From: Dmitry Kurtaev Date: Wed, 11 Jul 2018 09:48:34 +0000 (+0300) Subject: Replace std::vector to std::vector for Java bindings of dnn importers X-Git-Tag: accepted/tizen/6.0/unified/20201030.111113~1^2~600^2~1^2 X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=8b5f061dae9908222bf373e071ac3d6c314dafc1;p=platform%2Fupstream%2Fopencv.git Replace std::vector to std::vector for Java bindings of dnn importers --- diff --git a/modules/dnn/include/opencv2/dnn/dnn.hpp b/modules/dnn/include/opencv2/dnn/dnn.hpp index a32b33d..7cc95ca 100644 --- a/modules/dnn/include/opencv2/dnn/dnn.hpp +++ b/modules/dnn/include/opencv2/dnn/dnn.hpp @@ -649,8 +649,8 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN * @param bufferModel A buffer contains a content of .weights file with learned network. * @returns Net object. */ - CV_EXPORTS_W Net readNetFromDarknet(const std::vector& bufferCfg, - const std::vector& bufferModel = std::vector()); + CV_EXPORTS_W Net readNetFromDarknet(const std::vector& bufferCfg, + const std::vector& bufferModel = std::vector()); /** @brief Reads a network model stored in Darknet model files. * @param bufferCfg A buffer contains a content of .cfg file with text description of the network architecture. @@ -674,8 +674,8 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN * @param bufferModel buffer containing the content of the .caffemodel file * @returns Net object. */ - CV_EXPORTS_W Net readNetFromCaffe(const std::vector& bufferProto, - const std::vector& bufferModel = std::vector()); + CV_EXPORTS_W Net readNetFromCaffe(const std::vector& bufferProto, + const std::vector& bufferModel = std::vector()); /** @brief Reads a network model stored in Caffe model in memory. * @details This is an overloaded member function, provided for convenience. @@ -703,8 +703,8 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN * @param bufferConfig buffer containing the content of the pbtxt file * @returns Net object. */ - CV_EXPORTS_W Net readNetFromTensorflow(const std::vector& bufferModel, - const std::vector& bufferConfig = std::vector()); + CV_EXPORTS_W Net readNetFromTensorflow(const std::vector& bufferModel, + const std::vector& bufferConfig = std::vector()); /** @brief Reads a network model stored in TensorFlow framework's format. * @details This is an overloaded member function, provided for convenience. @@ -778,8 +778,8 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN * @param[in] bufferConfig A buffer with a content of text file contains network configuration. * @returns Net object. */ - CV_EXPORTS_W Net readNet(const String& framework, const std::vector& bufferModel, - const std::vector& bufferConfig = std::vector()); + CV_EXPORTS_W Net readNet(const String& framework, const std::vector& bufferModel, + const std::vector& bufferConfig = std::vector()); /** @brief Loads blob which was serialized as torch.Tensor object of Torch7 framework. * @warning This function has the same limitations as readNetFromTorch(). diff --git a/modules/dnn/misc/java/test/DnnTensorFlowTest.java b/modules/dnn/misc/java/test/DnnTensorFlowTest.java index 5dd4236..4e96c73 100644 --- a/modules/dnn/misc/java/test/DnnTensorFlowTest.java +++ b/modules/dnn/misc/java/test/DnnTensorFlowTest.java @@ -1,10 +1,14 @@ package org.opencv.test.dnn; import java.io.File; +import java.io.FileInputStream; +import java.io.IOException; import java.util.ArrayList; import java.util.List; import org.opencv.core.Core; import org.opencv.core.Mat; +import org.opencv.core.MatOfFloat; +import org.opencv.core.MatOfByte; import org.opencv.core.Scalar; import org.opencv.core.Size; import org.opencv.dnn.DictValue; @@ -26,6 +30,15 @@ public class DnnTensorFlowTest extends OpenCVTestCase { Net net; + private static void normAssert(Mat ref, Mat test) { + final double l1 = 1e-5; + final double lInf = 1e-4; + double normL1 = Core.norm(ref, test, Core.NORM_L1) / ref.total(); + double normLInf = Core.norm(ref, test, Core.NORM_INF) / ref.total(); + assertTrue(normL1 < l1); + assertTrue(normLInf < lInf); + } + @Override protected void setUp() throws Exception { super.setUp(); @@ -46,7 +59,7 @@ public class DnnTensorFlowTest extends OpenCVTestCase { File testDataPath = new File(envTestDataPath); - File f = new File(testDataPath, "dnn/space_shuttle.jpg"); + File f = new File(testDataPath, "dnn/grace_hopper_227.png"); sourceImageFile = f.toString(); if(!f.exists()) throw new Exception("Test image is missing: " + sourceImageFile); @@ -77,31 +90,55 @@ public class DnnTensorFlowTest extends OpenCVTestCase { } - public void testTestNetForward() { - Mat rawImage = Imgcodecs.imread(sourceImageFile); - - assertNotNull("Loading image from file failed!", rawImage); + public void checkInceptionNet(Net net) + { + Mat image = Imgcodecs.imread(sourceImageFile); + assertNotNull("Loading image from file failed!", image); - Mat image = new Mat(); - Imgproc.resize(rawImage, image, new Size(224,224)); - - Mat inputBlob = Dnn.blobFromImage(image); + Mat inputBlob = Dnn.blobFromImage(image, 1.0, new Size(224, 224), new Scalar(0), true, true); assertNotNull("Converting image to blob failed!", inputBlob); - Mat inputBlobP = new Mat(); - Core.subtract(inputBlob, new Scalar(117.0), inputBlobP); - - net.setInput(inputBlobP, "input" ); - - Mat result = net.forward(); + net.setInput(inputBlob, "input"); + Mat result = new Mat(); + try { + net.setPreferableBackend(Dnn.DNN_BACKEND_OPENCV); + result = net.forward("softmax2"); + } + catch (Exception e) { + fail("DNN forward failed: " + e.getMessage()); + } assertNotNull("Net returned no result!", result); - Core.MinMaxLocResult minmax = Core.minMaxLoc(result.reshape(1, 1)); + result = result.reshape(1, 1); + Core.MinMaxLocResult minmax = Core.minMaxLoc(result); + assertEquals("Wrong prediction", (int)minmax.maxLoc.x, 866); + + Mat top5RefScores = new MatOfFloat(new float[] { + 0.63032645f, 0.2561979f, 0.032181446f, 0.015721032f, 0.014785315f + }).reshape(1, 1); - assertTrue("No image recognized!", minmax.maxVal > 0.9); + Core.sort(result, result, Core.SORT_DESCENDING); + normAssert(result.colRange(0, 5), top5RefScores); + } + public void testTestNetForward() { + checkInceptionNet(net); } + public void testReadFromBuffer() { + File modelFile = new File(modelFileName); + byte[] modelBuffer = new byte[ (int)modelFile.length() ]; + + try { + FileInputStream fis = new FileInputStream(modelFile); + fis.read(modelBuffer); + fis.close(); + } catch (IOException e) { + fail("Failed to read a model: " + e.getMessage()); + } + net = Dnn.readNetFromTensorflow(new MatOfByte(modelBuffer)); + checkInceptionNet(net); + } } diff --git a/modules/dnn/src/caffe/caffe_importer.cpp b/modules/dnn/src/caffe/caffe_importer.cpp index b47c586..59f47ee 100644 --- a/modules/dnn/src/caffe/caffe_importer.cpp +++ b/modules/dnn/src/caffe/caffe_importer.cpp @@ -453,10 +453,13 @@ Net readNetFromCaffe(const char *bufferProto, size_t lenProto, return net; } -Net readNetFromCaffe(const std::vector& bufferProto, const std::vector& bufferModel) +Net readNetFromCaffe(const std::vector& bufferProto, const std::vector& bufferModel) { - return readNetFromCaffe(&bufferProto[0], bufferProto.size(), - bufferModel.empty() ? NULL : &bufferModel[0], bufferModel.size()); + const char* bufferProtoPtr = reinterpret_cast(&bufferProto[0]); + const char* bufferModelPtr = bufferModel.empty() ? NULL : + reinterpret_cast(&bufferModel[0]); + return readNetFromCaffe(bufferProtoPtr, bufferProto.size(), + bufferModelPtr, bufferModel.size()); } #endif //HAVE_PROTOBUF diff --git a/modules/dnn/src/darknet/darknet_importer.cpp b/modules/dnn/src/darknet/darknet_importer.cpp index 08083a3..282b372 100644 --- a/modules/dnn/src/darknet/darknet_importer.cpp +++ b/modules/dnn/src/darknet/darknet_importer.cpp @@ -242,10 +242,13 @@ Net readNetFromDarknet(const char *bufferCfg, size_t lenCfg, const char *bufferM return readNetFromDarknet(cfgStream); } -Net readNetFromDarknet(const std::vector& bufferCfg, const std::vector& bufferModel) +Net readNetFromDarknet(const std::vector& bufferCfg, const std::vector& bufferModel) { - return readNetFromDarknet(&bufferCfg[0], bufferCfg.size(), - bufferModel.empty() ? NULL : &bufferModel[0], bufferModel.size()); + const char* bufferCfgPtr = reinterpret_cast(&bufferCfg[0]); + const char* bufferModelPtr = bufferModel.empty() ? NULL : + reinterpret_cast(&bufferModel[0]); + return readNetFromDarknet(bufferCfgPtr, bufferCfg.size(), + bufferModelPtr, bufferModel.size()); } CV__DNN_EXPERIMENTAL_NS_END diff --git a/modules/dnn/src/dnn.cpp b/modules/dnn/src/dnn.cpp index 3803743..21c8693 100644 --- a/modules/dnn/src/dnn.cpp +++ b/modules/dnn/src/dnn.cpp @@ -3047,8 +3047,8 @@ Net readNet(const String& _model, const String& _config, const String& _framewor model + (config.empty() ? "" : ", " + config)); } -Net readNet(const String& _framework, const std::vector& bufferModel, - const std::vector& bufferConfig) +Net readNet(const String& _framework, const std::vector& bufferModel, + const std::vector& bufferConfig) { String framework = _framework.toLowerCase(); if (framework == "caffe") diff --git a/modules/dnn/src/tensorflow/tf_importer.cpp b/modules/dnn/src/tensorflow/tf_importer.cpp index 987d63d..89732b4 100644 --- a/modules/dnn/src/tensorflow/tf_importer.cpp +++ b/modules/dnn/src/tensorflow/tf_importer.cpp @@ -1856,10 +1856,13 @@ Net readNetFromTensorflow(const char* bufferModel, size_t lenModel, return net; } -Net readNetFromTensorflow(const std::vector& bufferModel, const std::vector& bufferConfig) +Net readNetFromTensorflow(const std::vector& bufferModel, const std::vector& bufferConfig) { - return readNetFromCaffe(&bufferModel[0], bufferModel.size(), - bufferConfig.empty() ? NULL : &bufferConfig[0], bufferConfig.size()); + const char* bufferModelPtr = reinterpret_cast(&bufferModel[0]); + const char* bufferConfigPtr = bufferConfig.empty() ? NULL : + reinterpret_cast(&bufferConfig[0]); + return readNetFromTensorflow(bufferModelPtr, bufferModel.size(), + bufferConfigPtr, bufferConfig.size()); } CV__DNN_EXPERIMENTAL_NS_END