TEST_P(DNNTestNetwork, GoogLeNet) { applyTestTag(target == DNN_TARGET_CPU ? "" : CV_TEST_TAG_MEMORY_512MB); processNet("dnn/bvlc_googlenet.caffemodel", "dnn/bvlc_googlenet.prototxt", Size(224, 224), "prob"); expectNoFallbacksFromIE(net); }
TEST_P(Test_ONNX_nets, ResNet50v1) { applyTestTag(CV_TEST_TAG_MEMORY_512MB); // output range: [-67; 75], after Softmax [0, 0.98] testONNXModels("resnet50v1", pb, default_l1, default_lInf, true); }
TEST_P(Test_ONNX_nets, VGG16) { applyTestTag(CV_TEST_TAG_MEMORY_6GB); // > 2.3Gb // output range: [-69; 72], after Softmax [0; 0.96] testONNXModels("vgg16", pb, default_l1, default_lInf, true); }
TEST_P(Test_ONNX_nets, RCNN_ILSVRC13) { applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB); // Reference output values are in range [-4.992, -1.161] testONNXModels("rcnn_ilsvrc13", pb, 0.0045); }
TEST_P(Test_ONNX_nets, DenseNet121) { applyTestTag(CV_TEST_TAG_MEMORY_512MB); // output range: [-87; 138], after Softmax [0; 1] testONNXModels("densenet121", pb, default_l1, default_lInf, true); }
TEST_P(Test_ONNX_nets, VGG16_bn) { applyTestTag(CV_TEST_TAG_MEMORY_6GB); // > 2.3Gb // output range: [-16; 27], after Softmax [0; 0.67] const double lInf = (target == DNN_TARGET_MYRIAD) ? 0.038 : default_lInf; testONNXModels("vgg16-bn", pb, default_l1, lInf, true); }
TEST_P(DNNTestNetwork, ENet) { applyTestTag(target == DNN_TARGET_CPU ? "" : CV_TEST_TAG_MEMORY_512MB); if ((backend == DNN_BACKEND_INFERENCE_ENGINE) || (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16)) throw SkipTestException(""); processNet("dnn/Enet-model-best.net", "", Size(512, 512), "l367_Deconvolution", target == DNN_TARGET_OPENCL ? "dnn/halide_scheduler_opencl_enet.yml" : "dnn/halide_scheduler_enet.yml", 2e-5, 0.15); }
TEST_P(DNNTestNetwork, MobileNet_SSD_v2_TensorFlow) { applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB); if (backend == DNN_BACKEND_HALIDE) throw SkipTestException(""); Mat sample = imread(findDataFile("dnn/street.png", false)); Mat inp = blobFromImage(sample, 1.0f, Size(300, 300), Scalar(), false); float l1 = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.013 : 2e-5; float lInf = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.062 : 0.0; processNet("dnn/ssd_mobilenet_v2_coco_2018_03_29.pb", "dnn/ssd_mobilenet_v2_coco_2018_03_29.pbtxt", inp, "detection_out", "", l1, lInf, 0.25); expectNoFallbacksFromIE(net); }
TEST_P(DNNTestNetwork, SSD_VGG16) { applyTestTag(CV_TEST_TAG_LONG, (target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_1GB : CV_TEST_TAG_MEMORY_2GB), CV_TEST_TAG_DEBUG_VERYLONG); if (backend == DNN_BACKEND_HALIDE && target == DNN_TARGET_CPU) throw SkipTestException(""); double scoreThreshold = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.0325 : 0.0; const float lInf = (target == DNN_TARGET_MYRIAD) ? 0.032 : 0.0; Mat sample = imread(findDataFile("dnn/street.png", false)); Mat inp = blobFromImage(sample, 1.0f, Size(300, 300), Scalar(), false); processNet("dnn/VGG_ILSVRC2016_SSD_300x300_iter_440000.caffemodel", "dnn/ssd_vgg16.prototxt", inp, "detection_out", "", scoreThreshold, lInf); expectNoFallbacksFromIE(net); }
TEST_P(DNNTestNetwork, MobileNet_SSD_Caffe) { applyTestTag(CV_TEST_TAG_MEMORY_512MB); if (backend == DNN_BACKEND_HALIDE) throw SkipTestException(""); Mat sample = imread(findDataFile("dnn/street.png", false)); Mat inp = blobFromImage(sample, 1.0f / 127.5, Size(300, 300), Scalar(127.5, 127.5, 127.5), false); float diffScores = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 1.5e-2 : 0.0; float diffSquares = (target == DNN_TARGET_MYRIAD) ? 0.063 : 0.0; float detectionConfThresh = (target == DNN_TARGET_MYRIAD) ? 0.252 : FLT_MIN; processNet("dnn/MobileNetSSD_deploy.caffemodel", "dnn/MobileNetSSD_deploy.prototxt", inp, "detection_out", "", diffScores, diffSquares, detectionConfThresh); expectNoFallbacksFromIE(net); }
TEST_P(DNNTestNetwork, Inception_5h) { applyTestTag(CV_TEST_TAG_MEMORY_512MB); double l1 = default_l1, lInf = default_lInf; if (backend == DNN_BACKEND_INFERENCE_ENGINE && (target == DNN_TARGET_CPU || target == DNN_TARGET_OPENCL)) { l1 = 1.72e-5; lInf = 8e-4; } processNet("dnn/tensorflow_inception_graph.pb", "", Size(224, 224), "softmax2", target == DNN_TARGET_OPENCL ? "dnn/halide_scheduler_opencl_inception_5h.yml" : "dnn/halide_scheduler_inception_5h.yml", l1, lInf); expectNoFallbacksFromIE(net); }
TEST_P(DNNTestNetwork, OpenPose_pose_mpi_faster_4_stages) { applyTestTag(CV_TEST_TAG_LONG, CV_TEST_TAG_MEMORY_1GB); if (backend == DNN_BACKEND_HALIDE) throw SkipTestException(""); #if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LE(2018050000) if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X) throw SkipTestException("Test is disabled for OpenVINO <= 2018R5 + MyriadX target"); #endif // The same .caffemodel but modified .prototxt // See https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/src/openpose/pose/poseParameters.cpp processNet("dnn/openpose_pose_mpi.caffemodel", "dnn/openpose_pose_mpi_faster_4_stages.prototxt", Size(46, 46)); expectNoFallbacksFromIE(net); }
TEST_P(Test_ONNX_nets, ResNet101_DUC_HDC) { applyTestTag(CV_TEST_TAG_VERYLONG); #if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000) if (backend == DNN_BACKEND_INFERENCE_ENGINE) throw SkipTestException("Test is disabled for DLIE targets"); #endif #if defined(INF_ENGINE_RELEASE) if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD) throw SkipTestException("Test is disabled for Myriad targets"); #endif if (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_OPENCL) throw SkipTestException("Test is disabled for OpenCL targets"); testONNXModels("resnet101_duc_hdc", pb); }
TEST_P(DNNTestNetwork, OpenPose_pose_mpi) { applyTestTag(CV_TEST_TAG_LONG, (target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_1GB : CV_TEST_TAG_MEMORY_2GB), CV_TEST_TAG_DEBUG_VERYLONG); if (backend == DNN_BACKEND_HALIDE) throw SkipTestException(""); #if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LE(2018050000) if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X) throw SkipTestException("Test is disabled for OpenVINO <= 2018R5 + MyriadX target"); #endif // output range: [-0.001, 0.97] const float l1 = (target == DNN_TARGET_MYRIAD) ? 0.012 : 0.0; const float lInf = (target == DNN_TARGET_MYRIAD || target == DNN_TARGET_OPENCL_FP16) ? 0.16 : 0.0; processNet("dnn/openpose_pose_mpi.caffemodel", "dnn/openpose_pose_mpi.prototxt", Size(46, 46), "", "", l1, lInf); expectNoFallbacksFromIE(net); }
TEST_P(DNNTestNetwork, DenseNet_121) { applyTestTag(CV_TEST_TAG_MEMORY_512MB); if (backend == DNN_BACKEND_HALIDE) throw SkipTestException(""); // Reference output values are in range [-3.807, 4.605] float l1 = 0.0, lInf = 0.0; if (target == DNN_TARGET_OPENCL_FP16) { l1 = 9e-3; lInf = 5e-2; } else if (target == DNN_TARGET_MYRIAD) { l1 = 0.1; lInf = 0.6; } processNet("dnn/DenseNet_121.caffemodel", "dnn/DenseNet_121.prototxt", Size(224, 224), "", "", l1, lInf); expectNoFallbacksFromIE(net); }
TEST_P(Test_ONNX_nets, LResNet100E_IR) { applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB); if (backend == DNN_BACKEND_INFERENCE_ENGINE && (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_OPENCL || target == DNN_TARGET_MYRIAD)) throw SkipTestException(""); double l1 = default_l1; double lInf = default_lInf; // output range: [-3; 3] if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16) { l1 = 0.009; lInf = 0.035; } else if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_CPU) { l1 = 4.6e-5; lInf = 1.9e-4; } testONNXModels("LResNet100E_IR", pb, l1, lInf); }
TEST_P(DNNTestNetwork, Inception_v2_SSD_TensorFlow) { applyTestTag( (target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB), CV_TEST_TAG_DEBUG_LONG ); #if defined(INF_ENGINE_RELEASE) if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X) throw SkipTestException("Test is disabled for MyriadX"); #endif if (backend == DNN_BACKEND_HALIDE) throw SkipTestException(""); Mat sample = imread(findDataFile("dnn/street.png", false)); Mat inp = blobFromImage(sample, 1.0f, Size(300, 300), Scalar(), false); float l1 = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.015 : 0.0; float lInf = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.0731 : 0.0; processNet("dnn/ssd_inception_v2_coco_2017_11_17.pb", "dnn/ssd_inception_v2_coco_2017_11_17.pbtxt", inp, "detection_out", "", l1, lInf); expectNoFallbacksFromIE(net); }
TEST_P(Test_ONNX_nets, Alexnet) { applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB); const String model = _tf("models/alexnet.onnx"); Net net = readNetFromONNX(model); ASSERT_FALSE(net.empty()); net.setPreferableBackend(backend); net.setPreferableTarget(target); Mat inp = imread(_tf("../grace_hopper_227.png")); Mat ref = blobFromNPY(_tf("../caffe_alexnet_prob.npy")); checkBackend(&inp, &ref); net.setInput(blobFromImage(inp, 1.0f, Size(227, 227), Scalar(), false)); ASSERT_FALSE(net.empty()); Mat out = net.forward(); normAssert(out, ref, "", default_l1, default_lInf); expectNoFallbacksFromIE(net); }
TEST_P(DNNTestNetwork, FastNeuralStyle_eccv16) { applyTestTag(CV_TEST_TAG_MEMORY_512MB, CV_TEST_TAG_DEBUG_VERYLONG); if (backend == DNN_BACKEND_HALIDE || (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)) throw SkipTestException(""); #if defined(INF_ENGINE_RELEASE) #if INF_ENGINE_RELEASE <= 2018050000 if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL) throw SkipTestException(""); #endif #endif Mat img = imread(findDataFile("dnn/googlenet_1.png", false)); Mat inp = blobFromImage(img, 1.0, Size(320, 240), Scalar(103.939, 116.779, 123.68), false, false); // Output image has values in range [-143.526, 148.539]. float l1 = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.4 : 4e-5; float lInf = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 7.28 : 2e-3; processNet("dnn/fast_neural_style_eccv16_starry_night.t7", "", inp, "", "", l1, lInf); }
TEST_P(Test_ONNX_nets, TinyYolov2) { applyTestTag(CV_TEST_TAG_MEMORY_512MB); if (cvtest::skipUnstableTests) throw SkipTestException("Skip unstable test"); #if defined(INF_ENGINE_RELEASE) if (backend == DNN_BACKEND_INFERENCE_ENGINE && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16) ) throw SkipTestException("Test is disabled for DLIE OpenCL targets"); if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X ) throw SkipTestException("Test is disabled for MyriadX"); #endif // output range: [-11; 8] double l1 = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.017 : default_l1; double lInf = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.14 : default_lInf; testONNXModels("tiny_yolo2", pb, l1, lInf); }
TEST_P(Test_ONNX_nets, ZFNet) { applyTestTag(CV_TEST_TAG_MEMORY_2GB); testONNXModels("zfnet512", pb); }
TEST_P(Test_ONNX_nets, CaffeNet) { applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB); testONNXModels("caffenet", pb); }
TEST_P(Test_ONNX_nets, ZFNet) { applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB); testONNXModels("zfnet512", pb); }