From: Tae-Young Chung Date: Thu, 4 Jul 2019 11:15:34 +0000 (+0900) Subject: Initial codes X-Git-Tag: submit/tizen/20190904.072843~1 X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=1464cf16c3003a8b45db06f68b6cf0dc3702fc76;p=platform%2Fcore%2Fmultimedia%2Finference-engine-opencv.git Initial codes Note that this initial code is under development and provides limited functionality. In addition, OpenCV based implementation must be applied to vision specific purpose. Signed-off-by: Tae-Young Chung --- diff --git a/AUTHORS b/AUTHORS new file mode 100644 index 0000000..596e163 --- /dev/null +++ b/AUTHORS @@ -0,0 +1 @@ +Taeyoung Chung \ No newline at end of file diff --git a/CMakeLists.txt b/CMakeLists.txt new file mode 100644 index 0000000..60a1e98 --- /dev/null +++ b/CMakeLists.txt @@ -0,0 +1,99 @@ + +CMAKE_MINIMUM_REQUIRED(VERSION 2.6) +SET(fw_name "inference-engine-opencv") + +PROJECT(${fw_name}) + +SET(CMAKE_INSTALL_PREFIX /usr) +SET(PREFIX ${CMAKE_INSTALL_PREFIX}) + +SET(INC_DIR "${PROJECT_SOURCE_DIR}/include") +SET(dependents "dlog inference-engine-interface-vision inference-engine-interface-common") + +INCLUDE(FindPkgConfig) +pkg_check_modules(${fw_name} REQUIRED ${dependents}) +FOREACH(flag ${${fw_name}_CFLAGS}) + SET(EXTRA_CFLAGS "${EXTRA_CFLAGS} ${flag}") + SET(EXTRA_CXXFLAGS "${EXTRA_CXXFLAGS} ${flag}") +ENDFOREACH(flag) + +FOREACH(flag ${${fw_name}_LDFLAGS}) + SET(EXTRA_LDFLAGS "${EXTRA_LDFLAGS} ${flag}") +ENDFOREACH(flag) +#Remove leading whitespace POLICY CMP0004 +STRING(REGEX REPLACE "^ " "" EXTRA_LDFLAGS ${EXTRA_LDFLAGS}) + +#OpenCV +FIND_PACKAGE(OpenCV REQUIRED core dnn imgproc) +if(NOT OpenCV_FOUND) + MESSAGE(SEND_ERROR "OpenCV NOT FOUND") + RETURN() +else() + INCLUDE_DIRECTORIES(${OpenCV_INCLUDE_DIRS}) +endif() + +SET(CMAKE_C_FLAGS "-I./include -I./include/headers ${CMAKE_C_FLAGS} ${EXTRA_CFLAGS} -fPIC -Wall -w") +SET(CMAKE_C_FLAGS_DEBUG "-O0 -g") + +SET(CMAKE_CXX_FLAGS "-I./include -I./include/headers ${CMAKE_CXX_FLAGS} ${EXTRA_CXXFLAGS} -fPIC") +SET(CMAKE_CXX_FLAGS_DEBUG "-O0 -g --w") + +ADD_DEFINITIONS("-DPREFIX=\"${CMAKE_INSTALL_PREFIX}\"") +ADD_DEFINITIONS("-DTIZEN_DEBUG") + +SET(CMAKE_EXE_LINKER_FLAGS "-Wl,--as-needed -Wl,--rpath=${LIB_INSTALL_DIR}") + +aux_source_directory(src SOURCES) +ADD_LIBRARY(${fw_name} SHARED ${SOURCES}) + +TARGET_LINK_LIBRARIES(${fw_name} ${OpenCV_LIBS} ${EXTRA_LDFLAGS}) + + +SET_TARGET_PROPERTIES(${fw_name} + PROPERTIES + CLEAN_DIRECT_OUTPUT 1 +) + +INSTALL(TARGETS ${fw_name} DESTINATION ${LIB_INSTALL_DIR}) +INSTALL( + DIRECTORY ${INC_DIR}/ DESTINATION include/media + FILES_MATCHING + PATTERN "*_private.h" EXCLUDE + PATTERN "*.h" + ) + +SET(PC_NAME ${fw_name}) +SET(PC_REQUIRED ${pc_dependents}) +SET(PC_LDFLAGS -l${fw_name}) +SET(PC_CFLAGS -I\${includedir}/media) + +IF(UNIX) + +ADD_CUSTOM_TARGET (distclean @echo cleaning for source distribution) +ADD_CUSTOM_COMMAND( + DEPENDS clean + COMMENT "distribution clean" + COMMAND find + ARGS . + -not -name config.cmake -and \( + -name tester.c -or + -name Testing -or + -name CMakeFiles -or + -name cmake.depends -or + -name cmake.check_depends -or + -name CMakeCache.txt -or + -name cmake.check_cache -or + -name *.cmake -or + -name Makefile -or + -name core -or + -name core.* -or + -name gmon.out -or + -name install_manifest.txt -or + -name *.pc -or + -name *~ \) + | grep -v TC | xargs rm -rf + TARGET distclean + VERBATIM +) + +ENDIF(UNIX) \ No newline at end of file diff --git a/LICENSE.APLv2 b/LICENSE.APLv2 new file mode 100644 index 0000000..bbe9d02 --- /dev/null +++ b/LICENSE.APLv2 @@ -0,0 +1,206 @@ +Copyright (c) 2000 - 2011 Samsung Electronics Co., Ltd. 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All rights reserved. +Except as noted, this software is licensed under Apache License, Version 2. +Please, see the LICENSE.APLv2 file for Apache License terms and conditions. diff --git a/README.md b/README.md new file mode 100644 index 0000000..194ea88 --- /dev/null +++ b/README.md @@ -0,0 +1,2 @@ +# inference-engine-opencv +This is OpenCV based implementation of inference-engine-interface \ No newline at end of file diff --git a/inference-engine-opencv.manifest b/inference-engine-opencv.manifest new file mode 100644 index 0000000..a76fdba --- /dev/null +++ b/inference-engine-opencv.manifest @@ -0,0 +1,5 @@ + + + + + diff --git a/packaging/inference-engine-opencv.spec b/packaging/inference-engine-opencv.spec new file mode 100644 index 0000000..c4cd8c1 --- /dev/null +++ b/packaging/inference-engine-opencv.spec @@ -0,0 +1,47 @@ +Name: inference-engine-opencv +Summary: OpenCV based implementation of inference-engine-interface +Version: 0.0.1 +Release: 1 +Group: Multimedia/Libraries +License: Apache-2.0 +Source0: %{name}-%{version}.tar.gz +Requires(post): /sbin/ldconfig +Requires(postun): /sbin/ldconfig +BuildRequires: cmake +BuildRequires: pkgconfig(dlog) +BuildRequires: pkgconfig(opencv) >= 3.4.1 +BuildRequires: pkgconfig(inference-engine-interface-vision) +BuildRequires: pkgconfig(inference-engine-interface-common) + +%description +OpenCV based implementation of inference-engine-interface + + +%prep +%setup -q + +%build +%if 0%{?sec_build_binary_debug_enable} +export CFLAGS="$CFLAGS -DTIZEN_DEBUG_ENABLE" +export CXXFLAGS="$CXXFLAGS -DTIZEN_DEBUG_ENABLE" +export FFLAGS="$FFLAGS -DTIZEN_DEBUG_ENABLE" +%endif + +#MAJORVER=`echo %{version} | awk 'BEGIN {FS="."}{print $1}'` +%cmake . + +make %{?jobs:-j%jobs} + +%install +rm -rf %{buildroot} + +%make_install + +%post -p /sbin/ldconfig +%postun -p /sbin/ldconfig + +%files +%manifest %{name}.manifest +%license LICENSE.APLv2 +%defattr(-,root,root,-) +%{_libdir}/*.so diff --git a/src/inference_engine_opencv.cpp b/src/inference_engine_opencv.cpp new file mode 100644 index 0000000..119e9d1 --- /dev/null +++ b/src/inference_engine_opencv.cpp @@ -0,0 +1,431 @@ +/** + * Copyright (c) 2019 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 +#include "inference_engine_opencv_private.h" + +#include + +#include +#include +#include +#include + +namespace InferenceEngineImpl { +namespace OpenCVImpl { + +InferenceOpenCV::InferenceOpenCV(std::string protoFile, std::string weightFile, + std::string userFile) : + mNet(), + mConfigFile(protoFile), + mWeightFile(weightFile), + mUserFile(userFile) +{ + LOGE("ENTER"); + LOGE("LEAVE"); +} + +InferenceOpenCV::~InferenceOpenCV() +{ + ; +} + +int InferenceOpenCV::SetUserFile() +{ + std::ifstream fp(mUserFile.c_str()); + if (!fp.is_open()) { + return INFERENCE_ENGINE_ERROR_INVALID_PATH; + } + + std::string userListName; + while (!fp.eof()) { + std::getline(fp, userListName); + if (userListName.length()) + SetUserListName(userListName); + } + + fp.close(); + + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::SetInputTensorParam() +{ + LOGE("Not supported"); + return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED; +} + +int InferenceOpenCV::SetInputTensorParamInput(int width, int height, int dim, int ch) +{ + mCh = ch; + mDim = dim; + mInputSize = cv::Size(width, height); + + LOGE("InputSize is %d x %d\n", mInputSize.width, mInputSize.height); + + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::SetInputTensorParamNorm(double deviation, double mean) +{ + mDeviation = deviation; + mMean = mean; + + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::SetInputTensorParamNode(std::string node) +{ + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::SetOutputTensorParam() +{ + return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED; +} + +int InferenceOpenCV::SetOutputTensorParamThresHold(double threshold) +{ + mThreshold = threshold; + + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::SetOutputTensorParamNumbers(int number) +{ + mOutputNumbers = number; + + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::SetOutputTensorParamType(int type) +{ + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::SetOutPutTensorParamNodes(std::string node) +{ + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::SetTargetDevice(inference_target_type_e type) +{ + switch (type) { + case INFERENCE_TARGET_CPU : + mNet.setPreferableTarget(cv::dnn::DNN_TARGET_CPU); + break; + case INFERENCE_TARGET_GPU : + mNet.setPreferableTarget(cv::dnn::DNN_TARGET_OPENCL); + break; + case INFERENCE_TARGET_NONE: + default: + LOGE("Not supported device type [%d], Set CPU mode", (int)type); + mNet.setPreferableTarget(cv::dnn::DNN_TARGET_CPU); + } + + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::Load() +{ + int ret = INFERENCE_ENGINE_ERROR_NONE; + + if (access(mConfigFile.c_str(), F_OK) || + access(mWeightFile.c_str(), F_OK)) { + LOGE("protofile in [%s] ", mConfigFile.c_str()); + LOGE("weightFilePath in [%s] ", mWeightFile.c_str()); + return INFERENCE_ENGINE_ERROR_INVALID_PATH; + } + + size_t userFileLength = mUserFile.length(); + if (userFileLength > 0 && access(mUserFile.c_str(), F_OK)) { + LOGE("userFilePath in [%s] ", mUserFile.c_str()); + return INFERENCE_ENGINE_ERROR_INVALID_PATH; + } + + // This call may be changed if OpenCV version would be upgraded + mNet = cv::dnn::readNetFromCaffe(mConfigFile, mWeightFile); + + if (mNet.empty()) { + LOGE("Net is empty"); + return INFERENCE_ENGINE_ERROR_INVALID_DATA; + } + + ret = (userFileLength > 0) ? SetUserFile() : INFERENCE_ENGINE_ERROR_NONE; + if (ret != INFERENCE_ENGINE_ERROR_NONE) + LOGE("Fail to read categoryList"); + + return ret; +} + +int InferenceOpenCV::CreateInputLayerPassage() +{ + return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED; +} + +int InferenceOpenCV::PrepareInputLayerPassage() +{ + return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED; +} + +int InferenceOpenCV::PrepareInputLayerPassage(inference_input_type_e type) +{ + return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED; +} + +int InferenceOpenCV::Run(cv::Mat tensor) +{ + double scaleVal = 1.0/mDeviation; + mSourceSize = tensor.size(); + cv::Scalar meanScalar = cv::Scalar((float)mMean,(float)mMean, (float)mMean); + + mInputBlob = cv::dnn::blobFromImage(tensor, scaleVal, mInputSize, meanScalar, false, false); + + if (mInputBlob.empty()) { + LOGE("Fail to get input blob"); + return INFERENCE_ENGINE_ERROR_INTERNAL; + } + + mNet.setInput(mInputBlob); + + /* foward */ + mOutputProb = mNet.forward(); + /* TODO */ + // std::vector mOutputProb, + // std::vector mOuputLayer; + // mNet.forward(mOutputProb, mOutputLayer); + + if (mOutputProb.empty()) { + LOGE("OutputProb is empty"); + return INFERENCE_ENGINE_ERROR_INTERNAL; + } + + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::Run(std::vector tensor) +{ + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::GetInferenceResult(ImageClassificationResults& results) +{ + int dims = mOutputProb.dims; + for (int k = 0; k < dims; ++k) { + LOGE("%d: %d", k, mOutputProb.size[k]); + } + LOGI("dims: %d", dims); + cv::Mat reShapedProb = mOutputProb.reshape(1,1); + + + int classIdx = -1; + double classProb = 0.0; + + cv::Mat outputIdx, outputProb; + + cv::sortIdx(reShapedProb, outputIdx, CV_SORT_EVERY_ROW + CV_SORT_DESCENDING); + + for (int idx = 0; idx < mOutputNumbers; ++idx) { + classIdx = outputIdx.at(0,idx); + int y = classIdx / reShapedProb.cols; + int x = classIdx % reShapedProb.cols; + + classProb = (double)reShapedProb.at(y,x); + results.indices.push_back(classIdx); + results.confidences.push_back(classProb); + LOGI("classIdx: %d", classIdx); + LOGI("classProb: %lf", classProb); + LOGI("test...."); + LOGI("names: %s", mUserListName[classIdx].c_str()); + results.names.push_back(mUserListName[classIdx]); + + } + + results.number_of_classes = mOutputNumbers; + + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::GetInferenceResult(ObjectDetectionResults& results) +{ + int dims = mOutputProb.dims; + for (int k = 0; k < dims; ++k) { + LOGE("%d: %d", k, mOutputProb.size[k]); + } + LOGI("dims: %d", dims); + cv::Mat detectionMat(mOutputProb.size[2], mOutputProb.size[3], CV_32F, mOutputProb.ptr()); + + float confidence; + size_t objectClass; + int left, top, right, bottom; + cv::Rect loc; + for(int i = 0; i < detectionMat.rows; i++) { + confidence = detectionMat.at(i, 2); + + if(confidence > (float)mThreshold) { + objectClass = (size_t)(detectionMat.at(i, 1)); + + left = static_cast(detectionMat.at(i, 3) * mSourceSize.width); + top = static_cast(detectionMat.at(i, 4) * mSourceSize.height); + right = static_cast(detectionMat.at(i, 5) * mSourceSize.width); + bottom = static_cast(detectionMat.at(i, 6) * mSourceSize.height); + + loc.x = left; + loc.y = top; + loc.width = right - left + 1; + loc.height = bottom - top + 1; + + //classNames[objectClass]; + LOGE("objectClass: %d", objectClass); + LOGE("confidence:%f", confidence); + LOGE("left:%d, top:%d, right:%d, bottom:%d", left, top, right, bottom); + + results.indices.push_back(objectClass); + results.confidences.push_back(confidence); + results.names.push_back(mUserListName[objectClass]); + results.locations.push_back(loc); + } + } + + results.number_of_objects = results.indices.size(); + + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::GetInferenceResult(FaceDetectionResults& results) +{ + int dims = mOutputProb.dims; + for (int k = 0; k < dims; ++k) { + LOGE("%d: %d", k, mOutputProb.size[k]); + } + LOGI("dims: %d", dims); + + cv::Mat detectionMat(mOutputProb.size[2], mOutputProb.size[3], CV_32F, mOutputProb.ptr()); + + float confidence; + int left, top, right, bottom; + cv::Rect loc; + for(int i = 0; i < detectionMat.rows; i++) { + confidence = detectionMat.at(i, 2); + + if(confidence > (float)mThreshold) { + left = static_cast(detectionMat.at(i, 3) * mSourceSize.width); + top = static_cast(detectionMat.at(i, 4) * mSourceSize.height); + right = static_cast(detectionMat.at(i, 5) * mSourceSize.width); + bottom = static_cast(detectionMat.at(i, 6) * mSourceSize.height); + + loc.x = left; + loc.y = top; + loc.width = right - left + 1; + loc.height = bottom - top + 1; + + //classNames[objectClass]; + LOGE("confidence:%f", confidence); + LOGE("left:%d, top:%d, right:%d, bottom:%d", left, top, right, bottom); + + results.confidences.push_back(confidence); + results.locations.push_back(loc); + } + } + + results.number_of_faces = results.locations.size(); + + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::GetInferenceResult(FacialLandMarkDetectionResults& results) +{ + int dims = mOutputProb.dims; + for (int k = 0; k < dims; ++k) { + LOGE("%d: %d", k, mOutputProb.size[k]); + } + LOGI("dims: %d", dims); + + cv::Mat outputs = mOutputProb.reshape(1,1); + + int number_of_landmarks = (outputs.cols >> 1); + + int pos = 0; + cv::Point pint; + for (int idx = 0; idx < number_of_landmarks; ++idx) { + pos = (idx << 1); + pint.x = static_cast((outputs.at(0, pos) + 0.5) * mSourceSize.width); + pint.y = static_cast((outputs.at(0, pos+1) + 0.5) * mSourceSize.height); + + results.locations.push_back(pint); + LOGI("x:%d, y:%d", pint.x, pint.y); + } + + results.number_of_landmarks = number_of_landmarks; + + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::GetInferenceResult(std::vector>& dimInfo, std::vector& results) +{ + dimInfo.clear(); + results.clear(); + + int dims = mOutputProb.dims; + std::vector tmpDimInfo; + for (int d = 0; d < dims; ++d) { + tmpDimInfo.push_back(mOutputProb.size[d]); + } + + dimInfo.push_back(tmpDimInfo); + results.push_back(mOutputProb.ptr()); + + return INFERENCE_ENGINE_ERROR_NONE; +} + +int InferenceOpenCV::GetNumberOfOutputs() +{ + return mOutputNumbers; +} + +void InferenceOpenCV::SetUserListName(std::string userlist) +{ + mUserListName.push_back(userlist); +} + +extern "C" +{ +class IInferenceEngineVision* EngineVisionInit(std::string protoFile, std::string weightFile, + std::string userFile) +{ + InferenceOpenCV *engine = new InferenceOpenCV(protoFile, weightFile, userFile); + return engine; +} + +void EngineVisionDestroy(class IInferenceEngineVision *engine) +{ + delete engine; +} + +class IInferenceEngineCommon* EngineCommonInit(std::string protoFile, std::string weightFile, + std::string userFile) +{ + InferenceOpenCV *engine = new InferenceOpenCV(protoFile, weightFile, userFile); + return engine; +} + +void EngineCommonDestroy(class IInferenceEngineCommon *engine) +{ + delete engine; +} +} +} /* OpenCVImpl */ +} /* InferenceEngineImpl */ \ No newline at end of file diff --git a/src/inference_engine_opencv_private.h b/src/inference_engine_opencv_private.h new file mode 100644 index 0000000..3e7acc8 --- /dev/null +++ b/src/inference_engine_opencv_private.h @@ -0,0 +1,130 @@ +/** + * Copyright (c) 2019 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 __INFERENCE_ENGINE_IMPL_OPENCV_H__ +#define __INFERENCE_ENGINE_IMPL_OPENCV_H__ + +#include +#include + +#include +#include + +#include +/** + * @file inference_engine_opencv_private.h + * @brief This file contains the InferenceOpenCV class which + * provide OpenCV based inference functionality + */ + +#ifdef LOG_TAG +#undef LOG_TAG +#endif + +#define LOG_TAG "INFERENCE_ENGINE_OPENCV" + +using namespace InferenceEngineInterface::Vision; +using namespace InferenceEngineInterface::Common; + +namespace InferenceEngineImpl { +namespace OpenCVImpl { + +class InferenceOpenCV : public IInferenceEngineVision, public IInferenceEngineCommon { +public: + InferenceOpenCV(std::string protoFile, + std::string weightFile, + std::string userFile); + + ~InferenceOpenCV(); + + // Input Tensor Params + + int SetInputTensorParam() override; + + int SetInputTensorParamNode(std::string node = "input") override; + + int SetInputTensorParamInput(int width, int height, int dim, int ch) override; + + int SetInputTensorParamNorm(double deviation = 1.0, double mean = 0.0) override; + + // Output Tensor Params + int SetOutputTensorParam() override; + + int SetOutputTensorParamThresHold(double threshold) override; + + int SetOutputTensorParamNumbers(int number) override; + + int SetOutputTensorParamType(int type) override; + + int SetOutPutTensorParamNodes(std::string node) override; + + int SetTargetDevice(inference_target_type_e type) override; + + int Load() override; + + int CreateInputLayerPassage() override; + + int PrepareInputLayerPassage() override; + + int PrepareInputLayerPassage(inference_input_type_e type) override; + + int Run(cv::Mat tensor) override; + + int Run(std::vector tensor) override; + + int GetInferenceResult(ImageClassificationResults& results) override; + + int GetInferenceResult(ObjectDetectionResults& results) override; + + int GetInferenceResult(FaceDetectionResults& results) override; + + int GetInferenceResult(FacialLandMarkDetectionResults& results) override; + + int GetInferenceResult(std::vector>& dimInfo, std::vector& results); + + int GetNumberOfOutputs() override; + + void SetUserListName(std::string userList) override; + +public: + int SetUserFile(); + int setInput(cv::Mat cvImg); + +private: + cv::Mat mInputBlob; + cv::Mat mOutputProb; + cv::dnn::Net mNet; /**< Network associated with a network model */ + + int mCh; + int mDim; + cv::Size mInputSize; /**< input tensor size */ + + double mDeviation; + double mMean; + double mThreshold; + int mOutputNumbers; + cv::Size mSourceSize; /**< input image's size */ + + std::string mConfigFile; + std::string mWeightFile; + std::string mUserFile; + std::vector mUserListName; +}; + +} /* InferenceEngineImpl */ +} /* TFImpl */ + +#endif /* __MEDIA_VISION_INFERENCE_OPENCV_H__ */ \ No newline at end of file