
 	pad = gst_element_get_static_pad(reader->queue, "src");
 
-	gst_pad_add_probe(pad, GST_PAD_PROBE_TYPE_BUFFER,
-			(GstPadProbeCallback)pad_probe_data_cb, reader, NULL);
+	gst_pad_add_probe(pad, GST_PAD_PROBE_TYPE_BUFFER, (GstPadProbeCallback) pad_probe_data_cb, reader, NULL);
 	gst_object_unref(pad);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-static int _mv_video_reader_state_change(
-		mv_video_reader_s *reader,
-		GstState state)
+static int _mv_video_reader_state_change(mv_video_reader_s *reader, GstState state)
 {
 	mv_video_reader_s *handle = (mv_video_reader_s *) reader;
 	GstStateChangeReturn state_ret = GST_STATE_CHANGE_FAILURE;
 	GstState pipeline_state = GST_STATE_NULL;
 
-	state_ret = gst_element_set_state(handle->pl,
-			state);
+	state_ret = gst_element_set_state(handle->pl, state);
 
 	if (GST_STATE_CHANGE_FAILURE == state_ret) {
 		LOGE("Set state failure");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
-	LOGI("Set state [%d], change return [%d]",
-			state, state_ret);
+	LOGI("Set state [%d], change return [%d]", state, state_ret);
 
-	state_ret = gst_element_get_state(handle->pl,
-			&pipeline_state,
-			NULL,
-			GST_CLOCK_TIME_NONE);
+	state_ret = gst_element_get_state(handle->pl, &pipeline_state, NULL, GST_CLOCK_TIME_NONE);
 
 	if (GST_STATE_CHANGE_FAILURE == state_ret) {
 		LOGE("get state failure");
@@ -584,8 +519,7 @@ static int _mv_video_reader_state_change(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-static int _mv_video_writer_create_internals(
-		mv_video_writer_s *writer)
+static int _mv_video_writer_create_internals(mv_video_writer_s *writer)
 {
 	writer->pl = gst_pipeline_new(NULL);
 
@@ -597,33 +531,19 @@ static int _mv_video_writer_create_internals(
 	writer->muxer = gst_element_factory_make("avimux", "muxer");
 	writer->filesink = gst_element_factory_make("filesink", "filesink");
 
-	if ((!writer->pl) ||
-			(!writer->appsrc) ||
-			(!writer->capsfilter) ||
-			(!writer->videoconvert) ||
-			(!writer->encoder) ||
-			(!writer->queue) ||
-			(!writer->muxer) ||
-			(!writer->filesink)) {
+	if ((!writer->pl) || (!writer->appsrc) || (!writer->capsfilter) || (!writer->videoconvert) || (!writer->encoder) ||
+		(!writer->queue) || (!writer->muxer) || (!writer->filesink)) {
 		LOGE("Unable to create video read pipeline elements\n");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
-	gst_bin_add_many(GST_BIN(writer->pl),
-			writer->appsrc,
-			writer->capsfilter,
-			writer->videoconvert,
-			writer->encoder,
-			writer->queue,
-			writer->muxer,
-			writer->filesink,
-			NULL);
+	gst_bin_add_many(GST_BIN(writer->pl), writer->appsrc, writer->capsfilter, writer->videoconvert, writer->encoder,
+					 writer->queue, writer->muxer, writer->filesink, NULL);
 
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-static int _mv_video_writer_link_internals(
-		mv_video_writer_s *writer)
+static int _mv_video_writer_link_internals(mv_video_writer_s *writer)
 {
 	GstVideoInfo vinfo;
 	GstCaps *caps = NULL;
@@ -659,17 +579,13 @@ static int _mv_video_writer_link_internals(
 		format = "RGBA";
 		break;
 	default:
-		LOGE("Selected format %d is not supported",
-				writer->image_data.image_colorspace);
+		LOGE("Selected format %d is not supported", writer->image_data.image_colorspace);
 		return MEDIA_VISION_ERROR_NOT_SUPPORTED_FORMAT;
 	}
 
-	caps = gst_caps_new_simple("video/x-raw",
-				"format", G_TYPE_STRING, format,
-				"width", G_TYPE_INT, writer->image_data.image_width,
-				"height", G_TYPE_INT, writer->image_data.image_height,
-				"framerate", GST_TYPE_FRACTION, writer->fps, 1,
-				NULL);
+	caps = gst_caps_new_simple("video/x-raw", "format", G_TYPE_STRING, format, "width", G_TYPE_INT,
+							   writer->image_data.image_width, "height", G_TYPE_INT, writer->image_data.image_height,
+							   "framerate", GST_TYPE_FRACTION, writer->fps, 1, NULL);
 
 	if (NULL == caps) {
 		LOGE("Failed to create new caps");
@@ -685,38 +601,24 @@ static int _mv_video_writer_link_internals(
 
 	writer->buffer_size = vinfo.size;
 
-	g_object_set(G_OBJECT(writer->appsrc),
-			"max-bytes", 0,
-			"blocksize", writer->buffer_size,
-			"stream-type", 0,
-			"format", GST_FORMAT_BYTES,
-			"do-timestamp", true,
-			"is-live", true,
-			NULL);
+	g_object_set(G_OBJECT(writer->appsrc), "max-bytes", 0, "blocksize", writer->buffer_size, "stream-type", 0, "format",
+				 GST_FORMAT_BYTES, "do-timestamp", true, "is-live", true, NULL);
 
 	/* link appsrc and capsfilter */
-	if ((!gst_element_link_filtered(writer->appsrc,
-					writer->capsfilter,
-					caps))) {
+	if ((!gst_element_link_filtered(writer->appsrc, writer->capsfilter, caps))) {
 		LOGE("Failed to link appsrc to capsfilter");
 		gst_caps_unref(caps);
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 	gst_caps_unref(caps);
 
-	if (!gst_element_link_many(writer->capsfilter,
-				writer->videoconvert,
-				writer->encoder,
-				writer->queue,
-				writer->muxer,
-				writer->filesink,
-				NULL)) {
+	if (!gst_element_link_many(writer->capsfilter, writer->videoconvert, writer->encoder, writer->queue, writer->muxer,
+							   writer->filesink, NULL)) {
 		LOGE("Unable to capsfilter to filesink");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
-	if (_mv_video_writer_state_change(writer,
-				GST_STATE_PLAYING)) {
+	if (_mv_video_writer_state_change(writer, GST_STATE_PLAYING)) {
 		LOGE("Unable to change video writer state");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
@@ -724,23 +626,19 @@ static int _mv_video_writer_link_internals(
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-static int _mv_video_writer_state_change(
-		mv_video_writer_s *writer,
-		GstState state)
+static int _mv_video_writer_state_change(mv_video_writer_s *writer, GstState state)
 {
 	mv_video_writer_s *handle = (mv_video_writer_s *) writer;
 	GstStateChangeReturn state_ret = GST_STATE_CHANGE_FAILURE;
 
-	state_ret = gst_element_set_state(handle->pl,
-			state);
+	state_ret = gst_element_set_state(handle->pl, state);
 
 	if (GST_STATE_CHANGE_FAILURE == state_ret) {
 		LOGE("Set state failure");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
 	}
 
-	LOGI("Set state [%d], change return [%d]",
-			state, state_ret);
+	LOGI("Set state [%d], change return [%d]", state, state_ret);
 
 	/* AppSrc can't go to PLAYING state before buffer is not pushed */
 
@@ -748,9 +646,7 @@ static int _mv_video_writer_state_change(
 }
 
 /* Callbacks */
-static GstFlowReturn appsink_newsample(
-		GstAppSink *appsink,
-		gpointer user_data)
+static GstFlowReturn appsink_newsample(GstAppSink *appsink, gpointer user_data)
 {
 	mv_video_reader_s *handle = NULL;
 	GstSample *sample = gst_app_sink_pull_sample(appsink);
@@ -817,11 +713,7 @@ static GstFlowReturn appsink_newsample(
 
 		pthread_spin_lock(&(handle->new_sample_cb_guard));
 		if (handle->new_sample_cb != NULL) {
-			handle->new_sample_cb(
-				buffer,
-				info.size,
-				im_data,
-				handle->new_sample_cb_user_data);
+			handle->new_sample_cb(buffer, info.size, im_data, handle->new_sample_cb_user_data);
 		}
 		pthread_spin_unlock(&(handle->new_sample_cb_guard));
 
@@ -835,9 +727,7 @@ static GstFlowReturn appsink_newsample(
 	return GST_FLOW_OK;
 }
 
-static void appsink_eos(
-		GstAppSink *appsink,
-		gpointer user_data)
+static void appsink_eos(GstAppSink *appsink, gpointer user_data)
 {
 	if (user_data == NULL) {
 		LOGE("NULL pointer passed");
@@ -856,10 +746,7 @@ static void appsink_eos(
 	gst_pad_remove_probe(gst_element_get_static_pad(handle->queue, "src"), handle->pad_probe_id);
 }
 
-static void cb_newpad(
-		GstElement *decodebin,
-		GstPad *pad,
-		gpointer user_data)
+static void cb_newpad(GstElement *decodebin, GstPad *pad, gpointer user_data)
 {
 	mv_video_reader_s *reader = (mv_video_reader_s *) user_data;
 	GstStructure *str = NULL;
@@ -887,10 +774,7 @@ static void cb_newpad(
 	g_object_unref(video_pad);
 }
 
-static GstPadProbeReturn pad_probe_data_cb(
-		GstPad *pad,
-		GstPadProbeInfo *info,
-		gpointer user_data)
+static GstPadProbeReturn pad_probe_data_cb(GstPad *pad, GstPadProbeInfo *info, gpointer user_data)
 {
 	if (user_data == NULL)
 		return GST_PAD_PROBE_PASS;
diff --git a/test/testsuites/common/video_helper/mv_video_helper.h b/test/testsuites/common/video_helper/mv_video_helper.h
index 17574d8..d54aa09 100644
--- a/test/testsuites/common/video_helper/mv_video_helper.h
+++ b/test/testsuites/common/video_helper/mv_video_helper.h
@@ -49,11 +49,8 @@ typedef void *mv_video_writer_h;
  *
  * @see mv_video_reader_set_new_sample_cb()
  */
-typedef void (*mv_video_reader_new_sample_cb) (
-		char *buffer,
-		unsigned int buffer_size,
-		image_data_s image_data,
-		void *user_data);
+typedef void (*mv_video_reader_new_sample_cb)(char *buffer, unsigned int buffer_size, image_data_s image_data,
+											  void *user_data);
 
 /**
  * @brief Called when stream from video reader is finished.
@@ -66,8 +63,7 @@ typedef void (*mv_video_reader_new_sample_cb) (
  *
  * @see mv_video_reader_set_eos_cb()
  */
-typedef void (*mv_video_reader_eos_cb) (
-		void *user_data);
+typedef void (*mv_video_reader_eos_cb)(void *user_data);
 
 /**
  * @brief Creates a video reader handle.
@@ -82,8 +78,7 @@ typedef void (*mv_video_reader_eos_cb) (
  *
  * @see mv_destroy_video_reader()
  */
-int mv_create_video_reader(
-		mv_video_reader_h *reader);
+int mv_create_video_reader(mv_video_reader_h *reader);
 
 /**
  * @brief Destroys the video reader handle and releases all its resources.
@@ -96,8 +91,7 @@ int mv_create_video_reader(
  *
  * @see mv_create_video_reader()
  */
-int mv_destroy_video_reader(
-		mv_video_reader_h reader);
+int mv_destroy_video_reader(mv_video_reader_h reader);
 
 /**
  * @brief Loads video from file.
@@ -115,11 +109,7 @@ int mv_destroy_video_reader(
  *
  * @pre Create a video reader handle by calling @ref mv_create_video_reader()
  */
-int mv_video_reader_load(
-		mv_video_reader_h reader,
-		const char *path,
-		image_data_s *image_data,
-		unsigned int *fps);
+int mv_video_reader_load(mv_video_reader_h reader, const char *path, image_data_s *image_data, unsigned int *fps);
 
 /**
  * @brief Starts reader playback.
@@ -136,8 +126,7 @@ int mv_video_reader_load(
  *
  * @post Stop reader playback by calling @ref mv_video_reader_stop()
  */
-int mv_video_reader_start(
-		mv_video_reader_h reader);
+int mv_video_reader_start(mv_video_reader_h reader);
 
 /**
  * @brief Stops reader playback.
@@ -152,8 +141,7 @@ int mv_video_reader_start(
  * @pre Create a video reader handle by calling @ref mv_create_video_reader()
  *      and call @ref mv_video_reader_load()
  */
-int mv_video_reader_stop(
-		mv_video_reader_h reader);
+int mv_video_reader_stop(mv_video_reader_h reader);
 
 /**
  * @brief Sets new sample callback to video reader.
@@ -173,10 +161,8 @@ int mv_video_reader_stop(
  * @see mv_video_reader_load()
  *
  */
-int mv_video_reader_set_new_sample_cb(
-		mv_video_reader_h reader,
-		mv_video_reader_new_sample_cb callback,
-		void *user_data);
+int mv_video_reader_set_new_sample_cb(mv_video_reader_h reader, mv_video_reader_new_sample_cb callback,
+									  void *user_data);
 
 /**
  * @brief Sets end of stream callback to video reader.
@@ -196,10 +182,7 @@ int mv_video_reader_set_new_sample_cb(
  * @see mv_video_reader_load()
  *
  */
-int mv_video_reader_set_eos_cb(
-		mv_video_reader_h reader,
-		mv_video_reader_eos_cb callback,
-		void *user_data);
+int mv_video_reader_set_eos_cb(mv_video_reader_h reader, mv_video_reader_eos_cb callback, void *user_data);
 
 /**
  * @brief Creates a video writer handle.
@@ -214,8 +197,7 @@ int mv_video_reader_set_eos_cb(
  *
  * @see mv_destroy_video_writer()
  */
-int mv_create_video_writer(
-		mv_video_writer_h *writer);
+int mv_create_video_writer(mv_video_writer_h *writer);
 
 /**
  * @brief Destroys the video writer handle and releases all its resources.
@@ -229,8 +211,7 @@ int mv_create_video_writer(
  *
  * @see mv_create_video_writer()
  */
-int mv_destroy_video_writer(
-		mv_video_writer_h writer);
+int mv_destroy_video_writer(mv_video_writer_h writer);
 
 /**
  * @brief Sets path and frame size for video file to be stored.
@@ -248,11 +229,7 @@ int mv_destroy_video_writer(
  *
  * @pre Create a video writer handle by calling @ref mv_create_video_writer()
  */
-int mv_video_writer_init(
-		mv_video_writer_h writer,
-		const char *path,
-		image_data_s image_data,
-		unsigned int fps);
+int mv_video_writer_init(mv_video_writer_h writer, const char *path, image_data_s image_data, unsigned int fps);
 
 /**
  * @brief   Writes consequently video frame to the file.
@@ -270,8 +247,6 @@ int mv_video_writer_init(
  * @pre Create a video writer handle by calling @ref mv_create_video_writer()
  *      and initialize video with @ref mv_video_writer_init()
  */
-int mv_video_writer_write_frame(
-		mv_video_writer_h writer,
-		unsigned char *frame);
+int mv_video_writer_write_frame(mv_video_writer_h writer, unsigned char *frame);
 
 #endif /* __MEDIA_VISION_MV_VIDEO_HELPER_H__ */
diff --git a/test/testsuites/face/face_test_suite.c b/test/testsuites/face/face_test_suite.c
index b20e620..1b421fd 100644
--- a/test/testsuites/face/face_test_suite.c
+++ b/test/testsuites/face/face_test_suite.c
@@ -41,12 +41,8 @@
 static bool Perform_eye_condition_recognize = false;
 static bool Perform_facial_expression_recognize = false;
 
-void eye_condition_cb(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s face_location,
-		mv_face_eye_condition_e eye_condition,
-		void *user_data)
+void eye_condition_cb(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s face_location,
+					  mv_face_eye_condition_e eye_condition, void *user_data)
 {
 	switch (eye_condition) {
 	case MV_FACE_EYES_NOT_FOUND:
@@ -61,12 +57,8 @@ void eye_condition_cb(
 	}
 }
 
-void face_expression_cb(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s face_location,
-		mv_face_facial_expression_e facial_expression,
-		void *user_data)
+void face_expression_cb(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s face_location,
+						mv_face_facial_expression_e facial_expression, void *user_data)
 {
 	switch (facial_expression) {
 	case MV_FACE_NEUTRAL:
@@ -83,12 +75,8 @@ void face_expression_cb(
 	}
 }
 
-void on_face_detected_cb(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s *faces_locations,
-		int number_of_faces,
-		void *user_data)
+void on_face_detected_cb(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s *faces_locations,
+						 int number_of_faces, void *user_data)
 {
 	printf("%i faces were detected on the image.\n", number_of_faces);
 	if (number_of_faces > 0) {
@@ -99,43 +87,35 @@ void on_face_detected_cb(
 		unsigned int buf_size = 0;
 		image_data_s image_data = { 0, 0, MEDIA_VISION_COLORSPACE_INVALID };
 		if (MEDIA_VISION_ERROR_NONE != mv_source_get_buffer(source, &out_buffer, &buf_size) ||
-				MEDIA_VISION_ERROR_NONE != mv_source_get_width(source, &(image_data.image_width)) ||
-				MEDIA_VISION_ERROR_NONE != mv_source_get_height(source, &(image_data.image_height)) ||
-				MEDIA_VISION_ERROR_NONE != mv_source_get_colorspace(source, &(image_data.image_colorspace)) ||
-				user_data == NULL) {
+			MEDIA_VISION_ERROR_NONE != mv_source_get_width(source, &(image_data.image_width)) ||
+			MEDIA_VISION_ERROR_NONE != mv_source_get_height(source, &(image_data.image_height)) ||
+			MEDIA_VISION_ERROR_NONE != mv_source_get_colorspace(source, &(image_data.image_colorspace)) ||
+			user_data == NULL) {
 			printf("ERROR: Creating out image is impossible.\n");
 		} else {
-			file_name = (char*)user_data;
+			file_name = (char *) user_data;
 			is_source_data_loaded = 1;
 		}
 
 		int i = 0;
 		for (i = 0; i < number_of_faces; ++i) {
-			printf("\nFace %i : x - %i, y - %i, width - %i, height - %i ", i,
-					faces_locations[i].point.x, faces_locations[i].point.y,
-					faces_locations[i].width, faces_locations[i].height);
+			printf("\nFace %i : x - %i, y - %i, width - %i, height - %i ", i, faces_locations[i].point.x,
+				   faces_locations[i].point.y, faces_locations[i].width, faces_locations[i].height);
 
 			if (Perform_eye_condition_recognize) {
-				if (MEDIA_VISION_ERROR_NONE != mv_face_eye_condition_recognize(
-							source,
-							engine_cfg,
-							faces_locations[i],
-							eye_condition_cb,
-							user_data)) {
-					printf(TEXT_RED "\nEye condition recognition for %i face failed"
-							TEXT_RESET "\n", i);
+				if (MEDIA_VISION_ERROR_NONE != mv_face_eye_condition_recognize(source, engine_cfg, faces_locations[i],
+																			   eye_condition_cb, user_data)) {
+					printf(TEXT_RED "\nEye condition recognition for %i face failed" TEXT_RESET "\n", i);
 				}
 			}
 
 			if (Perform_facial_expression_recognize) {
-				if (MEDIA_VISION_ERROR_NONE != mv_face_facial_expression_recognize(
-							source,
-							engine_cfg,
-							faces_locations[i],
-							face_expression_cb,
-							user_data)) {
+				if (MEDIA_VISION_ERROR_NONE != mv_face_facial_expression_recognize(source, engine_cfg,
+																				   faces_locations[i],
+																				   face_expression_cb, user_data)) {
 					printf(TEXT_RED "\nFacial expression recognition for %i "
-							"face failed" TEXT_RESET "\n", i);
+									"face failed" TEXT_RESET "\n",
+						   i);
 				}
 			}
 
@@ -143,16 +123,12 @@ void on_face_detected_cb(
 
 			if ((is_source_data_loaded == 1) && !Perform_eye_condition_recognize) {
 				const int rectangle_thickness = 3;
-				const int drawing_color[] = {255, 0, 0};
-				if (MEDIA_VISION_ERROR_NONE != draw_rectangle_on_buffer(
-							faces_locations[i].point.x,
-							faces_locations[i].point.y,
-							faces_locations[i].point.x + faces_locations[i].width,
-							faces_locations[i].point.y + faces_locations[i].height,
-							rectangle_thickness,
-							drawing_color,
-							&image_data,
-							out_buffer)) {
+				const int drawing_color[] = { 255, 0, 0 };
+				if (MEDIA_VISION_ERROR_NONE !=
+					draw_rectangle_on_buffer(faces_locations[i].point.x, faces_locations[i].point.y,
+											 faces_locations[i].point.x + faces_locations[i].width,
+											 faces_locations[i].point.y + faces_locations[i].height,
+											 rectangle_thickness, drawing_color, &image_data, out_buffer)) {
 					continue;
 				}
 			}
@@ -160,11 +136,7 @@ void on_face_detected_cb(
 
 		if (!Perform_eye_condition_recognize) {
 			if (file_name != NULL &&
-				MEDIA_VISION_ERROR_NONE == save_image_from_buffer(
-												file_name,
-												out_buffer,
-												&image_data,
-												100)) {
+				MEDIA_VISION_ERROR_NONE == save_image_from_buffer(file_name, out_buffer, &image_data, 100)) {
 				printf("Image was generated as %s\n", file_name);
 			} else {
 				printf("ERROR: Failed to generate output file. Check file name and permissions. \n");
@@ -175,22 +147,16 @@ void on_face_detected_cb(
 	}
 }
 
-void on_face_recognized_cb(
-		mv_source_h source,
-		mv_face_recognition_model_h recognition_model,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s *face_location,
-		const int *face_label,
-		double confidence,
-		void *user_data)
+void on_face_recognized_cb(mv_source_h source, mv_face_recognition_model_h recognition_model,
+						   mv_engine_config_h engine_cfg, mv_rectangle_s *face_location, const int *face_label,
+						   double confidence, void *user_data)
 {
 	if (NULL == face_location) {
-		printf(TEXT_YELLOW "No faces were recognized in the source"
-				TEXT_RESET "\n");
+		printf(TEXT_YELLOW "No faces were recognized in the source" TEXT_RESET "\n");
 	} else {
 		printf(TEXT_GREEN "Face labeled %i was recognized in the source with "
-						"recognition confidence of %.2f"
-						TEXT_RESET "\n", *face_label, confidence);
+						  "recognition confidence of %.2f" TEXT_RESET "\n",
+			   *face_label, confidence);
 	}
 }
 
@@ -206,9 +172,7 @@ int perform_detect()
 	mv_source_h source;
 	int err = mv_create_source(&source);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during creating the source!!! code: %i"
-				TEXT_RESET "\n", err);
+		printf(TEXT_RED "ERROR: Errors were occurred during creating the source!!! code: %i" TEXT_RESET "\n", err);
 
 		free(in_file_name);
 
@@ -219,9 +183,8 @@ int perform_detect()
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		const int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
-			printf(TEXT_RED
-					"ERROR: Errors were occurred during destroying the source!!! code: %i"
-					TEXT_RESET "\n", err2);
+			printf(TEXT_RED "ERROR: Errors were occurred during destroying the source!!! code: %i" TEXT_RESET "\n",
+				   err2);
 
 			free(in_file_name);
 
@@ -241,26 +204,23 @@ int perform_detect()
 
 	/* 3. Select Haar cascade */
 	const int options[3] = { 1, 2, 3 };
-	const char *names[3] = { "haarcascade_frontalface_alt.xml",
-								"haarcascade_frontalface_alt2.xml",
-								"haarcascade_frontalface_alt_tree.xml"};
+	const char *names[3] = { "haarcascade_frontalface_alt.xml", "haarcascade_frontalface_alt2.xml",
+							 "haarcascade_frontalface_alt_tree.xml" };
 
 	const int haarcascade = show_menu("Select Haarcascade:", options, names, 3);
 
 	mv_engine_config_h eng_config;
 	err = mv_create_engine_config(&eng_config);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during creating the engine config!!! code: %i"
-				TEXT_RESET "\n", err);
+		printf(TEXT_RED "ERROR: Errors were occurred during creating the engine config!!! code: %i" TEXT_RESET "\n",
+			   err);
 
 		free(out_file_name);
 
 		const int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
-			printf(TEXT_RED
-					"ERROR: Errors were occurred during destroying the source!!! code: %i"
-					TEXT_RESET "\n", err2);
+			printf(TEXT_RED "ERROR: Errors were occurred during destroying the source!!! code: %i" TEXT_RESET "\n",
+				   err2);
 		}
 
 		return err;
@@ -268,22 +228,16 @@ int perform_detect()
 
 	switch (haarcascade) {
 	case 1:
-		mv_engine_config_set_string_attribute(
-						eng_config,
-						MV_FACE_DETECTION_MODEL_FILE_PATH,
-						"/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt.xml");
+		mv_engine_config_set_string_attribute(eng_config, MV_FACE_DETECTION_MODEL_FILE_PATH,
+											  "/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt.xml");
 		break;
 	case 2:
-		mv_engine_config_set_string_attribute(
-						eng_config,
-						MV_FACE_DETECTION_MODEL_FILE_PATH,
-						"/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt2.xml");
+		mv_engine_config_set_string_attribute(eng_config, MV_FACE_DETECTION_MODEL_FILE_PATH,
+											  "/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt2.xml");
 		break;
 	case 3:
-		mv_engine_config_set_string_attribute(
-						eng_config,
-						MV_FACE_DETECTION_MODEL_FILE_PATH,
-						"/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt_tree.xml");
+		mv_engine_config_set_string_attribute(eng_config, MV_FACE_DETECTION_MODEL_FILE_PATH,
+											  "/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt_tree.xml");
 		break;
 	default:
 		printf(TEXT_YELLOW "Default Haar cascade was set.\n" TEXT_RESET);
@@ -295,23 +249,20 @@ int perform_detect()
 	free(out_file_name);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during face detection!!! code: %i"
-				TEXT_RESET "\n", err);
+		printf(TEXT_RED "ERROR: Errors were occurred during face detection!!! code: %i" TEXT_RESET "\n", err);
 
 		int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
-			printf(TEXT_RED
-					"ERROR: Errors were occurred during destroying the source!!! code: %i"
-					TEXT_RESET "\n", err2);
+			printf(TEXT_RED "ERROR: Errors were occurred during destroying the source!!! code: %i" TEXT_RESET "\n",
+				   err2);
 			return err2;
 		}
 
 		err2 = mv_destroy_engine_config(eng_config);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
-			printf(TEXT_RED
-					"ERROR: Errors were occurred during destroying the engine config!!! code: %i"
-					TEXT_RESET "\n", err2);
+			printf(TEXT_RED "ERROR: Errors were occurred during destroying the engine config!!! code: %i" TEXT_RESET
+							"\n",
+				   err2);
 			return err2;
 		}
 
@@ -320,17 +271,14 @@ int perform_detect()
 
 	err = mv_destroy_source(source);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during destroying the source!!! code: %i"
-				TEXT_RESET "\n", err);
+		printf(TEXT_RED "ERROR: Errors were occurred during destroying the source!!! code: %i" TEXT_RESET "\n", err);
 		return err;
 	}
 
 	err = mv_destroy_engine_config(eng_config);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during destroying the engine config!!! code: %i"
-				TEXT_RESET "\n", err);
+		printf(TEXT_RED "ERROR: Errors were occurred during destroying the engine config!!! code: %i" TEXT_RESET "\n",
+			   err);
 		return err;
 	}
 
@@ -345,25 +293,18 @@ int perform_mv_face_recognize(mv_face_recognition_model_h model)
 	int err = mv_create_source(&source);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during creating the source!!! code: %i"
-				TEXT_RESET "\n", err);
+		printf(TEXT_RED "ERROR: Errors were occurred during creating the source!!! code: %i" TEXT_RESET "\n", err);
 		return err;
 	}
 
-	printf(TEXT_GREEN "HINT:" TEXT_RESET "\n"
-			TEXT_YELLOW "To achieve appropriate accuracy of recognition,\n"
-						"choose images with only faces. I.e. face has to cover\n"
-						"approximately 95-100%% of the image (passport photos\n"
-						"are the best example :)). Note that if this value is\n"
-						"less than 95%%, accuracy can be significantly reduced.\n"
-						"In real code such images can be achieved by cropping\n"
-						"faces from images with face detection functionality.\n"
-			TEXT_RESET);
-	while (-1 == input_string(
-				"Input file name with the face to be recognized:",
-				1024,
-				&(in_file_name)))
+	printf(TEXT_GREEN "HINT:" TEXT_RESET "\n" TEXT_YELLOW "To achieve appropriate accuracy of recognition,\n"
+					  "choose images with only faces. I.e. face has to cover\n"
+					  "approximately 95-100%% of the image (passport photos\n"
+					  "are the best example :)). Note that if this value is\n"
+					  "less than 95%%, accuracy can be significantly reduced.\n"
+					  "In real code such images can be achieved by cropping\n"
+					  "faces from images with face detection functionality.\n" TEXT_RESET);
+	while (-1 == input_string("Input file name with the face to be recognized:", 1024, &(in_file_name)))
 		printf(TEXT_RED "Incorrect input! Try again." TEXT_RESET "\n");
 
 	err = load_mv_source_from_file(in_file_name, source);
@@ -373,9 +314,8 @@ int perform_mv_face_recognize(mv_face_recognition_model_h model)
 
 		const int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
-			printf(TEXT_RED
-					"ERROR: Errors were occurred during destroying the source!!! code: %i"
-					TEXT_RESET "\n", err2);
+			printf(TEXT_RED "ERROR: Errors were occurred during destroying the source!!! code: %i" TEXT_RESET "\n",
+				   err2);
 			return err2;
 		}
 
@@ -387,15 +327,12 @@ int perform_mv_face_recognize(mv_face_recognition_model_h model)
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		free(in_file_name);
 
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during face recognition!!! code: %i"
-				TEXT_RESET "\n", err);
+		printf(TEXT_RED "ERROR: Errors were occurred during face recognition!!! code: %i" TEXT_RESET "\n", err);
 
 		int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
-			printf(TEXT_RED
-					"ERROR: Errors were occurred during destroying the source!!! code: %i"
-					TEXT_RESET "\n", err2);
+			printf(TEXT_RED "ERROR: Errors were occurred during destroying the source!!! code: %i" TEXT_RESET "\n",
+				   err2);
 			return err2;
 		}
 
@@ -407,16 +344,13 @@ int perform_mv_face_recognize(mv_face_recognition_model_h model)
 	return err;
 }
 
-int add_single_example(
-		mv_face_recognition_model_h model, const char *in_file_name,
-		mv_rectangle_s *roi, int *face_label)
+int add_single_example(mv_face_recognition_model_h model, const char *in_file_name, mv_rectangle_s *roi,
+					   int *face_label)
 {
 	mv_source_h source;
 	int err = mv_create_source(&source);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during creating the source!!! code: %i"
-				TEXT_RESET "\n", err);
+		printf(TEXT_RED "ERROR: Errors were occurred during creating the source!!! code: %i" TEXT_RESET "\n", err);
 
 		return err;
 	}
@@ -425,9 +359,8 @@ int add_single_example(
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		const int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
-			printf(TEXT_RED
-					"ERROR: Errors were occurred during destroying the source!!! code: %i"
-					TEXT_RESET "\n", err2);
+			printf(TEXT_RED "ERROR: Errors were occurred during destroying the source!!! code: %i" TEXT_RESET "\n",
+				   err2);
 			return err2;
 		}
 
@@ -436,24 +369,19 @@ int add_single_example(
 
 	if (NULL != roi && !show_confirm_dialog("Do you want to use full image?")) {
 		printf(TEXT_YELLOW "Specify the ROI as rectangle where face is located.\n"
-							"Use negative values if you want to check correctness\n"
-							"of error handling.\n"
-				TEXT_RESET);
+						   "Use negative values if you want to check correctness\n"
+						   "of error handling.\n" TEXT_RESET);
 
-		while (-1 == input_int("Specify top left ROI x coordinate:",
-					INT_MIN, INT_MAX, &(roi->point.x)))
+		while (-1 == input_int("Specify top left ROI x coordinate:", INT_MIN, INT_MAX, &(roi->point.x)))
 			printf("Incorrect input! Try again.\n");
 
-		while (-1 == input_int("Specify top left ROI y coordinate:",
-					INT_MIN, INT_MAX, &(roi->point.y)))
+		while (-1 == input_int("Specify top left ROI y coordinate:", INT_MIN, INT_MAX, &(roi->point.y)))
 			printf("Incorrect input! Try again.\n");
 
-		while (-1 == input_int("Specify top left ROI width:",
-					INT_MIN, INT_MAX, &(roi->width)))
+		while (-1 == input_int("Specify top left ROI width:", INT_MIN, INT_MAX, &(roi->width)))
 			printf("Incorrect input! Try again.\n");
 
-		while (-1 == input_int("Specify top left ROI height:",
-					INT_MIN, INT_MAX, &(roi->height)))
+		while (-1 == input_int("Specify top left ROI height:", INT_MIN, INT_MAX, &(roi->height)))
 			printf("Incorrect input! Try again.\n");
 	} else {
 		roi = NULL;
@@ -462,63 +390,51 @@ int add_single_example(
 	int real_label = 0;
 	if (NULL == face_label) {
 		printf(TEXT_YELLOW "Also, you has to assign label for the face in the\n"
-							"image. You has assign the same labels for the same\n"
-							"persons. For example, always assign label '1' for\n"
-							"images with Alice's face; label '2' for Bob's faces,\n"
-							"'3' for Ann's faces and so on...\n"
-				TEXT_RESET);
+						   "image. You has assign the same labels for the same\n"
+						   "persons. For example, always assign label '1' for\n"
+						   "images with Alice's face; label '2' for Bob's faces,\n"
+						   "'3' for Ann's faces and so on...\n" TEXT_RESET);
 
 		face_label = &real_label;
-		while (-1 == input_int("Specify label as integer:",
-								MIN_ALLOWED_LABEL,
-								MAX_ALLOWED_LABEL,
-								face_label)) {
-			printf("Incorrect input! You can use %i-%i labels only. Try again.\n",
-					MIN_ALLOWED_LABEL,
-					MAX_ALLOWED_LABEL);
+		while (-1 == input_int("Specify label as integer:", MIN_ALLOWED_LABEL, MAX_ALLOWED_LABEL, face_label)) {
+			printf("Incorrect input! You can use %i-%i labels only. Try again.\n", MIN_ALLOWED_LABEL,
+				   MAX_ALLOWED_LABEL);
 		}
 	}
 
 	err = mv_face_recognition_model_add(source, model, roi, *face_label);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during adding the sample image from "
-				"[%s] to the face recognition model!!! code: %i"
-				TEXT_RESET "\n", in_file_name, err);
+		printf(TEXT_RED "ERROR: Errors were occurred during adding the sample image from "
+						"[%s] to the face recognition model!!! code: %i" TEXT_RESET "\n",
+			   in_file_name, err);
 	}
 
 	const int err2 = mv_destroy_source(source);
 	if (MEDIA_VISION_ERROR_NONE != err2) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during destroying the source!!! code: %i"
-				TEXT_RESET "\n", err2);
+		printf(TEXT_RED "ERROR: Errors were occurred during destroying the source!!! code: %i" TEXT_RESET "\n", err2);
 	}
 
 	return err;
 }
 
-int perform_mv_face_recognition_model_add_face_example(
-		mv_face_recognition_model_h model,
-		notification_type_e *notification_type)
+int perform_mv_face_recognition_model_add_face_example(mv_face_recognition_model_h model,
+													   notification_type_e *notification_type)
 {
 	char *in_file_name = NULL;
 
-	printf(TEXT_GREEN "HINT:" TEXT_RESET "\n"
-			TEXT_YELLOW "To achieve appropriate accuracy of recognition,\n"
-						"choose images with only faces. I.e. face has to cover\n"
-						"approximately 95-100%% of the image (passport photos\n"
-						"are the best example :)). Note that if this value is\n"
-						"less than 95%%, accuracy can be significantly reduced.\n"
-						"In real code such images can be achieved by cropping\n"
-						"faces from images with face detection functionality.\n"
-			TEXT_RESET);
+	printf(TEXT_GREEN "HINT:" TEXT_RESET "\n" TEXT_YELLOW "To achieve appropriate accuracy of recognition,\n"
+					  "choose images with only faces. I.e. face has to cover\n"
+					  "approximately 95-100%% of the image (passport photos\n"
+					  "are the best example :)). Note that if this value is\n"
+					  "less than 95%%, accuracy can be significantly reduced.\n"
+					  "In real code such images can be achieved by cropping\n"
+					  "faces from images with face detection functionality.\n" TEXT_RESET);
 
 	const bool from_dir = show_confirm_dialog("Do add images from directory?");
-	const char *input_path_msg =
-			from_dir ? "Input path to the directory with the face images to be "
-						"loaded to the model:"
-						: "Input file name with the face to be loaded to the model:";
+	const char *input_path_msg = from_dir ? "Input path to the directory with the face images to be "
+											"loaded to the model:" :
+											"Input file name with the face to be loaded to the model:";
 
 	while (-1 == input_string(input_path_msg, 1024, &(in_file_name)))
 		printf(TEXT_RED "Incorrect input! Try again." TEXT_RESET "\n");
@@ -528,13 +444,9 @@ int perform_mv_face_recognition_model_add_face_example(
 	if (from_dir) {
 		*notification_type = FAIL_OR_DONE;
 		int face_label = 0;
-		while (-1 == input_int("Specify label as integer:",
-								MIN_ALLOWED_LABEL,
-								MAX_ALLOWED_LABEL,
-								&face_label)) {
-			printf("Incorrect input! You can use %i-%i labels only. Try again.\n",
-					MIN_ALLOWED_LABEL,
-					MAX_ALLOWED_LABEL);
+		while (-1 == input_int("Specify label as integer:", MIN_ALLOWED_LABEL, MAX_ALLOWED_LABEL, &face_label)) {
+			printf("Incorrect input! You can use %i-%i labels only. Try again.\n", MIN_ALLOWED_LABEL,
+				   MAX_ALLOWED_LABEL);
 		}
 
 		DIR *dir;
@@ -554,17 +466,16 @@ int perform_mv_face_recognition_model_add_face_example(
 				if (MEDIA_VISION_ERROR_NONE != err) {
 					printf(TEXT_RED "Failed to add example from %s. "
 									"Error code: %i\n" TEXT_RESET,
-									file_path, err);
+						   file_path, err);
 				} else {
-					printf(TEXT_GREEN "Example labeled [%i] added from " TEXT_RESET
-							TEXT_YELLOW "%s\n" TEXT_RESET, face_label, file_path);
+					printf(TEXT_GREEN "Example labeled [%i] added from " TEXT_RESET TEXT_YELLOW "%s\n" TEXT_RESET,
+						   face_label, file_path);
 				}
 			}
 
 			closedir(dir);
 		} else {
-			printf(TEXT_RED "Can't read from specified directory (%s)\n"
-					TEXT_RESET, in_file_name);
+			printf(TEXT_RED "Can't read from specified directory (%s)\n" TEXT_RESET, in_file_name);
 		}
 	} else {
 		*notification_type = FAIL_OR_SUCCESSS;
@@ -577,52 +488,45 @@ int perform_mv_face_recognition_model_add_face_example(
 	return err;
 }
 
-int perform_mv_face_recognition_model_reset_face_examples(
-		mv_face_recognition_model_h model,
-		bool full_reset)
+int perform_mv_face_recognition_model_reset_face_examples(mv_face_recognition_model_h model, bool full_reset)
 {
-	printf(TEXT_GREEN "HINT:" TEXT_RESET "\n"
-			TEXT_YELLOW "Reset of the examples will affect only examples has\n"
-						"been collected via mv_face_recognition_model_add()\n"
-						"function calls (i.e. through 'Add image example' menu\n"
-						"item). Previously learned model will be not affected,\n"
-						"so it is possible to recognize faces with this model\n"
-						"after examples reset. Reset of the examples can be\n"
-						"useful to erase a class of faces (i.e. all examples\n"
-						"related to this class) before learning the model.\n"
-						"Or, if it is needed to reset all collected previously\n"
-						"examples as an alternative to the creating the new\n"
-						"model.\n"
-			TEXT_RESET);
+	printf(TEXT_GREEN "HINT:" TEXT_RESET "\n" TEXT_YELLOW "Reset of the examples will affect only examples has\n"
+					  "been collected via mv_face_recognition_model_add()\n"
+					  "function calls (i.e. through 'Add image example' menu\n"
+					  "item). Previously learned model will be not affected,\n"
+					  "so it is possible to recognize faces with this model\n"
+					  "after examples reset. Reset of the examples can be\n"
+					  "useful to erase a class of faces (i.e. all examples\n"
+					  "related to this class) before learning the model.\n"
+					  "Or, if it is needed to reset all collected previously\n"
+					  "examples as an alternative to the creating the new\n"
+					  "model.\n" TEXT_RESET);
 
 	int err = MEDIA_VISION_ERROR_NONE;
 
 	if (full_reset) {
 		err = mv_face_recognition_model_reset(model, NULL);
 		if (MEDIA_VISION_ERROR_NONE != err) {
-			printf(TEXT_RED
-					"ERROR: Errors were occurred during reset of all examples!!!"
-					" code: %i" TEXT_RESET "\n", err);
+			printf(TEXT_RED "ERROR: Errors were occurred during reset of all examples!!!"
+							" code: %i" TEXT_RESET "\n",
+				   err);
 			return err;
 		}
 	} else {
 		int reset_label = 0;
 
-		while (-1 == input_int("Specify label for the examples to be reset:",
-								MIN_ALLOWED_LABEL,
-								MAX_ALLOWED_LABEL,
-								&reset_label)) {
-			printf("Incorrect input! You can use %i-%i labels only. Try again.\n",
-					MIN_ALLOWED_LABEL,
-					MAX_ALLOWED_LABEL);
+		while (-1 == input_int("Specify label for the examples to be reset:", MIN_ALLOWED_LABEL, MAX_ALLOWED_LABEL,
+							   &reset_label)) {
+			printf("Incorrect input! You can use %i-%i labels only. Try again.\n", MIN_ALLOWED_LABEL,
+				   MAX_ALLOWED_LABEL);
 		}
 
 		err = mv_face_recognition_model_reset(model, &reset_label);
 
 		if (MEDIA_VISION_ERROR_NONE != err) {
-			printf(TEXT_RED
-					"ERROR: Errors were occurred during reset of examples labeled"
-					" with  %i!!! code: %i" TEXT_RESET "\n", reset_label, err);
+			printf(TEXT_RED "ERROR: Errors were occurred during reset of examples labeled"
+							" with  %i!!! code: %i" TEXT_RESET "\n",
+				   reset_label, err);
 			return err;
 		}
 	}
@@ -634,8 +538,7 @@ int perform_mv_face_recognition_model_save(mv_face_recognition_model_h model)
 {
 	char *out_file_name = NULL;
 
-	while (input_string("Input file name to save the model:",
-				1024, &(out_file_name)) == -1)
+	while (input_string("Input file name to save the model:", 1024, &(out_file_name)) == -1)
 		printf(TEXT_RED "Incorrect input! Try again." TEXT_RESET "\n");
 
 	const int err = mv_face_recognition_model_save(out_file_name, model);
@@ -649,8 +552,7 @@ int perform_mv_face_recognition_model_load(mv_face_recognition_model_h *model)
 {
 	char *in_file_name = NULL;
 
-	while (input_string("Input file name to load model from:",
-				1024, &(in_file_name)) == -1)
+	while (input_string("Input file name to load model from:", 1024, &(in_file_name)) == -1)
 		printf(TEXT_RED "Incorrect input! Try again." TEXT_RESET "\n");
 
 	const int err = mv_face_recognition_model_load(in_file_name, model);
@@ -660,51 +562,46 @@ int perform_mv_face_recognition_model_load(mv_face_recognition_model_h *model)
 	return err;
 }
 
-int perform_mv_face_recognition_model_clone(
-		mv_face_recognition_model_h model_to_clone)
+int perform_mv_face_recognition_model_clone(mv_face_recognition_model_h model_to_clone)
 {
 	int err = MEDIA_VISION_ERROR_NONE;
 
 	mv_face_recognition_model_h cloned_model = NULL;
 
-	printf(TEXT_GREEN "Perform clone of the recognition model..."
-			TEXT_RESET "\n");
+	printf(TEXT_GREEN "Perform clone of the recognition model..." TEXT_RESET "\n");
 
 	err = mv_face_recognition_model_clone(model_to_clone, &cloned_model);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED "Errors were occurred during model clone. Error code %i"
-				TEXT_RESET "\n", err);
+		printf(TEXT_RED "Errors were occurred during model clone. Error code %i" TEXT_RESET "\n", err);
 		return err;
 	}
 
 	printf(TEXT_YELLOW "Model cloning is done." TEXT_RESET "\n");
 
-	if (show_confirm_dialog("Save " TEXT_YELLOW "source model" TEXT_RESET
-							" to file?")) {
+	if (show_confirm_dialog("Save " TEXT_YELLOW "source model" TEXT_RESET " to file?")) {
 		const int serr = perform_mv_face_recognition_model_save(model_to_clone);
 		if (MEDIA_VISION_ERROR_NONE != serr) {
-			printf(TEXT_RED
-					"Errors were occurred when trying to save "
-					"source model to file. Error code %i" TEXT_RESET "\n", serr);
+			printf(TEXT_RED "Errors were occurred when trying to save "
+							"source model to file. Error code %i" TEXT_RESET "\n",
+				   serr);
 		}
 	}
 
-	if (show_confirm_dialog("Save " TEXT_YELLOW "destination model" TEXT_RESET
-							" to file?")) {
+	if (show_confirm_dialog("Save " TEXT_YELLOW "destination model" TEXT_RESET " to file?")) {
 		const int serr = perform_mv_face_recognition_model_save(cloned_model);
 		if (MEDIA_VISION_ERROR_NONE != serr) {
-			printf(TEXT_RED
-					"Errors were occurred when trying to save destination model "
-					"to file. Error code %i" TEXT_RESET "\n", serr);
+			printf(TEXT_RED "Errors were occurred when trying to save destination model "
+							"to file. Error code %i" TEXT_RESET "\n",
+				   serr);
 		}
 	}
 
 	if (cloned_model) {
 		const int dest_err = mv_face_recognition_model_destroy(cloned_model);
 		if (MEDIA_VISION_ERROR_NONE != dest_err) {
-			printf(TEXT_RED
-				"Errors were occurred when destroying destination model ."
-				"Error code %i" TEXT_RESET "\n", dest_err);
+			printf(TEXT_RED "Errors were occurred when destroying destination model ."
+							"Error code %i" TEXT_RESET "\n",
+				   dest_err);
 		}
 	}
 
@@ -714,13 +611,12 @@ int perform_mv_face_recognition_model_clone(
 int perform_mv_face_recognition_model_learn(mv_face_recognition_model_h model)
 {
 	printf(TEXT_YELLOW "Learning the model has to be performed after\n"
-						"adding some amount of examples to the model.\n"
-						"If you learn without examples, you will get useless\n"
-						"model, which will be unavailable to recognize. Anyway,\n"
-						"you can add examples and launch this method again to\n"
-						"get the appropriate recognition model suitable for\n"
-						"recognition."
-			TEXT_RESET "\n");
+					   "adding some amount of examples to the model.\n"
+					   "If you learn without examples, you will get useless\n"
+					   "model, which will be unavailable to recognize. Anyway,\n"
+					   "you can add examples and launch this method again to\n"
+					   "get the appropriate recognition model suitable for\n"
+					   "recognition." TEXT_RESET "\n");
 
 	printf(TEXT_GREEN "Start learning process..." TEXT_RESET "\n");
 
@@ -728,11 +624,10 @@ int perform_mv_face_recognition_model_learn(mv_face_recognition_model_h model)
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf(TEXT_RED "Learning the model failed. Error code: %i. "
-				"But you still can test with this model.\n"
-				TEXT_RESET "\n", err);
+						"But you still can test with this model.\n" TEXT_RESET "\n",
+			   err);
 	} else {
-		printf(TEXT_YELLOW "Recognition model has been learned."
-				TEXT_RESET "\n");
+		printf(TEXT_YELLOW "Recognition model has been learned." TEXT_RESET "\n");
 	}
 
 	return err;
@@ -751,8 +646,7 @@ int perform_mv_face_recognition_model_query_labels(mv_face_recognition_model_h m
 		return err;
 	}
 
-	printf(TEXT_YELLOW "Recognition model had been learned for the following labels: "
-			TEXT_RESET "\n" TEXT_GREEN);
+	printf(TEXT_YELLOW "Recognition model had been learned for the following labels: " TEXT_RESET "\n" TEXT_GREEN);
 	for (unsigned i = 0; i < learned_labels_n; ++i)
 		printf("%i, ", learned_labels[i]);
 
@@ -769,17 +663,11 @@ static int TN = 0;
 static int FN = 0;
 static double THRESHOLD = 0.75;
 
-void evaluation_cb(
-		mv_source_h source,
-		mv_face_recognition_model_h recognition_model,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s *face_location,
-		const int *face_label,
-		double confidence,
-		void *user_data)
+void evaluation_cb(mv_source_h source, mv_face_recognition_model_h recognition_model, mv_engine_config_h engine_cfg,
+				   mv_rectangle_s *face_location, const int *face_label, double confidence, void *user_data)
 {
 	if (NULL != user_data) {
-		const int real_label = *((int*)user_data);
+		const int real_label = *((int *) user_data);
 		const int rec_label = (NULL != face_label ? *face_label : -1);
 		if (real_label == -1) {
 			confidence >= THRESHOLD ? ++FP : ++TN;
@@ -802,8 +690,7 @@ int perform_model_evaluation(mv_face_recognition_model_h model)
 	mv_face_recognition_model_query_labels(model, &learned_labels, &learned_labels_n);
 
 	int i = 0;
-	printf(TEXT_YELLOW "Evaluating model had been learned for the following labels: "
-			TEXT_RESET "\n" TEXT_GREEN);
+	printf(TEXT_YELLOW "Evaluating model had been learned for the following labels: " TEXT_RESET "\n" TEXT_GREEN);
 	for (i = 0; i < learned_labels_n; ++i)
 		printf("%i, ", learned_labels[i]);
 
@@ -811,7 +698,7 @@ int perform_model_evaluation(mv_face_recognition_model_h model)
 
 	/* 100 directories are allowed: */
 	const int max_dir_allowed = 100;
-	char (*directories)[1024] = malloc(sizeof *directories * max_dir_allowed);
+	char(*directories)[1024] = malloc(sizeof *directories * max_dir_allowed);
 	int labels[max_dir_allowed];
 	int unique_checks[MAX_ALLOWED_LABEL + 1];
 	for (i = 0; i < MAX_ALLOWED_LABEL + 1; ++i)
@@ -819,16 +706,14 @@ int perform_model_evaluation(mv_face_recognition_model_h model)
 
 	int dir_n = 0;
 	int label_count = 0;
-	while (show_confirm_dialog("Add test images directory?") &&
-			dir_n < max_dir_allowed) {
+	while (show_confirm_dialog("Add test images directory?") && dir_n < max_dir_allowed) {
 		char *in_file_name = NULL;
 		while (-1 == input_string("Specify path to the test images directory:", 1024, &(in_file_name)))
 			printf(TEXT_RED "Incorrect input! Try again." TEXT_RESET "\n");
 
 		DIR *dir;
 		if ((dir = opendir(in_file_name)) == NULL) {
-			printf(TEXT_RED "Incorrect input! Directory %s can't be read.\n"
-					TEXT_RESET, in_file_name);
+			printf(TEXT_RED "Incorrect input! Directory %s can't be read.\n" TEXT_RESET, in_file_name);
 			free(in_file_name);
 			in_file_name = NULL;
 			continue;
@@ -837,14 +722,9 @@ int perform_model_evaluation(mv_face_recognition_model_h model)
 		}
 
 		int face_label = 0;
-		if (-1 == input_int("Specify label as integer:",
-								MIN_ALLOWED_LABEL,
-								MAX_ALLOWED_LABEL,
-								&face_label)) {
-			printf(TEXT_RED "Incorrect input! You can use %i-%i labels only.\n"
-					TEXT_RESET,
-					MIN_ALLOWED_LABEL,
-					MAX_ALLOWED_LABEL);
+		if (-1 == input_int("Specify label as integer:", MIN_ALLOWED_LABEL, MAX_ALLOWED_LABEL, &face_label)) {
+			printf(TEXT_RED "Incorrect input! You can use %i-%i labels only.\n" TEXT_RESET, MIN_ALLOWED_LABEL,
+				   MAX_ALLOWED_LABEL);
 			free(in_file_name);
 			in_file_name = NULL;
 			continue;
@@ -860,7 +740,7 @@ int perform_model_evaluation(mv_face_recognition_model_h model)
 
 		if (!known_label) {
 			printf(TEXT_YELLOW "Recognition model didn't learn with specified label.\n"
-								"Images will be marked as unknown (-1)\n" TEXT_RESET);
+							   "Images will be marked as unknown (-1)\n" TEXT_RESET);
 		}
 
 		labels[dir_n] = known_label ? face_label : -1;
@@ -898,9 +778,7 @@ int perform_model_evaluation(mv_face_recognition_model_h model)
 	int err = mv_create_source(&source);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		free(directories);
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during creating the source!!! code: %i"
-				TEXT_RESET "\n", err);
+		printf(TEXT_RED "ERROR: Errors were occurred during creating the source!!! code: %i" TEXT_RESET "\n", err);
 		return err;
 	}
 
@@ -923,38 +801,35 @@ int perform_model_evaluation(mv_face_recognition_model_h model)
 					printf(TEXT_RED "Failed to test on example from %s. "
 									"Example will not affect the evaluation. "
 									"Error code: %i\n" TEXT_RESET,
-									file_path, err);
+						   file_path, err);
 				} else {
 					err = mv_face_recognize(source, model, NULL, NULL, evaluation_cb, &(labels[i]));
-				if (MEDIA_VISION_ERROR_NONE != err) {
-					printf(TEXT_RED "Failed to recognize on example from %s. "
+					if (MEDIA_VISION_ERROR_NONE != err) {
+						printf(TEXT_RED "Failed to recognize on example from %s. "
 										"Example will not affect the evaluation. "
 										"Error code: %i\n" TEXT_RESET,
-										file_path, err);
+							   file_path, err);
 					}
 				}
 			}
 
 			closedir(dir);
 		} else {
-			printf(TEXT_RED "Can't read from directory [%s]\n"
-					TEXT_RESET, directories[i]);
+			printf(TEXT_RED "Can't read from directory [%s]\n" TEXT_RESET, directories[i]);
 		}
 	}
 
 	int err2 = mv_destroy_source(source);
 	if (MEDIA_VISION_ERROR_NONE != err2) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during destroying the source!!! code: %i"
-				TEXT_RESET "\n", err2);
+		printf(TEXT_RED "ERROR: Errors were occurred during destroying the source!!! code: %i" TEXT_RESET "\n", err2);
 	}
 
 	double accuracy = (TP + TN) / (double) (TP + FP + TN + FN);
 
-	double prec_denom = (double)(TP + FP);
+	double prec_denom = (double) (TP + FP);
 	double precision = (prec_denom < 1.0) ? 0.0 : TP / prec_denom;
 
-	double recall_denom = (double)(TP + FN);
+	double recall_denom = (double) (TP + FN);
 	double recall = (recall_denom < 1.0) ? 0.0 : TP / recall_denom;
 
 	double f1 = 2 * precision * recall / (precision + recall);
@@ -976,13 +851,10 @@ int perform_model_evaluation(mv_face_recognition_model_h model)
 
 int perform_recognize()
 {
-	printf("\n" TEXT_YELLOW
-			"Recognition model isn't now created.\n"
-			"You may create it to perform positive \n"
-			"testing, or don't create to check the \n"
-			"functionality behaviour for uncreated model."
-			TEXT_RESET
-			"\n");
+	printf("\n" TEXT_YELLOW "Recognition model isn't now created.\n"
+		   "You may create it to perform positive \n"
+		   "testing, or don't create to check the \n"
+		   "functionality behaviour for uncreated model." TEXT_RESET "\n");
 
 	int err = MEDIA_VISION_ERROR_NONE;
 	mv_face_recognition_model_h recognition_model = NULL;
@@ -993,27 +865,19 @@ int perform_recognize()
 		err = mv_face_recognition_model_create(&recognition_model);
 		if (MEDIA_VISION_ERROR_NONE != err) {
 			printf(TEXT_RED "Creating the model failed. Error code: %i. "
-					"But you still can test with uncreated model.\n"
-					TEXT_RESET "\n", err);
+							"But you still can test with uncreated model.\n" TEXT_RESET "\n",
+				   err);
 		} else {
-			printf(TEXT_YELLOW "Recognition model has been created."
-					TEXT_RESET "\n");
+			printf(TEXT_YELLOW "Recognition model has been created." TEXT_RESET "\n");
 		}
 	}
 
 	int sel_opt = 0;
 	const int options[11] = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 };
-	const char *names[11] = { "Add image example",
-								"Reset examples by id",
-								"Reset all examples",
-								"Clone the model",
-								"Learn the model",
-								"Show learned labels",
-								"Save model to file",
-								"Load model from file",
-								"Recognize with model",
-								"Evaluate the model",
-								"Destroy model and exit" };
+	const char *names[11] = { "Add image example",	"Reset examples by id",	 "Reset all examples",
+							  "Clone the model",	"Learn the model",		 "Show learned labels",
+							  "Save model to file", "Load model from file",	 "Recognize with model",
+							  "Evaluate the model", "Destroy model and exit" };
 
 	while (!sel_opt) {
 		sel_opt = show_menu("Select action:", options, names, 11);
@@ -1054,9 +918,7 @@ int perform_recognize()
 			if (do_create) {
 				err = mv_face_recognition_model_destroy(recognition_model);
 				if (MEDIA_VISION_ERROR_NONE != err) {
-					printf(TEXT_RED
-								"Error with code %i was occurred during destroy"
-								TEXT_RESET "\n", err);
+					printf(TEXT_RED "Error with code %i was occurred during destroy" TEXT_RESET "\n", err);
 				}
 			} else {
 				err = MEDIA_VISION_ERROR_NONE;
@@ -1081,8 +943,7 @@ int perform_mv_face_tracking_model_save(mv_face_tracking_model_h model)
 {
 	char *out_file_name = NULL;
 
-	while (input_string("Input file name to save the model:",
-						1024, &(out_file_name)) == -1) {
+	while (input_string("Input file name to save the model:", 1024, &(out_file_name)) == -1) {
 		printf(TEXT_RED "Incorrect input! Try again." TEXT_RESET "\n");
 	}
 
@@ -1097,8 +958,7 @@ int perform_mv_face_tracking_model_load(mv_face_tracking_model_h *model)
 {
 	char *in_file_name = NULL;
 
-	while (input_string("Input file name to load model from:",
-						1024, &(in_file_name)) == -1) {
+	while (input_string("Input file name to load model from:", 1024, &(in_file_name)) == -1) {
 		printf(TEXT_RED "Incorrect input! Try again." TEXT_RESET "\n");
 	}
 
@@ -1109,51 +969,46 @@ int perform_mv_face_tracking_model_load(mv_face_tracking_model_h *model)
 	return err;
 }
 
-int perform_mv_face_tracking_model_clone(
-		mv_face_tracking_model_h model_to_clone)
+int perform_mv_face_tracking_model_clone(mv_face_tracking_model_h model_to_clone)
 {
 	int err = MEDIA_VISION_ERROR_NONE;
 
 	mv_face_tracking_model_h cloned_model = NULL;
 
-	printf(TEXT_GREEN "Perform clone of the tracking model..."
-			TEXT_RESET "\n");
+	printf(TEXT_GREEN "Perform clone of the tracking model..." TEXT_RESET "\n");
 
 	err = mv_face_tracking_model_clone(model_to_clone, &cloned_model);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED "Errors were occurred during model clone. Error code %i"
-				TEXT_RESET "\n", err);
+		printf(TEXT_RED "Errors were occurred during model clone. Error code %i" TEXT_RESET "\n", err);
 		return err;
 	}
 
 	printf(TEXT_YELLOW "Model cloning is done." TEXT_RESET "\n");
 
-	if (show_confirm_dialog("Save " TEXT_YELLOW "source model" TEXT_RESET
-							" to file?")) {
+	if (show_confirm_dialog("Save " TEXT_YELLOW "source model" TEXT_RESET " to file?")) {
 		const int serr = perform_mv_face_tracking_model_save(model_to_clone);
 		if (MEDIA_VISION_ERROR_NONE != serr) {
-			printf(TEXT_RED
-					"Errors were occurred when trying to save "
-					"source model to file. Error code %i" TEXT_RESET "\n", serr);
+			printf(TEXT_RED "Errors were occurred when trying to save "
+							"source model to file. Error code %i" TEXT_RESET "\n",
+				   serr);
 		}
 	}
 
-	if (show_confirm_dialog("Save " TEXT_YELLOW "destination model" TEXT_RESET
-							" to file?")) {
+	if (show_confirm_dialog("Save " TEXT_YELLOW "destination model" TEXT_RESET " to file?")) {
 		const int serr = perform_mv_face_tracking_model_save(cloned_model);
 		if (MEDIA_VISION_ERROR_NONE != serr) {
-			printf(TEXT_RED
-					"Errors were occurred when trying to save destination model "
-					"to file. Error code %i" TEXT_RESET "\n", serr);
+			printf(TEXT_RED "Errors were occurred when trying to save destination model "
+							"to file. Error code %i" TEXT_RESET "\n",
+				   serr);
 		}
 	}
 
 	if (cloned_model) {
 		const int dest_err = mv_face_tracking_model_destroy(cloned_model);
 		if (MEDIA_VISION_ERROR_NONE != dest_err) {
-			printf(TEXT_RED
-					"Errors were occurred when destroying destination model ."
-					"Error code %i" TEXT_RESET "\n", dest_err);
+			printf(TEXT_RED "Errors were occurred when destroying destination model ."
+							"Error code %i" TEXT_RESET "\n",
+				   dest_err);
 		}
 	}
 
@@ -1162,68 +1017,51 @@ int perform_mv_face_tracking_model_clone(
 
 static volatile bool frame_read = false;
 
-void video_1_sample_cb(
-		char *buffer,
-		unsigned int buffer_size,
-		image_data_s image_data,
-		void *user_data)
+void video_1_sample_cb(char *buffer, unsigned int buffer_size, image_data_s image_data, void *user_data)
 {
 	if (!frame_read) {
-		mv_source_h source = (mv_source_h)user_data;
+		mv_source_h source = (mv_source_h) user_data;
 
-		const int err = mv_source_fill_by_buffer(
-							source,
-							(unsigned char*)buffer,
-							buffer_size,
-							image_data.image_width,
-							image_data.image_height,
-							image_data.image_colorspace);
+		const int err = mv_source_fill_by_buffer(source, (unsigned char *) buffer, buffer_size, image_data.image_width,
+												 image_data.image_height, image_data.image_colorspace);
 
 		if (MEDIA_VISION_ERROR_NONE != err) {
 			printf(TEXT_RED "ERROR: Errors were occurred during filling the "
-					"source based on the video frame! Error code: %i"
-					TEXT_RESET, err);
+							"source based on the video frame! Error code: %i" TEXT_RESET,
+				   err);
 		}
 
 		frame_read = true;
 	}
 }
 
-void face_detected_for_tracking_cb(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		mv_rectangle_s *faces_locations,
-		int number_of_faces,
-		void *user_data)
+void face_detected_for_tracking_cb(mv_source_h source, mv_engine_config_h engine_cfg, mv_rectangle_s *faces_locations,
+								   int number_of_faces, void *user_data)
 {
 	if (number_of_faces < 1) {
 		printf(TEXT_RED "Unfortunately, no faces were detected on the\n"
 						"preparation frame. You has to specify bounding\n"
-						"quadrangles for tracking without advices."
-				TEXT_RESET "\n");
+						"quadrangles for tracking without advices." TEXT_RESET "\n");
 		return;
 	}
 
 	printf(TEXT_YELLOW "%i face(s) were detected at the preparation frame.\n"
-						"Following list includes information on faces bounding\n"
-						"boxes coordinates:"
-			TEXT_RESET "\n", number_of_faces);
+					   "Following list includes information on faces bounding\n"
+					   "boxes coordinates:" TEXT_RESET "\n",
+		   number_of_faces);
 
 	int idx = 0;
 	while (idx < number_of_faces) {
 		printf(TEXT_MAGENTA "Face %i bounding box: " TEXT_RESET "\n", ++idx);
-		printf(TEXT_CYAN "\tTop left point:     x1: %4i;  y1: %4i\n" TEXT_RESET,
-				faces_locations[idx - 1].point.x,
-				faces_locations[idx - 1].point.y);
+		printf(TEXT_CYAN "\tTop left point:     x1: %4i;  y1: %4i\n" TEXT_RESET, faces_locations[idx - 1].point.x,
+			   faces_locations[idx - 1].point.y);
 		printf(TEXT_CYAN "\tTop right point:    x2: %4i;  y2: %4i\n" TEXT_RESET,
-				faces_locations[idx - 1].point.x + faces_locations[idx - 1].width,
-				faces_locations[idx - 1].point.y);
+			   faces_locations[idx - 1].point.x + faces_locations[idx - 1].width, faces_locations[idx - 1].point.y);
 		printf(TEXT_CYAN "\tBottom right point: x3: %4i;  y3: %4i\n" TEXT_RESET,
-				faces_locations[idx - 1].point.x + faces_locations[idx - 1].width,
-				faces_locations[idx - 1].point.y + faces_locations[idx - 1].height);
-		printf(TEXT_CYAN "\tBottom right point: x4: %4i;  y4: %4i\n" TEXT_RESET,
-				faces_locations[idx - 1].point.x,
-				faces_locations[idx - 1].point.y + faces_locations[idx - 1].height);
+			   faces_locations[idx - 1].point.x + faces_locations[idx - 1].width,
+			   faces_locations[idx - 1].point.y + faces_locations[idx - 1].height);
+		printf(TEXT_CYAN "\tBottom right point: x4: %4i;  y4: %4i\n" TEXT_RESET, faces_locations[idx - 1].point.x,
+			   faces_locations[idx - 1].point.y + faces_locations[idx - 1].height);
 	}
 }
 
@@ -1233,22 +1071,22 @@ int load_source_from_first_video_frame(const char *video_file, mv_source_h sourc
 	int err = mv_create_video_reader(&reader);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf(TEXT_RED "ERROR: Errors were occurred during creating the video "
-				"reader! Error code: %i\n" TEXT_RESET, err);
+						"reader! Error code: %i\n" TEXT_RESET,
+			   err);
 		return err;
 	}
 
-	err = mv_video_reader_set_new_sample_cb(
-					reader,
-					video_1_sample_cb,
-					source);
+	err = mv_video_reader_set_new_sample_cb(reader, video_1_sample_cb, source);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf(TEXT_RED "ERROR: Errors were occurred during new sample "
-				"callback set! Error code: %i\n" TEXT_RESET, err);
+						"callback set! Error code: %i\n" TEXT_RESET,
+			   err);
 
 		const int err2 = mv_destroy_video_reader(reader);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf(TEXT_RED "ERROR: Errors were occurred during video reader "
-					"destroy! Error code: %i\n" TEXT_RESET, err);
+							"destroy! Error code: %i\n" TEXT_RESET,
+				   err);
 		}
 
 		return err;
@@ -1260,12 +1098,14 @@ int load_source_from_first_video_frame(const char *video_file, mv_source_h sourc
 	err = mv_video_reader_load(reader, video_file, &video_info, &fps);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf(TEXT_RED "ERROR: Errors were occurred during loading the video "
-				"by reader! Error code: %i\n" TEXT_RESET, err);
+						"by reader! Error code: %i\n" TEXT_RESET,
+			   err);
 
 		const int err2 = mv_destroy_video_reader(reader);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf(TEXT_RED "ERROR: Errors were occurred during video reader "
-					"destroy! Error code: %i\n" TEXT_RESET, err);
+							"destroy! Error code: %i\n" TEXT_RESET,
+				   err);
 		}
 
 		return err;
@@ -1277,13 +1117,15 @@ int load_source_from_first_video_frame(const char *video_file, mv_source_h sourc
 			int err2 = mv_video_reader_stop(reader);
 			if (MEDIA_VISION_ERROR_NONE != err2) {
 				printf(TEXT_RED "ERROR: Errors were occurred during attempt to "
-						"stop video reader! Error code: %i\n" TEXT_RESET, err2);
+								"stop video reader! Error code: %i\n" TEXT_RESET,
+					   err2);
 			}
 
 			err2 = mv_destroy_video_reader(reader);
 			if (MEDIA_VISION_ERROR_NONE != err2) {
 				printf(TEXT_RED "ERROR: Errors were occurred during video "
-						"reader destroy! Error code: %i\n" TEXT_RESET, err2);
+								"reader destroy! Error code: %i\n" TEXT_RESET,
+					   err2);
 			}
 
 			break;
@@ -1296,26 +1138,24 @@ int load_source_from_first_video_frame(const char *video_file, mv_source_h sourc
 int perform_mv_face_tracking_model_prepare(mv_face_tracking_model_h model)
 {
 	printf(TEXT_YELLOW "Before any tracking session the tracking model\n"
-						"preparation is required. Exception is the case when\n"
-						"the next tracking session will be performed with the\n"
-						"video which is the direct continuation of the video\n"
-						"has been used at the previous tracking session.\n"
-						"Preparation has to be done with the first frame of\n"
-						"the video or first image from continuous image\n"
-						"sequence for which next tracking session plan to be\n"
-						"performed.\nTracking model preparation includes\n"
-						"specifying the location of the face to be tracked on\n"
-						"the first frame. Face tracking algorithm will try to\n"
-						"grab the face image significant features and\n"
-						"optionally will try to determine the background.\n"
-						"Actually, preparation is model-dependent and may\n"
-						"differs in respect to used tracking algorithm."
-			TEXT_RESET "\n");
+					   "preparation is required. Exception is the case when\n"
+					   "the next tracking session will be performed with the\n"
+					   "video which is the direct continuation of the video\n"
+					   "has been used at the previous tracking session.\n"
+					   "Preparation has to be done with the first frame of\n"
+					   "the video or first image from continuous image\n"
+					   "sequence for which next tracking session plan to be\n"
+					   "performed.\nTracking model preparation includes\n"
+					   "specifying the location of the face to be tracked on\n"
+					   "the first frame. Face tracking algorithm will try to\n"
+					   "grab the face image significant features and\n"
+					   "optionally will try to determine the background.\n"
+					   "Actually, preparation is model-dependent and may\n"
+					   "differs in respect to used tracking algorithm." TEXT_RESET "\n");
 
 	int sel_opt = 0;
 	const int options[2] = { 1, 2 };
-	const char *names[2] = { "Prepare with the video file",
-								"Prepare with the image file" };
+	const char *names[2] = { "Prepare with the video file", "Prepare with the image file" };
 	bool is_video = false;
 
 	while (!sel_opt) {
@@ -1337,17 +1177,14 @@ int perform_mv_face_tracking_model_prepare(mv_face_tracking_model_h model)
 	int err = mv_create_source(&preparation_frame);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during creating the source!!! code: %i"
-				TEXT_RESET "\n", err);
+		printf(TEXT_RED "ERROR: Errors were occurred during creating the source!!! code: %i" TEXT_RESET "\n", err);
 
 		return err;
 	}
 
 	char *init_frame_file_name = NULL;
 	const char *prompt_str =
-			(is_video ? "Input video file name to prepare the model:"
-						: "Input image file name to prepare the model:");
+			(is_video ? "Input video file name to prepare the model:" : "Input image file name to prepare the model:");
 
 	while (input_string(prompt_str, 1024, &(init_frame_file_name)) == -1)
 		printf(TEXT_RED "Incorrect input! Try again.\n" TEXT_RESET);
@@ -1362,12 +1199,14 @@ int perform_mv_face_tracking_model_prepare(mv_face_tracking_model_h model)
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf(TEXT_RED "ERROR: Errors were occurred during preparation "
-				"frame/image load! Error code: %i\n" TEXT_RESET, err);
+						"frame/image load! Error code: %i\n" TEXT_RESET,
+			   err);
 
 		int err2 = mv_destroy_source(preparation_frame);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf(TEXT_RED "ERROR: Errors were occurred during destroying the "
-					"source! Error code: %i\n" TEXT_RESET, err2);
+							"source! Error code: %i\n" TEXT_RESET,
+				   err2);
 		}
 
 		return err;
@@ -1377,35 +1216,33 @@ int perform_mv_face_tracking_model_prepare(mv_face_tracking_model_h model)
 	err = mv_create_engine_config(&eng_config);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf(TEXT_RED "ERROR: Errors were occurred during creating the "
-				"engine config! Error code: %i\n" TEXT_RESET, err);
+						"engine config! Error code: %i\n" TEXT_RESET,
+			   err);
 	} else {
-		err = mv_engine_config_set_string_attribute(
-					eng_config,
-					MV_FACE_DETECTION_MODEL_FILE_PATH,
-					"/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt2.xml");
+		err = mv_engine_config_set_string_attribute(eng_config, MV_FACE_DETECTION_MODEL_FILE_PATH,
+													"/usr/share/OpenCV/haarcascades/haarcascade_frontalface_alt2.xml");
 
 		if (MEDIA_VISION_ERROR_NONE != err) {
 			printf(TEXT_RED "ERROR: Errors were occurred during setting of the "
-					"the 'MV_FACE_DETECTION_MODEL_FILE_PATH' attribute "
-					"for engine configuration! Check media-vision-config.json "
-					"file existence. Error code: %i" TEXT_RESET, err);
+							"the 'MV_FACE_DETECTION_MODEL_FILE_PATH' attribute "
+							"for engine configuration! Check media-vision-config.json "
+							"file existence. Error code: %i" TEXT_RESET,
+				   err);
 		}
 	}
 
-	err = mv_face_detect(
-				preparation_frame,
-				eng_config,
-				face_detected_for_tracking_cb,
-				NULL);
+	err = mv_face_detect(preparation_frame, eng_config, face_detected_for_tracking_cb, NULL);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf(TEXT_RED "ERROR: Errors were occurred during face detection! "
-				"Error code: %i\n" TEXT_RESET, err);
+						"Error code: %i\n" TEXT_RESET,
+			   err);
 
 		int err2 = mv_destroy_engine_config(eng_config);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf(TEXT_RED "ERROR: Errors were occurred during destroying the "
-					"engine configuration! Error code: %i\n" TEXT_RESET, err2);
+							"engine configuration! Error code: %i\n" TEXT_RESET,
+				   err2);
 		}
 
 		return err;
@@ -1415,54 +1252,50 @@ int perform_mv_face_tracking_model_prepare(mv_face_tracking_model_h model)
 
 	if (show_confirm_dialog("Do specify the face location?")) {
 		printf(TEXT_YELLOW "Specify the coordinates of the quadrangle to be used\n"
-							"for tracking model preparation:" TEXT_RESET "\n");
+						   "for tracking model preparation:" TEXT_RESET "\n");
 		int idx = 0;
 		char str_prompt[100];
 		while (idx < 4) {
 			++idx;
-			snprintf(str_prompt, 100, "Specify point %i x coordinate: x%i = ",
-					idx - 1, idx);
-			while (-1 == input_int(str_prompt, INT_MIN, INT_MAX,
-									&(roi.points[idx - 1].x)))
+			snprintf(str_prompt, 100, "Specify point %i x coordinate: x%i = ", idx - 1, idx);
+			while (-1 == input_int(str_prompt, INT_MIN, INT_MAX, &(roi.points[idx - 1].x)))
 				printf("Incorrect input! Try again.\n");
 
-			snprintf(str_prompt, 100, "Specify point %i y coordinate: y%i = ",
-								idx - 1, idx);
-			while (-1 == input_int(str_prompt, INT_MIN, INT_MAX,
-									&(roi.points[idx - 1].y)))
+			snprintf(str_prompt, 100, "Specify point %i y coordinate: y%i = ", idx - 1, idx);
+			while (-1 == input_int(str_prompt, INT_MIN, INT_MAX, &(roi.points[idx - 1].y)))
 				printf("Incorrect input! Try again.\n");
 		}
 
-		err = mv_face_tracking_model_prepare(
-					model, eng_config, preparation_frame, &roi);
+		err = mv_face_tracking_model_prepare(model, eng_config, preparation_frame, &roi);
 	} else {
-		err = mv_face_tracking_model_prepare(
-					model, eng_config, preparation_frame, NULL);
+		err = mv_face_tracking_model_prepare(model, eng_config, preparation_frame, NULL);
 	}
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf(TEXT_RED "ERROR: Errors were occurred during the tracking model "
-				"preparation! Error code: %i\n" TEXT_RESET, err);
+						"preparation! Error code: %i\n" TEXT_RESET,
+			   err);
 	}
 
 	const int err2 = mv_destroy_source(preparation_frame);
 	if (MEDIA_VISION_ERROR_NONE != err2) {
 		printf(TEXT_RED "ERROR: Errors were occurred during destroying the "
-				"source! Error code: %i\n" TEXT_RESET, err2);
+						"source! Error code: %i\n" TEXT_RESET,
+			   err2);
 	}
 
 	int err3 = mv_destroy_engine_config(eng_config);
 	if (MEDIA_VISION_ERROR_NONE != err3) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during destroying the engine config!!! code: %i"
-				TEXT_RESET "\n", err3);
+		printf(TEXT_RED "ERROR: Errors were occurred during destroying the engine config!!! code: %i" TEXT_RESET "\n",
+			   err3);
 		return err3;
 	}
 	eng_config = NULL;
 	return err;
 }
 
-typedef struct {
+typedef struct
+{
 	mv_face_tracking_model_h target;
 	mv_video_writer_h writer;
 	int frame_number;
@@ -1470,13 +1303,8 @@ typedef struct {
 	char out_file_path[FILE_PATH_SIZE];
 } tracking_cb_data;
 
-void track_cb(
-		mv_source_h source,
-		mv_face_tracking_model_h tracking_model,
-		mv_engine_config_h engine_cfg,
-		mv_quadrangle_s *location,
-		double confidence,
-		void *user_data)
+void track_cb(mv_source_h source, mv_face_tracking_model_h tracking_model, mv_engine_config_h engine_cfg,
+			  mv_quadrangle_s *location, double confidence, void *user_data)
 {
 	int err = MEDIA_VISION_ERROR_NONE;
 
@@ -1486,14 +1314,10 @@ void track_cb(
 	unsigned char *out_buffer = NULL;
 	unsigned int buf_size = 0;
 	image_data_s image_data = { 0, 0, MEDIA_VISION_COLORSPACE_INVALID };
-	if (MEDIA_VISION_ERROR_NONE !=
-			mv_source_get_buffer(source, &out_buffer, &buf_size) ||
-			MEDIA_VISION_ERROR_NONE !=
-			mv_source_get_width(source, &(image_data.image_width)) ||
-			MEDIA_VISION_ERROR_NONE !=
-			mv_source_get_height(source, &(image_data.image_height)) ||
-			MEDIA_VISION_ERROR_NONE !=
-			mv_source_get_colorspace(source, &(image_data.image_colorspace))) {
+	if (MEDIA_VISION_ERROR_NONE != mv_source_get_buffer(source, &out_buffer, &buf_size) ||
+		MEDIA_VISION_ERROR_NONE != mv_source_get_width(source, &(image_data.image_width)) ||
+		MEDIA_VISION_ERROR_NONE != mv_source_get_height(source, &(image_data.image_height)) ||
+		MEDIA_VISION_ERROR_NONE != mv_source_get_colorspace(source, &(image_data.image_colorspace))) {
 		printf("ERROR: Creating out image is impossible.\n");
 
 		return;
@@ -1501,51 +1325,36 @@ void track_cb(
 
 	if (NULL != location) {
 		if (!track_catch_face) {
-			printf(TEXT_GREEN "Frame %i : Tracked object is appeared" TEXT_RESET "\n",
-					cb_data->frame_number);
+			printf(TEXT_GREEN "Frame %i : Tracked object is appeared" TEXT_RESET "\n", cb_data->frame_number);
 			track_catch_face = true;
 		} else {
-			printf(TEXT_YELLOW "Frame %i : Tracked object is tracked" TEXT_RESET "\n",
-					cb_data->frame_number);
+			printf(TEXT_YELLOW "Frame %i : Tracked object is tracked" TEXT_RESET "\n", cb_data->frame_number);
 		}
 
 		const int rectangle_thickness = 3;
-		const int drawing_color[] = {255, 0, 0};
-
-		printf(TEXT_YELLOW
-				"Location: (%i,%i) -> (%i,%i) -> (%i,%i) -> (%i,%i)\n"
-				TEXT_RESET,
-				location->points[0].x,
-				location->points[0].y,
-				location->points[1].x,
-				location->points[1].y,
-				location->points[2].x,
-				location->points[2].y,
-				location->points[3].x,
-				location->points[3].y);
+		const int drawing_color[] = { 255, 0, 0 };
+
+		printf(TEXT_YELLOW "Location: (%i,%i) -> (%i,%i) -> (%i,%i) -> (%i,%i)\n" TEXT_RESET, location->points[0].x,
+			   location->points[0].y, location->points[1].x, location->points[1].y, location->points[2].x,
+			   location->points[2].y, location->points[3].x, location->points[3].y);
 		printf(TEXT_YELLOW "Track confidence: %f" TEXT_RESET "\n", confidence);
 
-		const int err = draw_quadrangle_on_buffer(
-								*location,
-								rectangle_thickness,
-								drawing_color,
-								&image_data,
-								out_buffer);
+		const int err =
+				draw_quadrangle_on_buffer(*location, rectangle_thickness, drawing_color, &image_data, out_buffer);
 
 		if (MEDIA_VISION_ERROR_NONE != err) {
 			printf(TEXT_RED "ERROR: Quadrangle wasn't drew on frame buffer! "
-					"Error code: %i\n" TEXT_RESET, err);
+							"Error code: %i\n" TEXT_RESET,
+				   err);
 
 			return;
 		}
 	} else {
 		if (track_catch_face) {
-			printf(TEXT_RED "Frame %i : Tracked object is lost" TEXT_RESET "\n",
-					cb_data->frame_number);
+			printf(TEXT_RED "Frame %i : Tracked object is lost" TEXT_RESET "\n", cb_data->frame_number);
 			track_catch_face = false;
 		} else {
-			printf(TEXT_YELLOW "Frame %i : Tracked object isn't detected" TEXT_RESET "\n",
-					cb_data->frame_number);
+			printf(TEXT_YELLOW "Frame %i : Tracked object isn't detected" TEXT_RESET "\n", cb_data->frame_number);
 		}
 	}
 
@@ -1553,85 +1362,65 @@ void track_cb(
 		err = mv_video_writer_write_frame(cb_data->writer, out_buffer);
 		if (MEDIA_VISION_ERROR_NONE != err) {
 			printf(TEXT_RED "ERROR: Errors were occurred during writing frame #%i"
-					"to the result video file; code %i" TEXT_RESET "\n",
-					cb_data->frame_number,
-					err);
+							"to the result video file; code %i" TEXT_RESET "\n",
+				   cb_data->frame_number, err);
 			return;
 		}
 	} else {
 		char out_file_name[FILE_PATH_SIZE];
-		if(snprintf(out_file_name, FILE_PATH_SIZE, "%s_%03d.jpg",
-					cb_data->out_file_path,
-					cb_data->frame_number) < 0)
-					{
-						printf("Output file name truncated.");
-					}
+		if (snprintf(out_file_name, FILE_PATH_SIZE, "%s_%03d.jpg", cb_data->out_file_path, cb_data->frame_number) < 0) {
+			printf("Output file name truncated.");
+		}
 
 		err = save_image_from_buffer(out_file_name, out_buffer, &image_data, 100);
 		if (MEDIA_VISION_ERROR_NONE != err) {
 			printf(TEXT_RED "ERROR: Errors were occurred during writing frame #%i"
-					"to the result image file; code %i" TEXT_RESET "\n",
-					cb_data->frame_number,
-					err);
+							"to the result image file; code %i" TEXT_RESET "\n",
+				   cb_data->frame_number, err);
 			return;
 		}
 	}
 }
 
-void track_on_sample_cb(
-		char *buffer,
-		unsigned int buffer_size,
-		image_data_s image_data,
-		void *user_data)
+void track_on_sample_cb(char *buffer, unsigned int buffer_size, image_data_s image_data, void *user_data)
 {
 	mv_source_h source = NULL;
 	int err = mv_create_source(&source);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf(TEXT_RED "ERROR: Errors were occurred during creating the source "
-				"based on the video frame! Error code: %i\n" TEXT_RESET, err);
+						"based on the video frame! Error code: %i\n" TEXT_RESET,
+			   err);
 
 		return;
 	}
 
-	err = mv_source_fill_by_buffer(
-						source,
-						(unsigned char*)buffer,
-						buffer_size,
-						image_data.image_width,
-						image_data.image_height,
-						image_data.image_colorspace);
+	err = mv_source_fill_by_buffer(source, (unsigned char *) buffer, buffer_size, image_data.image_width,
+								   image_data.image_height, image_data.image_colorspace);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf(TEXT_RED "ERROR: Errors were occurred during filling the source "
-				"based on the video frame! Error code: %i\n" TEXT_RESET , err);
+						"based on the video frame! Error code: %i\n" TEXT_RESET,
+			   err);
 
 		const int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
-			printf(TEXT_RED
-					"ERROR: Errors were occurred during destroying the source!!! code: %i"
-					TEXT_RESET "\n", err2);
+			printf(TEXT_RED "ERROR: Errors were occurred during destroying the source!!! code: %i" TEXT_RESET "\n",
+				   err2);
 		}
 
 		return;
 	}
 
-	tracking_cb_data *cb_data = (tracking_cb_data*)user_data;
+	tracking_cb_data *cb_data = (tracking_cb_data *) user_data;
 	++(cb_data->frame_number);
 
-	err = mv_face_track(
-			source,
-			cb_data->target,
-			NULL,
-			track_cb,
-			false,
-			cb_data);
+	err = mv_face_track(source, cb_data->target, NULL, track_cb, false, cb_data);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED "ERROR: Errors were occurred during tracking the face "
-				TEXT_RESET "on the video frame #%i! Error code: %i\n",
-				cb_data->frame_number,
-				err);
+		printf(TEXT_RED "ERROR: Errors were occurred during tracking the face " TEXT_RESET
+						"on the video frame #%i! Error code: %i\n",
+			   cb_data->frame_number, err);
 	}
 
 	return;
@@ -1642,25 +1431,23 @@ void eos_cb(void *user_data)
 {
 	printf("Video was fully processed\n");
 	if (NULL == user_data) {
-		printf(TEXT_RED
-				"ERROR: eos callback can't stop tracking process."TEXT_RESET);
+		printf(TEXT_RED "ERROR: eos callback can't stop tracking process." TEXT_RESET);
 		return;
 	}
 
-	pthread_mutex_unlock((pthread_mutex_t*)user_data);
+	pthread_mutex_unlock((pthread_mutex_t *) user_data);
 }
 
-static inline void release_resources_for_process_video_file_function(
-	mv_video_reader_h *reader,
-	mv_video_writer_h *writer)
+static inline void release_resources_for_process_video_file_function(mv_video_reader_h *reader,
+																	 mv_video_writer_h *writer)
 {
 	int err = MEDIA_VISION_ERROR_NONE;
 	if (*reader) {
 		err = mv_destroy_video_reader(*reader);
 		if (MEDIA_VISION_ERROR_NONE != err) {
 			printf(TEXT_RED "ERROR: Errors were occurred during video reader"
-					"destroying; code %i" TEXT_RESET "\n",
-					err);
+							"destroying; code %i" TEXT_RESET "\n",
+				   err);
 		}
 		*reader = NULL;
 	}
@@ -1668,26 +1455,24 @@ static inline void release_resources_for_process_video_file_function(
 		err = mv_destroy_video_writer(*writer);
 		if (MEDIA_VISION_ERROR_NONE != err) {
 			printf(TEXT_RED "ERROR: Errors were occurred during video writer"
-					"destroying; code %i" TEXT_RESET "\n",
-					err);
+							"destroying; code %i" TEXT_RESET "\n",
+				   err);
 		}
 		*writer = NULL;
 	}
 }
 
-int process_video_file(
-	mv_face_tracking_model_h tracking_model,
-	const char *track_target_file_name,
-	const char *track_result_file_name)
+int process_video_file(mv_face_tracking_model_h tracking_model, const char *track_target_file_name,
+					   const char *track_result_file_name)
 {
 	mv_video_reader_h reader = NULL;
 	mv_video_writer_h writer = NULL;
 
 	int err = mv_create_video_reader(&reader);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during creating the video "
-				"reader! Error code: %i" TEXT_RESET "\n", err);
+		printf(TEXT_RED "ERROR: Errors were occurred during creating the video "
+						"reader! Error code: %i" TEXT_RESET "\n",
+			   err);
 		release_resources_for_process_video_file_function(&reader, &writer);
 
 		return err;
@@ -1695,9 +1480,9 @@ int process_video_file(
 
 	err = mv_create_video_writer(&writer);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during creating the video "
-				"writer! Error code: %i" TEXT_RESET "\n", err);
+		printf(TEXT_RED "ERROR: Errors were occurred during creating the video "
+						"writer! Error code: %i" TEXT_RESET "\n",
+			   err);
 		release_resources_for_process_video_file_function(&reader, &writer);
 
 		return err;
@@ -1709,7 +1494,8 @@ int process_video_file(
 	err = mv_video_reader_load(reader, track_target_file_name, &video_info, &fps);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf(TEXT_RED "ERROR: Errors were occurred during loading the video "
-				"by reader! Error code: %i" TEXT_RESET "\n", err);
+						"by reader! Error code: %i" TEXT_RESET "\n",
+			   err);
 		release_resources_for_process_video_file_function(&reader, &writer);
 
 		return err;
@@ -1717,14 +1503,11 @@ int process_video_file(
 
 	video_info.image_colorspace = MEDIA_VISION_COLORSPACE_RGB888;
 
-	err = mv_video_writer_init(
-			writer,
-			track_result_file_name,
-			video_info,
-			fps);
+	err = mv_video_writer_init(writer, track_result_file_name, video_info, fps);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf(TEXT_RED "\nERROR: Errors were occurred during video writer"
-				"initializing; code %i" TEXT_RESET "\n", err);
+						"initializing; code %i" TEXT_RESET "\n",
+			   err);
 		release_resources_for_process_video_file_function(&reader, &writer);
 
 		return err;
@@ -1736,14 +1519,11 @@ int process_video_file(
 	cb_data.frame_number = 0;
 	cb_data.is_video = true;
 
-	err = mv_video_reader_set_new_sample_cb(
-			reader,
-			track_on_sample_cb,
-			&cb_data);
+	err = mv_video_reader_set_new_sample_cb(reader, track_on_sample_cb, &cb_data);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during new sample callback set!"
-				" Error code: %i" TEXT_RESET "\n", err);
+		printf(TEXT_RED "ERROR: Errors were occurred during new sample callback set!"
+						" Error code: %i" TEXT_RESET "\n",
+			   err);
 		release_resources_for_process_video_file_function(&reader, &writer);
 
 		return err;
@@ -1756,9 +1536,9 @@ int process_video_file(
 	/* set end of stream callback */
 	err = mv_video_reader_set_eos_cb(reader, eos_cb, &block_during_tracking_mutex);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(TEXT_RED
-				"ERROR: Errors were occurred during setting the eos "
-				"callback for reader! Error code: %i" TEXT_RESET "\n", err);
+		printf(TEXT_RED "ERROR: Errors were occurred during setting the eos "
+						"callback for reader! Error code: %i" TEXT_RESET "\n",
+			   err);
 		release_resources_for_process_video_file_function(&reader, &writer);
 
 		pthread_mutex_unlock(&block_during_tracking_mutex);
@@ -1770,7 +1550,8 @@ int process_video_file(
 	err = mv_video_reader_start(reader);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf(TEXT_RED "ERROR: Errors were occurred during starting the "
-				"video reader! Error code: %i" TEXT_RESET "\n", err);
+						"video reader! Error code: %i" TEXT_RESET "\n",
+			   err);
 		release_resources_for_process_video_file_function(&reader, &writer);
 
 		pthread_mutex_unlock(&block_during_tracking_mutex);
@@ -1788,8 +1569,8 @@ int process_video_file(
 	err = mv_video_reader_stop(reader);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf(TEXT_RED "ERROR: Errors were occurred during "
-				"attempt to stop video reader! Error code: %i\n"
-				TEXT_RESET, err);
+						"attempt to stop video reader! Error code: %i\n" TEXT_RESET,
+			   err);
 	}
 
 	release_resources_for_process_video_file_function(&reader, &writer);
@@ -1799,13 +1580,11 @@ int process_video_file(
 
 static int cmpstring(const void *p1, const void *p2)
 {
-	return strcmp((char * const) p1, (char * const) p2);
+	return strcmp((char *const) p1, (char *const) p2);
 }
 
-int process_image_file(
-	mv_face_tracking_model_h tracking_model,
-	const char *track_target_file_name,
-	const char *track_result_file_name)
+int process_image_file(mv_face_tracking_model_h tracking_model, const char *track_target_file_name,
+					   const char *track_result_file_name)
 {
 	if (track_target_file_name == NULL)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -1813,7 +1592,7 @@ int process_image_file(
 	int frame_idx;
 	int err = MEDIA_VISION_ERROR_NONE;
 	int frames_counter = 0;
-	char (*frames)[FILE_PATH_SIZE] = malloc(0);
+	char(*frames)[FILE_PATH_SIZE] = malloc(0);
 
 	struct dirent *ent_eof;
 	DIR *dir = opendir(track_target_file_name);
@@ -1827,14 +1606,13 @@ int process_image_file(
 		if (ent_eof->d_name[0] == '.' || strlen(ent_eof->d_name) < 4)
 			continue;
 
-		if (strcmp(".jpg", ent_eof->d_name + strlen(ent_eof->d_name) -4) != 0)
+		if (strcmp(".jpg", ent_eof->d_name + strlen(ent_eof->d_name) - 4) != 0)
 			continue;
 
 		frames_counter++;
 		frames = realloc(frames, frames_counter * FILE_PATH_SIZE);
 
-		snprintf(frames[frames_counter -1], FILE_PATH_SIZE, "%s/%s",
-			track_target_file_name, ent_eof->d_name);
+		snprintf(frames[frames_counter - 1], FILE_PATH_SIZE, "%s/%s", track_target_file_name, ent_eof->d_name);
 	}
 	closedir(dir);
 
@@ -1849,7 +1627,8 @@ int process_image_file(
 	err = mv_create_source(&source);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf(TEXT_RED "\nERROR: Errors(code %i) were occurred during"
-				"mv_create_source" TEXT_RESET "\n", err);
+						"mv_create_source" TEXT_RESET "\n",
+			   err);
 		free(frames);
 		if (source)
 			mv_destroy_source(source);
@@ -1869,7 +1648,8 @@ int process_image_file(
 		err = mv_source_clear(source);
 		if (err != MEDIA_VISION_ERROR_NONE) {
 			printf(TEXT_RED "\nWARN: WARN(code %i) were occurred during"
-				"mv_source_clear, but keep going" TEXT_RESET "\n", err);
+							"mv_source_clear, but keep going" TEXT_RESET "\n",
+				   err);
 		}
 
 		unsigned char *data_buffer = NULL;
@@ -1879,7 +1659,8 @@ int process_image_file(
 		err = load_image_to_buffer(frames[frame_idx], &data_buffer, &buffer_size, &image_data);
 		if (err != MEDIA_VISION_ERROR_NONE) {
 			printf(TEXT_RED "\nWARN: WARN(code %i) were occurred during"
-				"load_image_to_media_source, but continue" TEXT_RESET "\n", err);
+							"load_image_to_media_source, but continue" TEXT_RESET "\n",
+				   err);
 
 			if (data_buffer != NULL)
 				destroy_loaded_buffer(data_buffer);
@@ -1887,31 +1668,31 @@ int process_image_file(
 			continue;
 		}
 
-		err = mv_source_fill_by_buffer(source, data_buffer,
-						buffer_size,
-						image_data.image_width,
-						image_data.image_height,
-						image_data.image_colorspace);
+		err = mv_source_fill_by_buffer(source, data_buffer, buffer_size, image_data.image_width,
+									   image_data.image_height, image_data.image_colorspace);
 		if (data_buffer != NULL)
 			destroy_loaded_buffer(data_buffer);
 
 		if (err != MEDIA_VISION_ERROR_NONE) {
 			printf(TEXT_RED "\nWARN: WARN(code %i) were occurred during"
-				"mv_source_fill_by_buffer, but continue" TEXT_RESET "\n", err);
+							"mv_source_fill_by_buffer, but continue" TEXT_RESET "\n",
+				   err);
 			continue;
 		}
 
 		err = mv_face_track(source, tracking_model, NULL, track_cb, false, &cb_data);
 		if (err != MEDIA_VISION_ERROR_NONE) {
 			printf(TEXT_RED "\nWARN: WARN(code %i) were occurred during"
-				"mv_face_track, but keep going" TEXT_RESET "\n", err);
+							"mv_face_track, but keep going" TEXT_RESET "\n",
+				   err);
 		}
 	}
 
 	err = mv_destroy_source(source);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf(TEXT_RED "\nWARN: WARN(code %i) were occurred during"
-				"mv_destroy_source, but keep going" TEXT_RESET "\n", err);
+						"mv_destroy_source, but keep going" TEXT_RESET "\n",
+			   err);
 	}
 	free(frames);
 
@@ -1921,22 +1702,20 @@ int process_image_file(
 int perform_mv_face_track(mv_face_tracking_model_h tracking_model)
 {
 	printf(TEXT_YELLOW "Before any tracking session the tracking model\n"
-						"preparation is required. Exception is the case when\n"
-						"the next tracking session will be performed with the\n"
-						"video which is the direct continuation of the video\n"
-						"has been used at the previous tracking session.\n"
-						"If you want to test correct tracking case, don't\n"
-						"forget to perform preparation before tracking."
-			TEXT_RESET "\n");
+					   "preparation is required. Exception is the case when\n"
+					   "the next tracking session will be performed with the\n"
+					   "video which is the direct continuation of the video\n"
+					   "has been used at the previous tracking session.\n"
+					   "If you want to test correct tracking case, don't\n"
+					   "forget to perform preparation before tracking." TEXT_RESET "\n");
 
 	char *track_target_file_name = NULL;
 	char *track_result_file_name = NULL;
 
 	int res = MEDIA_VISION_ERROR_NONE;
 	int sel_opt = 0;
-	const int options[2] = {1, 2};
-	const char *names[2] = {"Track with the video file",
-				"Track with the image files"};
+	const int options[2] = { 1, 2 };
+	const char *names[2] = { "Track with the video file", "Track with the image files" };
 
 	bool is_video = false;
 	while (!sel_opt) {
@@ -1956,31 +1735,21 @@ int perform_mv_face_track(mv_face_tracking_model_h tracking_model)
 	}
 
 	if (is_video) {
-		while (input_string("Input video file name to track on:",
-							1024, &(track_target_file_name)) == -1)
+		while (input_string("Input video file name to track on:", 1024, &(track_target_file_name)) == -1)
 			printf(TEXT_RED "Incorrect input! Try again." TEXT_RESET "\n");
 
-		while (input_string("Input video file name to save tracking results:",
-							1024, &(track_result_file_name)) == -1)
+		while (input_string("Input video file name to save tracking results:", 1024, &(track_result_file_name)) == -1)
 			printf(TEXT_RED "Incorrect input! Try again." TEXT_RESET "\n");
 
-		res =  process_video_file(
-				tracking_model,
-				track_target_file_name,
-				track_result_file_name);
+		res = process_video_file(tracking_model, track_target_file_name, track_result_file_name);
 	} else {
-		while (input_string("Input image file path to track on:",
-							1024, &(track_target_file_name)) == -1)
+		while (input_string("Input image file path to track on:", 1024, &(track_target_file_name)) == -1)
 			printf(TEXT_RED "Incorrect input! Try again." TEXT_RESET "\n");
 
-		while (input_string("Input image file name to save tracking results:",
-							1024, &(track_result_file_name)) == -1)
+		while (input_string("Input image file name to save tracking results:", 1024, &(track_result_file_name)) == -1)
 			printf(TEXT_RED "Incorrect input! Try again." TEXT_RESET "\n");
 
-		res = process_image_file(
-				tracking_model,
-				track_target_file_name,
-				track_result_file_name);
+		res = process_image_file(tracking_model, track_target_file_name, track_result_file_name);
 	}
 
 	free(track_target_file_name);
@@ -1991,13 +1760,10 @@ int perform_mv_face_track(mv_face_tracking_model_h tracking_model)
 
 int perform_track()
 {
-	printf("\n" TEXT_YELLOW
-			"Tracking model isn't now created.\n"
-			"You may create it to perform positive \n"
-			"testing, or don't create to check the \n"
-			"functionality behaviour for uncreated model."
-			TEXT_RESET
-			"\n");
+	printf("\n" TEXT_YELLOW "Tracking model isn't now created.\n"
+		   "You may create it to perform positive \n"
+		   "testing, or don't create to check the \n"
+		   "functionality behaviour for uncreated model." TEXT_RESET "\n");
 
 	int err = MEDIA_VISION_ERROR_NONE;
 	mv_face_tracking_model_h tracking_model = NULL;
@@ -2008,22 +1774,17 @@ int perform_track()
 		err = mv_face_tracking_model_create(&tracking_model);
 		if (MEDIA_VISION_ERROR_NONE != err) {
 			printf(TEXT_RED "Creating the model failed. Error code: %i. "
-					"But you still can test with uncreated model.\n"
-					TEXT_RESET "\n", err);
+							"But you still can test with uncreated model.\n" TEXT_RESET "\n",
+				   err);
 		} else {
-			printf(TEXT_YELLOW "Tracking model has been created."
-					TEXT_RESET "\n");
+			printf(TEXT_YELLOW "Tracking model has been created." TEXT_RESET "\n");
 		}
 	}
 
 	int sel_opt = 0;
 	const int options[6] = { 1, 2, 3, 4, 5, 6 };
-	const char *names[6] = { "Prepare the model",
-								"Clone the model",
-								"Save model to file",
-								"Load model from file",
-								"Track with model",
-								"Destroy model and exit" };
+	const char *names[6] = { "Prepare the model",	 "Clone the model",	 "Save model to file",
+							 "Load model from file", "Track with model", "Destroy model and exit" };
 
 	while (!sel_opt) {
 		sel_opt = show_menu("Select action:", options, names, 6);
@@ -2050,9 +1811,7 @@ int perform_track()
 			if (do_create) {
 				err = mv_face_tracking_model_destroy(tracking_model);
 				if (MEDIA_VISION_ERROR_NONE != err) {
-					printf(TEXT_RED
-							"Error with code %i was occurred during destroy"
-							TEXT_RESET "\n", err);
+					printf(TEXT_RED "Error with code %i was occurred during destroy" TEXT_RESET "\n", err);
 				}
 			} else {
 				err = MEDIA_VISION_ERROR_NONE;
@@ -2101,12 +1860,7 @@ int main(void)
 
 	int sel_opt = 0;
 	const int options[6] = { 1, 2, 3, 4, 5, 6 };
-	const char *names[6] = { "Detect",
-								"Track",
-								"Recognize",
-								"Eye condition",
-								"Face expression",
-								"Exit" };
+	const char *names[6] = { "Detect", "Track", "Recognize", "Eye condition", "Face expression", "Exit" };
 
 	while (sel_opt == 0) {
 		sel_opt = show_menu("Select action:", options, names, 6);
diff --git a/test/testsuites/image/image_test_suite.c b/test/testsuites/image/image_test_suite.c
index a18ef5a..c564059 100644
--- a/test/testsuites/image/image_test_suite.c
+++ b/test/testsuites/image/image_test_suite.c
@@ -29,7 +29,8 @@
 
 #define FILE_PATH_SIZE 1024
 
-typedef enum {
+typedef enum
+{
 	SOURCE_TYPE_GENERATION,
 	SOURCE_TYPE_LOADING,
 	SOURCE_TYPE_CLONING,
@@ -37,7 +38,8 @@ typedef enum {
 	SOURCE_TYPE_INVALID
 } source_type_e;
 
-typedef enum {
+typedef enum
+{
 	OBJECT_TYPE_IMAGE_OBJECT,
 	OBJECT_TYPE_IMAGE_TRACKING_MODEL,
 	OBJECT_TYPE_INVALID
@@ -45,7 +47,8 @@ typedef enum {
 
 #define testing_object_maximum_label_length 300
 
-typedef struct testing_object_s {
+typedef struct testing_object_s
+{
 	void *entity;
 
 	char origin_label[testing_object_maximum_label_length];
@@ -65,7 +68,7 @@ void testing_object_create(testing_object_h *result)
 {
 	(*result) = malloc(sizeof(testing_object));
 
-	(*result)->entity = (void*)NULL;
+	(*result)->entity = (void *) NULL;
 	(*result)->object_type = OBJECT_TYPE_INVALID;
 	(*result)->source_type = SOURCE_TYPE_INVALID;
 	(*result)->cloning_counter = 0;
@@ -73,12 +76,8 @@ void testing_object_create(testing_object_h *result)
 	(*result)->actual_label[0] = '\0';
 }
 
-void testing_object_fill(
-		testing_object_h target,
-		void *entity,
-		testing_object_type_e object_type,
-		source_type_e source_type,
-		void *source)
+void testing_object_fill(testing_object_h target, void *entity, testing_object_type_e object_type,
+						 source_type_e source_type, void *source)
 {
 	target->entity = entity;
 	target->object_type = object_type;
@@ -88,43 +87,38 @@ void testing_object_fill(
 	switch (source_type) {
 	case SOURCE_TYPE_GENERATION: {
 		if (OBJECT_TYPE_IMAGE_OBJECT == object_type) {
-			snprintf(
-						target->origin_label,
-						testing_object_maximum_label_length,
-						"generated from \"%s\"",
-						(char*)source);
+			snprintf(target->origin_label, testing_object_maximum_label_length, "generated from \"%s\"",
+					 (char *) source);
 		} else if (OBJECT_TYPE_IMAGE_TRACKING_MODEL == object_type) {
 			char *title = "generated from image object which is ";
 			memcpy(target->origin_label, title, strlen(title));
-			memcpy(target->origin_label + strlen(title), ((testing_object_h)source)->actual_label,
-				testing_object_maximum_label_length - strlen(title));
-			int pos = MIN(strlen(title) + strlen(((testing_object_h)source)->actual_label), testing_object_maximum_label_length - 1);
+			memcpy(target->origin_label + strlen(title), ((testing_object_h) source)->actual_label,
+				   testing_object_maximum_label_length - strlen(title));
+			int pos = MIN(strlen(title) + strlen(((testing_object_h) source)->actual_label),
+						  testing_object_maximum_label_length - 1);
 			target->origin_label[pos] = '\0';
 		} else {
-			snprintf(
-						target->origin_label,
-						testing_object_maximum_label_length,
-						"generated unknown type of testing object");
+			snprintf(target->origin_label, testing_object_maximum_label_length,
+					 "generated unknown type of testing object");
 		}
 
 		strncpy(target->actual_label, target->origin_label, testing_object_maximum_label_length);
 		break;
 	}
 	case SOURCE_TYPE_LOADING: {
-		snprintf(target->origin_label, testing_object_maximum_label_length, "loaded from \"%s\"", (char*)source);
+		snprintf(target->origin_label, testing_object_maximum_label_length, "loaded from \"%s\"", (char *) source);
 		strncpy(target->actual_label, target->origin_label, testing_object_maximum_label_length);
 		break;
 	}
 	case SOURCE_TYPE_CLONING: {
-		testing_object_h source_object = (testing_object_h)source;
+		testing_object_h source_object = (testing_object_h) source;
 		strncpy(target->origin_label, source_object->origin_label, testing_object_maximum_label_length);
 		target->cloning_counter = source_object->cloning_counter + 1;
 
 		char number_of_cloning[20];
 		number_of_cloning[0] = '\0';
 		if (1 < target->cloning_counter) {
-			snprintf(number_of_cloning, 20, "%s%i%s",
-						"(x", target->cloning_counter, ")");
+			snprintf(number_of_cloning, 20, "%s%i%s", "(x", target->cloning_counter, ")");
 		}
 
 		char type_name[20];
@@ -135,13 +129,10 @@ void testing_object_fill(
 		else
 			snprintf(type_name, 20, "unknown object");
 
-		snprintf(target->actual_label, testing_object_maximum_label_length,
-						"%s%s%s%s%s",
-						"cloned ", number_of_cloning,
-						" from ", type_name,
-						" which is ");
-		memcpy(target->actual_label+strlen(target->actual_label), target->origin_label,
-				testing_object_maximum_label_length - strlen(target->actual_label));
+		snprintf(target->actual_label, testing_object_maximum_label_length, "%s%s%s%s%s", "cloned ", number_of_cloning,
+				 " from ", type_name, " which is ");
+		memcpy(target->actual_label + strlen(target->actual_label), target->origin_label,
+			   testing_object_maximum_label_length - strlen(target->actual_label));
 		break;
 	}
 	case SOURCE_TYPE_EMPTY: {
@@ -163,29 +154,31 @@ void testing_object_destroy(testing_object_h *target)
 		int err = mv_image_object_destroy((mv_image_object_h)((*target)->entity));
 		if (MEDIA_VISION_ERROR_NONE != err) {
 			printf("\nERROR: Errors were occurred during image object "
-						"destroying; code %i\n", err);
+				   "destroying; code %i\n",
+				   err);
 		}
 		break;
 	}
 	case OBJECT_TYPE_IMAGE_TRACKING_MODEL: {
-		int err = mv_image_tracking_model_destroy(
-					(mv_image_tracking_model_h)((*target)->entity));
+		int err = mv_image_tracking_model_destroy((mv_image_tracking_model_h)((*target)->entity));
 		if (MEDIA_VISION_ERROR_NONE != err) {
 			printf("\nERROR: Errors were occurred during image tracking "
-						"model destroying; code %i\n", err);
+				   "model destroying; code %i\n",
+				   err);
 		}
 		break;
 	}
-	case OBJECT_TYPE_INVALID :
+	case OBJECT_TYPE_INVALID:
 		printf("\nERROR: Errors were occurred during image tracking "
-					"model destroying; OBJECT_TYPE_INVALID\n");
+			   "model destroying; OBJECT_TYPE_INVALID\n");
 		break;
 	}
 	free(*target);
 	(*target) = NULL;
 }
 
-typedef struct {
+typedef struct
+{
 	mv_quadrangle_s **locations;
 	unsigned int locations_size;
 	unsigned int currently_number;
@@ -204,20 +197,15 @@ void destroy_recognition_result(recognition_result *result)
 	free(result->locations);
 }
 
-void recognized_cb(
-		mv_source_h source,
-		mv_engine_config_h engine_cfg,
-		const mv_image_object_h *image_objects,
-		mv_quadrangle_s **locations,
-		unsigned int number_of_objects,
-		void *user_data)
+void recognized_cb(mv_source_h source, mv_engine_config_h engine_cfg, const mv_image_object_h *image_objects,
+				   mv_quadrangle_s **locations, unsigned int number_of_objects, void *user_data)
 {
 	MEDIA_VISION_FUNCTION_ENTER();
 
 	if (NULL == user_data)
 		return;
 
-	recognition_result *result = (recognition_result*)user_data;
+	recognition_result *result = (recognition_result *) user_data;
 
 	int object_num = 0;
 	for (; object_num < number_of_objects; ++object_num) {
@@ -237,11 +225,8 @@ void recognized_cb(
 	MEDIA_VISION_FUNCTION_LEAVE();
 }
 
-void handle_recognition_result(
-		const recognition_result *result,
-		int number_of_objects,
-		mv_source_h *source,
-		const char *file_name)
+void handle_recognition_result(const recognition_result *result, int number_of_objects, mv_source_h *source,
+							   const char *file_name)
 {
 	int is_source_data_loaded = 0;
 
@@ -250,10 +235,10 @@ void handle_recognition_result(
 	image_data_s image_data = { 0, 0, MEDIA_VISION_COLORSPACE_INVALID };
 
 	if (MEDIA_VISION_ERROR_NONE != mv_source_get_buffer(source, &(out_buffer), &buffer_size) ||
-			MEDIA_VISION_ERROR_NONE != mv_source_get_width(source, &(image_data.image_width)) ||
-			MEDIA_VISION_ERROR_NONE != mv_source_get_height(source, &(image_data.image_height)) ||
-			MEDIA_VISION_ERROR_NONE != mv_source_get_colorspace(source, &(image_data.image_colorspace)) ||
-			NULL == file_name) {
+		MEDIA_VISION_ERROR_NONE != mv_source_get_width(source, &(image_data.image_width)) ||
+		MEDIA_VISION_ERROR_NONE != mv_source_get_height(source, &(image_data.image_height)) ||
+		MEDIA_VISION_ERROR_NONE != mv_source_get_colorspace(source, &(image_data.image_colorspace)) ||
+		NULL == file_name) {
 		printf("ERROR: Creating out image is impossible.\n");
 	} else {
 		is_source_data_loaded = 1;
@@ -272,39 +257,31 @@ void handle_recognition_result(
 
 		int point_num = 0;
 		for (; point_num < 4; ++point_num) {
-			printf("%d point - x = %d, y = %d\n", point_num + 1,
-					result->locations[object_num]->points[point_num].x,
-					result->locations[object_num]->points[point_num].y);
+			printf("%d point - x = %d, y = %d\n", point_num + 1, result->locations[object_num]->points[point_num].x,
+				   result->locations[object_num]->points[point_num].y);
 		}
 
 		if (is_source_data_loaded) {
 			const int thickness = 2;
-			const int color[] = {0, 255, 0};
+			const int color[] = { 0, 255, 0 };
 
-			const int err = draw_quadrangle_on_buffer(
-					*(result->locations[object_num]),
-					thickness,
-					color,
-					&image_data,
-					out_buffer);
+			const int err = draw_quadrangle_on_buffer(*(result->locations[object_num]), thickness, color, &image_data,
+													  out_buffer);
 
 			if (MEDIA_VISION_ERROR_NONE != err)
 				printf("ERROR: Impossible to draw quadrangle\n");
 		}
 	}
 
-	if (save_image_from_buffer(file_name, out_buffer,
-			&image_data, 100) != MEDIA_VISION_ERROR_NONE) {
+	if (save_image_from_buffer(file_name, out_buffer, &image_data, 100) != MEDIA_VISION_ERROR_NONE) {
 		printf("\nERROR: Failed to generate output file\n");
 	} else {
 		printf("\nImage was generated as %s\n", file_name);
 	}
 }
 
-int generate_image_object_from_file(const char *path_to_image,
-						bool roi_selected,
-						mv_rectangle_s roi,
-						mv_image_object_h *result)
+int generate_image_object_from_file(const char *path_to_image, bool roi_selected, mv_rectangle_s roi,
+									mv_image_object_h *result)
 {
 	MEDIA_VISION_FUNCTION_ENTER();
 
@@ -321,7 +298,8 @@ int generate_image_object_from_file(const char *path_to_image,
 		int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during source "
-					"destroying; code %i\n", err2);
+				   "destroying; code %i\n",
+				   err2);
 		}
 
 		MEDIA_VISION_FUNCTION_LEAVE();
@@ -337,7 +315,8 @@ int generate_image_object_from_file(const char *path_to_image,
 		int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during source "
-					"destroying; code %i\n", err2);
+				   "destroying; code %i\n",
+				   err2);
 		}
 
 		MEDIA_VISION_FUNCTION_LEAVE();
@@ -348,18 +327,21 @@ int generate_image_object_from_file(const char *path_to_image,
 	err = mv_image_object_create(result);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf("ERROR: Errors were occurred during creating image object; "
-				"code %i\n", err);
+			   "code %i\n",
+			   err);
 
 		int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during source "
-					"destroying; code %i\n", err2);
+				   "destroying; code %i\n",
+				   err2);
 		}
 
 		err2 = mv_destroy_engine_config(config);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during engine config "
-					"destroying; code %i\n", err2);
+				   "destroying; code %i\n",
+				   err2);
 		}
 
 		MEDIA_VISION_FUNCTION_LEAVE();
@@ -374,24 +356,28 @@ int generate_image_object_from_file(const char *path_to_image,
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf("ERROR: Errors were occurred during filling image object; "
-				"code %i\n", err);
+			   "code %i\n",
+			   err);
 
 		int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during source "
-					"destroying; code %i\n", err2);
+				   "destroying; code %i\n",
+				   err2);
 		}
 
 		err2 = mv_image_object_destroy(*result);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during image object "
-					"destroying; code %i\n", err2);
+				   "destroying; code %i\n",
+				   err2);
 		}
 
 		err2 = mv_destroy_engine_config(config);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during engine config "
-					"destroying; code %i\n", err2);
+				   "destroying; code %i\n",
+				   err2);
 		}
 
 		*result = NULL;
@@ -404,12 +390,14 @@ int generate_image_object_from_file(const char *path_to_image,
 	err = mv_destroy_source(source);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf("\nERROR: Errors were occurred during source "
-				"destroying; code %i\n", err);
+			   "destroying; code %i\n",
+			   err);
 
 		int err2 = mv_destroy_engine_config(config);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during engine config "
-					"destroying; code %i\n", err2);
+				   "destroying; code %i\n",
+				   err2);
 		}
 
 		MEDIA_VISION_FUNCTION_LEAVE();
@@ -420,7 +408,8 @@ int generate_image_object_from_file(const char *path_to_image,
 	err = mv_destroy_engine_config(config);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf("\nERROR: Errors were occurred during engine config "
-				"destroying; code %i\n", err);
+			   "destroying; code %i\n",
+			   err);
 
 		MEDIA_VISION_FUNCTION_LEAVE();
 
@@ -431,10 +420,8 @@ int generate_image_object_from_file(const char *path_to_image,
 	return err;
 }
 
-int recognize_image(const char *path_to_image,
-		const char *path_to_generated_image,
-		mv_image_object_h *targets,
-		int number_of_targets)
+int recognize_image(const char *path_to_image, const char *path_to_generated_image, mv_image_object_h *targets,
+					int number_of_targets)
 {
 	MEDIA_VISION_FUNCTION_ENTER();
 
@@ -456,7 +443,8 @@ int recognize_image(const char *path_to_image,
 		int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during source destroying; "
-						"code %i\n", err2);
+				   "code %i\n",
+				   err2);
 		}
 		MEDIA_VISION_FUNCTION_LEAVE();
 		return err;
@@ -465,7 +453,7 @@ int recognize_image(const char *path_to_image,
 	recognition_result result;
 	result.currently_number = 0;
 	if (0 < number_of_targets) {
-		result.locations = malloc(sizeof(mv_quadrangle_s*) * number_of_targets);
+		result.locations = malloc(sizeof(mv_quadrangle_s *) * number_of_targets);
 		result.locations_size = number_of_targets;
 	} else {
 		result.locations = NULL;
@@ -479,15 +467,15 @@ int recognize_image(const char *path_to_image,
 		int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during source destroying;"
-					"code %i\n", err2);
+				   "code %i\n",
+				   err2);
 		}
 		destroy_recognition_result(&result);
 		MEDIA_VISION_FUNCTION_LEAVE();
 		return err;
 	}
 
-	err = mv_image_recognize(source, targets, number_of_targets, config,
-								recognized_cb, &result);
+	err = mv_image_recognize(source, targets, number_of_targets, config, recognized_cb, &result);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf("\nERROR: Image is not recognized; code %i\n", err);
@@ -497,12 +485,14 @@ int recognize_image(const char *path_to_image,
 		int err2 = mv_destroy_source(source);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during source "
-					"destroying; code %i\n", err2);
+				   "destroying; code %i\n",
+				   err2);
 		}
 		err2 = mv_destroy_engine_config(config);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during engine config "
-					"destroying; code %i\n", err2);
+				   "destroying; code %i\n",
+				   err2);
 		}
 
 		MEDIA_VISION_FUNCTION_LEAVE();
@@ -510,20 +500,19 @@ int recognize_image(const char *path_to_image,
 		return err;
 	}
 
-	handle_recognition_result(&result, number_of_targets, source,
-			path_to_generated_image);
+	handle_recognition_result(&result, number_of_targets, source, path_to_generated_image);
 
 	destroy_recognition_result(&result);
 
 	err = mv_destroy_source(source);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf("\nERROR: Errors were occurred during source destroying; code %i\n",
-				err);
+		printf("\nERROR: Errors were occurred during source destroying; code %i\n", err);
 
 		int err2 = mv_destroy_engine_config(config);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during engine config "
-					"destroying; code %i\n", err2);
+				   "destroying; code %i\n",
+				   err2);
 		}
 
 		MEDIA_VISION_FUNCTION_LEAVE();
@@ -534,7 +523,8 @@ int recognize_image(const char *path_to_image,
 	err = mv_destroy_engine_config(config);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf("\nERROR: Errors were occurred during engine config destroying; "
-				"code %i\n", err);
+			   "code %i\n",
+			   err);
 
 		MEDIA_VISION_FUNCTION_LEAVE();
 
@@ -611,16 +601,13 @@ int perform_recognize(mv_image_object_h *targets, int number_of_targets)
 	char *path_to_image = NULL;
 	char *path_to_generated_image = NULL;
 
-	while (input_string("Input file name with image for recognizing:",
-						1024, &path_to_image) == -1)
+	while (input_string("Input file name with image for recognizing:", 1024, &path_to_image) == -1)
 		printf("Incorrect input! Try again.\n");
 
-	while (input_string("Input file name for generated image:",
-						1024, &path_to_generated_image) == -1)
+	while (input_string("Input file name for generated image:", 1024, &path_to_generated_image) == -1)
 		printf("Incorrect input! Try again.\n");
 
-	const int err = recognize_image(path_to_image, path_to_generated_image, targets,
-									number_of_targets);
+	const int err = recognize_image(path_to_image, path_to_generated_image, targets, number_of_targets);
 
 	free(path_to_image);
 	free(path_to_generated_image);
@@ -639,8 +626,7 @@ int perform_load_image_object(char **path_to_object, mv_image_object_h *result)
 		*result = NULL;
 	}
 
-	while (input_string("Input file name with image object to be loaded:",
-						1024, path_to_object) == -1)
+	while (input_string("Input file name with image object to be loaded:", 1024, path_to_object) == -1)
 		printf("Incorrect input! Try again.\n");
 
 	int err = mv_image_object_load(*path_to_object, result);
@@ -663,8 +649,7 @@ int perform_save_image_object(mv_image_object_h object)
 	int err = MEDIA_VISION_ERROR_NONE;
 	char *path_to_object = NULL;
 
-	while (input_string("Input file name to be generated for image object storing:",
-						1024, &path_to_object) == -1)
+	while (input_string("Input file name to be generated for image object storing:", 1024, &path_to_object) == -1)
 		printf("Incorrect input! Try again.\n");
 
 	err = mv_image_object_save(path_to_object, object);
@@ -691,30 +676,24 @@ int perform_generate_image_object(mv_image_object_h *result, char **path_to_imag
 	if (NULL == path_to_image || NULL == result)
 		return MEDIA_VISION_ERROR_INVALID_PARAMETER;
 
-	while (input_string("Input file name with image to be analyzed:",
-							1024, path_to_image) == -1)
+	while (input_string("Input file name with image to be analyzed:", 1024, path_to_image) == -1)
 		printf("Incorrect input! Try again.\n");
 
 	mv_rectangle_s roi;
 	const bool sel_roi = show_confirm_dialog("Select if you want to set ROI");
 	if (sel_roi) {
 		printf("\nInput ROI coordinates\n");
-		while (input_int("Input x coordinate:", INT_MIN, INT_MAX,
-					&(roi.point.x)) == -1)
+		while (input_int("Input x coordinate:", INT_MIN, INT_MAX, &(roi.point.x)) == -1)
 			printf("Incorrect input! Try again.\n");
 
-		while (input_int("Input y coordinate:", INT_MIN, INT_MAX,
-					&(roi.point.y)) == -1)
+		while (input_int("Input y coordinate:", INT_MIN, INT_MAX, &(roi.point.y)) == -1)
 			printf("Incorrect input! Try again.\n");
 
-		while (input_int("Input ROI width:", INT_MIN, INT_MAX,
-					&(roi.width)) == -1)
+		while (input_int("Input ROI width:", INT_MIN, INT_MAX, &(roi.width)) == -1)
 			printf("Incorrect input! Try again.\n");
 
-		while (input_int("Input ROI height:", INT_MIN, INT_MAX,
-					&(roi.height)) == -1)
+		while (input_int("Input ROI height:", INT_MIN, INT_MAX, &(roi.height)) == -1)
 			printf("Incorrect input! Try again.\n");
-
 	}
 
 	int err = generate_image_object_from_file(*path_to_image, sel_roi, roi, result);
@@ -747,7 +726,8 @@ int perform_clone_image_object(mv_image_object_h src, mv_image_object_h *result)
 		int err2 = mv_image_object_destroy(*result);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during image object "
-					"destroying; code %i\n", err);
+				   "destroying; code %i\n",
+				   err);
 		}
 
 		(*result) = NULL;
@@ -760,11 +740,8 @@ int perform_clone_image_object(mv_image_object_h src, mv_image_object_h *result)
 	return err;
 }
 
-int handle_tracking_video_result(
-		mv_video_writer_h writer,
-		mv_source_h frame,
-		int frame_number,
-		mv_quadrangle_s *location)
+int handle_tracking_video_result(mv_video_writer_h writer, mv_source_h frame, int frame_number,
+								 mv_quadrangle_s *location)
 {
 	unsigned char *data_buffer = NULL;
 	unsigned int buffer_size = 0;
@@ -772,67 +749,49 @@ int handle_tracking_video_result(
 
 	int err = mv_source_get_buffer(frame, &data_buffer, &buffer_size);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"ERROR: Errors were occurred during getting buffer from the "
-				"source; code %i\n",
-				err);
+		printf("ERROR: Errors were occurred during getting buffer from the "
+			   "source; code %i\n",
+			   err);
 		return err;
 	}
 
 	err = mv_source_get_width(frame, &image_data.image_width);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"ERROR: Errors were occurred during getting width from the "
-				"source; code %i\n",
-				err);
+		printf("ERROR: Errors were occurred during getting width from the "
+			   "source; code %i\n",
+			   err);
 		return err;
 	}
 
 	err = mv_source_get_height(frame, &image_data.image_height);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"ERROR: Errors were occurred during getting height from the "
-				"source; code %i\n",
-				err);
+		printf("ERROR: Errors were occurred during getting height from the "
+			   "source; code %i\n",
+			   err);
 		return err;
 	}
 
 	err = mv_source_get_colorspace(frame, &image_data.image_colorspace);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"ERROR: Errors were occurred during getting colorspace from the "
-				"source; code %i\n",
-				err);
+		printf("ERROR: Errors were occurred during getting colorspace from the "
+			   "source; code %i\n",
+			   err);
 		return err;
 	}
 
 	if (location) {
-		printf(
-				"Frame #%i: object is found."
-				"Location: {%i, %i}; {%i, %i}; {%i, %i}; {%i, %i}.\n",
-				frame_number,
-				location->points[0].x,
-				location->points[0].y,
-				location->points[1].x,
-				location->points[1].y,
-				location->points[2].x,
-				location->points[2].y,
-				location->points[3].x,
-				location->points[3].y);
+		printf("Frame #%i: object is found."
+			   "Location: {%i, %i}; {%i, %i}; {%i, %i}; {%i, %i}.\n",
+			   frame_number, location->points[0].x, location->points[0].y, location->points[1].x, location->points[1].y,
+			   location->points[2].x, location->points[2].y, location->points[3].x, location->points[3].y);
 		const int thickness = 2;
-		const int color[] = {0, 255, 0};
-
-		err = draw_quadrangle_on_buffer(
-				*location,
-				thickness,
-				color,
-				&image_data,
-				data_buffer);
+		const int color[] = { 0, 255, 0 };
+
+		err = draw_quadrangle_on_buffer(*location, thickness, color, &image_data, data_buffer);
 		if (MEDIA_VISION_ERROR_NONE != err) {
-			printf(
-					"ERROR: Errors were occurred during drawing quadrangle on "
-					"the frame; code %i\n",
-					err);
+			printf("ERROR: Errors were occurred during drawing quadrangle on "
+				   "the frame; code %i\n",
+				   err);
 			return err;
 		}
 	} else {
@@ -842,21 +801,17 @@ int handle_tracking_video_result(
 
 	err = mv_video_writer_write_frame(writer, data_buffer);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"ERROR: Errors were occurred during writing frame to the "
-				"result video file; code %i\n",
-				err);
+		printf("ERROR: Errors were occurred during writing frame to the "
+			   "result video file; code %i\n",
+			   err);
 		return err;
 	}
 
 	return err;
 }
 
-int handle_tracking_image_result(
-		const char *out_file_path,
-		mv_source_h frame,
-		int frame_number,
-		mv_quadrangle_s *location)
+int handle_tracking_image_result(const char *out_file_path, mv_source_h frame, int frame_number,
+								 mv_quadrangle_s *location)
 {
 	unsigned char *data_buffer = NULL;
 	unsigned int buffer_size = 0;
@@ -864,67 +819,49 @@ int handle_tracking_image_result(
 
 	int err = mv_source_get_buffer(frame, &data_buffer, &buffer_size);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"ERROR: Errors were occurred during getting buffer from the "
-				"source; code %i\n",
-				err);
+		printf("ERROR: Errors were occurred during getting buffer from the "
+			   "source; code %i\n",
+			   err);
 		return err;
 	}
 
 	err = mv_source_get_width(frame, &image_data.image_width);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"ERROR: Errors were occurred during getting width from the "
-				"source; code %i\n",
-				err);
+		printf("ERROR: Errors were occurred during getting width from the "
+			   "source; code %i\n",
+			   err);
 		return err;
 	}
 
 	err = mv_source_get_height(frame, &image_data.image_height);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"ERROR: Errors were occurred during getting height from the "
-				"source; code %i\n",
-				err);
+		printf("ERROR: Errors were occurred during getting height from the "
+			   "source; code %i\n",
+			   err);
 		return err;
 	}
 
 	err = mv_source_get_colorspace(frame, &image_data.image_colorspace);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"ERROR: Errors were occurred during getting image colorspace from the "
-				"source; code %i\n",
-				err);
+		printf("ERROR: Errors were occurred during getting image colorspace from the "
+			   "source; code %i\n",
+			   err);
 		return err;
 	}
 
 	if (location) {
-		printf(
-				"Frame #%i: object is found."
-				"Location: {%i, %i}; {%i, %i}; {%i, %i}; {%i, %i}.\n",
-				frame_number,
-				location->points[0].x,
-				location->points[0].y,
-				location->points[1].x,
-				location->points[1].y,
-				location->points[2].x,
-				location->points[2].y,
-				location->points[3].x,
-				location->points[3].y);
+		printf("Frame #%i: object is found."
+			   "Location: {%i, %i}; {%i, %i}; {%i, %i}; {%i, %i}.\n",
+			   frame_number, location->points[0].x, location->points[0].y, location->points[1].x, location->points[1].y,
+			   location->points[2].x, location->points[2].y, location->points[3].x, location->points[3].y);
 		const int thickness = 2;
-		const int color[] = {0, 255, 0};
-
-		err = draw_quadrangle_on_buffer(
-				*location,
-				thickness,
-				color,
-				&image_data,
-				data_buffer);
+		const int color[] = { 0, 255, 0 };
+
+		err = draw_quadrangle_on_buffer(*location, thickness, color, &image_data, data_buffer);
 		if (MEDIA_VISION_ERROR_NONE != err) {
-			printf(
-					"ERROR: Errors were occurred during drawing quadrangle on "
-					"the frame; code %i\n",
-					err);
+			printf("ERROR: Errors were occurred during drawing quadrangle on "
+				   "the frame; code %i\n",
+				   err);
 			return err;
 		}
 	} else {
@@ -933,23 +870,21 @@ int handle_tracking_image_result(
 	}
 
 	char out_file_name[FILE_PATH_SIZE];
-	snprintf(out_file_name, FILE_PATH_SIZE, "%s_%03d.jpg",
-					out_file_path,
-					frame_number);
+	snprintf(out_file_name, FILE_PATH_SIZE, "%s_%03d.jpg", out_file_path, frame_number);
 
 	err = save_image_from_buffer(out_file_name, data_buffer, &image_data, 100);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"ERROR: Errors were occurred during writing frame to the "
-				"result image file; code %i\n",
-				err);
+		printf("ERROR: Errors were occurred during writing frame to the "
+			   "result image file; code %i\n",
+			   err);
 		return err;
 	}
 
 	return err;
 }
 
-typedef struct {
+typedef struct
+{
 	mv_image_tracking_model_h target;
 	mv_video_writer_h writer;
 	int frame_number;
@@ -957,19 +892,15 @@ typedef struct {
 	char out_file_path[FILE_PATH_SIZE];
 } tracking_cb_data;
 
-void tracked_cb(
-		mv_source_h source,
-		mv_image_object_h image_object,
-		mv_engine_config_h engine_cfg,
-		mv_quadrangle_s *location,
-		void *user_data)
+void tracked_cb(mv_source_h source, mv_image_object_h image_object, mv_engine_config_h engine_cfg,
+				mv_quadrangle_s *location, void *user_data)
 {
 	MEDIA_VISION_FUNCTION_ENTER();
 
 	if (NULL == user_data)
 		return;
 
-	tracking_cb_data *cb_data = (tracking_cb_data*)user_data;
+	tracking_cb_data *cb_data = (tracking_cb_data *) user_data;
 
 	if (cb_data->is_video)
 		handle_tracking_video_result(cb_data->writer, source, cb_data->frame_number, location);
@@ -979,66 +910,49 @@ void tracked_cb(
 	MEDIA_VISION_FUNCTION_LEAVE();
 }
 
-void new_frame_cb(
-		char *buffer,
-		unsigned int buffer_size,
-		image_data_s image_data,
-		void *user_data)
+void new_frame_cb(char *buffer, unsigned int buffer_size, image_data_s image_data, void *user_data)
 {
 	if (NULL == user_data)
 		return;
 
 	mv_source_h frame = NULL;
 
-#define release_resources() \
-	if (frame) { \
-		const int err2 = mv_destroy_source(frame); \
-		if (MEDIA_VISION_ERROR_NONE != err2) { \
-			printf( \
-					"\nERROR: Errors were occurred during source destroying; " \
-					"code %i\n", \
-					err2); \
-		} \
+#define release_resources()                                                   \
+	if (frame) {                                                              \
+		const int err2 = mv_destroy_source(frame);                            \
+		if (MEDIA_VISION_ERROR_NONE != err2) {                                \
+			printf("\nERROR: Errors were occurred during source destroying; " \
+				   "code %i\n",                                               \
+				   err2);                                                     \
+		}                                                                     \
 	}
 
-	tracking_cb_data *cb_data = (tracking_cb_data*)user_data;
+	tracking_cb_data *cb_data = (tracking_cb_data *) user_data;
 
 	++(cb_data->frame_number);
 
 	int err = mv_create_source(&frame);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"\nERROR: Errors were occurred during source creating; "
-				"code %i\n",
-				err);
+		printf("\nERROR: Errors were occurred during source creating; "
+			   "code %i\n",
+			   err);
 		release_resources();
 		return;
 	}
 
-	err = mv_source_fill_by_buffer(
-			frame,
-			(unsigned char*)buffer,
-			buffer_size,
-			image_data.image_width,
-			image_data.image_height,
-			image_data.image_colorspace);
+	err = mv_source_fill_by_buffer(frame, (unsigned char *) buffer, buffer_size, image_data.image_width,
+								   image_data.image_height, image_data.image_colorspace);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf("ERROR: mv_source_h for frame is not filled; code %i\n", err);
 		release_resources();
 		return;
 	}
 
-	err = mv_image_track(
-			frame,
-			cb_data->target,
-			NULL,
-			tracked_cb,
-			cb_data);
+	err = mv_image_track(frame, cb_data->target, NULL, tracked_cb, cb_data);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"ERROR: Errors were occurred during tracking object on "
-				"the video; code %i\n",
-				err);
+		printf("ERROR: Errors were occurred during tracking object on "
+			   "the video; code %i\n",
+			   err);
 		release_resources();
 		return;
 	}
@@ -1048,15 +962,14 @@ void new_frame_cb(
 #undef release_resources
 }
 
-void eos_frame_cb(
-		void *user_data)
+void eos_frame_cb(void *user_data)
 {
 	if (NULL == user_data) {
 		printf("ERROR: eos callback can't stop tracking process.");
 		return;
 	}
 
-	pthread_mutex_unlock((pthread_mutex_t*)user_data);
+	pthread_mutex_unlock((pthread_mutex_t *) user_data);
 }
 
 int perform_track_video(mv_image_tracking_model_h target)
@@ -1072,50 +985,47 @@ int perform_track_video(mv_image_tracking_model_h target)
 	mv_video_writer_h writer = NULL;
 	char *path_to_video = NULL;
 	char *path_to_generated_video = NULL;
-	image_data_s image_data = {0};
+	image_data_s image_data = { 0 };
 	unsigned int fps = 0;
 
-#define release_resources() \
-	int err2 = MEDIA_VISION_ERROR_NONE; \
-	if (reader) { \
-		err2 = mv_destroy_video_reader(reader); \
-		if (MEDIA_VISION_ERROR_NONE != err2) { \
-			printf( \
-					"\nERROR: Errors were occurred during video reader destroying; " \
-					"code %i\n", \
-					err2); \
-		} \
-	} \
-	if (writer) { \
-		err2 = mv_destroy_video_writer(writer); \
-		if (MEDIA_VISION_ERROR_NONE != err2) { \
-			printf( \
-					"\nERROR: Errors were occurred during video writer destroying; " \
-					"code %i\n", \
-					err2); \
-		} \
-	} \
-	if (path_to_video) { \
-		free(path_to_video); \
-	} \
-	if (path_to_generated_video) { \
-		free(path_to_generated_video); \
-	}
-
-	while (input_string("Input file name with video for tracking:",
-							1024, &path_to_video) == -1) {
+#define release_resources()                                                         \
+	int err2 = MEDIA_VISION_ERROR_NONE;                                             \
+	if (reader) {                                                                   \
+		err2 = mv_destroy_video_reader(reader);                                     \
+		if (MEDIA_VISION_ERROR_NONE != err2) {                                      \
+			printf("\nERROR: Errors were occurred during video reader destroying; " \
+				   "code %i\n",                                                     \
+				   err2);                                                           \
+		}                                                                           \
+	}                                                                               \
+	if (writer) {                                                                   \
+		err2 = mv_destroy_video_writer(writer);                                     \
+		if (MEDIA_VISION_ERROR_NONE != err2) {                                      \
+			printf("\nERROR: Errors were occurred during video writer destroying; " \
+				   "code %i\n",                                                     \
+				   err2);                                                           \
+		}                                                                           \
+	}                                                                               \
+	if (path_to_video) {                                                            \
+		free(path_to_video);                                                        \
+	}                                                                               \
+	if (path_to_generated_video) {                                                  \
+		free(path_to_generated_video);                                              \
+	}
+
+	while (input_string("Input file name with video for tracking:", 1024, &path_to_video) == -1) {
 		printf("Incorrect input! Try again.\n");
 	}
 
-	while (input_string("Input file name for generated video:",
-							1024, &path_to_generated_video) == -1) {
+	while (input_string("Input file name for generated video:", 1024, &path_to_generated_video) == -1) {
 		printf("Incorrect input! Try again.\n");
 	}
 
 	int err = mv_create_video_reader(&reader);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf("\nERROR: Errors were occurred during video reader creating; "
-				"code %i\n", err);
+			   "code %i\n",
+			   err);
 		release_resources();
 		MEDIA_VISION_FUNCTION_LEAVE();
 		return err;
@@ -1123,20 +1033,15 @@ int perform_track_video(mv_image_tracking_model_h target)
 
 	err = mv_create_video_writer(&writer);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"\nERROR: Errors were occurred during video writer creating; "
-				"code %i\n",
-				err);
+		printf("\nERROR: Errors were occurred during video writer creating; "
+			   "code %i\n",
+			   err);
 		release_resources();
 		MEDIA_VISION_FUNCTION_LEAVE();
 		return err;
 	}
 
-	err = mv_video_reader_load(
-		reader,
-		path_to_video,
-		&image_data,
-		&fps);
+	err = mv_video_reader_load(reader, path_to_video, &image_data, &fps);
 	if (MEDIA_VISION_ERROR_NONE != err) {
 		printf("\nERROR: Errors were occurred during video loading; code %i\n", err);
 		release_resources();
@@ -1144,22 +1049,17 @@ int perform_track_video(mv_image_tracking_model_h target)
 		return err;
 	}
 
-	printf("Receive frame metadata: wxh - %ux%u, fps - %u, format - %d\n",
-		image_data.image_width, image_data.image_height, fps, image_data.image_colorspace);
+	printf("Receive frame metadata: wxh - %ux%u, fps - %u, format - %d\n", image_data.image_width,
+		   image_data.image_height, fps, image_data.image_colorspace);
 
 	/* Temporary we accept only RGB888 */
 	image_data.image_colorspace = MEDIA_VISION_COLORSPACE_RGB888;
 
-	err = mv_video_writer_init(
-			writer,
-			path_to_generated_video,
-			image_data,
-			fps);
+	err = mv_video_writer_init(writer, path_to_generated_video, image_data, fps);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"\nERROR: Errors were occurred during video writer initializing; "
-				"code %i\n",
-				err);
+		printf("\nERROR: Errors were occurred during video writer initializing; "
+			   "code %i\n",
+			   err);
 		release_resources();
 		MEDIA_VISION_FUNCTION_LEAVE();
 		return err;
@@ -1172,10 +1072,9 @@ int perform_track_video(mv_image_tracking_model_h target)
 	cb_data.is_video = true;
 	err = mv_video_reader_set_new_sample_cb(reader, new_frame_cb, &cb_data);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"\nERROR: Errors were occurred during set new frame callback; "
-				"code %i\n",
-				err);
+		printf("\nERROR: Errors were occurred during set new frame callback; "
+			   "code %i\n",
+			   err);
 		release_resources();
 		MEDIA_VISION_FUNCTION_LEAVE();
 		return err;
@@ -1186,23 +1085,21 @@ int perform_track_video(mv_image_tracking_model_h target)
 	pthread_mutex_lock(&block_during_tracking_mutex);
 	err = mv_video_reader_set_eos_cb(reader, eos_frame_cb, &block_during_tracking_mutex);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"\nERROR: Errors were occurred during set new frame callback; "
-				"code %i\n",
-				err);
-			release_resources();
-			pthread_mutex_unlock(&block_during_tracking_mutex);
-			pthread_mutex_destroy(&block_during_tracking_mutex);
-			MEDIA_VISION_FUNCTION_LEAVE();
-			return err;
+		printf("\nERROR: Errors were occurred during set new frame callback; "
+			   "code %i\n",
+			   err);
+		release_resources();
+		pthread_mutex_unlock(&block_during_tracking_mutex);
+		pthread_mutex_destroy(&block_during_tracking_mutex);
+		MEDIA_VISION_FUNCTION_LEAVE();
+		return err;
 	}
 
 	err = mv_video_reader_start(reader);
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"\nERROR: Errors were occurred during video reading starts; "
-				"code %i\n",
-				err);
+		printf("\nERROR: Errors were occurred during video reading starts; "
+			   "code %i\n",
+			   err);
 		release_resources();
 		pthread_mutex_unlock(&block_during_tracking_mutex);
 		pthread_mutex_destroy(&block_during_tracking_mutex);
@@ -1226,7 +1123,7 @@ int perform_track_video(mv_image_tracking_model_h target)
 
 static int cmpstring(const void *p1, const void *p2)
 {
-	return strcmp((char * const) p1, (char * const) p2);
+	return strcmp((char *const) p1, (char *const) p2);
 }
 
 int perform_track_image(mv_image_tracking_model_h target)
@@ -1241,20 +1138,18 @@ int perform_track_image(mv_image_tracking_model_h target)
 	char *path_to_image = NULL;
 	char *path_to_generated_image = NULL;
 
-	while (input_string("Input path for tracking:",
-							1024, &path_to_image) == -1) {
+	while (input_string("Input path for tracking:", 1024, &path_to_image) == -1) {
 		printf("Incorrect input! Try again.\n");
 	}
 
-	while (input_string("Input file name for generated results:",
-							1024, &path_to_generated_image) == -1) {
+	while (input_string("Input file name for generated results:", 1024, &path_to_generated_image) == -1) {
 		printf("Incorrect input! Try again.\n");
 	}
 
 	int frame_idx;
 	int err = MEDIA_VISION_ERROR_NONE;
 	int frames_counter = 0;
-	char (*frames)[FILE_PATH_SIZE] = malloc(0);
+	char(*frames)[FILE_PATH_SIZE] = malloc(0);
 
 	struct dirent *ent_eof;
 	DIR *dir = opendir(path_to_image);
@@ -1270,13 +1165,13 @@ int perform_track_image(mv_image_tracking_model_h target)
 		if (ent_eof->d_name[0] == '.' || strlen(ent_eof->d_name) < 4)
 			continue;
 
-		if (strcmp(".jpg", ent_eof->d_name + strlen(ent_eof->d_name) -4) != 0)
+		if (strcmp(".jpg", ent_eof->d_name + strlen(ent_eof->d_name) - 4) != 0)
 			continue;
 
 		frames_counter++;
 		frames = realloc(frames, frames_counter * FILE_PATH_SIZE);
 
-		snprintf(frames[frames_counter -1], FILE_PATH_SIZE, "%s/%s", path_to_image, ent_eof->d_name);
+		snprintf(frames[frames_counter - 1], FILE_PATH_SIZE, "%s/%s", path_to_image, ent_eof->d_name);
 	}
 	closedir(dir);
 
@@ -1293,7 +1188,8 @@ int perform_track_image(mv_image_tracking_model_h target)
 	err = mv_create_source(&source);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf("\nERROR: Errors(code %i) were occurred during"
-				"mv_create_source\n", err);
+			   "mv_create_source\n",
+			   err);
 		free(frames);
 		free(path_to_image);
 		free(path_to_generated_image);
@@ -1322,7 +1218,8 @@ int perform_track_image(mv_image_tracking_model_h target)
 		err = load_image_to_buffer(frames[frame_idx], &data_buffer, &buffer_size, &image_data);
 		if (err != MEDIA_VISION_ERROR_NONE) {
 			printf("\nWARN: WARN(code %i) were occurred during"
-				"load_image_to_media_source, but continue\n", err);
+				   "load_image_to_media_source, but continue\n",
+				   err);
 
 			if (data_buffer != NULL)
 				destroy_loaded_buffer(data_buffer);
@@ -1330,27 +1227,20 @@ int perform_track_image(mv_image_tracking_model_h target)
 			continue;
 		}
 
-		err = mv_source_fill_by_buffer(source, data_buffer,
-						buffer_size,
-						image_data.image_width,
-						image_data.image_height,
-						image_data.image_colorspace);
+		err = mv_source_fill_by_buffer(source, data_buffer, buffer_size, image_data.image_width,
+									   image_data.image_height, image_data.image_colorspace);
 
 		if (data_buffer != NULL)
 			destroy_loaded_buffer(data_buffer);
 
 		if (err != MEDIA_VISION_ERROR_NONE) {
 			printf("\nWARN: WARN(code %i) were occurred during"
-				"mv_source_fill_by_buffer, but continue\n", err);
+				   "mv_source_fill_by_buffer, but continue\n",
+				   err);
 			continue;
 		}
 
-		err = mv_image_track(source,
-				cb_data.target,
-				NULL,
-				tracked_cb,
-				&cb_data);
-
+		err = mv_image_track(source, cb_data.target, NULL, tracked_cb, &cb_data);
 	}
 
 	mv_destroy_source(source);
@@ -1373,19 +1263,17 @@ int perform_save_image_tracking_model(mv_image_tracking_model_h model)
 	int err = MEDIA_VISION_ERROR_NONE;
 	char *path_to_file = NULL;
 
-	while (input_string(
-			"Input file name to be generated for image tracking model storing:",
-			1024, &path_to_file) == -1) {
+	while (input_string("Input file name to be generated for image tracking model storing:", 1024, &path_to_file) ==
+		   -1) {
 		printf("Incorrect input! Try again.\n");
 	}
 
 	err = mv_image_tracking_model_save(path_to_file, model);
 
 	if (MEDIA_VISION_ERROR_NONE != err) {
-		printf(
-				"\nError during saving the image tracking model. "
-				"Error code is %i\n",
-				err);
+		printf("\nError during saving the image tracking model. "
+			   "Error code is %i\n",
+			   err);
 		free(path_to_file);
 		return err;
 	}
@@ -1399,15 +1287,12 @@ int perform_save_image_tracking_model(mv_image_tracking_model_h model)
 	return err;
 }
 
-int perform_load_image_tracking_model(
-		char **path_to_file, mv_image_tracking_model_h *result)
+int perform_load_image_tracking_model(char **path_to_file, mv_image_tracking_model_h *result)
 {
 	MEDIA_VISION_FUNCTION_ENTER();
 
-	while (input_string(
-			"Input file name with image tracking model to be loaded:",
-			1024, path_to_file) == -1) {
-			printf("Incorrect input! Try again.\n");
+	while (input_string("Input file name with image tracking model to be loaded:", 1024, path_to_file) == -1) {
+		printf("Incorrect input! Try again.\n");
 	}
 
 	int err = mv_image_tracking_model_load(*path_to_file, result);
@@ -1427,9 +1312,7 @@ int perform_load_image_tracking_model(
 	return err;
 }
 
-int perform_clone_image_tracking_model(
-		mv_image_tracking_model_h src,
-		mv_image_tracking_model_h *result)
+int perform_clone_image_tracking_model(mv_image_tracking_model_h src, mv_image_tracking_model_h *result)
 {
 	MEDIA_VISION_FUNCTION_ENTER();
 
@@ -1441,7 +1324,8 @@ int perform_clone_image_tracking_model(
 		int err2 = mv_image_tracking_model_destroy(*result);
 		if (MEDIA_VISION_ERROR_NONE != err2) {
 			printf("\nERROR: Errors were occurred during tracking model "
-				"destroying; code %i\n", err);
+				   "destroying; code %i\n",
+				   err);
 		}
 
 		(*result) = NULL;
@@ -1507,8 +1391,7 @@ int select_testing_object(GArray *testing_objects, testing_object_h *result, cha
 
 	show_testing_objects(title, testing_objects);
 	int sel_index = 0;
-	while (input_int("Input number of element:", 0,
-			testing_objects->len - 1, &sel_index) == -1) {
+	while (input_int("Input number of element:", 0, testing_objects->len - 1, &sel_index) == -1) {
 		printf("Incorrect input! Try again.\n");
 	}
 	(*result) = g_array_index(testing_objects, testing_object_h, sel_index);
@@ -1525,8 +1408,7 @@ int select_testing_object_index(GArray *testing_objects, guint *result_index, ch
 	show_testing_objects(title, testing_objects);
 
 	int sel_index = 0;
-	while (input_int("Input number of element:", 0,
-		testing_objects->len - 1, &sel_index) == -1) {
+	while (input_int("Input number of element:", 0, testing_objects->len - 1, &sel_index) == -1) {
 		printf("Incorrect input! Try again.\n");
 	}
 	(*result_index) = sel_index;
@@ -1553,19 +1435,18 @@ int remove_testing_object(GArray *testing_objects, guint index)
 
 void perform_recognition_cases(GArray *image_objects)
 {
-	const char *names[] = {
-			"Show created set of image objects",
-			"Generate new image object from source image  (mv_image_object_fill )",
-			"Load existed image object from file          (mv_image_object_load)",
-			"Clone existed image object                   (mv_image_object_clone)",
-			"Create empty image object                    (mv_image_object_create)",
-			"Save existed image object to the file        (mv_image_object_save)",
-			"Remove image object from created set         (mv_image_object_destroy)",
-			"Get confidence from existed image object     (mv_image_object_get_recognition_rate)",
-			"Recognize all image objects on image         (mv_image_recognize)",
-			"Set label for existed image object           (mv_image_set_label_of_object)",
-			"Get label from existed image object          (mv_image_get_label_of_object)",
-			"Back to the main menu"};
+	const char *names[] = { "Show created set of image objects",
+							"Generate new image object from source image  (mv_image_object_fill )",
+							"Load existed image object from file          (mv_image_object_load)",
+							"Clone existed image object                   (mv_image_object_clone)",
+							"Create empty image object                    (mv_image_object_create)",
+							"Save existed image object to the file        (mv_image_object_save)",
+							"Remove image object from created set         (mv_image_object_destroy)",
+							"Get confidence from existed image object     (mv_image_object_get_recognition_rate)",
+							"Recognize all image objects on image         (mv_image_recognize)",
+							"Set label for existed image object           (mv_image_set_label_of_object)",
+							"Get label from existed image object          (mv_image_get_label_of_object)",
+							"Back to the main menu" };
 
 	int number_of_options = sizeof(names) / sizeof(names[0]);
 	int options[number_of_options];
@@ -1580,12 +1461,12 @@ void perform_recognition_cases(GArray *image_objects)
 
 		switch (sel_opt) {
 		case 1: {
-		/* Show created set of image objects */
+			/* Show created set of image objects */
 			show_testing_objects("Set of image objects", image_objects);
 			break;
 		}
 		case 2: {
-		/* Generate new image object from source image (mv_image_object_fill) */
+			/* Generate new image object from source image (mv_image_object_fill) */
 			mv_image_object_h temporary = NULL;
 			char *path_to_image = NULL;
 
@@ -1600,9 +1481,8 @@ void perform_recognition_cases(GArray *image_objects)
 
 			testing_object_h added_object = NULL;
 			testing_object_create(&added_object);
-			testing_object_fill(added_object, temporary,
-					OBJECT_TYPE_IMAGE_OBJECT, SOURCE_TYPE_GENERATION,
-					path_to_image);
+			testing_object_fill(added_object, temporary, OBJECT_TYPE_IMAGE_OBJECT, SOURCE_TYPE_GENERATION,
+								path_to_image);
 
 			if (NULL != path_to_image)
 				free(path_to_image);
@@ -1615,8 +1495,7 @@ void perform_recognition_cases(GArray *image_objects)
 			mv_image_object_h temporary_image_object = NULL;
 			char *path_to_object = NULL;
 
-			err = perform_load_image_object(
-						&path_to_object, &temporary_image_object);
+			err = perform_load_image_object(&path_to_object, &temporary_image_object);
 
 			if (MEDIA_VISION_ERROR_NONE != err) {
 				printf("Loading failed (error code - %i)\n", err);
@@ -1625,12 +1504,8 @@ void perform_recognition_cases(GArray *image_objects)
 
 			testing_object_h added_object = NULL;
 			testing_object_create(&added_object);
-			testing_object_fill(
-						added_object,
-						temporary_image_object,
-						OBJECT_TYPE_IMAGE_OBJECT,
-						SOURCE_TYPE_LOADING,
-						path_to_object);
+			testing_object_fill(added_object, temporary_image_object, OBJECT_TYPE_IMAGE_OBJECT, SOURCE_TYPE_LOADING,
+								path_to_object);
 
 			free(path_to_object);
 
@@ -1645,24 +1520,15 @@ void perform_recognition_cases(GArray *image_objects)
 			}
 
 			testing_object_h temporary_testing_object = NULL;
-			select_testing_object(
-						image_objects,
-						&temporary_testing_object,
-						"Select the object you want to clone");
+			select_testing_object(image_objects, &temporary_testing_object, "Select the object you want to clone");
 
 			mv_image_object_h temporary_image_object = NULL;
-			perform_clone_image_object(
-						temporary_testing_object->entity,
-						&temporary_image_object);
+			perform_clone_image_object(temporary_testing_object->entity, &temporary_image_object);
 
 			testing_object_h added_object = NULL;
 			testing_object_create(&added_object);
-			testing_object_fill(
-						added_object,
-						temporary_image_object,
-						OBJECT_TYPE_IMAGE_OBJECT,
-						SOURCE_TYPE_CLONING,
-						temporary_testing_object);
+			testing_object_fill(added_object, temporary_image_object, OBJECT_TYPE_IMAGE_OBJECT, SOURCE_TYPE_CLONING,
+								temporary_testing_object);
 
 			add_testing_object(image_objects, added_object);
 			break;
@@ -1679,12 +1545,8 @@ void perform_recognition_cases(GArray *image_objects)
 
 			testing_object_h added_object = NULL;
 			testing_object_create(&added_object);
-			testing_object_fill(
-						added_object,
-						temporary_image_object,
-						OBJECT_TYPE_IMAGE_OBJECT,
-						SOURCE_TYPE_EMPTY,
-						NULL);
+			testing_object_fill(added_object, temporary_image_object, OBJECT_TYPE_IMAGE_OBJECT, SOURCE_TYPE_EMPTY,
+								NULL);
 
 			add_testing_object(image_objects, added_object);
 			printf("\nImage object successfully created\n");
@@ -1698,8 +1560,7 @@ void perform_recognition_cases(GArray *image_objects)
 			}
 
 			testing_object_h temporary_testing_object = NULL;
-			select_testing_object(image_objects, &temporary_testing_object,
-						"Select the object you want to save");
+			select_testing_object(image_objects, &temporary_testing_object, "Select the object you want to save");
 			perform_save_image_object(temporary_testing_object->entity);
 			break;
 		}
@@ -1711,10 +1572,8 @@ void perform_recognition_cases(GArray *image_objects)
 			}
 
 			guint selected_index;
-			int err = select_testing_object_index(
-						image_objects,
-						&selected_index,
-						"Select the object you want to remove");
+			int err =
+					select_testing_object_index(image_objects, &selected_index, "Select the object you want to remove");
 			if (MEDIA_VISION_ERROR_NONE == err) {
 				remove_testing_object(image_objects, selected_index);
 				printf("\nImage object successfully removed\n");
@@ -1730,7 +1589,7 @@ void perform_recognition_cases(GArray *image_objects)
 
 			testing_object_h temporary_testing_object = NULL;
 			select_testing_object(image_objects, &temporary_testing_object,
-						"Select the object from which you want getting confidence");
+								  "Select the object from which you want getting confidence");
 			perform_get_confidence(temporary_testing_object->entity);
 			break;
 		}
@@ -1763,10 +1622,10 @@ void perform_recognition_cases(GArray *image_objects)
 
 			testing_object_h temporary_testing_object = NULL;
 			select_testing_object(image_objects, &temporary_testing_object,
-						"Select the object for which you want setting label");
+								  "Select the object for which you want setting label");
 			perform_set_label(temporary_testing_object->entity);
 			break;
-			}
+		}
 		case 11: {
 			/* Get label from existed image object (mv_image_object_get_label) */
 			if (image_objects->len <= 0) {
@@ -1776,7 +1635,7 @@ void perform_recognition_cases(GArray *image_objects)
 
 			testing_object_h temporary_testing_object = NULL;
 			select_testing_object(image_objects, &temporary_testing_object,
-						"Select the object from which you want getting label");
+								  "Select the object from which you want getting label");
 			perform_get_label(temporary_testing_object->entity);
 			break;
 		}
@@ -1792,17 +1651,16 @@ void perform_recognition_cases(GArray *image_objects)
 
 void perform_tracking_cases(GArray *image_objects, GArray *image_tracking_models)
 {
-	const char *names[] = {
-			"Show created set of tracking models",
-			"Create empty tracking model              (mv_image_tracking_model_create)",
-			"Generate model based on image object     (mv_image_tracking_model_set_target)",
-			"Load existed tracking model from file    (mv_image_tracking_model_load)",
-			"Clone existed tracking model             (mv_image_tracking_model_clone)",
-			"Save existed tracking model to the file  (mv_image_tracking_model_save)",
-			"Remove tracking model from created set   (mv_image_tracking_model_destroy)",
-			"Refresh tracking model                   (mv_image_tracking_model_refresh)",
-			"Track                                    (mv_image_track)",
-			"Back to the main menu"};
+	const char *names[] = { "Show created set of tracking models",
+							"Create empty tracking model              (mv_image_tracking_model_create)",
+							"Generate model based on image object     (mv_image_tracking_model_set_target)",
+							"Load existed tracking model from file    (mv_image_tracking_model_load)",
+							"Clone existed tracking model             (mv_image_tracking_model_clone)",
+							"Save existed tracking model to the file  (mv_image_tracking_model_save)",
+							"Remove tracking model from created set   (mv_image_tracking_model_destroy)",
+							"Refresh tracking model                   (mv_image_tracking_model_refresh)",
+							"Track                                    (mv_image_track)",
+							"Back to the main menu" };
 
 	int number_of_options = sizeof(names) / sizeof(names[0]);
 	int options[number_of_options];
@@ -1834,12 +1692,8 @@ void perform_tracking_cases(GArray *image_objects, GArray *image_tracking_models
 
 			testing_object_h added_object = NULL;
 			testing_object_create(&added_object);
-			testing_object_fill(
-					added_object,
-					temporary_image_tracking_model,
-					OBJECT_TYPE_IMAGE_TRACKING_MODEL,
-					SOURCE_TYPE_EMPTY,
-					NULL);
+			testing_object_fill(added_object, temporary_image_tracking_model, OBJECT_TYPE_IMAGE_TRACKING_MODEL,
+								SOURCE_TYPE_EMPTY, NULL);
 
 			add_testing_object(image_tracking_models, added_object);
 			printf("\nTracking model successfully created\n");
@@ -1860,32 +1714,24 @@ void perform_tracking_cases(GArray *image_objects, GArray *image_tracking_models
 			}
 
 			testing_object_h temporary_testing_object = NULL;
-			select_testing_object(
-					image_objects,
-					&temporary_testing_object,
-					"Select the image object for tracking");
-
-			err = mv_image_tracking_model_set_target(
-					(mv_image_object_h)(temporary_testing_object->entity),
-					temporary_image_tracking_model);
+			select_testing_object(image_objects, &temporary_testing_object, "Select the image object for tracking");
+
+			err = mv_image_tracking_model_set_target((mv_image_object_h)(temporary_testing_object->entity),
+													 temporary_image_tracking_model);
 			if (MEDIA_VISION_ERROR_NONE != err) {
 				printf("Error: target isn't set with error code %i\n", err);
-				int err2 = mv_image_tracking_model_destroy(
-						temporary_image_tracking_model);
+				int err2 = mv_image_tracking_model_destroy(temporary_image_tracking_model);
 				if (MEDIA_VISION_ERROR_NONE != err2)
 					printf("Error: tracking model destroying return"
-							"error code %i\n", err);
+						   "error code %i\n",
+						   err);
 				break;
 			}
 
 			testing_object_h added_object = NULL;
 			testing_object_create(&added_object);
-			testing_object_fill(
-					added_object,
-					temporary_image_tracking_model,
-					OBJECT_TYPE_IMAGE_TRACKING_MODEL,
-					SOURCE_TYPE_GENERATION,
-					temporary_testing_object);
+			testing_object_fill(added_object, temporary_image_tracking_model, OBJECT_TYPE_IMAGE_TRACKING_MODEL,
+								SOURCE_TYPE_GENERATION, temporary_testing_object);
 
 			add_testing_object(image_tracking_models, added_object);
 			printf("\nTracking model successfully generated\n");
@@ -1896,8 +1742,7 @@ void perform_tracking_cases(GArray *image_objects, GArray *image_tracking_models
 			mv_image_tracking_model_h temporary_image_tracking_model = NULL;
 			char *path_to_object = NULL;
 
-			err = perform_load_image_tracking_model(
-					&path_to_object, &temporary_image_tracking_model);
+			err = perform_load_image_tracking_model(&path_to_object, &temporary_image_tracking_model);
 
 			if (MEDIA_VISION_ERROR_NONE != err) {
 				printf("Loading failed (error code - %i)\n", err);
@@ -1906,12 +1751,8 @@ void perform_tracking_cases(GArray *image_objects, GArray *image_tracking_models
 
 			testing_object_h added_object = NULL;
 			testing_object_create(&added_object);
-			testing_object_fill(
-					added_object,
-					temporary_image_tracking_model,
-					OBJECT_TYPE_IMAGE_TRACKING_MODEL,
-					SOURCE_TYPE_LOADING,
-					path_to_object);
+			testing_object_fill(added_object, temporary_image_tracking_model, OBJECT_TYPE_IMAGE_TRACKING_MODEL,
+								SOURCE_TYPE_LOADING, path_to_object);
 
 			free(path_to_object);
 
@@ -1922,31 +1763,22 @@ void perform_tracking_cases(GArray *image_objects, GArray *image_tracking_models
 		case 5: {
 			/* Clone existed tracking model (mv_image_tracking_model_clone) */
 			if (image_tracking_models->len <= 0) {
-				printf(
-					"\nFirstly you must create at least one image "
-					"tracking model.\n");
+				printf("\nFirstly you must create at least one image "
+					   "tracking model.\n");
 				break;
 			}
 
 			testing_object_h temporary_testing_object = NULL;
-			select_testing_object(
-					image_tracking_models,
-					&temporary_testing_object,
-					"Select the tracking model you want to clone");
+			select_testing_object(image_tracking_models, &temporary_testing_object,
+								  "Select the tracking model you want to clone");
 
 			mv_image_tracking_model_h temporary_image_tracking_model = NULL;
-			perform_clone_image_tracking_model(
-					temporary_testing_object->entity,
-					&temporary_image_tracking_model);
+			perform_clone_image_tracking_model(temporary_testing_object->entity, &temporary_image_tracking_model);
 
 			testing_object_h added_object = NULL;
 			testing_object_create(&added_object);
-			testing_object_fill(
-					added_object,
-					temporary_image_tracking_model,
-					OBJECT_TYPE_IMAGE_TRACKING_MODEL,
-					SOURCE_TYPE_CLONING,
-					temporary_testing_object);
+			testing_object_fill(added_object, temporary_image_tracking_model, OBJECT_TYPE_IMAGE_TRACKING_MODEL,
+								SOURCE_TYPE_CLONING, temporary_testing_object);
 
 			add_testing_object(image_tracking_models, added_object);
 			break;
@@ -1954,17 +1786,14 @@ void perform_tracking_cases(GArray *image_objects, GArray *image_tracking_models
 		case 6: {
 			/* Save existed tracking model to the file (mv_image_tracking_model_save) */
 			if (image_tracking_models->len <= 0) {
-				printf(
-						"\nFirstly you must create at least one image "
-						"tracking model.\n");
-						break;
+				printf("\nFirstly you must create at least one image "
+					   "tracking model.\n");
+				break;
 			}
 
 			testing_object_h temporary_testing_object = NULL;
-			select_testing_object(
-					image_tracking_models,
-					&temporary_testing_object,
-					"Select the tracking model you want to save");
+			select_testing_object(image_tracking_models, &temporary_testing_object,
+								  "Select the tracking model you want to save");
 
 			perform_save_image_tracking_model(temporary_testing_object->entity);
 			break;
@@ -1972,17 +1801,14 @@ void perform_tracking_cases(GArray *image_objects, GArray *image_tracking_models
 		case 7: {
 			/* Remove tracking model from created set (mv_image_tracking_model_destroy) */
 			if (image_tracking_models->len <= 0) {
-				printf(
-						"\nFirstly you must create at least one image "
-						"tracking model.\n");
+				printf("\nFirstly you must create at least one image "
+					   "tracking model.\n");
 				break;
 			}
 
 			guint selected_index;
-			err = select_testing_object_index(
-					image_tracking_models,
-					&selected_index,
-					"Select the object you want to remove");
+			err = select_testing_object_index(image_tracking_models, &selected_index,
+											  "Select the object you want to remove");
 
 			if (MEDIA_VISION_ERROR_NONE == err) {
 				remove_testing_object(image_tracking_models, selected_index);
@@ -1993,17 +1819,14 @@ void perform_tracking_cases(GArray *image_objects, GArray *image_tracking_models
 		case 8: {
 			/* Refresh tracking model (mv_image_tracking_model_refresh) */
 			if (image_tracking_models->len <= 0) {
-				printf(
-						"\nFirstly you must create at least one image "
-						"tracking model.\n");
-						break;
+				printf("\nFirstly you must create at least one image "
+					   "tracking model.\n");
+				break;
 			}
 
 			testing_object_h temporary_testing_object = NULL;
-			select_testing_object(
-					image_tracking_models,
-					&temporary_testing_object,
-					"Select the tracking model you want to refresh");
+			select_testing_object(image_tracking_models, &temporary_testing_object,
+								  "Select the tracking model you want to refresh");
 
 			perform_refresh_image_tracking_model(temporary_testing_object->entity);
 			break;
@@ -2011,46 +1834,43 @@ void perform_tracking_cases(GArray *image_objects, GArray *image_tracking_models
 		case 9: {
 			/* Track (mv_image_track) */
 			if (image_tracking_models->len <= 0) {
-				printf(
-						"\nFirstly you must create at least one image "
-						"tracking model.\n");
+				printf("\nFirstly you must create at least one image "
+					   "tracking model.\n");
 				break;
 			}
 
 			testing_object_h temporary_testing_object = NULL;
-			err = select_testing_object(
-					image_tracking_models,
-					&temporary_testing_object,
-					"Select the object which you want to track");
+			err = select_testing_object(image_tracking_models, &temporary_testing_object,
+										"Select the object which you want to track");
 
 			if (MEDIA_VISION_ERROR_NONE != err) {
 				printf("\nERROR: Errors(code %i) were occurred during "
-					"select_testing_object\n", err);
+					   "select_testing_object\n",
+					   err);
 				break;
 			}
 
 			int track_opt = 0;
-			const int track_options[2] = {1, 2};
-			const char *track_opt_names[2] = {"Track with the video file",
-						"Track with the image files"};
+			const int track_options[2] = { 1, 2 };
+			const char *track_opt_names[2] = { "Track with the video file", "Track with the image files" };
 			while (!track_opt) {
 				track_opt = show_menu("Select actions:", track_options, track_opt_names, 2);
 
 				switch (track_opt) {
 				case 1:
-						perform_track_video(temporary_testing_object->entity);
-						break;
+					perform_track_video(temporary_testing_object->entity);
+					break;
 				case 2:
-						perform_track_image(temporary_testing_object->entity);
-						break;
+					perform_track_image(temporary_testing_object->entity);
+					break;
 				default:
-						track_opt = 0;
-						break;
+					track_opt = 0;
+					break;
 				}
 			}
 			break;
 		}
-		 case 10: {
+		case 10: {
 			/* Back to the main menu */
 			return;
 		}
@@ -2076,10 +1896,7 @@ int main(void)
 	}
 
 	const int options[3] = { 1, 2, 3 };
-	const char *names[3] = {
-			"Recognition cases",
-			"Tracking cases",
-			"Exit" };
+	const char *names[3] = { "Recognition cases", "Tracking cases", "Exit" };
 
 	while (1) {
 		char exit = 'n';
@@ -2109,8 +1926,7 @@ int main(void)
 			const char *names_last[2] = { "No", "Yes" };
 
 			while (sel_opt == 0) {
-				sel_opt = show_menu("Are you sure?",
-										options_last, names_last, 2);
+				sel_opt = show_menu("Are you sure?", options_last, names_last, 2);
 				switch (sel_opt) {
 				case 1:
 					exit = 'n';
@@ -2132,17 +1948,13 @@ int main(void)
 
 	guint i = 0;
 	for (i = 0; i < image_objects->len; ++i) {
-		testing_object_h temp = g_array_index(
-				image_objects,
-				testing_object_h, i);
+		testing_object_h temp = g_array_index(image_objects, testing_object_h, i);
 		testing_object_destroy(&temp);
 	}
 	g_array_free(image_objects, TRUE);
 
 	for (i = 0; i < image_tracking_models->len; ++i) {
-		testing_object_h temp = g_array_index(
-				image_tracking_models,
-				testing_object_h, i);
+		testing_object_h temp = g_array_index(image_tracking_models, testing_object_h, i);
 		testing_object_destroy(&temp);
 	}
 	g_array_free(image_tracking_models, TRUE);
diff --git a/test/testsuites/machine_learning/face_recognition/measure_face_recognition.cpp b/test/testsuites/machine_learning/face_recognition/measure_face_recognition.cpp
index 80b4e40..9311728 100644
--- a/test/testsuites/machine_learning/face_recognition/measure_face_recognition.cpp
+++ b/test/testsuites/machine_learning/face_recognition/measure_face_recognition.cpp
@@ -26,12 +26,12 @@
 #include "ImageHelper.h"
 #include "mv_face_recognition.h"
 
-#define TRAIN_LIST_FILE	"/home/owner/media/res/face_recognition/res/measurement/train_list.txt"
-#define TEST_LIST_FILE	"/home/owner/media/res/face_recognition/res/measurement/test_list.txt"
-#define TRAINING_IMAGE_PATH	"/home/owner/media/res/face_recognition/res/measurement/train/"
-#define TEST_IMAGE_PATH	"/home/owner/media/res/face_recognition/res/measurement/test/"
-#define MAX_TRAINING_CLASS			20
-#define SHOT_PER_CLASS				5
+#define TRAIN_LIST_FILE "/home/owner/media/res/face_recognition/res/measurement/train_list.txt"
+#define TEST_LIST_FILE "/home/owner/media/res/face_recognition/res/measurement/test_list.txt"
+#define TRAINING_IMAGE_PATH "/home/owner/media/res/face_recognition/res/measurement/train/"
+#define TEST_IMAGE_PATH "/home/owner/media/res/face_recognition/res/measurement/test/"
+#define MAX_TRAINING_CLASS 20
+#define SHOT_PER_CLASS 5
 
 using namespace testing;
 using namespace std;
@@ -39,7 +39,6 @@ using namespace MediaVision::Common;
 
 TEST(FaceRecognitionAccuracy, Measure)
 {
-
 	ifstream train_file(TRAIN_LIST_FILE, ios::in | ios::binary);
 
 	if (!train_file.is_open()) {
@@ -59,15 +58,15 @@ TEST(FaceRecognitionAccuracy, Measure)
 
 	vector<string> cached_label;
 
-
 	while (!train_file.eof()) {
 		string filename, label, index;
 
-		train_file >> filename  >> label >> index;
+		train_file >> filename >> label >> index;
 
 		const string image_path = string(TRAINING_IMAGE_PATH) + filename;
 
-		cout << "training " << image_path << " file" << " with " << label << " train cnt = " << train_cnt << endl;
+		cout << "training " << image_path << " file"
+			 << " with " << label << " train cnt = " << train_cnt << endl;
 
 		mv_source_h mv_source = NULL;
 
@@ -112,14 +111,15 @@ TEST(FaceRecognitionAccuracy, Measure)
 	while (!test_file.eof()) {
 		string filename, label, index;
 
-		test_file >> filename  >> label >> index;
+		test_file >> filename >> label >> index;
 
 		if (filename.empty() || label.empty() || index.empty())
 			break;
 
 		string image_path = string(TEST_IMAGE_PATH) + filename;
 
-		cout << "inferencing " << image_path << " file" << " with " << label << " index = " << test_cnt++ << endl;
+		cout << "inferencing " << image_path << " file"
+			 << " with " << label << " index = " << test_cnt++ << endl;
 
 		mv_source_h mv_source = NULL;
 
@@ -134,7 +134,7 @@ TEST(FaceRecognitionAccuracy, Measure)
 		bool is_no_data = (ret == MEDIA_VISION_ERROR_NO_DATA);
 		const char *out_label = NULL;
 
-		ret  = mv_face_recognition_get_label(handle, &out_label);
+		ret = mv_face_recognition_get_label(handle, &out_label);
 		ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
 
 		auto it = find(cached_label.begin(), cached_label.end(), label);
diff --git a/test/testsuites/machine_learning/face_recognition/test_face_recognition.cpp b/test/testsuites/machine_learning/face_recognition/test_face_recognition.cpp
index f1be72d..37a278b 100644
--- a/test/testsuites/machine_learning/face_recognition/test_face_recognition.cpp
+++ b/test/testsuites/machine_learning/face_recognition/test_face_recognition.cpp
@@ -23,49 +23,27 @@
 #include "ImageHelper.h"
 #include "mv_face_recognition.h"
 
-#define TRAINING_IMAGE_PATH	"/home/owner/media/res/face_recognition/res/test/training/"
-#define TEST_IMAGE_PATH		"/home/owner/media/res/face_recognition/res/test/test/"
-#define LABEL_FILE_PATH		"/home/owner/media/res/face_recognition/training/labels.dat"
-#define MODEL_FILE_PATH		"/home/owner/media/res/face_recognition/training/model_and_weights.ini"
-#define FV_FILE_PATH		"/home/owner/media/res/face_recognition/training/feature_vector_file.dat"
+#define TRAINING_IMAGE_PATH "/home/owner/media/res/face_recognition/res/test/training/"
+#define TEST_IMAGE_PATH "/home/owner/media/res/face_recognition/res/test/test/"
+#define LABEL_FILE_PATH "/home/owner/media/res/face_recognition/training/labels.dat"
+#define MODEL_FILE_PATH "/home/owner/media/res/face_recognition/training/model_and_weights.ini"
+#define FV_FILE_PATH "/home/owner/media/res/face_recognition/training/feature_vector_file.dat"
 
 using namespace testing;
 using namespace std;
 
 static const map<string, string> training_images = {
-	{ "037830.png", "2929" },
-	{ "038965.png", "2929" },
-	{ "045978.png", "2929" },
-	{ "050501.png", "2929" },
-	{ "065899.png", "2929" },
-	{ "010348.png", "7779" },
-	{ "029342.png", "7779" },
-	{ "035939.png", "7779" },
-	{ "061310.png", "7779" },
-	{ "062261.png", "7779" },
-	{ "000928.png", "3448" },
-	{ "008922.png", "3448" },
-	{ "029633.png", "3448" },
-	{ "032962.png", "3448" },
-	{ "054616.png", "3448" }
+	{ "037830.png", "2929" }, { "038965.png", "2929" }, { "045978.png", "2929" }, { "050501.png", "2929" },
+	{ "065899.png", "2929" }, { "010348.png", "7779" }, { "029342.png", "7779" }, { "035939.png", "7779" },
+	{ "061310.png", "7779" }, { "062261.png", "7779" }, { "000928.png", "3448" }, { "008922.png", "3448" },
+	{ "029633.png", "3448" }, { "032962.png", "3448" }, { "054616.png", "3448" }
 };
 
 static const map<string, string> test_images = {
-	{ "068468.png", "2929" },
-	{ "068883.png", "2929" },
-	{ "075004.png", "2929" },
-	{ "078125.png", "2929" },
-	{ "080649.png", "2929" },
-	{ "074645.png", "7779" },
-	{ "086536.png", "7779" },
-	{ "089334.png", "7779" },
-	{ "096514.png", "7779" },
-	{ "100336.png", "7779" },
-	{ "054757.png", "3448" },
-	{ "064838.png", "3448" },
-	{ "072749.png", "3448" },
-	{ "073526.png", "3448" },
-	{ "080451.png", "3448" }
+	{ "068468.png", "2929" }, { "068883.png", "2929" }, { "075004.png", "2929" }, { "078125.png", "2929" },
+	{ "080649.png", "2929" }, { "074645.png", "7779" }, { "086536.png", "7779" }, { "089334.png", "7779" },
+	{ "096514.png", "7779" }, { "100336.png", "7779" }, { "054757.png", "3448" }, { "064838.png", "3448" },
+	{ "072749.png", "3448" }, { "073526.png", "3448" }, { "080451.png", "3448" }
 };
 
 using namespace MediaVision::Common;
@@ -91,11 +69,8 @@ TEST(FaceRecognitionTest, CreateAndDestroyShouldBeOk)
 TEST(FaceRecognitionTest, InferenceAfterTrainingShouldBeOk)
 {
 	mv_face_recognition_h handle;
-	vector<string> answers = {
-		"3448", "3448", "2929", "2929", "3448",
-		"3448", "7779", "2929", "2929", "3448",
-		"2929", "7779", "7779", "7779", "7779"
-	};
+	vector<string> answers = { "3448", "3448", "2929", "2929", "3448", "3448", "7779", "2929",
+							   "2929", "3448", "2929", "7779", "7779", "7779", "7779" };
 
 	int ret = mv_face_recognition_create(&handle);
 	ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
@@ -103,7 +78,7 @@ TEST(FaceRecognitionTest, InferenceAfterTrainingShouldBeOk)
 	ret = mv_face_recognition_prepare(handle);
 	ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
 
-	for (auto& image : training_images) {
+	for (auto &image : training_images) {
 		const string image_path = string(TRAINING_IMAGE_PATH) + image.first;
 		mv_source_h mv_source = NULL;
 
@@ -123,7 +98,7 @@ TEST(FaceRecognitionTest, InferenceAfterTrainingShouldBeOk)
 	unsigned int image_idx = 0;
 	unsigned int correct_cnt = 0;
 
-	for (auto& image : test_images) {
+	for (auto &image : test_images) {
 		const string image_path = string(TEST_IMAGE_PATH) + image.first;
 		mv_source_h mv_source = NULL;
 
@@ -143,7 +118,7 @@ TEST(FaceRecognitionTest, InferenceAfterTrainingShouldBeOk)
 
 		const char *out_label = NULL;
 
-		ret  = mv_face_recognition_get_label(handle, &out_label);
+		ret = mv_face_recognition_get_label(handle, &out_label);
 		ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
 
 		string label_str(out_label);
@@ -170,7 +145,7 @@ TEST(FaceRecognitionTest, InferenceWithoutLabelShouldBeOk)
 	ret = mv_face_recognition_prepare(handle);
 	ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
 
-	for (auto& image : test_images) {
+	for (auto &image : test_images) {
 		const string image_path = string(TEST_IMAGE_PATH) + image.first;
 		mv_source_h mv_source = NULL;
 
@@ -188,7 +163,7 @@ TEST(FaceRecognitionTest, InferenceWithoutLabelShouldBeOk)
 
 		const char *out_label = NULL;
 
-		ret  = mv_face_recognition_get_label(handle, &out_label);
+		ret = mv_face_recognition_get_label(handle, &out_label);
 		ASSERT_NE(ret, MEDIA_VISION_ERROR_NONE);
 	}
 
@@ -199,17 +174,12 @@ TEST(FaceRecognitionTest, InferenceWithoutLabelShouldBeOk)
 TEST(FaceRecognitionTest, LabelRemovalShouldBeOk)
 {
 	vector<string> labels = { "3448", "2929", "7779" };
-	vector<vector<string>> answers = {
-			{ "none", "none", "2929", "2929", "none",
-			"none", "7779", "2929", "2929", "none",
-			"2929", "7779", "7779", "7779", "7779" },
-			{ "3448", "3448", "none", "none", "3448",
-			"3448", "7779", "none", "none", "3448",
-			"none", "7779", "7779", "7779", "7779" },
-			{ "3448", "3448", "2929", "2929", "3448",
-			"3448", "none", "2929", "2929", "3448",
-			"2929", "none", "none", "none", "none" }
-		};
+	vector<vector<string> > answers = { { "none", "none", "2929", "2929", "none", "none", "7779", "2929", "2929",
+										  "none", "2929", "7779", "7779", "7779", "7779" },
+										{ "3448", "3448", "none", "none", "3448", "3448", "7779", "none", "none",
+										  "3448", "none", "7779", "7779", "7779", "7779" },
+										{ "3448", "3448", "2929", "2929", "3448", "3448", "none", "2929", "2929",
+										  "3448", "2929", "none", "none", "none", "none" } };
 
 	unsigned int label_idx = 0;
 	mv_face_recognition_h handle;
@@ -217,13 +187,13 @@ TEST(FaceRecognitionTest, LabelRemovalShouldBeOk)
 	int ret = mv_face_recognition_create(&handle);
 	ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
 
-	for (auto& label : labels) {
+	for (auto &label : labels) {
 		ret = mv_face_recognition_prepare(handle);
 		ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
 
-		auto& answer = answers[label_idx++];
+		auto &answer = answers[label_idx++];
 
-		for (auto& image : training_images) {
+		for (auto &image : training_images) {
 			const string image_path = string(TRAINING_IMAGE_PATH) + image.first;
 			mv_source_h mv_source = NULL;
 			ret = mv_create_source(&mv_source);
@@ -247,7 +217,7 @@ TEST(FaceRecognitionTest, LabelRemovalShouldBeOk)
 		unsigned int image_idx = 0;
 		unsigned int correct_cnt = 0;
 
-		for (auto& image : test_images) {
+		for (auto &image : test_images) {
 			const string image_path = string(TEST_IMAGE_PATH) + image.first;
 			mv_source_h mv_source = NULL;
 
@@ -305,7 +275,7 @@ TEST(FaceRecognitionTest, RemoveAllLabelsShouldBeOk)
 	ret = mv_face_recognition_prepare(handle);
 	ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
 
-	for (auto& image : training_images) {
+	for (auto &image : training_images) {
 		const string image_path = string(TRAINING_IMAGE_PATH) + image.first;
 		mv_source_h mv_source = NULL;
 		ret = mv_create_source(&mv_source);
@@ -321,7 +291,7 @@ TEST(FaceRecognitionTest, RemoveAllLabelsShouldBeOk)
 		ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
 	}
 
-	for (auto& label : labels) {
+	for (auto &label : labels) {
 		ret = mv_face_recognition_unregister(handle, label.c_str());
 		ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
 	}
diff --git a/test/testsuites/machine_learning/inference/inference_test_suite.c b/test/testsuites/machine_learning/inference/inference_test_suite.c
index 135081b..8220ee7 100644
--- a/test/testsuites/machine_learning/inference/inference_test_suite.c
+++ b/test/testsuites/machine_learning/inference/inference_test_suite.c
@@ -35,93 +35,62 @@
 #define FILE_PATH_SIZE 1024
 
 //Image Classification
-#define IC_LABEL_PATH \
-	"/usr/share/capi-media-vision/models/IC/tflite/ic_label.txt"
-#define IC_TFLITE_WEIGHT_PATH \
-	"/usr/share/capi-media-vision/models/IC/tflite/ic_tflite_model.tflite"
-#define IC_Q_LABEL_PATH \
-	"/usr/share/capi-media-vision/models/IC_Q/tflite/ic_label.txt"
-#define IC_Q_TFLITE_WEIGHT_PATH \
-	"/usr/share/capi-media-vision/models/IC_Q/tflite/ic_tflite_model.tflite"
+#define IC_LABEL_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_label.txt"
+#define IC_TFLITE_WEIGHT_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_tflite_model.tflite"
+#define IC_Q_LABEL_PATH "/usr/share/capi-media-vision/models/IC_Q/tflite/ic_label.txt"
+#define IC_Q_TFLITE_WEIGHT_PATH "/usr/share/capi-media-vision/models/IC_Q/tflite/ic_tflite_model.tflite"
 
 /*
  * Hosted models
  */
-#define IC_LABEL_MOBILENET_V1_224_PATH\
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_mobilenet_v1_label.txt"
+#define IC_LABEL_MOBILENET_V1_224_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_mobilenet_v1_label.txt"
 #define IC_TFLITE_WEIGHT_MOBILENET_V1_224_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_mobilenet_v1_224x224.tflite"
+	"/usr/share/capi-media-vision/models/IC/tflite/ic_mobilenet_v1_224x224.tflite"
 #define IC_TFLITE_META_MOBILENET_V1_224_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_mobilenet_v1_224x224.json"
-#define IC_LABEL_MOBILENET_V2_224_PATH\
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_mobilenet_v2_label.txt"
+	"/usr/share/capi-media-vision/models/IC/tflite/ic_mobilenet_v1_224x224.json"
+#define IC_LABEL_MOBILENET_V2_224_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_mobilenet_v2_label.txt"
 #define IC_TFLITE_WEIGHT_MOBILENET_V2_224_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_mobilenet_v2_224x224.tflite"
+	"/usr/share/capi-media-vision/models/IC/tflite/ic_mobilenet_v2_224x224.tflite"
 #define IC_TFLITE_META_MOBILENET_V2_224_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_mobilenet_v2_224x224.json"
-#define IC_LABEL_DENSENET_224_PATH\
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_densenet_label.txt"
-#define IC_TFLITE_WEIGHT_DENSENET_224_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_densenet_224x224.tflite"
-#define IC_TFLITE_META_DENSENET_224_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_densenet_224x224.json"
-#define IC_LABEL_INCEPTION_RESENET_299_PATH\
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_densenet_label.txt"
+	"/usr/share/capi-media-vision/models/IC/tflite/ic_mobilenet_v2_224x224.json"
+#define IC_LABEL_DENSENET_224_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_densenet_label.txt"
+#define IC_TFLITE_WEIGHT_DENSENET_224_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_densenet_224x224.tflite"
+#define IC_TFLITE_META_DENSENET_224_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_densenet_224x224.json"
+#define IC_LABEL_INCEPTION_RESENET_299_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_densenet_label.txt"
 #define IC_TFLITE_WEIGHT_INCEPTION_RESENET_299_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_inception_resnet_v2_299x299.tflite"
-#define IC_LABEL_INCEPTION_V3_299_PATH\
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_inception_v3_label.txt"
+	"/usr/share/capi-media-vision/models/IC/tflite/ic_inception_resnet_v2_299x299.tflite"
+#define IC_LABEL_INCEPTION_V3_299_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_inception_v3_label.txt"
 #define IC_TFLITE_WEIGHT_INCEPTION_V3_299_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_inception_v3_299x299.tflite"
-#define IC_LABEL_INCEPTION_V4_299_PATH\
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_inception_v4_label.txt"
+	"/usr/share/capi-media-vision/models/IC/tflite/ic_inception_v3_299x299.tflite"
+#define IC_LABEL_INCEPTION_V4_299_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_inception_v4_label.txt"
 #define IC_TFLITE_WEIGHT_INCEPTION_V4_299_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_inception_v4_299x299.tflite"
-#define IC_LABEL_NASNET_224_PATH\
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_nasnet_label.txt"
-#define IC_TFLITE_WEIGHT_NASNET_224_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_nasnet_224x224.tflite"
-#define IC_TFLITE_META_NASNET_224_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_nasnet_224x224.json"
-#define IC_LABEL_MNASNET_224_PATH\
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_mnasnet_label.txt"
-#define IC_TFLITE_WEIGHT_MNASNET_224_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_mnasnet_224x224.tflite"
-#define IC_TFLITE_META_MNASNET_224_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_mnasnet_224x224.json"
-#define IC_LABEL_RESNET_V2_299_PATH\
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_resnet_v2_label.txt"
-#define IC_TFLITE_WEIGHT_RESNET_V2_299_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_resnet_v2_299x299.tflite"
-#define IC_LABEL_SQUEEZENET_224_PATH\
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_squeezenet_label.txt"
+	"/usr/share/capi-media-vision/models/IC/tflite/ic_inception_v4_299x299.tflite"
+#define IC_LABEL_NASNET_224_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_nasnet_label.txt"
+#define IC_TFLITE_WEIGHT_NASNET_224_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_nasnet_224x224.tflite"
+#define IC_TFLITE_META_NASNET_224_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_nasnet_224x224.json"
+#define IC_LABEL_MNASNET_224_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_mnasnet_label.txt"
+#define IC_TFLITE_WEIGHT_MNASNET_224_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_mnasnet_224x224.tflite"
+#define IC_TFLITE_META_MNASNET_224_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_mnasnet_224x224.json"
+#define IC_LABEL_RESNET_V2_299_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_resnet_v2_label.txt"
+#define IC_TFLITE_WEIGHT_RESNET_V2_299_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_resnet_v2_299x299.tflite"
+#define IC_LABEL_SQUEEZENET_224_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_squeezenet_label.txt"
 #define IC_TFLITE_WEIGHT_SQUEEZENET_224_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_squeezenet_224x224.tflite"
-#define IC_TFLITE_META_SQUEEZENET_224_PATH \
-       "/usr/share/capi-media-vision/models/IC/tflite/ic_squeezenet_224x224.json"
-
-#define IC_VIVANTE_LABEL_PATH \
-	"/usr/share/capi-media-vision/models/IC/vivante/ic_label.txt"
-#define IC_VIVANTE_WEIGHT_PATH \
-	"/usr/share/capi-media-vision/models/IC/vivante/ic_vivante_model.nb"
-#define IC_VIVANTE_CONFIG_PATH \
-	"/usr/share/capi-media-vision/models/IC/vivante/ic_vivante_model.so"
-
-#define IC_OPENCV_LABEL_CAFFE_PATH \
-	"/usr/share/capi-media-vision/models/IC/caffe/ic_caffe_label_squeezenet.txt"
-#define IC_OPENCV_WEIGHT_CAFFE_PATH \
-	"/usr/share/capi-media-vision/models/IC/caffe/ic_caffe_model_squeezenet.caffemodel"
-#define IC_OPENCV_CONFIG_CAFFE_PATH \
-	"/usr/share/capi-media-vision/models/IC/caffe/ic_caffe_model_squeezenet.prototxt"
+	"/usr/share/capi-media-vision/models/IC/tflite/ic_squeezenet_224x224.tflite"
+#define IC_TFLITE_META_SQUEEZENET_224_PATH "/usr/share/capi-media-vision/models/IC/tflite/ic_squeezenet_224x224.json"
+
+#define IC_VIVANTE_LABEL_PATH "/usr/share/capi-media-vision/models/IC/vivante/ic_label.txt"
+#define IC_VIVANTE_WEIGHT_PATH "/usr/share/capi-media-vision/models/IC/vivante/ic_vivante_model.nb"
+#define IC_VIVANTE_CONFIG_PATH "/usr/share/capi-media-vision/models/IC/vivante/ic_vivante_model.so"
+
+#define IC_OPENCV_LABEL_CAFFE_PATH "/usr/share/capi-media-vision/models/IC/caffe/ic_caffe_label_squeezenet.txt"
+#define IC_OPENCV_WEIGHT_CAFFE_PATH "/usr/share/capi-media-vision/models/IC/caffe/ic_caffe_model_squeezenet.caffemodel"
+#define IC_OPENCV_CONFIG_CAFFE_PATH "/usr/share/capi-media-vision/models/IC/caffe/ic_caffe_model_squeezenet.prototxt"
 
 //Object Detection
-#define OD_LABEL_PATH \
-	"/usr/share/capi-media-vision/models/OD/tflite/od_label.txt"
-#define OD_TFLITE_WEIGHT_PATH \
-	"/usr/share/capi-media-vision/models/OD/tflite/od_tflite_model.tflite"
+#define OD_LABEL_PATH "/usr/share/capi-media-vision/models/OD/tflite/od_label.txt"
+#define OD_TFLITE_WEIGHT_PATH "/usr/share/capi-media-vision/models/OD/tflite/od_tflite_model.tflite"
 
-#define OD_OPENCV_LABEL_CAFFE_PATH \
-	"/usr/share/capi-media-vision/models/OD/caffe/od_caffe_label_mobilenetv1ssd.txt"
+#define OD_OPENCV_LABEL_CAFFE_PATH "/usr/share/capi-media-vision/models/OD/caffe/od_caffe_label_mobilenetv1ssd.txt"
 #define OD_OPENCV_WEIGHT_CAFFE_PATH \
 	"/usr/share/capi-media-vision/models/OD/caffe/od_caffe_model_mobilenetv1ssd.caffemodel"
 #define OD_OPENCV_CONFIG_CAFFE_PATH \
@@ -136,33 +105,23 @@
 	"/usr/share/capi-media-vision/models/OD/tflite/od_mobilenet_v1_ssd_postop_300x300.tflite"
 #define OD_TFLITE_META_MOBILENET_V1_SSD_300_PATH \
 	"/usr/share/capi-media-vision/models/OD/tflite/od_mobilenet_v1_ssd_postop_300x300.json"
-#define OD_LABEL_MOBILENET_V2_SSD_320_PATH \
-	"/usr/share/capi-media-vision/models/OD/tflite/od_mobilenet_v2_ssd_label.txt"
+#define OD_LABEL_MOBILENET_V2_SSD_320_PATH "/usr/share/capi-media-vision/models/OD/tflite/od_mobilenet_v2_ssd_label.txt"
 #define OD_TFLITE_WEIGHT_MOBILENET_V2_SSD_320_PATH \
 	"/usr/share/capi-media-vision/models/OD/tflite/od_mobilenet_v2_ssd_320x320.tflite"
 #define OD_TFLITE_META_MOBILENET_V2_SSD_320_PATH \
 	"/usr/share/capi-media-vision/models/OD/tflite/od_mobilenet_v2_ssd_320x320.json"
-#define OD_LABEL_QUANT_EFFICIENT_PATH \
-	"/usr/share/capi-media-vision/models/OD/tflite/od_efficientdet_label.txt"
-#define OD_TFLITE_WEIGHT_QUANT_EFFICIENT_PATH \
-	"/usr/share/capi-media-vision/models/OD/tflite/od_efficientdet.tflite"
-#define OD_TFLITE_META_QUANT_EFFICIENT_PATH \
-	"/usr/share/capi-media-vision/models/OD/tflite/od_efficientdet.json"
-#define OD_TFLITE_WEIGHT_YOLO_V5_320_PATH \
-	"/usr/share/capi-media-vision/models/OD/tflite/od_yolo_v5_320x320.tflite"
-#define OD_TFLITE_META_YOLO_V5_320_PATH \
-	"/usr/share/capi-media-vision/models/OD/tflite/od_yolo_v5_320x320.json"
-#define OD_LABLE_YOLO_V5_320_PATH \
-	"/usr/share/capi-media-vision/models/OD/tflite/od_yolo_v5_label.txt"
+#define OD_LABEL_QUANT_EFFICIENT_PATH "/usr/share/capi-media-vision/models/OD/tflite/od_efficientdet_label.txt"
+#define OD_TFLITE_WEIGHT_QUANT_EFFICIENT_PATH "/usr/share/capi-media-vision/models/OD/tflite/od_efficientdet.tflite"
+#define OD_TFLITE_META_QUANT_EFFICIENT_PATH "/usr/share/capi-media-vision/models/OD/tflite/od_efficientdet.json"
+#define OD_TFLITE_WEIGHT_YOLO_V5_320_PATH "/usr/share/capi-media-vision/models/OD/tflite/od_yolo_v5_320x320.tflite"
+#define OD_TFLITE_META_YOLO_V5_320_PATH "/usr/share/capi-media-vision/models/OD/tflite/od_yolo_v5_320x320.json"
+#define OD_LABLE_YOLO_V5_320_PATH "/usr/share/capi-media-vision/models/OD/tflite/od_yolo_v5_label.txt"
 
 //Face Detection
-#define FD_TFLITE_WEIGHT_PATH \
-	"/usr/share/capi-media-vision/models/FD/tflite/fd_tflite_model1.tflite"
+#define FD_TFLITE_WEIGHT_PATH "/usr/share/capi-media-vision/models/FD/tflite/fd_tflite_model1.tflite"
 
-#define FD_OPENCV_WEIGHT_CAFFE_PATH \
-	"/usr/share/capi-media-vision/models/FD/caffe/fd_caffe_model_resnet10ssd.caffemodel"
-#define FD_OPENCV_CONFIG_CAFFE_PATH \
-	"/usr/share/capi-media-vision/models/FD/caffe/fd_caffe_model_resnet10ssd.prototxt"
+#define FD_OPENCV_WEIGHT_CAFFE_PATH "/usr/share/capi-media-vision/models/FD/caffe/fd_caffe_model_resnet10ssd.caffemodel"
+#define FD_OPENCV_CONFIG_CAFFE_PATH "/usr/share/capi-media-vision/models/FD/caffe/fd_caffe_model_resnet10ssd.prototxt"
 
 /*
  * Hosted models
@@ -173,51 +132,38 @@
 	"/usr/share/capi-media-vision/models/FD/tflite/fd_mobilenet_v1_ssd_postop_300x300.tflite"
 #define FD_TFLITE_META_MOBILENET_V1_SSD_300_PATH \
 	"/usr/share/capi-media-vision/models/FD/tflite/fd_mobilenet_v1_ssd_postop_300x300.json"
-#define FD_LABEL_BLAZEFACE_128_PATH \
-	"/usr/share/capi-media-vision/models/FD/tflite/fd_blazeface_front_label.txt"
+#define FD_LABEL_BLAZEFACE_128_PATH "/usr/share/capi-media-vision/models/FD/tflite/fd_blazeface_front_label.txt"
 #define FD_TFLITE_WEIGHT_BLAZEFACE_128_PATH \
 	"/usr/share/capi-media-vision/models/FD/tflite/fd_blazeface_front_128x128.tflite"
 #define FD_TFLITE_META_BLAZEFACE_128_PATH \
 	"/usr/share/capi-media-vision/models/FD/tflite/fd_blazeface_front_128x128.json"
 
 //Facial LandmarkDetection
-#define FLD_TFLITE_WEIGHT_PATH \
-	"/usr/share/capi-media-vision/models/FLD/tflite/fld_tflite_model1.tflite"
+#define FLD_TFLITE_WEIGHT_PATH "/usr/share/capi-media-vision/models/FLD/tflite/fld_tflite_model1.tflite"
 
-#define FLD_OPENCV_WEIGHT_CAFFE_PATH \
-	"/usr/share/capi-media-vision/models/FLD/caffe/fld_caffe_model_tweak.caffemodel"
-#define FLD_OPENCV_CONFIG_CAFFE_PATH \
-	"/usr/share/capi-media-vision/models/FLD/caffe/fld_caffe_model_tweak.prototxt"
+#define FLD_OPENCV_WEIGHT_CAFFE_PATH "/usr/share/capi-media-vision/models/FLD/caffe/fld_caffe_model_tweak.caffemodel"
+#define FLD_OPENCV_CONFIG_CAFFE_PATH "/usr/share/capi-media-vision/models/FLD/caffe/fld_caffe_model_tweak.prototxt"
 
 /*
  * Hosted models
  */
-#define FLD_TFLITE_WIEGHT_TWEAKCNN_128_PATH \
-	"/usr/share/capi-media-vision/models/FLD/tflite/fld_tweakcnn_128x128.tflite"
-#define FLD_TFLITE_META_TWEAKCNN_128_PATH \
-	"/usr/share/capi-media-vision/models/FLD/tflite/fld_tweakcnn_128x128.json"
+#define FLD_TFLITE_WIEGHT_TWEAKCNN_128_PATH "/usr/share/capi-media-vision/models/FLD/tflite/fld_tweakcnn_128x128.tflite"
+#define FLD_TFLITE_META_TWEAKCNN_128_PATH "/usr/share/capi-media-vision/models/FLD/tflite/fld_tweakcnn_128x128.json"
 #define FLD_TFLITE_WIEGHT_MEDIAPIPE_192_PATH \
 	"/usr/share/capi-media-vision/models/FLD/tflite/fld_mediapipe_192x192.tflite"
-#define FLD_TFLITE_META_MEDIAPIPE_192_PATH \
-	"/usr/share/capi-media-vision/models/FLD/tflite/fld_mediapipe_192x192.json"
+#define FLD_TFLITE_META_MEDIAPIPE_192_PATH "/usr/share/capi-media-vision/models/FLD/tflite/fld_mediapipe_192x192.json"
 
 //Pose Detection
-#define PLD_TFLITE_WEIGHT_PATH \
-	"/usr/share/capi-media-vision/models/PLD/tflite/pld-tflite-001.tflite"
-#define PLD_POSE_LABEL_PATH \
-	"/usr/share/capi-media-vision/models/PLD/tflite/pose-label.txt"
-#define PLD_MOTION_CAPTURE_FILE_PATH \
-	"/usr/share/capi-media-vision/models/PLD/mocap/example.bvh"
-#define PLD_MOTION_CAPTURE_MAPPING_FILE_PATH \
-	"/usr/share/capi-media-vision/models/PLD/mocap/example-mocap-mapping.txt"
+#define PLD_TFLITE_WEIGHT_PATH "/usr/share/capi-media-vision/models/PLD/tflite/pld-tflite-001.tflite"
+#define PLD_POSE_LABEL_PATH "/usr/share/capi-media-vision/models/PLD/tflite/pose-label.txt"
+#define PLD_MOTION_CAPTURE_FILE_PATH "/usr/share/capi-media-vision/models/PLD/mocap/example.bvh"
+#define PLD_MOTION_CAPTURE_MAPPING_FILE_PATH "/usr/share/capi-media-vision/models/PLD/mocap/example-mocap-mapping.txt"
 
 /*
  * Hosted models
  */
-#define PLD_TFLITE_WEIGHT_CPM_192_PATH \
-	"/usr/share/capi-media-vision/models/PLD/tflite/pld_cpm_192x192.tflite"
-#define PLD_TFLITE_META_CPM_192_PATH \
-	"/usr/share/capi-media-vision/models/PLD/tflite/pld_cpm_192x192.json"
+#define PLD_TFLITE_WEIGHT_CPM_192_PATH "/usr/share/capi-media-vision/models/PLD/tflite/pld_cpm_192x192.tflite"
+#define PLD_TFLITE_META_CPM_192_PATH "/usr/share/capi-media-vision/models/PLD/tflite/pld_cpm_192x192.json"
 
 #define PLD_TFLITE_WEIGHT_MOBILENET_V1_POSENET_257_PATH \
 	"/usr/share/capi-media-vision/models/PLD/tflite/pld_mobilenet_v1_posenet_multi_257x257.tflite"
@@ -227,8 +173,7 @@
 	"/usr/share/capi-media-vision/models/PLD/tflite/pld_mobilenet_v1_posenet_multi_label.txt"
 
 // https://tfhub.dev/google/lite-model/movenet/singlepose/lightning/tflite/int8/4
-#define PLD_TFLITE_WEIGHT_INT8_MOVENET_PATH \
-	"/usr/share/capi-media-vision/models/PLD/tflite/pld_int8_movenet.tflite"
+#define PLD_TFLITE_WEIGHT_INT8_MOVENET_PATH "/usr/share/capi-media-vision/models/PLD/tflite/pld_int8_movenet.tflite"
 
 #define PLD_TFLITE_WEIGHT_MOVENET_THUNDER3_256_FLOAT32_PATH \
 	"/usr/share/capi-media-vision/models/PLD/tflite/pld_movenet_thunder3_256x256.tflite"
@@ -296,30 +241,21 @@
 #define NANO_PER_MILLI ((__clock_t) 1000000)
 #define MILLI_PER_SEC ((__clock_t) 1000)
 
-int engine_config_hosted_tflite_cpu(mv_engine_config_h handle,
-									const char *tf_weight,
-									const char *meta_file)
+int engine_config_hosted_tflite_cpu(mv_engine_config_h handle, const char *tf_weight, const char *meta_file)
 {
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH, tf_weight));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_TFLITE));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH, tf_weight));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_TFLITE));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
 	if (meta_file != NULL)
-		RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_META_FILE_PATH, meta_file));
+		RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_META_FILE_PATH, meta_file));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
-int engine_config_user_hosted_tflite_cpu(mv_engine_config_h handle,
-										 const char *tf_weight,
-										 const char *user_file,
+int engine_config_user_hosted_tflite_cpu(mv_engine_config_h handle, const char *tf_weight, const char *user_file,
 										 const char *meta_file)
 {
 	RET_IF_FAIL(engine_config_hosted_tflite_cpu(handle, tf_weight, meta_file));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_USER_FILE_PATH, user_file));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_USER_FILE_PATH, user_file));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
@@ -341,10 +277,8 @@ unsigned long gettotalmillisec(const struct timespec time)
 	return time.tv_sec * MILLI_PER_SEC + time.tv_nsec / NANO_PER_MILLI;
 }
 
-void _object_detected_cb(mv_source_h source, const int number_of_objects,
-						 const int *indices, const char **names,
-						 const float *confidences,
-						 const mv_rectangle_s *locations, void *user_data)
+void _object_detected_cb(mv_source_h source, const int number_of_objects, const int *indices, const char **names,
+						 const float *confidences, const mv_rectangle_s *locations, void *user_data)
 {
 	printf("In callback: %d objects\n", number_of_objects);
 
@@ -352,27 +286,23 @@ void _object_detected_cb(mv_source_h source, const int number_of_objects,
 		printf("%2d\n", indices[n]);
 		printf("%s\n", names[n]);
 		printf("%.3f\n", confidences[n]);
-		printf("%d,%d,%d,%d\n", locations[n].point.x, locations[n].point.y,
-			   locations[n].width, locations[n].height);
+		printf("%d,%d,%d,%d\n", locations[n].point.x, locations[n].point.y, locations[n].width, locations[n].height);
 	}
 }
 
-void _face_detected_cb(mv_source_h source, const int number_of_faces,
-					   const float *confidences,
+void _face_detected_cb(mv_source_h source, const int number_of_faces, const float *confidences,
 					   const mv_rectangle_s *locations, void *user_data)
 {
 	printf("In callback: %d faces\n", number_of_faces);
 
 	for (int n = 0; n < number_of_faces; n++) {
 		printf("%.3f\n", confidences[n]);
-		printf("%d,%d,%d,%d\n", locations[n].point.x, locations[n].point.y,
-			   locations[n].width, locations[n].height);
+		printf("%d,%d,%d,%d\n", locations[n].point.x, locations[n].point.y, locations[n].width, locations[n].height);
 	}
 }
 
-void _facial_landmark_detected_cb(mv_source_h source,
-								  const int number_of_landmarks,
-								  const mv_point_s *locations, void *user_data)
+void _facial_landmark_detected_cb(mv_source_h source, const int number_of_landmarks, const mv_point_s *locations,
+								  void *user_data)
 {
 	printf("In callback, %d landmarks\n", number_of_landmarks);
 	for (int n = 0; n < number_of_landmarks; n++) {
@@ -380,22 +310,21 @@ void _facial_landmark_detected_cb(mv_source_h source,
 	}
 }
 
-void _pose_landmark_detected_cb(mv_source_h source,
-								  mv_inference_pose_result_h pose, void *user_data)
+void _pose_landmark_detected_cb(mv_source_h source, mv_inference_pose_result_h pose, void *user_data)
 {
 	int cb_number_of_poses = 0;
 	int cb_number_of_landmarks = 0;
 	mv_inference_pose_get_number_of_poses(pose, &cb_number_of_poses);
 	mv_inference_pose_get_number_of_landmarks(pose, &cb_number_of_landmarks);
-	printf("%d pose with %d landmarks\n",cb_number_of_poses, cb_number_of_landmarks);
+	printf("%d pose with %d landmarks\n", cb_number_of_poses, cb_number_of_landmarks);
 
 	mv_point_s point;
 	float score;
 	for (int k = 0; k < cb_number_of_poses; ++k)
-	for (int n = 0; n < cb_number_of_landmarks; n++) {
-		mv_inference_pose_get_landmark(pose, k, n, &point, &score);
-		printf("%d-%d: x[%d], y[%d] with %.4f\n", k, n, point.x, point.y, score);
-	}
+		for (int n = 0; n < cb_number_of_landmarks; n++) {
+			mv_inference_pose_get_landmark(pose, k, n, &point, &score);
+			printf("%d-%d: x[%d], y[%d] with %.4f\n", k, n, point.x, point.y, score);
+		}
 
 	mv_pose_h poser;
 	float poseScore;
@@ -405,18 +334,15 @@ void _pose_landmark_detected_cb(mv_source_h source,
 		return;
 	}
 
-	ret = mv_pose_set_from_file(poser,
-						PLD_MOTION_CAPTURE_FILE_PATH,
-						PLD_MOTION_CAPTURE_MAPPING_FILE_PATH);
+	ret = mv_pose_set_from_file(poser, PLD_MOTION_CAPTURE_FILE_PATH, PLD_MOTION_CAPTURE_MAPPING_FILE_PATH);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		mv_pose_destroy(poser);
 		printf("Fail to mv_pose_set_from_file");
 		return;
 	}
 
-	ret = mv_pose_compare(poser, pose,
-			(MV_INFERENCE_HUMAN_BODY_PART_LEG_LEFT | MV_INFERENCE_HUMAN_BODY_PART_LEG_RIGHT),
-			&poseScore);
+	ret = mv_pose_compare(poser, pose, (MV_INFERENCE_HUMAN_BODY_PART_LEG_LEFT | MV_INFERENCE_HUMAN_BODY_PART_LEG_RIGHT),
+						  &poseScore);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		mv_pose_destroy(poser);
 		printf("Fail to mv_pose_compare");
@@ -433,8 +359,7 @@ void _pose_landmark_detected_cb(mv_source_h source,
 	return;
 }
 
-void _image_classified_cb(mv_source_h source, const int number_of_classes,
-						  const int *indices, const char **names,
+void _image_classified_cb(mv_source_h source, const int number_of_classes, const int *indices, const char **names,
 						  const float *confidences, void *user_data)
 {
 	printf("In callback: %d classes\n", number_of_classes);
@@ -468,24 +393,19 @@ int infer_task_with_img(char *img_file_name, mv_inference_h infer, int task_id)
 
 	switch (task_id) {
 	case TASK_IC:
-		err = mv_inference_image_classify(mvSource, infer, NULL,
-										  _image_classified_cb, NULL);
+		err = mv_inference_image_classify(mvSource, infer, NULL, _image_classified_cb, NULL);
 		break;
 	case TASK_OD:
-		err = mv_inference_object_detect(mvSource, infer, _object_detected_cb,
-										 NULL);
+		err = mv_inference_object_detect(mvSource, infer, _object_detected_cb, NULL);
 		break;
 	case TASK_FD:
-		err = mv_inference_face_detect(mvSource, infer, _face_detected_cb,
-									   NULL);
+		err = mv_inference_face_detect(mvSource, infer, _face_detected_cb, NULL);
 		break;
 	case TASK_FLD:
-		err = mv_inference_facial_landmark_detect(
-				mvSource, infer, NULL, _facial_landmark_detected_cb, NULL);
+		err = mv_inference_facial_landmark_detect(mvSource, infer, NULL, _facial_landmark_detected_cb, NULL);
 		break;
 	case TASK_PLD:
-		err = mv_inference_pose_landmark_detect(
-				mvSource, infer, NULL, _pose_landmark_detected_cb, NULL);
+		err = mv_inference_pose_landmark_detect(mvSource, infer, NULL, _pose_landmark_detected_cb, NULL);
 		break;
 	default:
 		err = MEDIA_VISION_ERROR_INVALID_PARAMETER;
@@ -510,8 +430,7 @@ int infer_task(mv_inference_h infer, int task_id)
 {
 	char *in_file_name = NULL;
 	/* Load media source */
-	while (input_string("Input file name to be inferred:", 1024,
-						&(in_file_name)) == -1)
+	while (input_string("Input file name to be inferred:", 1024, &(in_file_name)) == -1)
 		printf("Incorrect input! Try again.\n");
 
 	int err = infer_task_with_img(in_file_name, infer, task_id);
@@ -557,13 +476,11 @@ int perform_configure_set_model_config_path(mv_engine_config_h engine_cfg)
 {
 	int err = MEDIA_VISION_ERROR_NONE;
 	char *filePath = NULL;
-	while (-1 == input_string("Model configuration file path:", FILE_PATH_SIZE,
-							  &(filePath))) {
+	while (-1 == input_string("Model configuration file path:", FILE_PATH_SIZE, &(filePath))) {
 		printf("Incorrect file path! Try again.\n");
 	}
 
-	err = mv_engine_config_set_string_attribute(
-			engine_cfg, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH, filePath);
+	err = mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH, filePath);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf("Fail to set model configuration file path: %s\n", filePath);
 	}
@@ -578,13 +495,11 @@ int perform_configure_set_model_weights_path(mv_engine_config_h engine_cfg)
 {
 	int err = MEDIA_VISION_ERROR_NONE;
 	char *filePath = NULL;
-	while (-1 == input_string("Model weights file path:", FILE_PATH_SIZE,
-							  &(filePath))) {
+	while (-1 == input_string("Model weights file path:", FILE_PATH_SIZE, &(filePath))) {
 		printf("Incorrect file path! Try again.\n");
 	}
 
-	err = mv_engine_config_set_string_attribute(
-			engine_cfg, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH, filePath);
+	err = mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH, filePath);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf("Fail to set model weights file path: %s\n", filePath);
 	}
@@ -603,9 +518,8 @@ int perform_configure_set_input_data_type(mv_engine_config_h engine_cfg)
 		printf("Invalid type! Try again.\n");
 	}
 
-	err = mv_engine_config_set_int_attribute(
-			engine_cfg, MV_INFERENCE_INPUT_DATA_TYPE,
-			(mv_inference_data_type_e) dataType);
+	err = mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_DATA_TYPE,
+											 (mv_inference_data_type_e) dataType);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf("Fail to set input tensor data type: %d\n", dataType);
 	}
@@ -617,13 +531,11 @@ int perform_configure_set_model_userfile_path(mv_engine_config_h engine_cfg)
 {
 	int err = MEDIA_VISION_ERROR_NONE;
 	char *filePath = NULL;
-	while (-1 == input_string("Model user file (category list) path:",
-							  FILE_PATH_SIZE, &(filePath))) {
+	while (-1 == input_string("Model user file (category list) path:", FILE_PATH_SIZE, &(filePath))) {
 		printf("Incorrect file path! Try again.\n");
 	}
 
-	err = mv_engine_config_set_string_attribute(
-			engine_cfg, MV_INFERENCE_MODEL_USER_FILE_PATH, filePath);
+	err = mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_MODEL_USER_FILE_PATH, filePath);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf("Fail to set model user file path: %s\n", filePath);
 	}
@@ -642,8 +554,7 @@ int perform_configure_set_model_mean_value(mv_engine_config_h engine_cfg)
 		printf("Invalid value! Try again.\n");
 	}
 
-	err = mv_engine_config_set_double_attribute(
-			engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, meanValue);
+	err = mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, meanValue);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf("Fail to set model mean value: %f\n", meanValue);
 	}
@@ -659,8 +570,7 @@ int perform_configure_set_image_scale(mv_engine_config_h engine_cfg)
 		printf("Invalid value! Try again.\n");
 	}
 
-	err = mv_engine_config_set_double_attribute(
-			engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, stdValue);
+	err = mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, stdValue);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf("Fail to set std value: %lf\n", stdValue);
 	}
@@ -676,8 +586,7 @@ int perform_configure_set_confidence_threshold(mv_engine_config_h engine_cfg)
 		printf("Invalid value! Try again.\n");
 	}
 
-	err = mv_engine_config_set_double_attribute(
-			engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, threshold);
+	err = mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, threshold);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf("Fail to set image scale value: %lf\n", threshold);
 	}
@@ -693,9 +602,8 @@ int perform_configure_set_backend(mv_engine_config_h engine_cfg)
 		printf("Invalid type! Try again.\n");
 	}
 
-	err = mv_engine_config_set_int_attribute(
-			engine_cfg, MV_INFERENCE_BACKEND_TYPE,
-			(mv_inference_backend_type_e) backendType);
+	err = mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_BACKEND_TYPE,
+											 (mv_inference_backend_type_e) backendType);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf("Fail to set backend type: %d\n", backendType);
 	}
@@ -711,9 +619,8 @@ int perform_configure_set_target(mv_engine_config_h engine_cfg)
 		printf("Invalid type! Try again.\n");
 	}
 
-	err = mv_engine_config_set_int_attribute(
-			engine_cfg, MV_INFERENCE_TARGET_TYPE,
-			(mv_inference_target_type_e) targetType);
+	err = mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_TARGET_TYPE,
+											 (mv_inference_target_type_e) targetType);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf("Fail to set target type: %d\n", targetType);
 	}
@@ -729,8 +636,7 @@ int perform_configure_set_tensor_width(mv_engine_config_h engine_cfg)
 		printf("Invalid value! Try again.\n");
 	}
 
-	err = mv_engine_config_set_int_attribute(
-			engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, tensorW);
+	err = mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, tensorW);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf("Fail to set tensor width: %d\n", tensorW);
 	}
@@ -746,8 +652,7 @@ int perform_configure_set_tensor_height(mv_engine_config_h engine_cfg)
 		printf("Invalid value! Try again.\n");
 	}
 
-	err = mv_engine_config_set_int_attribute(
-			engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, tensorH);
+	err = mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, tensorH);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf("Fail to set tensor height: %d\n", tensorH);
 	}
@@ -763,8 +668,7 @@ int perform_configure_set_tensor_channels(mv_engine_config_h engine_cfg)
 		printf("Invalid value! Try again.\n");
 	}
 
-	err = mv_engine_config_set_int_attribute(
-			engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, tensorC);
+	err = mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, tensorC);
 	if (err != MEDIA_VISION_ERROR_NONE) {
 		printf("Fail to set tensor channels: %d\n", tensorC);
 	}
@@ -778,18 +682,18 @@ int perform_configuration(mv_engine_config_h *engine_cfg)
 
 	int sel_opt = 0;
 	const char *names[] = { "Set Model Configuration",
-							  "Set Model Weights",
-							  "Set Model Data Type",
-							  "Set Model UserFile",
-							  "Set Model MeanFile",
-							  "Set Image Scale",
-							  "Set Confidence Threshold",
-							  "Set Backend",
-							  "Set Target",
-							  "Set InputTensor Width",
-							  "Set InputTensor Height",
-							  "Set InputTensor Channels",
-							  "Back" };
+							"Set Model Weights",
+							"Set Model Data Type",
+							"Set Model UserFile",
+							"Set Model MeanFile",
+							"Set Image Scale",
+							"Set Confidence Threshold",
+							"Set Backend",
+							"Set Target",
+							"Set InputTensor Width",
+							"Set InputTensor Height",
+							"Set InputTensor Channels",
+							"Back" };
 
 	mv_engine_config_h handle = NULL;
 	err = mv_create_engine_config(&handle);
@@ -873,33 +777,20 @@ int perform_tflite_mobilenetv1_config(mv_engine_config_h handle)
 	const char *inputNodeName = "input_2";
 	const char *outputNodeName[] = { "dense_3/Softmax" };
 
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
-			IC_TFLITE_WEIGHT_PATH));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_USER_FILE_PATH, IC_LABEL_PATH));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.0));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_STD_VALUE, 127.0));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.6));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_TFLITE));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 224));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 224));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
-	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(
-			handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
+	RET_IF_FAIL(
+			mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH, IC_TFLITE_WEIGHT_PATH));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_USER_FILE_PATH, IC_LABEL_PATH));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.0));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_STD_VALUE, 127.0));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.6));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_TFLITE));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 224));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 224));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
+	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
@@ -908,33 +799,20 @@ int perform_armnn_mobilenetv1_config(mv_engine_config_h handle)
 	const char *inputNodeName = "input_2";
 	const char *outputNodeName[] = { "dense_3/Softmax" };
 
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
-			IC_TFLITE_WEIGHT_PATH));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_USER_FILE_PATH, IC_LABEL_PATH));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.0));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_STD_VALUE, 127.0));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.6));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_ARMNN));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 224));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 224));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
-	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(
-			handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
+	RET_IF_FAIL(
+			mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH, IC_TFLITE_WEIGHT_PATH));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_USER_FILE_PATH, IC_LABEL_PATH));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.0));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_STD_VALUE, 127.0));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.6));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_ARMNN));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 224));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 224));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
+	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
@@ -943,33 +821,20 @@ int perform_one_mobilenetv1_quant_config(mv_engine_config_h handle)
 	const char *inputNodeName = "input";
 	const char *outputNodeName[] = { "MobilenetV1/Predictions/Reshape_1" };
 
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
-			IC_Q_TFLITE_WEIGHT_PATH));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_UINT8));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_USER_FILE_PATH, IC_Q_LABEL_PATH));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_MEAN_VALUE, 0.0));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_STD_VALUE, 1.0));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.6));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_ONE));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 224));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 224));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
-	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(
-			handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
+													  IC_Q_TFLITE_WEIGHT_PATH));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_UINT8));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_USER_FILE_PATH, IC_Q_LABEL_PATH));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_MEAN_VALUE, 0.0));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_STD_VALUE, 1.0));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.6));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_ONE));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 224));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 224));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
+	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
@@ -978,38 +843,25 @@ int perform_vivante_inceptionv3_config(mv_engine_config_h handle)
 	const char *inputNodeName = "input";
 	const char *outputNodeName[] = { "InceptionV3/Predictions/Peshape_1" };
 
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
-			IC_VIVANTE_WEIGHT_PATH));
-
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH,
-			IC_VIVANTE_CONFIG_PATH));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_UINT8));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_USER_FILE_PATH, IC_VIVANTE_LABEL_PATH));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_MEAN_VALUE, 0.0));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_STD_VALUE, 1.0));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.6));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_MLAPI));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_TARGET_DEVICE_TYPE,
-			MV_INFERENCE_TARGET_DEVICE_CUSTOM));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 299));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 299));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
-	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(
-			handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
+	RET_IF_FAIL(
+			mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH, IC_VIVANTE_WEIGHT_PATH));
+
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH,
+													  IC_VIVANTE_CONFIG_PATH));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_UINT8));
+	RET_IF_FAIL(
+			mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_USER_FILE_PATH, IC_VIVANTE_LABEL_PATH));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_MEAN_VALUE, 0.0));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_STD_VALUE, 1.0));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.6));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_MLAPI));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_TARGET_DEVICE_TYPE,
+												   MV_INFERENCE_TARGET_DEVICE_CUSTOM));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 299));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 299));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
+	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
@@ -1018,37 +870,23 @@ int perform_opencv_caffe_squeezenet_config(mv_engine_config_h handle)
 	const char *inputNodeName = "data";
 	const char *outputNodeName[] = { "prob" };
 
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
-			IC_OPENCV_WEIGHT_CAFFE_PATH));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH,
-			IC_OPENCV_CONFIG_CAFFE_PATH));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_USER_FILE_PATH,
-			IC_OPENCV_LABEL_CAFFE_PATH));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_MEAN_VALUE, 0.0));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_STD_VALUE, 1.0));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_OPENCV));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 227));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 227));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
-	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(
-			handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
+													  IC_OPENCV_WEIGHT_CAFFE_PATH));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH,
+													  IC_OPENCV_CONFIG_CAFFE_PATH));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_USER_FILE_PATH,
+													  IC_OPENCV_LABEL_CAFFE_PATH));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_MEAN_VALUE, 0.0));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_STD_VALUE, 1.0));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_OPENCV));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 227));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 227));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
+	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
@@ -1099,64 +937,46 @@ int perform_image_classification()
 		err = perform_vivante_inceptionv3_config(engine_cfg);
 	} break;
 	case 6: {
-		err = engine_config_user_hosted_tflite_cpu(
-				engine_cfg, IC_TFLITE_WEIGHT_MOBILENET_V1_224_PATH,
-				IC_LABEL_MOBILENET_V1_224_PATH,
-				IC_TFLITE_META_MOBILENET_V1_224_PATH);
+		err = engine_config_user_hosted_tflite_cpu(engine_cfg, IC_TFLITE_WEIGHT_MOBILENET_V1_224_PATH,
+												   IC_LABEL_MOBILENET_V1_224_PATH,
+												   IC_TFLITE_META_MOBILENET_V1_224_PATH);
 	} break;
 	case 7: {
-		err = engine_config_user_hosted_tflite_cpu(
-				engine_cfg, IC_TFLITE_WEIGHT_MOBILENET_V2_224_PATH,
-				IC_LABEL_MOBILENET_V2_224_PATH,
-				IC_TFLITE_META_MOBILENET_V2_224_PATH);
+		err = engine_config_user_hosted_tflite_cpu(engine_cfg, IC_TFLITE_WEIGHT_MOBILENET_V2_224_PATH,
+												   IC_LABEL_MOBILENET_V2_224_PATH,
+												   IC_TFLITE_META_MOBILENET_V2_224_PATH);
 	} break;
 	case 8: {
-		err = engine_config_user_hosted_tflite_cpu(
-				engine_cfg, IC_TFLITE_WEIGHT_DENSENET_224_PATH,
-				IC_LABEL_DENSENET_224_PATH,
-				IC_TFLITE_META_DENSENET_224_PATH);
+		err = engine_config_user_hosted_tflite_cpu(engine_cfg, IC_TFLITE_WEIGHT_DENSENET_224_PATH,
+												   IC_LABEL_DENSENET_224_PATH, IC_TFLITE_META_DENSENET_224_PATH);
 	} break;
 	case 9: {
-		err = engine_config_user_hosted_tflite_cpu(
-				engine_cfg, IC_TFLITE_WEIGHT_INCEPTION_RESENET_299_PATH,
-				IC_LABEL_INCEPTION_RESENET_299_PATH,
-				NULL);
+		err = engine_config_user_hosted_tflite_cpu(engine_cfg, IC_TFLITE_WEIGHT_INCEPTION_RESENET_299_PATH,
+												   IC_LABEL_INCEPTION_RESENET_299_PATH, NULL);
 	} break;
 	case 10: {
-		err = engine_config_user_hosted_tflite_cpu(
-				engine_cfg, IC_TFLITE_WEIGHT_INCEPTION_V3_299_PATH,
-				IC_LABEL_INCEPTION_V3_299_PATH,
-				NULL);
+		err = engine_config_user_hosted_tflite_cpu(engine_cfg, IC_TFLITE_WEIGHT_INCEPTION_V3_299_PATH,
+												   IC_LABEL_INCEPTION_V3_299_PATH, NULL);
 	} break;
 	case 11: {
-		err = engine_config_user_hosted_tflite_cpu(
-				engine_cfg, IC_TFLITE_WEIGHT_INCEPTION_V4_299_PATH,
-				IC_LABEL_INCEPTION_V4_299_PATH,
-				NULL);
+		err = engine_config_user_hosted_tflite_cpu(engine_cfg, IC_TFLITE_WEIGHT_INCEPTION_V4_299_PATH,
+												   IC_LABEL_INCEPTION_V4_299_PATH, NULL);
 	} break;
 	case 12: {
-		err = engine_config_user_hosted_tflite_cpu(
-				engine_cfg, IC_TFLITE_WEIGHT_NASNET_224_PATH,
-				IC_LABEL_NASNET_224_PATH,
-				IC_TFLITE_META_NASNET_224_PATH);
+		err = engine_config_user_hosted_tflite_cpu(engine_cfg, IC_TFLITE_WEIGHT_NASNET_224_PATH,
+												   IC_LABEL_NASNET_224_PATH, IC_TFLITE_META_NASNET_224_PATH);
 	} break;
 	case 13: {
-		err = engine_config_user_hosted_tflite_cpu(
-				engine_cfg, IC_TFLITE_WEIGHT_MNASNET_224_PATH,
-				IC_LABEL_MNASNET_224_PATH,
-				IC_TFLITE_META_MOBILENET_V2_224_PATH);
+		err = engine_config_user_hosted_tflite_cpu(engine_cfg, IC_TFLITE_WEIGHT_MNASNET_224_PATH,
+												   IC_LABEL_MNASNET_224_PATH, IC_TFLITE_META_MOBILENET_V2_224_PATH);
 	} break;
 	case 14: {
-		err = engine_config_user_hosted_tflite_cpu(
-				engine_cfg, IC_TFLITE_WEIGHT_RESNET_V2_299_PATH,
-				IC_LABEL_RESNET_V2_299_PATH,
-				NULL);
+		err = engine_config_user_hosted_tflite_cpu(engine_cfg, IC_TFLITE_WEIGHT_RESNET_V2_299_PATH,
+												   IC_LABEL_RESNET_V2_299_PATH, NULL);
 	} break;
 	case 15: {
-		err = engine_config_user_hosted_tflite_cpu(
-				engine_cfg, IC_TFLITE_WEIGHT_SQUEEZENET_224_PATH,
-				IC_LABEL_SQUEEZENET_224_PATH,
-				IC_TFLITE_META_SQUEEZENET_224_PATH);
+		err = engine_config_user_hosted_tflite_cpu(engine_cfg, IC_TFLITE_WEIGHT_SQUEEZENET_224_PATH,
+												   IC_LABEL_SQUEEZENET_224_PATH, IC_TFLITE_META_SQUEEZENET_224_PATH);
 	} break;
 	}
 	if (err != MEDIA_VISION_ERROR_NONE) {
@@ -1181,38 +1001,23 @@ clean_image_engine:
 int perform_tflite_mobilenetv1ssd_config(mv_engine_config_h handle)
 {
 	const char *inputNodeName = "normalized_input_image_tensor";
-	const char *outputNodeName[] = { "TFLite_Detection_PostProcess",
-									 "TFLite_Detection_PostProcess:1",
-									 "TFLite_Detection_PostProcess:2",
-									 "TFLite_Detection_PostProcess:3" };
-
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
-			OD_TFLITE_WEIGHT_PATH));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_USER_FILE_PATH, OD_LABEL_PATH));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_STD_VALUE, 127.5));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_TFLITE));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
-	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(
-			handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 4));
+	const char *outputNodeName[] = { "TFLite_Detection_PostProcess", "TFLite_Detection_PostProcess:1",
+									 "TFLite_Detection_PostProcess:2", "TFLite_Detection_PostProcess:3" };
+
+	RET_IF_FAIL(
+			mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH, OD_TFLITE_WEIGHT_PATH));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_USER_FILE_PATH, OD_LABEL_PATH));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_STD_VALUE, 127.5));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_TFLITE));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
+	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 4));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
@@ -1221,75 +1026,46 @@ int perform_opencv_mobilenetv1ssd_config(mv_engine_config_h handle)
 	const char *inputNodeName = "data";
 	const char *outputNodeName[1] = { "detection_out" };
 
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
-			OD_OPENCV_WEIGHT_CAFFE_PATH));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH,
-			OD_OPENCV_CONFIG_CAFFE_PATH));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_USER_FILE_PATH,
-			OD_OPENCV_LABEL_CAFFE_PATH));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_STD_VALUE, 127.5));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_OPENCV));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
-	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(
-			handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
+													  OD_OPENCV_WEIGHT_CAFFE_PATH));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH,
+													  OD_OPENCV_CONFIG_CAFFE_PATH));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_USER_FILE_PATH,
+													  OD_OPENCV_LABEL_CAFFE_PATH));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_STD_VALUE, 127.5));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_OPENCV));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
+	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
 int perform_armnn_mobilenetv1ssd_config(mv_engine_config_h handle)
 {
 	const char *inputNodeName = "normalized_input_image_tensor";
-	const char *outputNodeName[] = { "TFLite_Detection_PostProcess",
-									 "TFLite_Detection_PostProcess:1",
-									 "TFLite_Detection_PostProcess:2",
-									 "TFLite_Detection_PostProcess:3" };
-
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
-			OD_TFLITE_WEIGHT_PATH));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_USER_FILE_PATH, OD_LABEL_PATH));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_STD_VALUE, 127.5));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_ARMNN));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
-	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(
-			handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 4));
+	const char *outputNodeName[] = { "TFLite_Detection_PostProcess", "TFLite_Detection_PostProcess:1",
+									 "TFLite_Detection_PostProcess:2", "TFLite_Detection_PostProcess:3" };
+
+	RET_IF_FAIL(
+			mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH, OD_TFLITE_WEIGHT_PATH));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_USER_FILE_PATH, OD_LABEL_PATH));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_STD_VALUE, 127.5));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_ARMNN));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
+	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 4));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
@@ -1297,15 +1073,13 @@ int perform_object_detection()
 {
 	int err = MEDIA_VISION_ERROR_NONE;
 	mv_engine_config_h engine_cfg = NULL;
-	const char *names[] = {
-		"TFLITE(CPU) + MobileNetV1+SSD",
-		"OPENCV(CPU) + MobileNetV1+SSD",
-		"ARMNN(CPU) + MobileNetV1+SSD",
-		"Hosted[o]: TFLite(cpu + MobilenetV1+SSD)",
-		"Hosted[o]: TFLite(cpu + MobilenetV2+SSD)",
-		"Hosted[o]: TFLite(Quant + EfficientDet)",
-		"Hosted[o]: TFLite(cpu + YoloV5)"
-	};
+	const char *names[] = { "TFLITE(CPU) + MobileNetV1+SSD",
+							"OPENCV(CPU) + MobileNetV1+SSD",
+							"ARMNN(CPU) + MobileNetV1+SSD",
+							"Hosted[o]: TFLite(cpu + MobilenetV1+SSD)",
+							"Hosted[o]: TFLite(cpu + MobilenetV2+SSD)",
+							"Hosted[o]: TFLite(Quant + EfficientDet)",
+							"Hosted[o]: TFLite(cpu + YoloV5)" };
 
 	int sel_opt = show_menu_linear("Select Action:", names, ARRAY_SIZE(names));
 	if (sel_opt <= 0 || sel_opt > ARRAY_SIZE(names)) {
@@ -1326,28 +1100,22 @@ int perform_object_detection()
 		err = perform_armnn_mobilenetv1ssd_config(engine_cfg);
 	} break;
 	case 4: {
-		err = engine_config_user_hosted_tflite_cpu(
-				engine_cfg, OD_TFLITE_WEIGHT_MOBILENET_V1_SSD_300_PATH,
-				OD_LABEL_MOBILENET_V1_SSD_300_PATH,
-				OD_TFLITE_META_MOBILENET_V1_SSD_300_PATH);
+		err = engine_config_user_hosted_tflite_cpu(engine_cfg, OD_TFLITE_WEIGHT_MOBILENET_V1_SSD_300_PATH,
+												   OD_LABEL_MOBILENET_V1_SSD_300_PATH,
+												   OD_TFLITE_META_MOBILENET_V1_SSD_300_PATH);
 	} break;
 	case 5: {
-		err = engine_config_user_hosted_tflite_cpu(
-				engine_cfg, OD_TFLITE_WEIGHT_MOBILENET_V2_SSD_320_PATH,
-				OD_LABEL_MOBILENET_V2_SSD_320_PATH,
-				OD_TFLITE_META_MOBILENET_V2_SSD_320_PATH);
+		err = engine_config_user_hosted_tflite_cpu(engine_cfg, OD_TFLITE_WEIGHT_MOBILENET_V2_SSD_320_PATH,
+												   OD_LABEL_MOBILENET_V2_SSD_320_PATH,
+												   OD_TFLITE_META_MOBILENET_V2_SSD_320_PATH);
 	} break;
 	case 6: {
-		err = engine_config_user_hosted_tflite_cpu(
-				engine_cfg, OD_TFLITE_WEIGHT_QUANT_EFFICIENT_PATH,
-				OD_LABEL_QUANT_EFFICIENT_PATH,
-				OD_TFLITE_META_QUANT_EFFICIENT_PATH);
+		err = engine_config_user_hosted_tflite_cpu(engine_cfg, OD_TFLITE_WEIGHT_QUANT_EFFICIENT_PATH,
+												   OD_LABEL_QUANT_EFFICIENT_PATH, OD_TFLITE_META_QUANT_EFFICIENT_PATH);
 	} break;
 	case 7: {
-		err = engine_config_user_hosted_tflite_cpu(
-				engine_cfg, OD_TFLITE_WEIGHT_YOLO_V5_320_PATH,
-				OD_LABLE_YOLO_V5_320_PATH,
-				OD_TFLITE_META_YOLO_V5_320_PATH);
+		err = engine_config_user_hosted_tflite_cpu(engine_cfg, OD_TFLITE_WEIGHT_YOLO_V5_320_PATH,
+												   OD_LABLE_YOLO_V5_320_PATH, OD_TFLITE_META_YOLO_V5_320_PATH);
 	} break;
 	}
 	if (err != MEDIA_VISION_ERROR_NONE) {
@@ -1367,30 +1135,19 @@ clean_object_detect_engine:
 int perform_tflite_mobilenetv1ssd_face(mv_engine_config_h handle)
 {
 	const char *inputNodeName = "normalized_input_image_tensor";
-	const char *outputNodeName[] = { "TFLite_Detection_PostProcess",
-									 "TFLite_Detection_PostProcess:1",
-									 "TFLite_Detection_PostProcess:2",
-									 "TFLite_Detection_PostProcess:3" };
+	const char *outputNodeName[] = { "TFLite_Detection_PostProcess", "TFLite_Detection_PostProcess:1",
+									 "TFLite_Detection_PostProcess:2", "TFLite_Detection_PostProcess:3" };
 
 	RET_IF_FAIL(engine_config_hosted_tflite_cpu(handle, FD_TFLITE_WEIGHT_PATH, NULL));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_STD_VALUE, 127.5));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
-	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(
-			handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 4));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_STD_VALUE, 127.5));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
+	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 4));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
@@ -1399,70 +1156,43 @@ int perform_opencv_resnet10ssd_face(mv_engine_config_h handle)
 	const char *inputNodeName = "data";
 	const char *outputNodeName[] = { "detection_out" };
 
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
-			FD_OPENCV_WEIGHT_CAFFE_PATH));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH,
-			FD_OPENCV_CONFIG_CAFFE_PATH));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_MEAN_VALUE, 135.7));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_STD_VALUE, 1.0));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_OPENCV));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
-	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(
-			handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
+													  FD_OPENCV_WEIGHT_CAFFE_PATH));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH,
+													  FD_OPENCV_CONFIG_CAFFE_PATH));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_MEAN_VALUE, 135.7));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_STD_VALUE, 1.0));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_OPENCV));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
+	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
 int perform_armnn_mobilenetv1ssd_face(mv_engine_config_h handle)
 {
 	const char *inputNodeName = "normalized_input_image_tensor";
-	const char *outputNodeName[] = { "TFLite_Detection_PostProcess",
-									 "TFLite_Detection_PostProcess:1",
-									 "TFLite_Detection_PostProcess:2",
-									 "TFLite_Detection_PostProcess:3" };
-
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
-			FD_TFLITE_WEIGHT_PATH));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_STD_VALUE, 127.5));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_ARMNN));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
-	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(
-			handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 4));
+	const char *outputNodeName[] = { "TFLite_Detection_PostProcess", "TFLite_Detection_PostProcess:1",
+									 "TFLite_Detection_PostProcess:2", "TFLite_Detection_PostProcess:3" };
+
+	RET_IF_FAIL(
+			mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH, FD_TFLITE_WEIGHT_PATH));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_STD_VALUE, 127.5));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_ARMNN));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
+	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 4));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
@@ -1471,10 +1201,8 @@ int perform_face_detection()
 	int err = MEDIA_VISION_ERROR_NONE;
 	mv_engine_config_h engine_cfg = NULL;
 	const char *names[] = {
-		"TFLite(CPU) + MobileNetV1 + SSD",
-		"OPENCV(CPU) + Resnet10 + SSD",
-		"ARMNN(CPU) + MobileNetV1 + SSD",
-		"Hosted[o]: TFLite(cpu + MobilenetV1+SSD)",
+		"TFLite(CPU) + MobileNetV1 + SSD",	  "OPENCV(CPU) + Resnet10 + SSD",
+		"ARMNN(CPU) + MobileNetV1 + SSD",	  "Hosted[o]: TFLite(cpu + MobilenetV1+SSD)",
 		"Hosted[o]: TFLite(cpu + BlazeFace)",
 	};
 
@@ -1497,14 +1225,12 @@ int perform_face_detection()
 		err = perform_armnn_mobilenetv1ssd_face(engine_cfg);
 	} break;
 	case 4: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, FD_TFLITE_WEIGHT_MOBILENET_V1_SSD_300_PATH,
-				FD_TFLITE_META_MOBILENET_V1_SSD_300_PATH);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, FD_TFLITE_WEIGHT_MOBILENET_V1_SSD_300_PATH,
+											  FD_TFLITE_META_MOBILENET_V1_SSD_300_PATH);
 	} break;
 	case 5: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, FD_TFLITE_WEIGHT_BLAZEFACE_128_PATH,
-				FD_TFLITE_META_BLAZEFACE_128_PATH);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, FD_TFLITE_WEIGHT_BLAZEFACE_128_PATH,
+											  FD_TFLITE_META_BLAZEFACE_128_PATH);
 	} break;
 	}
 	if (err != MEDIA_VISION_ERROR_NONE) {
@@ -1526,24 +1252,15 @@ int perform_tflite_TweakCNN(mv_engine_config_h handle)
 	const char *inputNodeName = "INPUT_TENSOR_NAME";
 	const char *outputNodeName[] = { "OUTPUT_TENSOR_NAME" };
 
-	RET_IF_FAIL(
-			engine_config_hosted_tflite_cpu(handle, FLD_TFLITE_WEIGHT_PATH, NULL));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_MEAN_VALUE, 0.0));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_STD_VALUE, 1.0));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 128));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 128));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
-	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(
-			handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
+	RET_IF_FAIL(engine_config_hosted_tflite_cpu(handle, FLD_TFLITE_WEIGHT_PATH, NULL));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_MEAN_VALUE, 0.0));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_STD_VALUE, 1.0));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 128));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 128));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
+	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
@@ -1552,32 +1269,20 @@ int perform_opencv_cnncascade(mv_engine_config_h handle)
 	const char *inputNodeName = "data";
 	const char *outputNodeName[] = { "Sigmoid_fc2" };
 
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
-			FLD_OPENCV_WEIGHT_CAFFE_PATH));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH,
-			FLD_OPENCV_CONFIG_CAFFE_PATH));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_STD_VALUE, 127.5));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_OPENCV));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 128));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 128));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
-	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(
-			handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
+													  FLD_OPENCV_WEIGHT_CAFFE_PATH));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH,
+													  FLD_OPENCV_CONFIG_CAFFE_PATH));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_STD_VALUE, 127.5));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_OPENCV));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 128));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 128));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
+	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
@@ -1608,14 +1313,12 @@ int perform_facial_landmark_detection()
 		err = perform_opencv_cnncascade(engine_cfg);
 	} break;
 	case 3: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, FLD_TFLITE_WIEGHT_TWEAKCNN_128_PATH,
-				FLD_TFLITE_META_TWEAKCNN_128_PATH);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, FLD_TFLITE_WIEGHT_TWEAKCNN_128_PATH,
+											  FLD_TFLITE_META_TWEAKCNN_128_PATH);
 	} break;
 	case 4: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, FLD_TFLITE_WIEGHT_MEDIAPIPE_192_PATH,
-				FLD_TFLITE_META_MEDIAPIPE_192_PATH);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, FLD_TFLITE_WIEGHT_MEDIAPIPE_192_PATH,
+											  FLD_TFLITE_META_MEDIAPIPE_192_PATH);
 	} break;
 	}
 	if (err != MEDIA_VISION_ERROR_NONE) {
@@ -1637,28 +1340,17 @@ int perform_armnn_cpm_config(mv_engine_config_h handle)
 	const char *inputNodeName = "image";
 	const char *outputNodeName[] = { "Convolutional_Pose_Machine/stage_5_out" };
 
-	RET_IF_FAIL(
-			engine_config_hosted_tflite_cpu(handle, PLD_TFLITE_WEIGHT_PATH, NULL));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_MODEL_USER_FILE_PATH, PLD_POSE_LABEL_PATH));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_MEAN_VALUE, 0.0));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_MODEL_STD_VALUE, 1.0));
-	RET_IF_FAIL(mv_engine_config_set_double_attribute(
-			handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 192));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 192));
-	RET_IF_FAIL(mv_engine_config_set_int_attribute(
-			handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
-	RET_IF_FAIL(mv_engine_config_set_string_attribute(
-			handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
-	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(
-			handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
+	RET_IF_FAIL(engine_config_hosted_tflite_cpu(handle, PLD_TFLITE_WEIGHT_PATH, NULL));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_USER_FILE_PATH, PLD_POSE_LABEL_PATH));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_MEAN_VALUE, 0.0));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_MODEL_STD_VALUE, 1.0));
+	RET_IF_FAIL(mv_engine_config_set_double_attribute(handle, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_WIDTH, 192));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 192));
+	RET_IF_FAIL(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3));
+	RET_IF_FAIL(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName));
+	RET_IF_FAIL(mv_engine_config_set_array_string_attribute(handle, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName, 1));
 	return MEDIA_VISION_ERROR_NONE;
 }
 
@@ -1698,59 +1390,46 @@ int perform_pose_landmark_detection()
 		err = perform_armnn_cpm_config(engine_cfg);
 	} break;
 	case 2: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, PLD_TFLITE_WEIGHT_CPM_192_PATH,
-				PLD_TFLITE_META_CPM_192_PATH);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, PLD_TFLITE_WEIGHT_CPM_192_PATH, PLD_TFLITE_META_CPM_192_PATH);
 	} break;
 	case 3: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, PLD_TFLITE_WEIGHT_MOBILENET_V1_POSENET_257_PATH,
-				PLD_TFLITE_META_MOBILENET_V1_POSENET_257_PATH);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, PLD_TFLITE_WEIGHT_MOBILENET_V1_POSENET_257_PATH,
+											  PLD_TFLITE_META_MOBILENET_V1_POSENET_257_PATH);
 	} break;
 	case 4: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, PLD_TFLITE_WEIGHT_INT8_MOVENET_PATH,
-				NULL);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, PLD_TFLITE_WEIGHT_INT8_MOVENET_PATH, NULL);
 	} break;
 	case 5: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_THUNDER3_256_FLOAT32_PATH,
-				PLD_TFLITE_META_MOVENET_THUNDER3_256_FLOAT32_PATH);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_THUNDER3_256_FLOAT32_PATH,
+											  PLD_TFLITE_META_MOVENET_THUNDER3_256_FLOAT32_PATH);
 	} break;
 	case 6: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_LIGHTNING3_192_FLOAT32_PATH,
-				PLD_TFLITE_META_MOVENET_LIGHTNING3_192_FLOAT32_PATH);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_LIGHTNING3_192_FLOAT32_PATH,
+											  PLD_TFLITE_META_MOVENET_LIGHTNING3_192_FLOAT32_PATH);
 	} break;
 	case 7: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_THUNDER3_256_INT8_QUANT_PATH,
-				PLD_TFLITE_META_MOVENET_THUNDER3_256_INT8_QUANT_PATH);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_THUNDER3_256_INT8_QUANT_PATH,
+											  PLD_TFLITE_META_MOVENET_THUNDER3_256_INT8_QUANT_PATH);
 	} break;
 	case 8: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_LIGHTNING3_192_INT8_QUANT_PATH,
-				PLD_TFLITE_META_MOVENET_LIGHTNING3_192_INT8_QUANT_PATH);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_LIGHTNING3_192_INT8_QUANT_PATH,
+											  PLD_TFLITE_META_MOVENET_LIGHTNING3_192_INT8_QUANT_PATH);
 	} break;
 	case 9: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_THUNDER4_256_FLOAT32_PATH,
-				PLD_TFLITE_META_MOVENET_THUNDER4_256_FLOAT32_PATH);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_THUNDER4_256_FLOAT32_PATH,
+											  PLD_TFLITE_META_MOVENET_THUNDER4_256_FLOAT32_PATH);
 	} break;
 	case 10: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_LIGHTNING4_192_FLOAT32_PATH,
-				PLD_TFLITE_META_MOVENET_LIGHTNING4_192_FLOAT32_PATH);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_LIGHTNING4_192_FLOAT32_PATH,
+											  PLD_TFLITE_META_MOVENET_LIGHTNING4_192_FLOAT32_PATH);
 	} break;
 	case 11: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_THUNDER4_256_INT8_QUANT_PATH,
-				PLD_TFLITE_META_MOVENET_THUNDER4_256_INT8_QUANT_PATH);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_THUNDER4_256_INT8_QUANT_PATH,
+											  PLD_TFLITE_META_MOVENET_THUNDER4_256_INT8_QUANT_PATH);
 	} break;
 	case 12: {
-		err = engine_config_hosted_tflite_cpu(
-				engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_LIGHTNING4_192_INT8_QUANT_PATH,
-				PLD_TFLITE_META_MOVENET_LIGHTNING4_192_INT8_QUANT_PATH);
+		err = engine_config_hosted_tflite_cpu(engine_cfg, PLD_TFLITE_WEIGHT_MOVENET_LIGHTNING4_192_INT8_QUANT_PATH,
+											  PLD_TFLITE_META_MOVENET_LIGHTNING4_192_INT8_QUANT_PATH);
 	} break;
 	}
 	if (err != MEDIA_VISION_ERROR_NONE) {
@@ -1771,8 +1450,7 @@ clean_pose_engine:
 int main()
 {
 	int err = MEDIA_VISION_ERROR_NONE;
-	const char *names[] = { "Image Classification", "Object Detection",
-							"Face Detection", "Facial Landmark Detection",
+	const char *names[] = { "Image Classification", "Object Detection", "Face Detection", "Facial Landmark Detection",
 							"Pose Landmark Detection" };
 
 	int sel_opt = show_menu_linear("Select Action:", names, ARRAY_SIZE(names));
diff --git a/test/testsuites/machine_learning/inference/test_face_detection.cpp b/test/testsuites/machine_learning/inference/test_face_detection.cpp
index 4e405e7..47ef375 100644
--- a/test/testsuites/machine_learning/inference/test_face_detection.cpp
+++ b/test/testsuites/machine_learning/inference/test_face_detection.cpp
@@ -13,8 +13,7 @@
 	MV_CONFIG_PATH \
 	"/res/inference/images/faceDetection.jpg"
 
-void _face_detected_cb(mv_source_h source, const int number_of_faces,
-					   const float *confidences,
+void _face_detected_cb(mv_source_h source, const int number_of_faces, const float *confidences,
 					   const mv_rectangle_s *locations, void *user_data)
 {
 	EXPECT_GT(number_of_faces, 0);
@@ -27,51 +26,43 @@ public:
 	{
 		TestInference::ConfigureInference();
 
-		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(
-						  IMG_FACE, mv_source),
-				  MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_inference_face_detect(mv_source, infer, _face_detected_cb,
-										   NULL),
-				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(IMG_FACE, mv_source), MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_inference_face_detect(mv_source, infer, _face_detected_cb, NULL), MEDIA_VISION_ERROR_NONE);
 	}
 };
 
 TEST_P(TestFaceDetectionTflite, MobilenetV1_SSD)
 {
-	engine_config_hosted_tflite_model(engine_cfg, FD_TFLITE_WEIGHT_MOBILENET_V1_SSD_300_PATH,
-									  NULL, _use_json_parser, _target_device_type);
+	engine_config_hosted_tflite_model(engine_cfg, FD_TFLITE_WEIGHT_MOBILENET_V1_SSD_300_PATH, NULL, _use_json_parser,
+									  _target_device_type);
 	if (!_use_json_parser) {
 		const char *inputNodeName = "normalized_input_image_tensor";
-		const char *outputNodeName[] = { "TFLite_Detection_PostProcess",
-											"TFLite_Detection_PostProcess:1",
-											"TFLite_Detection_PostProcess:2",
-											"TFLite_Detection_PostProcess:3" };
+		const char *outputNodeName[] = { "TFLite_Detection_PostProcess", "TFLite_Detection_PostProcess:1",
+										 "TFLite_Detection_PostProcess:2", "TFLite_Detection_PostProcess:3" };
 
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME,
-														inputNodeName), MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName),
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_array_string_attribute(engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
-																outputNodeName, 4), MEDIA_VISION_ERROR_NONE);
+															  outputNodeName, 4),
+				  MEDIA_VISION_ERROR_NONE);
 	}
 
 	inferenceFace();
 }
 
 INSTANTIATE_TEST_CASE_P(Prefix, TestFaceDetectionTflite,
-						::testing::Values(
-							ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
-							ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU)
-						)
-);
\ No newline at end of file
+						::testing::Values(ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
+										  ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU)));
\ No newline at end of file
diff --git a/test/testsuites/machine_learning/inference/test_face_landmark_detection.cpp b/test/testsuites/machine_learning/inference/test_face_landmark_detection.cpp
index f528619..aa6ce88 100644
--- a/test/testsuites/machine_learning/inference/test_face_landmark_detection.cpp
+++ b/test/testsuites/machine_learning/inference/test_face_landmark_detection.cpp
@@ -12,9 +12,8 @@
 	MV_CONFIG_PATH        \
 	"/res/inference/images/faceLandmark.jpg"
 
-void _facial_landmark_detected_cb(mv_source_h source,
-								  const int number_of_landmarks,
-								  const mv_point_s *locations, void *user_data)
+void _facial_landmark_detected_cb(mv_source_h source, const int number_of_landmarks, const mv_point_s *locations,
+								  void *user_data)
 {
 	EXPECT_GT(number_of_landmarks, 0);
 }
@@ -26,12 +25,9 @@ public:
 	{
 		TestInference::ConfigureInference();
 
-		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(
-						  IMG_FACE_LANDMARK, mv_source),
+		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(IMG_FACE_LANDMARK, mv_source),
 				  MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_inference_facial_landmark_detect(
-						  mv_source, infer, NULL, _facial_landmark_detected_cb,
-						  NULL),
+		ASSERT_EQ(mv_inference_facial_landmark_detect(mv_source, infer, NULL, _facial_landmark_detected_cb, NULL),
 				  MEDIA_VISION_ERROR_NONE);
 	}
 };
@@ -41,54 +37,36 @@ TEST_P(TestFaceLandmarkDetectionOpenCV, CAFFE_CNNCASCADE)
 	const char *inputNodeName = "data";
 	const char *outputNodeName[] = { "Sigmoid_fc2" };
 
-	ASSERT_EQ(mv_engine_config_set_string_attribute(
-					  engine_cfg, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
-					  FLD_OPENCV_WEIGHT_CAFFE_PATH),
+	ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH,
+													FLD_OPENCV_WEIGHT_CAFFE_PATH),
 			  MEDIA_VISION_ERROR_NONE);
-	ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg,
-												 MV_INFERENCE_INPUT_DATA_TYPE,
-												 MV_INFERENCE_DATA_FLOAT32),
+	ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_FLOAT32),
 			  MEDIA_VISION_ERROR_NONE);
-	ASSERT_EQ(mv_engine_config_set_string_attribute(
-					  engine_cfg, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH,
-					  FLD_OPENCV_CONFIG_CAFFE_PATH),
+	ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_MODEL_CONFIGURATION_FILE_PATH,
+													FLD_OPENCV_CONFIG_CAFFE_PATH),
 			  MEDIA_VISION_ERROR_NONE);
-	ASSERT_EQ(mv_engine_config_set_double_attribute(
-					  engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
+	ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
 			  MEDIA_VISION_ERROR_NONE);
-	ASSERT_EQ(mv_engine_config_set_double_attribute(
-					  engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 127.5),
+	ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 127.5),
 			  MEDIA_VISION_ERROR_NONE);
-	ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg,
-												 MV_INFERENCE_BACKEND_TYPE,
-												 MV_INFERENCE_BACKEND_OPENCV),
+	ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_OPENCV),
 			  MEDIA_VISION_ERROR_NONE);
-	ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg,
-												 MV_INFERENCE_TARGET_TYPE,
-												 MV_INFERENCE_TARGET_CPU),
+	ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_TARGET_TYPE, MV_INFERENCE_TARGET_CPU),
 			  MEDIA_VISION_ERROR_NONE);
-	ASSERT_EQ(mv_engine_config_set_int_attribute(
-					  engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 128),
+	ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 128),
 			  MEDIA_VISION_ERROR_NONE);
-	ASSERT_EQ(mv_engine_config_set_int_attribute(
-					  engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 128),
+	ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 128),
 			  MEDIA_VISION_ERROR_NONE);
-	ASSERT_EQ(mv_engine_config_set_int_attribute(
-					  engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
+	ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
 			  MEDIA_VISION_ERROR_NONE);
-	ASSERT_EQ(mv_engine_config_set_string_attribute(
-					  engine_cfg, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName),
+	ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName),
 			  MEDIA_VISION_ERROR_NONE);
-	ASSERT_EQ(mv_engine_config_set_array_string_attribute(
-					  engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
-					  outputNodeName, 1),
+	ASSERT_EQ(mv_engine_config_set_array_string_attribute(engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES, outputNodeName,
+														  1),
 			  MEDIA_VISION_ERROR_NONE);
 	inferenceFaceLandmark();
 }
 
 INSTANTIATE_TEST_CASE_P(Prefix, TestFaceLandmarkDetectionOpenCV,
-						::testing::Values(
-							ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
-							ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU)
-						)
-);
\ No newline at end of file
+						::testing::Values(ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
+										  ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU)));
\ No newline at end of file
diff --git a/test/testsuites/machine_learning/inference/test_image_classification.cpp b/test/testsuites/machine_learning/inference/test_image_classification.cpp
index fbece70..f7171bd 100644
--- a/test/testsuites/machine_learning/inference/test_image_classification.cpp
+++ b/test/testsuites/machine_learning/inference/test_image_classification.cpp
@@ -35,11 +35,10 @@
 	MV_CONFIG_PATH                     \
 	"/models/IC_Q/snpe/imagenet_slim_labels.txt"
 #define IC_SNPE_WEIGHT_QUANT_INCEPTION_V3_299_PATH \
-	MV_CONFIG_PATH                                   \
+	MV_CONFIG_PATH                                 \
 	"/models/IC_Q/snpe/inception_v3_quantized.dlc"
 
-void _image_classified_cb(mv_source_h source, const int number_of_classes,
-						  const int *indices, const char **names,
+void _image_classified_cb(mv_source_h source, const int number_of_classes, const int *indices, const char **names,
 						  const float *confidences, void *user_data)
 {
 	const std::string answer = "banana";
@@ -60,10 +59,8 @@ public:
 	{
 		TestInference::ConfigureInference();
 
-		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(IMG_BANANA, mv_source),
-																	  MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_inference_image_classify(mv_source, infer, NULL,
-											  _image_classified_cb, NULL),
+		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(IMG_BANANA, mv_source), MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_inference_image_classify(mv_source, infer, NULL, _image_classified_cb, NULL),
 				  MEDIA_VISION_ERROR_NONE);
 	}
 };
@@ -75,11 +72,8 @@ public:
 	{
 		TestInference::ConfigureInference();
 
-		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(
-						  IMG_BANANA, mv_source),
-				  MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_inference_image_classify(mv_source, infer, NULL,
-											  _image_classified_cb, NULL),
+		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(IMG_BANANA, mv_source), MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_inference_image_classify(mv_source, infer, NULL, _image_classified_cb, NULL),
 				  MEDIA_VISION_ERROR_NONE);
 	}
 };
@@ -87,29 +81,29 @@ public:
 TEST_P(TestImageClassificationTflite, MobilenetV1)
 {
 	engine_config_hosted_tflite_model(engine_cfg, IC_TFLITE_WEIGHT_MOBILENET_V1_224_PATH,
-									  IC_LABEL_MOBILENET_V1_224_PATH, _use_json_parser,
-									  _target_device_type);
+									  IC_LABEL_MOBILENET_V1_224_PATH, _use_json_parser, _target_device_type);
 
 	if (!_use_json_parser) {
 		const char *inputNodeName = "input";
 		const char *outputNodeName[] = { "MobilenetV1/Predictions/Reshape_1" };
 
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.0),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 224),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 224),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME,
-														inputNodeName), MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName),
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_array_string_attribute(engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
-															  outputNodeName, 1), MEDIA_VISION_ERROR_NONE);
+															  outputNodeName, 1),
+				  MEDIA_VISION_ERROR_NONE);
 	}
 
 	inferenceBanana();
@@ -118,29 +112,29 @@ TEST_P(TestImageClassificationTflite, MobilenetV1)
 TEST_P(TestImageClassificationTflite, MobilenetV2)
 {
 	engine_config_hosted_tflite_model(engine_cfg, IC_TFLITE_WEIGHT_MOBILENET_V2_224_PATH,
-									  IC_LABEL_MOBILENET_V1_224_PATH, _use_json_parser,
-									  _target_device_type);
+									  IC_LABEL_MOBILENET_V1_224_PATH, _use_json_parser, _target_device_type);
 
 	if (!_use_json_parser) {
 		const char *inputNodeName = "input";
 		const char *outputNodeName[] = { "MobilenetV2/Predictions/Reshape_1" };
 
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.01),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 224),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 224),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME,
-														inputNodeName), MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName),
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_array_string_attribute(engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
-															  outputNodeName, 1), MEDIA_VISION_ERROR_NONE);
+															  outputNodeName, 1),
+				  MEDIA_VISION_ERROR_NONE);
 	}
 
 	inferenceBanana();
@@ -148,30 +142,30 @@ TEST_P(TestImageClassificationTflite, MobilenetV2)
 
 TEST_P(TestImageClassificationTflite, Densenet)
 {
-	engine_config_hosted_tflite_model(engine_cfg, IC_TFLITE_WEIGHT_DENSENET_224_PATH,
-									  IC_LABEL_MOBILENET_V1_224_PATH, _use_json_parser,
-									  _target_device_type);
+	engine_config_hosted_tflite_model(engine_cfg, IC_TFLITE_WEIGHT_DENSENET_224_PATH, IC_LABEL_MOBILENET_V1_224_PATH,
+									  _use_json_parser, _target_device_type);
 
 	if (!_use_json_parser) {
 		const char *inputNodeName = "Placeholder";
 		const char *outputNodeName[] = { "softmax_tensor" };
 
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 255.0),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.0),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 224),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 224),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME,
-														inputNodeName), MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName),
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_array_string_attribute(engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
-															  outputNodeName, 1), MEDIA_VISION_ERROR_NONE);
+															  outputNodeName, 1),
+				  MEDIA_VISION_ERROR_NONE);
 	}
 
 	inferenceBanana();
@@ -179,30 +173,30 @@ TEST_P(TestImageClassificationTflite, Densenet)
 
 TEST_P(TestImageClassificationTflite, Nasnet)
 {
-	engine_config_hosted_tflite_model(engine_cfg, IC_TFLITE_WEIGHT_NASNET_224_PATH,
-									  IC_LABEL_MOBILENET_V1_224_PATH, _use_json_parser,
-									  _target_device_type);
+	engine_config_hosted_tflite_model(engine_cfg, IC_TFLITE_WEIGHT_NASNET_224_PATH, IC_LABEL_MOBILENET_V1_224_PATH,
+									  _use_json_parser, _target_device_type);
 
 	if (!_use_json_parser) {
 		const char *inputNodeName = "input";
 		const char *outputNodeName[] = { "final_layer/predictions" };
 
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.0),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 224),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 224),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME,
-														inputNodeName), MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName),
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_array_string_attribute(engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
-															  outputNodeName, 1), MEDIA_VISION_ERROR_NONE);
+															  outputNodeName, 1),
+				  MEDIA_VISION_ERROR_NONE);
 	}
 
 	inferenceBanana();
@@ -210,30 +204,30 @@ TEST_P(TestImageClassificationTflite, Nasnet)
 
 TEST_P(TestImageClassificationTflite, MNasnet)
 {
-	engine_config_hosted_tflite_model(engine_cfg, IC_TFLITE_WEIGHT_MNASNET_224_PATH,
-									  IC_LABEL_MOBILENET_V1_224_PATH, _use_json_parser,
-									  _target_device_type);
+	engine_config_hosted_tflite_model(engine_cfg, IC_TFLITE_WEIGHT_MNASNET_224_PATH, IC_LABEL_MOBILENET_V1_224_PATH,
+									  _use_json_parser, _target_device_type);
 
 	if (!_use_json_parser) {
 		const char *inputNodeName = "input";
 		const char *outputNodeName[] = { "output" };
 
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 57.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.0),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 224),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 224),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME,
-														inputNodeName), MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName),
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_array_string_attribute(engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
-															  outputNodeName, 1), MEDIA_VISION_ERROR_NONE);
+															  outputNodeName, 1),
+				  MEDIA_VISION_ERROR_NONE);
 	}
 
 	inferenceBanana();
@@ -241,30 +235,30 @@ TEST_P(TestImageClassificationTflite, MNasnet)
 
 TEST_P(TestImageClassificationTflite, Squeezenet)
 {
-	engine_config_hosted_tflite_model(engine_cfg, IC_TFLITE_WEIGHT_SQUEEZENET_224_PATH,
-									  IC_LABEL_MOBILENET_V1_224_PATH, _use_json_parser,
-									  _target_device_type);
+	engine_config_hosted_tflite_model(engine_cfg, IC_TFLITE_WEIGHT_SQUEEZENET_224_PATH, IC_LABEL_MOBILENET_V1_224_PATH,
+									  _use_json_parser, _target_device_type);
 
 	if (!_use_json_parser) {
 		const char *inputNodeName = "Placeholder";
 		const char *outputNodeName[] = { "softmax_tensor" };
 
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.0),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 224),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 224),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME,
-														inputNodeName), MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName),
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_array_string_attribute(engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
-															  outputNodeName, 1), MEDIA_VISION_ERROR_NONE);
+															  outputNodeName, 1),
+				  MEDIA_VISION_ERROR_NONE);
 	}
 
 	inferenceBanana();
@@ -273,31 +267,31 @@ TEST_P(TestImageClassificationTflite, Squeezenet)
 TEST_P(TestImageClassificationTflite, QUANT_MobilenetV1)
 {
 	engine_config_hosted_tflite_model(engine_cfg, IC_TFLITE_WEIGHT_QUANT_MOBILENET_V1_224_PATH,
-									  IC_LABEL_MOBILENET_V1_224_PATH, _use_json_parser,
-									  _target_device_type);
+									  IC_LABEL_MOBILENET_V1_224_PATH, _use_json_parser, _target_device_type);
 
 	if (!_use_json_parser) {
 		const char *inputNodeName = "input";
 		const char *outputNodeName[] = { "MobilenetV1/Predictions/Reshape_1" };
 
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_UINT8),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 0.0),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 1.0),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.0),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 224),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 224),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME,
-														inputNodeName), MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName),
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_array_string_attribute(engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
-															  outputNodeName, 1), MEDIA_VISION_ERROR_NONE);
+															  outputNodeName, 1),
+				  MEDIA_VISION_ERROR_NONE);
 	}
 
 	inferenceBanana();
@@ -306,50 +300,44 @@ TEST_P(TestImageClassificationTflite, QUANT_MobilenetV1)
 TEST_P(TestImageClassificationSnpe, DISABLED_InceptionV3_Quantized)
 {
 	engine_config_hosted_snpe_model(engine_cfg, IC_SNPE_WEIGHT_QUANT_INCEPTION_V3_299_PATH,
-									IC_LABEL_INCEPTION_V3_299_PATH, _use_json_parser,
-									_target_device_type);
+									IC_LABEL_INCEPTION_V3_299_PATH, _use_json_parser, _target_device_type);
 
 	if (!_use_json_parser) {
 		const char *inputNodeName = "input";
 		const char *outputNodeName[] = { "output" };
 
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_DATA_TYPE, MV_INFERENCE_DATA_UINT8),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.0),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 299),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 299),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME,
-														inputNodeName), MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName),
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_array_string_attribute(engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
-															  outputNodeName, 1), MEDIA_VISION_ERROR_NONE);
+															  outputNodeName, 1),
+				  MEDIA_VISION_ERROR_NONE);
 	}
 
 	inferenceBanana();
 }
 
 INSTANTIATE_TEST_CASE_P(Prefix, TestImageClassificationTflite,
-						::testing::Values(
-							ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
-							ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU)
-						)
-);
+						::testing::Values(ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
+										  ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU)));
 
 INSTANTIATE_TEST_CASE_P(Prefix, TestImageClassificationSnpe,
-						::testing::Values(
-							ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
-							ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_GPU),
-							ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CUSTOM),
-							ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU),
-							ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_GPU),
-							ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CUSTOM)
-						)
-);
\ No newline at end of file
+						::testing::Values(ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
+										  ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_GPU),
+										  ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CUSTOM),
+										  ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU),
+										  ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_GPU),
+										  ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CUSTOM)));
\ No newline at end of file
diff --git a/test/testsuites/machine_learning/inference/test_inference_helper.cpp b/test/testsuites/machine_learning/inference/test_inference_helper.cpp
index 1d66f77..df99f74 100644
--- a/test/testsuites/machine_learning/inference/test_inference_helper.cpp
+++ b/test/testsuites/machine_learning/inference/test_inference_helper.cpp
@@ -2,9 +2,7 @@
 #include <image_helper.h>
 #include "test_inference_helper.hpp"
 
-TestInference::TestInference() :
-		_use_json_parser(false),
-		_target_device_type(MV_INFERENCE_TARGET_DEVICE_NONE)
+TestInference::TestInference() : _use_json_parser(false), _target_device_type(MV_INFERENCE_TARGET_DEVICE_NONE)
 {
 	EXPECT_EQ(mv_create_engine_config(&engine_cfg), MEDIA_VISION_ERROR_NONE);
 	EXPECT_EQ(mv_inference_create(&infer), MEDIA_VISION_ERROR_NONE);
@@ -19,14 +17,11 @@ TestInference::~TestInference()
 
 void TestInference::ConfigureInference()
 {
-	ASSERT_EQ(mv_inference_configure(infer, engine_cfg),
-				MEDIA_VISION_ERROR_NONE);
+	ASSERT_EQ(mv_inference_configure(infer, engine_cfg), MEDIA_VISION_ERROR_NONE);
 	ASSERT_EQ(mv_inference_prepare(infer), MEDIA_VISION_ERROR_NONE);
 }
 
-void engine_config_hosted_model_config(mv_engine_config_h handle,
-									   const char *tf_weight,
-									   const bool use_json_parser)
+void engine_config_hosted_model_config(mv_engine_config_h handle, const char *tf_weight, const bool use_json_parser)
 {
 	EXPECT_EQ(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_WEIGHT_FILE_PATH, tf_weight),
 			  MEDIA_VISION_ERROR_NONE);
@@ -36,27 +31,21 @@ void engine_config_hosted_model_config(mv_engine_config_h handle,
 		meta_file_path = meta_file_path.substr(0, meta_file_path.find('.'));
 		meta_file_path += std::string(".json");
 
-		EXPECT_EQ(mv_engine_config_set_string_attribute(
-						handle, MV_INFERENCE_MODEL_META_FILE_PATH , meta_file_path.c_str()),
-				MEDIA_VISION_ERROR_NONE);
+		EXPECT_EQ(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_META_FILE_PATH,
+														meta_file_path.c_str()),
+				  MEDIA_VISION_ERROR_NONE);
 	}
 }
 
-void engine_config_hosted_tflite_model(mv_engine_config_h handle,
-									   const char *tf_weight,
-									   const char *user_file,
+void engine_config_hosted_tflite_model(mv_engine_config_h handle, const char *tf_weight, const char *user_file,
 									   const bool use_json_parser,
 									   const mv_inference_target_device_e target_device_type)
 {
 	engine_config_hosted_model_config(handle, tf_weight, use_json_parser);
 
-	EXPECT_EQ(mv_engine_config_set_int_attribute(handle,
-												 MV_INFERENCE_BACKEND_TYPE,
-												 MV_INFERENCE_BACKEND_TFLITE),
+	EXPECT_EQ(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_TFLITE),
 			  MEDIA_VISION_ERROR_NONE);
-	EXPECT_EQ(mv_engine_config_set_int_attribute(handle,
-												 MV_INFERENCE_TARGET_DEVICE_TYPE,
-												 target_device_type),
+	EXPECT_EQ(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_TARGET_DEVICE_TYPE, target_device_type),
 			  MEDIA_VISION_ERROR_NONE);
 
 	if (user_file) {
@@ -65,24 +54,16 @@ void engine_config_hosted_tflite_model(mv_engine_config_h handle,
 	}
 }
 
-void engine_config_hosted_snpe_model(mv_engine_config_h handle,
-									 const char *tf_weight,
-									 const char *user_file,
-									 const bool use_json_parser,
-									 const mv_inference_target_device_e target_device_type)
+void engine_config_hosted_snpe_model(mv_engine_config_h handle, const char *tf_weight, const char *user_file,
+									 const bool use_json_parser, const mv_inference_target_device_e target_device_type)
 {
 	engine_config_hosted_model_config(handle, tf_weight, use_json_parser);
 
-	EXPECT_EQ(mv_engine_config_set_int_attribute(handle,
-												 MV_INFERENCE_BACKEND_TYPE,
-												 MV_INFERENCE_BACKEND_SNPE),
+	EXPECT_EQ(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_BACKEND_TYPE, MV_INFERENCE_BACKEND_SNPE),
 			  MEDIA_VISION_ERROR_NONE);
-	EXPECT_EQ(mv_engine_config_set_int_attribute(handle,
-												 MV_INFERENCE_TARGET_DEVICE_TYPE,
-												 target_device_type),
+	EXPECT_EQ(mv_engine_config_set_int_attribute(handle, MV_INFERENCE_TARGET_DEVICE_TYPE, target_device_type),
 			  MEDIA_VISION_ERROR_NONE);
 
-	EXPECT_EQ(mv_engine_config_set_string_attribute(
-					  handle, MV_INFERENCE_MODEL_USER_FILE_PATH, user_file),
+	EXPECT_EQ(mv_engine_config_set_string_attribute(handle, MV_INFERENCE_MODEL_USER_FILE_PATH, user_file),
 			  MEDIA_VISION_ERROR_NONE);
 }
diff --git a/test/testsuites/machine_learning/inference/test_object_detection.cpp b/test/testsuites/machine_learning/inference/test_object_detection.cpp
index 42c0c48..b658a5b 100644
--- a/test/testsuites/machine_learning/inference/test_object_detection.cpp
+++ b/test/testsuites/machine_learning/inference/test_object_detection.cpp
@@ -19,10 +19,8 @@
 	MV_CONFIG_PATH                                   \
 	"/models/OD/snpe/lite2_fp32.dlc"
 
-void _object_detected_cb(mv_source_h source, const int number_of_objects,
-						 const int *indices, const char **names,
-						 const float *confidences,
-						 const mv_rectangle_s *locations, void *user_data)
+void _object_detected_cb(mv_source_h source, const int number_of_objects, const int *indices, const char **names,
+						 const float *confidences, const mv_rectangle_s *locations, void *user_data)
 {
 	auto answer = static_cast<std::string *>(user_data);
 	auto answer_found = false;
@@ -43,65 +41,47 @@ public:
 		std::string result("Dog");
 		TestInference::ConfigureInference();
 
-		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(
-						  IMG_DOG, mv_source),
-				  MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_inference_object_detect(mv_source, infer,
-											 _object_detected_cb, &result),
-				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(IMG_DOG, mv_source), MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_inference_object_detect(mv_source, infer, _object_detected_cb, &result), MEDIA_VISION_ERROR_NONE);
 	}
 };
 
 TEST_P(TestObjectDetectionTflite, MobilenetV1_SSD)
 {
-	engine_config_hosted_tflite_model(
-			engine_cfg, OD_TFLITE_WEIGHT_MOBILENET_V1_SSD_300_PATH,
-			OD_LABEL_MOBILENET_V1_SSD_300_PATH, _use_json_parser,
-			_target_device_type);
+	engine_config_hosted_tflite_model(engine_cfg, OD_TFLITE_WEIGHT_MOBILENET_V1_SSD_300_PATH,
+									  OD_LABEL_MOBILENET_V1_SSD_300_PATH, _use_json_parser, _target_device_type);
 
 	if (!_use_json_parser) {
 		const char *inputNodeName = "normalized_input_image_tensor";
-		const char *outputNodeName[] = { "TFLite_Detection_PostProcess",
-										 "TFLite_Detection_PostProcess:1",
-										 "TFLite_Detection_PostProcess:2",
-										 "TFLite_Detection_PostProcess:3" };
+		const char *outputNodeName[] = { "TFLite_Detection_PostProcess", "TFLite_Detection_PostProcess:1",
+										 "TFLite_Detection_PostProcess:2", "TFLite_Detection_PostProcess:3" };
 
-		ASSERT_EQ(mv_engine_config_set_double_attribute(
-						  engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
+		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
 				  MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_double_attribute(
-						  engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 127.5),
+		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 127.5),
 				  MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_double_attribute(
-						  engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3),
+		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3),
 				  MEDIA_VISION_ERROR_NONE);
 
-		ASSERT_EQ(mv_engine_config_set_int_attribute(
-						  engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300),
+		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300),
 				  MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_int_attribute(
-						  engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300),
+		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300),
 				  MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_int_attribute(
-						  engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
+		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
 				  MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_string_attribute(
-						  engine_cfg, MV_INFERENCE_INPUT_NODE_NAME,
-						  inputNodeName),
+		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName),
 				  MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_array_string_attribute(
-						  engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
-						  outputNodeName, 4),
+		ASSERT_EQ(mv_engine_config_set_array_string_attribute(engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
+															  outputNodeName, 4),
 				  MEDIA_VISION_ERROR_NONE);
 	}
 
 	inferenceDog();
 }
 
-INSTANTIATE_TEST_CASE_P(
-		Prefix, TestObjectDetectionTflite,
-		::testing::Values(ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
-						  ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU)));
+INSTANTIATE_TEST_CASE_P(Prefix, TestObjectDetectionTflite,
+						::testing::Values(ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
+										  ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU)));
 
 class TestObjectDetectionSnpe : public TestInference
 {
@@ -111,26 +91,19 @@ public:
 		std::string result("dog");
 		TestInference::ConfigureInference();
 
-		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(
-						  IMG_DOG, mv_source),
-				  MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_inference_object_detect(mv_source, infer,
-											 _object_detected_cb, &result),
-				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(IMG_DOG, mv_source), MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_inference_object_detect(mv_source, infer, _object_detected_cb, &result), MEDIA_VISION_ERROR_NONE);
 	}
 };
 
 TEST_P(TestObjectDetectionSnpe, DISABLED_EFDLite2QC)
 {
 	ASSERT_TRUE(_use_json_parser);
-	engine_config_hosted_snpe_model(
-			engine_cfg, OD_SNPE_WEIGHT_QC_EFFCIENTDET_LITE2_448_PATH,
-			OD_LABEL_EFFICIENTDET_LITE2_448_PATH, _use_json_parser,
-			_target_device_type);
+	engine_config_hosted_snpe_model(engine_cfg, OD_SNPE_WEIGHT_QC_EFFCIENTDET_LITE2_448_PATH,
+									OD_LABEL_EFFICIENTDET_LITE2_448_PATH, _use_json_parser, _target_device_type);
 
 	inferenceDog();
 }
 
-INSTANTIATE_TEST_CASE_P(
-		Prefix, TestObjectDetectionSnpe,
-		::testing::Values(ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CUSTOM)));
\ No newline at end of file
+INSTANTIATE_TEST_CASE_P(Prefix, TestObjectDetectionSnpe,
+						::testing::Values(ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CUSTOM)));
\ No newline at end of file
diff --git a/test/testsuites/machine_learning/inference/test_pose_landmark_detection.cpp b/test/testsuites/machine_learning/inference/test_pose_landmark_detection.cpp
index 88f9918..3d04221 100644
--- a/test/testsuites/machine_learning/inference/test_pose_landmark_detection.cpp
+++ b/test/testsuites/machine_learning/inference/test_pose_landmark_detection.cpp
@@ -9,13 +9,10 @@
 	MV_CONFIG_PATH        \
 	"/res/inference/images/poseLandmark.jpg"
 
-void _pose_landmark_detected_cb(mv_source_h source,
-								mv_inference_pose_result_h pose,
-								void *user_data)
+void _pose_landmark_detected_cb(mv_source_h source, mv_inference_pose_result_h pose, void *user_data)
 {
 	int cb_number_of_poses = 0;
-	ASSERT_EQ(mv_inference_pose_get_number_of_poses(pose, &cb_number_of_poses),
-			  MEDIA_VISION_ERROR_NONE);
+	ASSERT_EQ(mv_inference_pose_get_number_of_poses(pose, &cb_number_of_poses), MEDIA_VISION_ERROR_NONE);
 	ASSERT_EQ(cb_number_of_poses, 1);
 }
 
@@ -26,54 +23,47 @@ public:
 	{
 		TestInference::ConfigureInference();
 
-		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(
-						  IMG_POSE_LANDMARK, mv_source),
+		ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(IMG_POSE_LANDMARK, mv_source),
 				  MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_inference_pose_landmark_detect(mv_source, infer, NULL,
-													_pose_landmark_detected_cb,
-													NULL),
+		ASSERT_EQ(mv_inference_pose_landmark_detect(mv_source, infer, NULL, _pose_landmark_detected_cb, NULL),
 				  MEDIA_VISION_ERROR_NONE);
 	}
 };
 
 TEST_P(TestPoseLandmarkDetectionTflite, MobilenetV1)
 {
-	engine_config_hosted_tflite_model(engine_cfg, PLD_TFLITE_WEIGHT_MOBILENET_V1_POSENET_257_PATH,
-									  NULL, _use_json_parser, _target_device_type);
+	engine_config_hosted_tflite_model(engine_cfg, PLD_TFLITE_WEIGHT_MOBILENET_V1_POSENET_257_PATH, NULL,
+									  _use_json_parser, _target_device_type);
 
 	if (!_use_json_parser) {
 		const char *inputNodeName = "sub_2";
-		const char *outputNodeName[] = { "MobilenetV1/heatmap_2/BiasAdd",
-											"MobilenetV1/offset_2/BiasAdd",
-											"MobilenetV1/displacement_fwd_2/BiasAdd",
-											"MobilenetV1/displacement_bwd_2/BiasAdd" };
+		const char *outputNodeName[] = { "MobilenetV1/heatmap_2/BiasAdd", "MobilenetV1/offset_2/BiasAdd",
+										 "MobilenetV1/displacement_fwd_2/BiasAdd",
+										 "MobilenetV1/displacement_bwd_2/BiasAdd" };
 
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 127.5),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300),
-					MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
-					MEDIA_VISION_ERROR_NONE);
-		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME,
-														inputNodeName), MEDIA_VISION_ERROR_NONE);
+				  MEDIA_VISION_ERROR_NONE);
+		ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName),
+				  MEDIA_VISION_ERROR_NONE);
 		ASSERT_EQ(mv_engine_config_set_array_string_attribute(engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
-																outputNodeName, 4), MEDIA_VISION_ERROR_NONE);
+															  outputNodeName, 4),
+				  MEDIA_VISION_ERROR_NONE);
 	}
 
-
 	inferencePoseLandmark();
 }
 
 INSTANTIATE_TEST_CASE_P(Prefix, TestPoseLandmarkDetectionTflite,
-						::testing::Values(
-							ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
-							ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU)
-						)
-);
\ No newline at end of file
+						::testing::Values(ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
+										  ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU)));
\ No newline at end of file
diff --git a/test/testsuites/surveillance/surveillance_test_suite.c b/test/testsuites/surveillance/surveillance_test_suite.c
index 5b7810c..89987f7 100644
--- a/test/testsuites/surveillance/surveillance_test_suite.c
+++ b/test/testsuites/surveillance/surveillance_test_suite.c
@@ -52,9 +52,9 @@
 static mv_surveillance_event_trigger_h is_subscribed[MAX_EVENTS_NUMBER];
 static int video_streams_ids[MAX_EVENTS_NUMBER];
 static unsigned int trigger_id_cnt = 0;
-static const int green_color[] = {0, 255, 0};
-static const int red_color[] = {0, 0, 255};
-static const int blue_color[] = {255, 0, 0};
+static const int green_color[] = { 0, 255, 0 };
+static const int red_color[] = { 0, 0, 255 };
+static const int blue_color[] = { 255, 0, 0 };
 static bool save_results_to_image = false;
 /*----------------------------------------------------*/
 /*functions*/
@@ -95,26 +95,14 @@ void turn_on_off_saving_to_image();
 /*----------------------------------------------------*/
 /* callbacks */
 
-void detect_person_appeared_cb(
-	mv_surveillance_event_trigger_h handle,
-	mv_source_h source,
-	int video_stream_id,
-	mv_surveillance_result_h event_result,
-	void *user_data);
-
-void person_recognized_cb(
-	mv_surveillance_event_trigger_h handle,
-	mv_source_h source,
-	int video_stream_id,
-	mv_surveillance_result_h event_result,
-	void *user_data);
-
-void movement_detected_cb(
-	mv_surveillance_event_trigger_h handle,
-	mv_source_h source,
-	int video_stream_id,
-	mv_surveillance_result_h event_result,
-	void *user_data);
+void detect_person_appeared_cb(mv_surveillance_event_trigger_h handle, mv_source_h source, int video_stream_id,
+							   mv_surveillance_result_h event_result, void *user_data);
+
+void person_recognized_cb(mv_surveillance_event_trigger_h handle, mv_source_h source, int video_stream_id,
+						  mv_surveillance_result_h event_result, void *user_data);
+
+void movement_detected_cb(mv_surveillance_event_trigger_h handle, mv_source_h source, int video_stream_id,
+						  mv_surveillance_result_h event_result, void *user_data);
 
 /*----------------------------------------------------*/
 
@@ -127,16 +115,14 @@ int main(void)
 	init_is_subscribed();
 
 	const int options[8] = { 1, 2, 3, 4, 5, 6, 7, 8 };
-	const char *names[8] = {
-		"Get list of supported events",
-		"Get identificators of subscribed events",
-		"Subscribe to event",
-		"Unsubscribe from event",
-		"Unsubscribe from all events",
-		"Push source",
-		"Turn on (off) saving event result to image",
-		"Exit"
-	};
+	const char *names[8] = { "Get list of supported events",
+							 "Get identificators of subscribed events",
+							 "Subscribe to event",
+							 "Unsubscribe from event",
+							 "Unsubscribe from all events",
+							 "Push source",
+							 "Turn on (off) saving event result to image",
+							 "Exit" };
 
 	while (1) {
 		char exit = 'n';
@@ -178,8 +164,7 @@ int main(void)
 			const char *names_last[2] = { "No", "Yes" };
 
 			while (sel_opt == 0) {
-				sel_opt = show_menu("Are you sure?",
-									options_last, names_last, 2);
+				sel_opt = show_menu("Are you sure?", options_last, names_last, 2);
 				switch (sel_opt) {
 				case 1:
 					exit = 'n';
@@ -233,11 +218,9 @@ void print_is_subscribed()
 		PRINT_Y("List of subscribed events is empty");
 }
 
-static const char *EVENT_TYPES_NAMES[MAX_EVENT_TYPE_LEN] = {
-	MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED,
-	MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED,
-	MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED
-};
+static const char *EVENT_TYPES_NAMES[MAX_EVENT_TYPE_LEN] = { MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED,
+															 MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED,
+															 MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED };
 
 static const unsigned int NUMBER_OF_TYPES = 3u;
 
@@ -261,11 +244,12 @@ bool foreach_event_type_cb(const char *event_type, void *user_data)
 	PRINT_W("%s", event_type);
 	PRINT_G("\tList of supported event result value names is:");
 
-	const int error = mv_surveillance_foreach_event_result_name(
-			event_type, foreach_event_result_value_name_cb, user_data);
+	const int error =
+			mv_surveillance_foreach_event_result_name(event_type, foreach_event_result_value_name_cb, user_data);
 	if (MEDIA_VISION_ERROR_NONE != error) {
 		PRINT_E("Error occurred when trying to get value names for "
-				"event named '%s'", event_type);
+				"event named '%s'",
+				event_type);
 		return true;
 	}
 	return true;
@@ -275,15 +259,13 @@ void print_supported_events()
 {
 	PRINT_G("List of supported events is:");
 
-	const int error = mv_surveillance_foreach_supported_event_type(
-			foreach_event_type_cb, NULL);
+	const int error = mv_surveillance_foreach_supported_event_type(foreach_event_type_cb, NULL);
 
 	if (MEDIA_VISION_ERROR_NONE != error)
 		PRINT_R("Error occurred when trying to get list of event type names \n");
 }
 
-int create_trigger_handle_by_event_name(
-	mv_surveillance_event_trigger_h *handle)
+int create_trigger_handle_by_event_name(mv_surveillance_event_trigger_h *handle)
 {
 	PRINT_G("\nSelect event type:");
 
@@ -292,8 +274,7 @@ int create_trigger_handle_by_event_name(
 		printf("#%d. %s\n", i, EVENT_TYPES_NAMES[i]);
 
 	size_t event_id = 0ul;
-	while (input_size("Input event type (unsigned integer value):",
-				NUMBER_OF_TYPES - 1, &event_id) == -1) {
+	while (input_size("Input event type (unsigned integer value):", NUMBER_OF_TYPES - 1, &event_id) == -1) {
 		PRINT_R("Incorrect input! Try again.\n List of supported events is:");
 
 		unsigned int i = 0u;
@@ -301,11 +282,11 @@ int create_trigger_handle_by_event_name(
 			printf("%d\t%s\n", i, EVENT_TYPES_NAMES[i]);
 	}
 
-	const int error = mv_surveillance_event_trigger_create(
-						EVENT_TYPES_NAMES[event_id], handle);
+	const int error = mv_surveillance_event_trigger_create(EVENT_TYPES_NAMES[event_id], handle);
 	if (MEDIA_VISION_ERROR_NONE != error) {
 		PRINT_E("mv_surveillance_event_trigger_create() error!\n"
-				"Error code: %i\n", error);
+				"Error code: %i\n",
+				error);
 		return error;
 	}
 
@@ -317,7 +298,8 @@ bool try_destroy_event_trigger(mv_surveillance_event_trigger_h trigger)
 	const int error = mv_surveillance_event_trigger_destroy(trigger);
 	if (MEDIA_VISION_ERROR_NONE != error) {
 		PRINT_E("Error with code %d was occured when try to destroy "
-				"event trigger.", error);
+				"event trigger.",
+				error);
 		return false;
 	}
 	return true;
@@ -335,24 +317,23 @@ void subscribe_to_event()
 	int error = create_trigger_handle_by_event_name(&event_trigger);
 	if (MEDIA_VISION_ERROR_NONE != error) {
 		PRINT_E("Error occurred when creating of event trigger. "
-				"Error code: %i", error);
+				"Error code: %i",
+				error);
 		try_destroy_event_trigger(event_trigger);
 		return;
 	}
 
 	int video_stream_id = 0;
 
-	while (input_int("Input video stream identificator (integer value):",
-				INT_MIN,
-				INT_MAX,
-				&video_stream_id) == -1)
+	while (input_int("Input video stream identificator (integer value):", INT_MIN, INT_MAX, &video_stream_id) == -1)
 		PRINT_R("Incorrect input! Try again.");
 
 	char *event_type = NULL;
 	error = mv_surveillance_get_event_trigger_type(event_trigger, &event_type);
 	if (MEDIA_VISION_ERROR_NONE != error) {
 		PRINT_E("Error occurred when getting of event trigger type. "
-				"Error code: %i", error);
+				"Error code: %i",
+				error);
 		try_destroy_event_trigger(event_trigger);
 		return;
 	}
@@ -360,20 +341,12 @@ void subscribe_to_event()
 	if (show_confirm_dialog("Would you like to set ROI (Region Of Interest)?"))
 		add_roi_to_event(event_trigger);
 
-	if (strncmp(event_type,
-			MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED,
-			MAX_EVENT_TYPE_LEN) == 0) {
-		error = mv_surveillance_subscribe_event_trigger(
-			event_trigger,
-			video_stream_id,
-			NULL,
-			detect_person_appeared_cb,
-			NULL);
-	} else if (strncmp(event_type,
-					MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED,
-					MAX_EVENT_TYPE_LEN) == 0) {
-			PRINT_Y("Please create and save face recognition models\n"
-					"before subscribing to event. Use mv_face_test_suite.");
+	if (strncmp(event_type, MV_SURVEILLANCE_EVENT_TYPE_PERSON_APPEARED_DISAPPEARED, MAX_EVENT_TYPE_LEN) == 0) {
+		error = mv_surveillance_subscribe_event_trigger(event_trigger, video_stream_id, NULL, detect_person_appeared_cb,
+														NULL);
+	} else if (strncmp(event_type, MV_SURVEILLANCE_EVENT_TYPE_PERSON_RECOGNIZED, MAX_EVENT_TYPE_LEN) == 0) {
+		PRINT_Y("Please create and save face recognition models\n"
+				"before subscribing to event. Use mv_face_test_suite.");
 
 		mv_engine_config_h engine_cfg = NULL;
 		error = mv_create_engine_config(&engine_cfg);
@@ -393,17 +366,14 @@ void subscribe_to_event()
 			error = mv_destroy_engine_config(engine_cfg);
 			if (error != MEDIA_VISION_ERROR_NONE)
 				PRINT_E("Failed to destroy engine configuration for event trigger."
-						"Error code: %i", error);
+						"Error code: %i",
+						error);
 			free(event_type);
 			return;
 		}
 
-		error = mv_surveillance_subscribe_event_trigger(
-					event_trigger,
-					video_stream_id,
-					engine_cfg,
-					person_recognized_cb,
-					NULL);
+		error = mv_surveillance_subscribe_event_trigger(event_trigger, video_stream_id, engine_cfg,
+														person_recognized_cb, NULL);
 
 		if (error != MEDIA_VISION_ERROR_NONE) {
 			PRINT_E("Subscription failed. Error code: %i.", error);
@@ -411,7 +381,8 @@ void subscribe_to_event()
 			error = mv_destroy_engine_config(engine_cfg);
 			if (error != MEDIA_VISION_ERROR_NONE)
 				PRINT_E("Failed to destroy engine configuration for event trigger."
-						"Error code: %i", error);
+						"Error code: %i",
+						error);
 			free(event_type);
 			return;
 		}
@@ -419,16 +390,11 @@ void subscribe_to_event()
 		error = mv_destroy_engine_config(engine_cfg);
 		if (error != MEDIA_VISION_ERROR_NONE)
 			PRINT_E("Failed to destroy engine configuration for event trigger."
-					"Error code: %i", error);
-	} else if (strncmp(event_type,
-				MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED,
-				MAX_EVENT_TYPE_LEN) == 0) {
-		error = mv_surveillance_subscribe_event_trigger(
-					event_trigger,
-					video_stream_id,
-					NULL,
-					movement_detected_cb,
-					NULL);
+					"Error code: %i",
+					error);
+	} else if (strncmp(event_type, MV_SURVEILLANCE_EVENT_TYPE_MOVEMENT_DETECTED, MAX_EVENT_TYPE_LEN) == 0) {
+		error = mv_surveillance_subscribe_event_trigger(event_trigger, video_stream_id, NULL, movement_detected_cb,
+														NULL);
 	}
 
 	free(event_type);
@@ -447,13 +413,11 @@ void subscribe_to_event()
 void add_roi_to_event(mv_surveillance_event_trigger_h event_trigger)
 {
 	int number_of_roi_points = 0;
-	while (input_int("Input number of ROI points (integer value >2):",
-					MIN_NUMBER_OF_ROI_POINTS,
-					MAX_NUMBER_OF_ROI_POINTS,
-					&number_of_roi_points) == -1)
+	while (input_int("Input number of ROI points (integer value >2):", MIN_NUMBER_OF_ROI_POINTS,
+					 MAX_NUMBER_OF_ROI_POINTS, &number_of_roi_points) == -1)
 		PRINT_R("Incorrect input! Try again.");
 
-	mv_point_s* roi = (mv_point_s*) malloc(sizeof(mv_point_s) * number_of_roi_points);
+	mv_point_s *roi = (mv_point_s *) malloc(sizeof(mv_point_s) * number_of_roi_points);
 	if (roi == NULL) {
 		PRINT_E("Fail to alloc roi err[%d].", MEDIA_VISION_ERROR_OUT_OF_MEMORY);
 		return;
@@ -466,31 +430,22 @@ void add_roi_to_event(mv_surveillance_event_trigger_h event_trigger)
 	for (; i < number_of_roi_points; ++i) {
 		printf("Point %d \n", i + 1);
 
-		while (input_int("Input x (integer value):",
-						MIN_ROI_X_COORD,
-						MAX_ROI_X_COORD,
-						&x) == -1)
+		while (input_int("Input x (integer value):", MIN_ROI_X_COORD, MAX_ROI_X_COORD, &x) == -1)
 			PRINT_R("Incorrect input! Try again.");
 
-		while (input_int("Input y (integer value):",
-						MIN_ROI_Y_COORD,
-						MAX_ROI_Y_COORD,
-						&y) == -1)
+		while (input_int("Input y (integer value):", MIN_ROI_Y_COORD, MAX_ROI_Y_COORD, &y) == -1)
 			PRINT_R("Incorrect input! Try again.");
 
 		roi[i].x = x;
 		roi[i].y = y;
 	}
 
-	const int error = mv_surveillance_set_event_trigger_roi(
-						event_trigger,
-						number_of_roi_points,
-						roi);
+	const int error = mv_surveillance_set_event_trigger_roi(event_trigger, number_of_roi_points, roi);
 
 	if (error == MEDIA_VISION_ERROR_NONE)
 		PRINT_G("ROI was successfully set")
 	else
-		PRINT_R("Setting ROI failed. Please try again") ;
+		PRINT_R("Setting ROI failed. Please try again");
 
 	if (roi != NULL)
 		free(roi);
@@ -499,22 +454,16 @@ void add_roi_to_event(mv_surveillance_event_trigger_h event_trigger)
 void unsubscribe_from_event()
 {
 	int trigger_id = 0;
-	while (input_int("Input event identificator (1-100):",
-					1,
-					MAX_EVENTS_NUMBER - 1,
-					&trigger_id) == -1)
+	while (input_int("Input event identificator (1-100):", 1, MAX_EVENTS_NUMBER - 1, &trigger_id) == -1)
 		PRINT_R("Incorrect input! Try again.");
 
 	mv_surveillance_event_trigger_h event_trigger = is_subscribed[trigger_id];
 	if (NULL == event_trigger) {
-		PRINT_E("Sorry, event trigger with %i identifier wasn't subscribed.",
-				trigger_id);
+		PRINT_E("Sorry, event trigger with %i identifier wasn't subscribed.", trigger_id);
 		return;
 	}
 
-	const int error = mv_surveillance_unsubscribe_event_trigger(
-			event_trigger,
-			video_streams_ids[trigger_id]);
+	const int error = mv_surveillance_unsubscribe_event_trigger(event_trigger, video_streams_ids[trigger_id]);
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		PRINT_E("Error with code %d was occured in unsubscribe event.", error);
 		return;
@@ -532,15 +481,11 @@ void unsubscribe_from_all_events()
 	unsigned int trigger_id = 0;
 	int unsubscribed_number = 0;
 	for (; trigger_id < MAX_EVENTS_NUMBER; ++trigger_id) {
-		mv_surveillance_event_trigger_h event_trigger =
-			is_subscribed[trigger_id];
+		mv_surveillance_event_trigger_h event_trigger = is_subscribed[trigger_id];
 		if (NULL != event_trigger) {
-			error = mv_surveillance_unsubscribe_event_trigger(
-					event_trigger,
-					video_streams_ids[trigger_id]);
+			error = mv_surveillance_unsubscribe_event_trigger(event_trigger, video_streams_ids[trigger_id]);
 			if (error != MEDIA_VISION_ERROR_NONE) {
-				PRINT_E("Error with code %d was occurred in unsubscribe event.",
-						error);
+				PRINT_E("Error with code %d was occurred in unsubscribe event.", error);
 				continue;
 			}
 			++unsubscribed_number;
@@ -553,9 +498,8 @@ void unsubscribe_from_all_events()
 		}
 	}
 
-	unsubscribed_number > 0 ?
-	PRINT_S("%d event(s) was successfully unsubscribed", unsubscribed_number) :
-	PRINT_Y("\nThere are no triggers can be unsubscribed.");
+	unsubscribed_number > 0 ? PRINT_S("%d event(s) was successfully unsubscribed", unsubscribed_number) :
+							  PRINT_Y("\nThere are no triggers can be unsubscribed.");
 }
 
 void push_source()
@@ -563,15 +507,13 @@ void push_source()
 	mv_source_h source;
 	int error = mv_create_source(&source);
 	if (MEDIA_VISION_ERROR_NONE != error) {
-		PRINT_E("ERROR: Errors were occurred during source creating!!! Code %i" ,
-				error);
+		PRINT_E("ERROR: Errors were occurred during source creating!!! Code %i", error);
 		return;
 	}
 
 	char *path_to_image = NULL;
 
-	while (input_string("Input file name with image to be analyzed:",
-						1024, &path_to_image) == -1)
+	while (input_string("Input file name with image to be analyzed:", 1024, &path_to_image) == -1)
 		PRINT_R("Incorrect input! Try again.");
 
 	error = load_mv_source_from_file(path_to_image, source);
@@ -591,10 +533,7 @@ void push_source()
 
 	int video_stream_id = 0;
 
-	while (input_int("Input video stream identificator (integer value):",
-				INT_MIN,
-				INT_MAX,
-				&video_stream_id) == -1)
+	while (input_int("Input video stream identificator (integer value):", INT_MIN, INT_MAX, &video_stream_id) == -1)
 		PRINT_R("Incorrect input! Try again.");
 
 	error = mv_surveillance_push_source(source, video_stream_id);
@@ -621,18 +560,15 @@ bool fill_engine_cfg_person_recognized(mv_engine_config_h engine_cfg)
 	bool ret = false;
 	char *path_to_model = NULL;
 
-	while (input_string("Input file name with face recognition model:",
-						1024, &path_to_model) == -1)
+	while (input_string("Input file name with face recognition model:", 1024, &path_to_model) == -1)
 		PRINT_R("Incorrect input! Try again.");
 
 	const int error = mv_engine_config_set_string_attribute(
-						engine_cfg,
-						MV_SURVEILLANCE_FACE_RECOGNITION_MODEL_FILE_PATH,
-						path_to_model);
+			engine_cfg, MV_SURVEILLANCE_FACE_RECOGNITION_MODEL_FILE_PATH, path_to_model);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		PRINT_E("Setting path to face recognition model failed, code %i", error);
-	}	else {
+	} else {
 		printf("\nModel path is %s \n", path_to_model);
 		ret = true;
 	}
@@ -647,17 +583,12 @@ void turn_on_off_saving_to_image()
 {
 	save_results_to_image = !save_results_to_image;
 
-	save_results_to_image ?
-		PRINT_Y("Save event results to image files ON.") :
-		PRINT_Y("Save event results to image files OFF.");
+	save_results_to_image ? PRINT_Y("Save event results to image files ON.") :
+							PRINT_Y("Save event results to image files OFF.");
 }
 
-void detect_person_appeared_cb(
-	mv_surveillance_event_trigger_h handle,
-	mv_source_h source,
-	int video_stream_id,
-	mv_surveillance_result_h event_result,
-	void *user_data)
+void detect_person_appeared_cb(mv_surveillance_event_trigger_h handle, mv_source_h source, int video_stream_id,
+							   mv_surveillance_result_h event_result, void *user_data)
 {
 	PRINT_G("Person appeared / disappeared event was occured");
 	if (save_results_to_image)
@@ -671,12 +602,10 @@ void detect_person_appeared_cb(
 	image_data_s image_data = { 0, 0, MEDIA_VISION_COLORSPACE_INVALID };
 
 	if (save_results_to_image &&
-			(mv_source_get_buffer(source, &out_buffer, &buf_size) ||
-			mv_source_get_width(source, &(image_data.image_width)) ||
-			mv_source_get_height(source, &(image_data.image_height)) ||
-			mv_source_get_colorspace(source, &(image_data.image_colorspace)) ||
-			out_buffer == NULL ||
-			buf_size == 0)) {
+		(mv_source_get_buffer(source, &out_buffer, &buf_size) ||
+		 mv_source_get_width(source, &(image_data.image_width)) ||
+		 mv_source_get_height(source, &(image_data.image_height)) ||
+		 mv_source_get_colorspace(source, &(image_data.image_colorspace)) || out_buffer == NULL || buf_size == 0)) {
 		PRINT_R("ERROR: Creating out image is impossible.");
 
 		return;
@@ -689,14 +618,13 @@ void detect_person_appeared_cb(
 	}
 
 	int number_of_appeared_persons = 0;
-	int error = mv_surveillance_get_result_value(
-					event_result,
-					MV_SURVEILLANCE_PERSONS_APPEARED_NUMBER,
-					&number_of_appeared_persons);
+	int error = mv_surveillance_get_result_value(event_result, MV_SURVEILLANCE_PERSONS_APPEARED_NUMBER,
+												 &number_of_appeared_persons);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		PRINT_E("Error with code %d was occured in getting number of "
-				"appeared persons.", error);
+				"appeared persons.",
+				error);
 		if (out_buffer_copy != NULL)
 			free(out_buffer_copy);
 
@@ -705,17 +633,15 @@ void detect_person_appeared_cb(
 
 	printf("\nNumber of appeared persons is %d \n", number_of_appeared_persons);
 
-	mv_rectangle_s *appeared_locations =
-		malloc(sizeof(mv_rectangle_s) * number_of_appeared_persons);
+	mv_rectangle_s *appeared_locations = malloc(sizeof(mv_rectangle_s) * number_of_appeared_persons);
 
-	error = mv_surveillance_get_result_value(
-				event_result,
-				MV_SURVEILLANCE_PERSONS_APPEARED_LOCATIONS,
-				appeared_locations);
+	error = mv_surveillance_get_result_value(event_result, MV_SURVEILLANCE_PERSONS_APPEARED_LOCATIONS,
+											 appeared_locations);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		PRINT_E("Error with code %d was occured in getting locations of "
-				"appeared persons.", error);
+				"appeared persons.",
+				error);
 
 		if (appeared_locations != NULL)
 			free(appeared_locations);
@@ -728,34 +654,24 @@ void detect_person_appeared_cb(
 
 	int i = 0;
 	for (; i < number_of_appeared_persons; ++i) {
-		printf("Person #%d location is: x - %d, y - %d, w - %d, h - %d.\n",
-				i,
-				appeared_locations[i].point.x,
-				appeared_locations[i].point.y,
-				appeared_locations[i].width,
-				appeared_locations[i].height);
+		printf("Person #%d location is: x - %d, y - %d, w - %d, h - %d.\n", i, appeared_locations[i].point.x,
+			   appeared_locations[i].point.y, appeared_locations[i].width, appeared_locations[i].height);
 
 		if (save_results_to_image)
-			draw_rectangle_on_buffer(
-						appeared_locations[i].point.x,
-						appeared_locations[i].point.y,
-						appeared_locations[i].point.x + appeared_locations[i].width,
-						appeared_locations[i].point.y + appeared_locations[i].height,
-						3,
-						green_color,
-						&image_data,
-						out_buffer_copy);
+			draw_rectangle_on_buffer(appeared_locations[i].point.x, appeared_locations[i].point.y,
+									 appeared_locations[i].point.x + appeared_locations[i].width,
+									 appeared_locations[i].point.y + appeared_locations[i].height, 3, green_color,
+									 &image_data, out_buffer_copy);
 	}
 
 	int number_of_tracked_persons = 0;
-	error = mv_surveillance_get_result_value(
-				event_result,
-				MV_SURVEILLANCE_PERSONS_TRACKED_NUMBER,
-				&number_of_tracked_persons);
+	error = mv_surveillance_get_result_value(event_result, MV_SURVEILLANCE_PERSONS_TRACKED_NUMBER,
+											 &number_of_tracked_persons);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		PRINT_E("Error with code %d was occured in getting number of "
-				"tracked persons.", error);
+				"tracked persons.",
+				error);
 
 		if (appeared_locations != NULL)
 			free(appeared_locations);
@@ -768,17 +684,15 @@ void detect_person_appeared_cb(
 
 	printf("\nNumber of tracked persons is %d \n", number_of_tracked_persons);
 
-	mv_rectangle_s *tracked_locations =
-		malloc(sizeof(mv_rectangle_s) * number_of_tracked_persons);
+	mv_rectangle_s *tracked_locations = malloc(sizeof(mv_rectangle_s) * number_of_tracked_persons);
 
-	error = mv_surveillance_get_result_value(
-				event_result,
-				MV_SURVEILLANCE_PERSONS_TRACKED_LOCATIONS,
-				tracked_locations);
+	error = mv_surveillance_get_result_value(event_result, MV_SURVEILLANCE_PERSONS_TRACKED_LOCATIONS,
+											 tracked_locations);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		PRINT_E("Error with code %d was occured in getting locations of "
-				"tracked persons.", error);
+				"tracked persons.",
+				error);
 
 		if (appeared_locations != NULL)
 			free(appeared_locations);
@@ -793,34 +707,24 @@ void detect_person_appeared_cb(
 	}
 
 	for (i = 0; i < number_of_tracked_persons; ++i) {
-		printf("Person #%d location is: x - %d, y - %d, w - %d, h - %d.\n",
-				i,
-				tracked_locations[i].point.x,
-				tracked_locations[i].point.y,
-				tracked_locations[i].width,
-				tracked_locations[i].height);
+		printf("Person #%d location is: x - %d, y - %d, w - %d, h - %d.\n", i, tracked_locations[i].point.x,
+			   tracked_locations[i].point.y, tracked_locations[i].width, tracked_locations[i].height);
 
 		if (save_results_to_image)
-			draw_rectangle_on_buffer(
-						tracked_locations[i].point.x,
-						tracked_locations[i].point.y,
-						tracked_locations[i].point.x + tracked_locations[i].width,
-						tracked_locations[i].point.y + tracked_locations[i].height,
-						3,
-						blue_color,
-						&image_data,
-						out_buffer_copy);
+			draw_rectangle_on_buffer(tracked_locations[i].point.x, tracked_locations[i].point.y,
+									 tracked_locations[i].point.x + tracked_locations[i].width,
+									 tracked_locations[i].point.y + tracked_locations[i].height, 3, blue_color,
+									 &image_data, out_buffer_copy);
 	}
 
 	int number_of_disappeared_persons = 0;
-	error = mv_surveillance_get_result_value(
-				event_result,
-				MV_SURVEILLANCE_PERSONS_DISAPPEARED_NUMBER,
-				&number_of_disappeared_persons);
+	error = mv_surveillance_get_result_value(event_result, MV_SURVEILLANCE_PERSONS_DISAPPEARED_NUMBER,
+											 &number_of_disappeared_persons);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		PRINT_E("Error with code %d was occured in getting number of "
-				"disappeared persons.", error);
+				"disappeared persons.",
+				error);
 
 		if (appeared_locations != NULL)
 			free(appeared_locations);
@@ -836,17 +740,15 @@ void detect_person_appeared_cb(
 
 	printf("\nNumber of disappeared persons is %d \n", number_of_disappeared_persons);
 
-	mv_rectangle_s *disappeared_locations =
-		malloc(sizeof(mv_rectangle_s) * number_of_disappeared_persons);
+	mv_rectangle_s *disappeared_locations = malloc(sizeof(mv_rectangle_s) * number_of_disappeared_persons);
 
-	error = mv_surveillance_get_result_value(
-				event_result,
-				MV_SURVEILLANCE_PERSONS_DISAPPEARED_LOCATIONS,
-				disappeared_locations);
+	error = mv_surveillance_get_result_value(event_result, MV_SURVEILLANCE_PERSONS_DISAPPEARED_LOCATIONS,
+											 disappeared_locations);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		PRINT_E("Error with code %d was occured in getting locations of "
-				"disappeared persons.", error);
+				"disappeared persons.",
+				error);
 
 		if (appeared_locations != NULL)
 			free(appeared_locations);
@@ -864,23 +766,14 @@ void detect_person_appeared_cb(
 	}
 
 	for (i = 0; i < number_of_disappeared_persons; ++i) {
-		printf("Person #%d location is: x - %d, y - %d, w - %d, h - %d.\n",
-				i,
-				disappeared_locations[i].point.x,
-				disappeared_locations[i].point.y,
-				disappeared_locations[i].width,
-				disappeared_locations[i].height);
+		printf("Person #%d location is: x - %d, y - %d, w - %d, h - %d.\n", i, disappeared_locations[i].point.x,
+			   disappeared_locations[i].point.y, disappeared_locations[i].width, disappeared_locations[i].height);
 
 		if (save_results_to_image)
-			draw_rectangle_on_buffer(
-						disappeared_locations[i].point.x,
-						disappeared_locations[i].point.y,
-						disappeared_locations[i].point.x + disappeared_locations[i].width,
-						disappeared_locations[i].point.y + disappeared_locations[i].height,
-						3,
-						red_color,
-						&image_data,
-						out_buffer_copy);
+			draw_rectangle_on_buffer(disappeared_locations[i].point.x, disappeared_locations[i].point.y,
+									 disappeared_locations[i].point.x + disappeared_locations[i].width,
+									 disappeared_locations[i].point.y + disappeared_locations[i].height, 3, red_color,
+									 &image_data, out_buffer_copy);
 	}
 
 	if (save_results_to_image)
@@ -901,12 +794,8 @@ void detect_person_appeared_cb(
 		free(out_buffer_copy);
 }
 
-void person_recognized_cb(
-	mv_surveillance_event_trigger_h handle,
-	mv_source_h source,
-	int video_stream_id,
-	mv_surveillance_result_h event_result,
-	void *user_data)
+void person_recognized_cb(mv_surveillance_event_trigger_h handle, mv_source_h source, int video_stream_id,
+						  mv_surveillance_result_h event_result, void *user_data)
 {
 	PRINT_G("Person recognized event was occurred");
 	if (save_results_to_image)
@@ -914,14 +803,11 @@ void person_recognized_cb(
 				"Person recognized locations - red.");
 
 	int number_of_persons = 0;
-	int error = mv_surveillance_get_result_value(
-					event_result,
-					MV_SURVEILLANCE_PERSONS_RECOGNIZED_NUMBER,
-					&number_of_persons);
+	int error = mv_surveillance_get_result_value(event_result, MV_SURVEILLANCE_PERSONS_RECOGNIZED_NUMBER,
+												 &number_of_persons);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
-		PRINT_E("Error with code %d was occured in getting number of persons.",
-				error);
+		PRINT_E("Error with code %d was occured in getting number of persons.", error);
 		return;
 	}
 
@@ -929,14 +815,10 @@ void person_recognized_cb(
 
 	mv_rectangle_s *locations = (mv_rectangle_s *) malloc(sizeof(mv_rectangle_s) * number_of_persons);
 
-	error = mv_surveillance_get_result_value(
-				event_result,
-				MV_SURVEILLANCE_PERSONS_RECOGNIZED_LOCATIONS,
-				locations);
+	error = mv_surveillance_get_result_value(event_result, MV_SURVEILLANCE_PERSONS_RECOGNIZED_LOCATIONS, locations);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
-		PRINT_E("Error with code %d was occured in getting locations of persons.",
-				error);
+		PRINT_E("Error with code %d was occured in getting locations of persons.", error);
 
 		if (locations != NULL)
 			free(locations);
@@ -946,14 +828,10 @@ void person_recognized_cb(
 
 	int *labels = (int *) malloc(sizeof(int) * number_of_persons);
 
-	error = mv_surveillance_get_result_value(
-				event_result,
-				MV_SURVEILLANCE_PERSONS_RECOGNIZED_LABELS,
-				labels);
+	error = mv_surveillance_get_result_value(event_result, MV_SURVEILLANCE_PERSONS_RECOGNIZED_LABELS, labels);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
-		PRINT_E("Error with code %d was occured in getting labels of persons.",
-				error);
+		PRINT_E("Error with code %d was occured in getting labels of persons.", error);
 
 		if (locations != NULL)
 			free(locations);
@@ -966,14 +844,10 @@ void person_recognized_cb(
 
 	double *confidences = (double *) malloc(sizeof(double) * number_of_persons);
 
-	error = mv_surveillance_get_result_value(
-				event_result,
-				MV_SURVEILLANCE_PERSONS_RECOGNIZED_CONFIDENCES,
-				confidences);
+	error = mv_surveillance_get_result_value(event_result, MV_SURVEILLANCE_PERSONS_RECOGNIZED_CONFIDENCES, confidences);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
-		PRINT_E("Error with code %d was occured in getting confidences of persons.",
-				error);
+		PRINT_E("Error with code %d was occured in getting confidences of persons.", error);
 
 		if (locations != NULL)
 			free(locations);
@@ -992,12 +866,10 @@ void person_recognized_cb(
 	image_data_s image_data = { 0, 0, MEDIA_VISION_COLORSPACE_INVALID };
 
 	if (save_results_to_image &&
-			(mv_source_get_buffer(source, &out_buffer, &buf_size) ||
-			mv_source_get_width(source, &(image_data.image_width)) ||
-			mv_source_get_height(source, &(image_data.image_height)) ||
-			mv_source_get_colorspace(source, &(image_data.image_colorspace)) ||
-			out_buffer == NULL ||
-			buf_size == 0)) {
+		(mv_source_get_buffer(source, &out_buffer, &buf_size) ||
+		 mv_source_get_width(source, &(image_data.image_width)) ||
+		 mv_source_get_height(source, &(image_data.image_height)) ||
+		 mv_source_get_colorspace(source, &(image_data.image_colorspace)) || out_buffer == NULL || buf_size == 0)) {
 		PRINT_R("ERROR: Creating out image is impossible.");
 
 		if (locations != NULL)
@@ -1021,24 +893,16 @@ void person_recognized_cb(
 	int i = 0;
 	for (; i < number_of_persons; ++i) {
 		printf("Person %d:\n", labels[i]);
-		printf("Location is: x - %d, y - %d, w - %d, h - %d.\n",
-				locations[i].point.x,
-				locations[i].point.y,
-				locations[i].width,
-				locations[i].height);
+		printf("Location is: x - %d, y - %d, w - %d, h - %d.\n", locations[i].point.x, locations[i].point.y,
+			   locations[i].width, locations[i].height);
 		printf("Model confidence - %3.2f", confidences[i]);
 		printf("\n");
 
 		if (save_results_to_image)
-			draw_rectangle_on_buffer(
-						locations[i].point.x,
-						locations[i].point.y,
-						locations[i].point.x + locations[i].width,
-						locations[i].point.y + locations[i].height,
-						3,
-						red_color,
-						&image_data,
-						out_buffer_copy);
+			draw_rectangle_on_buffer(locations[i].point.x, locations[i].point.y,
+									 locations[i].point.x + locations[i].width,
+									 locations[i].point.y + locations[i].height, 3, red_color, &image_data,
+									 out_buffer_copy);
 	}
 
 	printf("\n");
@@ -1059,12 +923,8 @@ void person_recognized_cb(
 		free(out_buffer_copy);
 }
 
-void movement_detected_cb(
-	mv_surveillance_event_trigger_h event_trigger,
-	mv_source_h source,
-	int video_stream_id,
-	mv_surveillance_result_h event_result,
-	void *user_data)
+void movement_detected_cb(mv_surveillance_event_trigger_h event_trigger, mv_source_h source, int video_stream_id,
+						  mv_surveillance_result_h event_result, void *user_data)
 {
 	PRINT_G("Movement detected event was occured");
 	if (save_results_to_image)
@@ -1072,31 +932,25 @@ void movement_detected_cb(
 				"Movement detected locations - blue.");
 
 	int number_of_movement_regions = 0;
-	int error = mv_surveillance_get_result_value(
-					event_result,
-					MV_SURVEILLANCE_MOVEMENT_NUMBER_OF_REGIONS,
-					&number_of_movement_regions);
+	int error = mv_surveillance_get_result_value(event_result, MV_SURVEILLANCE_MOVEMENT_NUMBER_OF_REGIONS,
+												 &number_of_movement_regions);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
 		PRINT_E("Error with code %d was occured in getting number of "
-				"movement regions.", error);
+				"movement regions.",
+				error);
 
 		return;
 	}
 
 	printf("\nNumber of movement regions is %d \n", number_of_movement_regions);
 
-	mv_rectangle_s *movement_regions =
-		malloc(sizeof(mv_rectangle_s) * number_of_movement_regions);
+	mv_rectangle_s *movement_regions = malloc(sizeof(mv_rectangle_s) * number_of_movement_regions);
 
-	error = mv_surveillance_get_result_value(
-				event_result,
-				MV_SURVEILLANCE_MOVEMENT_REGIONS,
-				movement_regions);
+	error = mv_surveillance_get_result_value(event_result, MV_SURVEILLANCE_MOVEMENT_REGIONS, movement_regions);
 
 	if (error != MEDIA_VISION_ERROR_NONE) {
-		PRINT_E("Error with code %d was occured in getting movement regions.",
-				error);
+		PRINT_E("Error with code %d was occured in getting movement regions.", error);
 
 		if (movement_regions != NULL)
 			free(movement_regions);
@@ -1109,12 +963,10 @@ void movement_detected_cb(
 	image_data_s image_data = { 0, 0, MEDIA_VISION_COLORSPACE_INVALID };
 
 	if (save_results_to_image &&
-			(mv_source_get_buffer(source, &out_buffer, &buf_size) ||
-			mv_source_get_width(source, &(image_data.image_width)) ||
-			mv_source_get_height(source, &(image_data.image_height)) ||
-			mv_source_get_colorspace(source, &(image_data.image_colorspace)) ||
-			out_buffer == NULL ||
-			buf_size == 0)) {
+		(mv_source_get_buffer(source, &out_buffer, &buf_size) ||
+		 mv_source_get_width(source, &(image_data.image_width)) ||
+		 mv_source_get_height(source, &(image_data.image_height)) ||
+		 mv_source_get_colorspace(source, &(image_data.image_colorspace)) || out_buffer == NULL || buf_size == 0)) {
 		PRINT_R("ERROR: Creating out image is impossible.");
 
 		if (movement_regions != NULL)
@@ -1131,23 +983,14 @@ void movement_detected_cb(
 
 	int i = 0;
 	for (; i < number_of_movement_regions; ++i) {
-		printf("Movement #%d region is: x - %d, y - %d, w - %d, h - %d.\n",
-				i,
-				movement_regions[i].point.x,
-				movement_regions[i].point.y,
-				movement_regions[i].width,
-				movement_regions[i].height);
+		printf("Movement #%d region is: x - %d, y - %d, w - %d, h - %d.\n", i, movement_regions[i].point.x,
+			   movement_regions[i].point.y, movement_regions[i].width, movement_regions[i].height);
 
 		if (save_results_to_image)
-			draw_rectangle_on_buffer(
-						movement_regions[i].point.x,
-						movement_regions[i].point.y,
-						movement_regions[i].point.x + movement_regions[i].width,
-						movement_regions[i].point.y + movement_regions[i].height,
-						3,
-						blue_color,
-						&image_data,
-						out_buffer_copy);
+			draw_rectangle_on_buffer(movement_regions[i].point.x, movement_regions[i].point.y,
+									 movement_regions[i].point.x + movement_regions[i].width,
+									 movement_regions[i].point.y + movement_regions[i].height, 3, blue_color,
+									 &image_data, out_buffer_copy);
 	}
 
 	printf("\n");
diff --git a/test/testsuites/tracker/test_tracker.cpp b/test/testsuites/tracker/test_tracker.cpp
index dd24589..244e8d1 100644
--- a/test/testsuites/tracker/test_tracker.cpp
+++ b/test/testsuites/tracker/test_tracker.cpp
@@ -27,17 +27,14 @@ using namespace testing;
 using namespace std;
 using namespace MediaVision::Common;
 
-void _tracked_cb(mv_source_h source,
-				mv_rectangle_s roi,
-				void *user_data)
+void _tracked_cb(mv_source_h source, mv_rectangle_s roi, void *user_data)
 {
 	printf("In callback: roi.x y width height : %d %d %d %d\n", roi.point.x, roi.point.y, roi.width, roi.height);
 }
 
 int perform_tracker_configure(mv_engine_config_h engine_cfg)
 {
-	int ret = mv_engine_config_set_int_attribute(
-			engine_cfg, MV_ROI_TRACKER_TYPE, (int)MV_ROI_TRACKER_TYPE_BALANCE);
+	int ret = mv_engine_config_set_int_attribute(engine_cfg, MV_ROI_TRACKER_TYPE, (int) MV_ROI_TRACKER_TYPE_BALANCE);
 	if (ret != MEDIA_VISION_ERROR_NONE) {
 		printf("Fail to set roi tracker type");
 		return MEDIA_VISION_ERROR_INVALID_OPERATION;
-- 
2.7.4


From c4c4de7e2c09eb47452664402f2cae4eecf9c847 Mon Sep 17 00:00:00 2001
From: Kwanghoon Son <k.son@samsung.com>
Date: Wed, 7 Sep 2022 03:10:27 -0400
Subject: [PATCH 16/16] Fix memory leak

[Version] : 0.23.24-0
[Issue type] : bug fix

mv_engine_config_get_string_attribute allocate memory inside of function.

Change-Id: Ia511b42a45a2b04ee818396bba0a8dee356331bc
Signed-off-by: Kwanghoon Son <k.son@samsung.com>
---
 mv_machine_learning/inference/src/mv_inference_open.cpp | 2 +-
 packaging/capi-media-vision.spec                        | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/mv_machine_learning/inference/src/mv_inference_open.cpp b/mv_machine_learning/inference/src/mv_inference_open.cpp
index 28a052e..741a00c 100644
--- a/mv_machine_learning/inference/src/mv_inference_open.cpp
+++ b/mv_machine_learning/inference/src/mv_inference_open.cpp
@@ -201,7 +201,7 @@ static int configure_model_open(Inference *pInfer, mv_engine_config_h engine_con
 
 	if (std::string(modelMetaFilePath).empty()) {
 		LOGW("Skip ParseMetadata and run without Metadata");
-		goto release_model_user_file_path;
+		goto release_model_meta_file_path;
 	}
 
 	if (!IsJsonFile(std::string(modelMetaFilePath))) {
diff --git a/packaging/capi-media-vision.spec b/packaging/capi-media-vision.spec
index ba8863e..b63120d 100644
--- a/packaging/capi-media-vision.spec
+++ b/packaging/capi-media-vision.spec
@@ -1,6 +1,6 @@
 Name:        capi-media-vision
 Summary:     Media Vision library for Tizen Native API
-Version:     0.23.23
+Version:     0.23.24
 Release:     0
 Group:       Multimedia/Framework
 License:     Apache-2.0 and BSD-3-Clause
-- 
2.7.4