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Merge pull request #12913 from dkurt:dnn_fix_ie_hyperparams

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Alexander Alekhin
2018-11-16 18:36:12 +00:00
parent 1c04a5ec47 b5c54e447c
commit f2bec05e6d
18 changed files with 136 additions and 18 deletions
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modules/dnn/test/test_backends.cpp
+2 -2
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@@ -174,7 +174,7 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_v2_TensorFlow)
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) ? 0.011 : 0.0;
float l1 = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.013 : 0.0;
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);
@@ -184,7 +184,7 @@ TEST_P(DNNTestNetwork, SSD_VGG16)
{
if (backend == DNN_BACKEND_HALIDE && target == DNN_TARGET_CPU)
throw SkipTestException("");
double scoreThreshold = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.0252 : 0.0;
double scoreThreshold = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.0325 : 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",
modules/dnn/test/test_caffe_importer.cpp
+5 -1
View File
@@ -512,7 +512,11 @@ INSTANTIATE_TEST_CASE_P(Test_Caffe, opencv_face_detector,
TEST_P(Test_Caffe_nets, FasterRCNN_vgg16)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
if ((backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE > 2018030000
|| (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL_FP16)
#endif
)
throw SkipTestException("");
static Mat ref = (Mat_<float>(3, 7) << 0, 2, 0.949398, 99.2454, 210.141, 601.205, 462.849,
0, 7, 0.997022, 481.841, 92.3218, 722.685, 175.953,
modules/dnn/test/test_darknet_importer.cpp
+3
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@@ -306,6 +306,9 @@ TEST_P(Test_Darknet_nets, TinyYoloVoc)
// batch size 1
testDarknetModel(config_file, weights_file, ref.rowRange(0, 2), scoreDiff, iouDiff);
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE == 2018040000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target != DNN_TARGET_MYRIAD)
#endif
// batch size 2
testDarknetModel(config_file, weights_file, ref, scoreDiff, iouDiff);
}
modules/dnn/test/test_halide_layers.cpp
+5
View File
@@ -166,6 +166,11 @@ TEST_P(Deconvolution, Accuracy)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_CPU &&
dilation.width == 2 && dilation.height == 2)
throw SkipTestException("");
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE == 2018040000
if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_CPU &&
hasBias && group != 1)
throw SkipTestException("Test is disabled for OpenVINO 2018R4");
#endif
int sz[] = {inChannels, outChannels / group, kernel.height, kernel.width};
Mat weights(4, &sz[0], CV_32F);
modules/dnn/test/test_ie_models.cpp
+10
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@@ -177,10 +177,20 @@ TEST_P(DNNTestOpenVINO, models)
Target target = (dnn::Target)(int)get<0>(GetParam());
std::string modelName = get<1>(GetParam());
#ifdef INF_ENGINE_RELEASE
#if INF_ENGINE_RELEASE <= 2018030000
if (target == DNN_TARGET_MYRIAD && (modelName == "landmarks-regression-retail-0001" ||
modelName == "semantic-segmentation-adas-0001" ||
modelName == "face-reidentification-retail-0001"))
throw SkipTestException("");
#elif INF_ENGINE_RELEASE == 2018040000
if (modelName == "single-image-super-resolution-0034" ||
(target == DNN_TARGET_MYRIAD && (modelName == "license-plate-recognition-barrier-0001" ||
modelName == "landmarks-regression-retail-0009" ||
modelName == "semantic-segmentation-adas-0001")))
throw SkipTestException("");
#endif
#endif
std::string precision = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? "FP16" : "FP32";
std::string prefix = utils::fs::join("intel_models",
modules/dnn/test/test_layers.cpp
+4
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@@ -137,6 +137,10 @@ TEST_P(Test_Caffe_layers, Convolution)
TEST_P(Test_Caffe_layers, DeConvolution)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE == 2018040000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_CPU)
throw SkipTestException("Test is disabled for OpenVINO 2018R4");
#endif
testLayerUsingCaffeModels("layer_deconvolution", true, false);
}
modules/dnn/test/test_tf_importer.cpp
+1 -1
View File
@@ -475,7 +475,7 @@ TEST_P(Test_TensorFlow_nets, EAST_text_detection)
double l1_geometry = default_l1, lInf_geometry = default_lInf;
if (target == DNN_TARGET_OPENCL_FP16)
{
lInf_scores = 0.11;
lInf_scores = backend == DNN_BACKEND_INFERENCE_ENGINE ? 0.16 : 0.11;
l1_geometry = 0.28; lInf_geometry = 5.94;
}
else if (target == DNN_TARGET_MYRIAD)
modules/dnn/test/test_torch_importer.cpp
+8
View File
@@ -136,6 +136,10 @@ TEST_P(Test_Torch_layers, run_reshape_change_batch_size)
TEST_P(Test_Torch_layers, run_reshape)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE == 2018040000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is disabled for OpenVINO 2018R4");
#endif
runTorchNet("net_reshape_batch");
runTorchNet("net_reshape_channels", "", false, true);
}
@@ -168,6 +172,10 @@ TEST_P(Test_Torch_layers, run_depth_concat)
TEST_P(Test_Torch_layers, run_deconv)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE == 2018040000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is disabled for OpenVINO 2018R4");
#endif
runTorchNet("net_deconv");
}