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Merge remote-tracking branch 'upstream/3.4' into merge-3.4

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This commit is contained in:
Alexander Alekhin 2019-04-03 19:33:52 +00:00
commit 4001346a30
18 changed files with 166 additions and 60 deletions
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16
3rdparty/ffmpeg/ffmpeg-download.ps1.in vendored
View File

@ -12,6 +12,22 @@ Write-Output ("=" * 120)
Write-Output ""
if(![System.IO.File]::Exists($output)) {
try {
[io.file]::OpenWrite($output).close()
} catch {
Write-Warning "Unable to write: $output"
if (!([Security.Principal.WindowsPrincipal][Security.Principal.WindowsIdentity]::GetCurrent()).IsInRole([Security.Principal.WindowsBuiltInRole] "Administrator")) {
Write-Warning "Launching with 'Administrator' elevated privileges..."
Pause
Start-Process powershell.exe "-NoProfile -ExecutionPolicy Bypass -File `"$PSCommandPath`"" -Verb RunAs
exit
} else {
Write-Output "FATAL: Unable to write with elevated privileges: $output"
Pause
exit 1
}
}
try {
Write-Output ("Downloading: " + $output)
Import-Module BitsTransfer

2
3rdparty/libpng/CMakeLists.txt vendored
View File

@ -84,4 +84,4 @@ if(NOT BUILD_SHARED_LIBS)
ocv_install_target(${PNG_LIBRARY} EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT dev)
endif()
ocv_install_3rdparty_licenses(libpng LICENSE README opencv-libpng.patch)
ocv_install_3rdparty_licenses(libpng LICENSE README)

4
cmake/OpenCVDetectInferenceEngine.cmake
View File

@ -87,9 +87,9 @@ endif()
if(INF_ENGINE_TARGET)
if(NOT INF_ENGINE_RELEASE)
message(WARNING "InferenceEngine version have not been set, 2018R5 will be used by default. Set INF_ENGINE_RELEASE variable if you experience build errors.")
message(WARNING "InferenceEngine version have not been set, 2019R1 will be used by default. Set INF_ENGINE_RELEASE variable if you experience build errors.")
endif()
set(INF_ENGINE_RELEASE "2018050000" CACHE STRING "Force IE version, should be in form YYYYAABBCC (e.g. 2018R2.0.2 -> 2018020002)")
set(INF_ENGINE_RELEASE "2019010000" CACHE STRING "Force IE version, should be in form YYYYAABBCC (e.g. 2018R2.0.2 -> 2018020002)")
set_target_properties(${INF_ENGINE_TARGET} PROPERTIES
INTERFACE_COMPILE_DEFINITIONS "HAVE_INF_ENGINE=1;INF_ENGINE_RELEASE=${INF_ENGINE_RELEASE}"
)

7
cmake/OpenCVFindIPP.cmake
View File

@ -245,7 +245,12 @@ if(NOT DEFINED IPPROOT)
return()
endif()
set(IPPROOT "${ICV_PACKAGE_ROOT}/icv")
ocv_install_3rdparty_licenses(ippicv "${IPPROOT}/readme.htm" "${ICV_PACKAGE_ROOT}/EULA.txt")
ocv_install_3rdparty_licenses(ippicv "${IPPROOT}/readme.htm")
if(WIN32)
ocv_install_3rdparty_licenses(ippicv "${ICV_PACKAGE_ROOT}/EULA.rtf")
else()
ocv_install_3rdparty_licenses(ippicv "${ICV_PACKAGE_ROOT}/EULA.txt")
endif()
endif()
file(TO_CMAKE_PATH "${IPPROOT}" __IPPROOT)

6
cmake/OpenCVFindIPPIW.cmake
View File

@ -148,9 +148,13 @@ if(BUILD_IPP_IW)
set(IPPIW_ROOT "${IPPROOT}/../iw")
ocv_install_3rdparty_licenses(ippiw
"${IPPIW_ROOT}/../EULA.txt"
"${IPPIW_ROOT}/../support.txt"
"${IPPIW_ROOT}/../third-party-programs.txt")
if(WIN32)
ocv_install_3rdparty_licenses(ippiw "${IPPIW_ROOT}/../EULA.rtf")
else()
ocv_install_3rdparty_licenses(ippiw "${IPPIW_ROOT}/../EULA.txt")
endif()
# Package sources
get_filename_component(__PATH "${IPPROOT}/../iw/" ABSOLUTE)

8
cmake/OpenCVUtils.cmake
View File

@ -1200,13 +1200,17 @@ endfunction()
# ocv_install_3rdparty_licenses(<library-name> <filename1> [<filename2> ..])
function(ocv_install_3rdparty_licenses library)
foreach(filename ${ARGN})
set(filepath "${filename}")
if(NOT IS_ABSOLUTE "${filepath}")
set(filepath "${CMAKE_CURRENT_LIST_DIR}/${filepath}")
endif()
get_filename_component(name "${filename}" NAME)
install(
FILES "${filename}"
FILES "${filepath}"
DESTINATION "${OPENCV_LICENSES_INSTALL_PATH}"
COMPONENT licenses
RENAME "${library}-${name}"
OPTIONAL)
)
endforeach()
endfunction()

4
modules/dnn/perf/perf_net.cpp
View File

@ -222,6 +222,10 @@ PERF_TEST_P_(DNNTestNetwork, FastNeuralStyle_eccv16)
PERF_TEST_P_(DNNTestNetwork, Inception_v2_Faster_RCNN)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled in OpenVINO 2019R1");
#endif
if (backend == DNN_BACKEND_HALIDE ||
(backend == DNN_BACKEND_INFERENCE_ENGINE && target != DNN_TARGET_CPU) ||
(backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16))

15
modules/dnn/src/dnn.cpp
View File

@ -253,7 +253,7 @@ void blobFromImages(InputArrayOfArrays images_, OutputArray blob_, double scalef
std::vector<Mat> images;
images_.getMatVector(images);
CV_Assert(!images.empty());
for (int i = 0; i < images.size(); i++)
for (size_t i = 0; i < images.size(); i++)
{
Size imgSize = images[i].size();
if (size == Size())
@ -283,11 +283,10 @@ void blobFromImages(InputArrayOfArrays images_, OutputArray blob_, double scalef
images[i] *= scalefactor;
}
size_t i, nimages = images.size();
size_t nimages = images.size();
Mat image0 = images[0];
int nch = image0.channels();
CV_Assert(image0.dims == 2);
Mat image;
if (nch == 3 || nch == 4)
{
int sz[] = { (int)nimages, nch, image0.rows, image0.cols };
@ -295,9 +294,9 @@ void blobFromImages(InputArrayOfArrays images_, OutputArray blob_, double scalef
Mat blob = blob_.getMat();
Mat ch[4];
for( i = 0; i < nimages; i++ )
for(size_t i = 0; i < nimages; i++ )
{
image = images[i];
const Mat& image = images[i];
CV_Assert(image.depth() == blob_.depth());
nch = image.channels();
CV_Assert(image.dims == 2 && (nch == 3 || nch == 4));
@ -317,9 +316,9 @@ void blobFromImages(InputArrayOfArrays images_, OutputArray blob_, double scalef
blob_.create(4, sz, ddepth);
Mat blob = blob_.getMat();
for( i = 0; i < nimages; i++ )
for(size_t i = 0; i < nimages; i++ )
{
Mat image = images[i];
const Mat& image = images[i];
CV_Assert(image.depth() == blob_.depth());
nch = image.channels();
CV_Assert(image.dims == 2 && (nch == 1));
@ -1700,7 +1699,7 @@ struct Net::Impl
preferableTarget == DNN_TARGET_MYRIAD ||
preferableTarget == DNN_TARGET_FPGA) && !fused)
{
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
for (const std::string& name : {"weights", "biases"})
{
auto it = ieNode->layer.getParameters().find(name);

2
modules/dnn/src/layers/normalize_bbox_layer.cpp
View File

@ -290,7 +290,7 @@ public:
weights = wrapToInfEngineBlob(blobs[0], {(size_t)numChannels}, InferenceEngine::Layout::C);
l.getParameters()["channel_shared"] = blobs[0].total() == 1;
}
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
l.getParameters()["weights"] = weights;
#else
l.addConstantData("weights", weights);

8
modules/dnn/src/op_inf_engine.cpp
View File

@ -130,7 +130,7 @@ void InfEngineBackendNet::init(int targetId)
for (int id : unconnectedLayersIds)
{
InferenceEngine::Builder::OutputLayer outLayer("myconv1");
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
// Inference Engine determines network precision by ports.
InferenceEngine::Precision p = (targetId == DNN_TARGET_MYRIAD ||
targetId == DNN_TARGET_OPENCL_FP16) ?
@ -188,7 +188,7 @@ void InfEngineBackendNet::init(int targetId)
void InfEngineBackendNet::addLayer(InferenceEngine::Builder::Layer& layer)
{
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
// Add weights to network and connect them after input blobs.
std::map<std::string, InferenceEngine::Parameter>& params = layer.getParameters();
std::vector<int> blobsIds;
@ -229,7 +229,7 @@ void InfEngineBackendNet::addLayer(InferenceEngine::Builder::Layer& layer)
CV_Assert(layers.insert({layerName, id}).second);
unconnectedLayersIds.insert(id);
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
// By default, all the weights are connected to last ports ids.
for (int i = 0; i < blobsIds.size(); ++i)
{
@ -903,7 +903,7 @@ InferenceEngine::Blob::Ptr convertFp16(const InferenceEngine::Blob::Ptr& blob)
void addConstantData(const std::string& name, InferenceEngine::Blob::Ptr data,
InferenceEngine::Builder::Layer& l)
{
#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R5)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
l.getParameters()[name] = data;
#else
l.addConstantData(name, data);

5
modules/dnn/src/op_inf_engine.hpp
View File

@ -27,10 +27,11 @@
#define INF_ENGINE_RELEASE_2018R3 2018030000
#define INF_ENGINE_RELEASE_2018R4 2018040000
#define INF_ENGINE_RELEASE_2018R5 2018050000
#define INF_ENGINE_RELEASE_2019R1 2019010000
#ifndef INF_ENGINE_RELEASE
#warning("IE version have not been provided via command-line. Using 2018R5 by default")
#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2018R5
#warning("IE version have not been provided via command-line. Using 2019R1 by default")
#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2019R1
#endif
#define INF_ENGINE_VER_MAJOR_GT(ver) (((INF_ENGINE_RELEASE) / 10000) > ((ver) / 10000))

2
modules/dnn/test/test_backends.cpp
View File

@ -289,7 +289,7 @@ TEST_P(DNNTestNetwork, OpenFace)
#if INF_ENGINE_VER_MAJOR_EQ(2018050000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is disabled for Myriad targets");
#elif INF_ENGINE_VER_MAJOR_GT(2018050000)
#elif INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X
)

2
modules/dnn/test/test_darknet_importer.cpp
View File

@ -267,7 +267,7 @@ public:
TEST_P(Test_Darknet_nets, YoloVoc)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL_FP16)
throw SkipTestException("Test is disabled");
#endif

12
modules/dnn/test/test_halide_layers.cpp
View File

@ -169,7 +169,7 @@ TEST_P(Deconvolution, Accuracy)
throw SkipTestException("Test is disabled for OpenVINO 2018R4");
#endif
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X
&& inChannels == 6 && outChannels == 4 && group == 1
@ -351,7 +351,7 @@ TEST_P(MaxPooling, Accuracy)
throw SkipTestException("Problems with output dimension in OpenVINO 2018R5");
#endif
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X
&& (stride == Size(1, 1) || stride == Size(2, 2))
@ -561,7 +561,7 @@ TEST_P(ReLU, Accuracy)
float negativeSlope = get<0>(GetParam());
Backend backendId = get<0>(get<1>(GetParam()));
Target targetId = get<1>(get<1>(GetParam()));
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE
&& negativeSlope < 0
)
@ -589,7 +589,7 @@ TEST_P(NoParamActivation, Accuracy)
LayerParams lp;
lp.type = get<0>(GetParam());
lp.name = "testLayer";
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE
&& lp.type == "AbsVal"
)
@ -688,7 +688,7 @@ TEST_P(Concat, Accuracy)
throw SkipTestException("Test is disabled for Myriad target"); // crash
#endif
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_CPU
&& inSize == Vec3i(1, 4, 5) && numChannels == Vec3i(1, 6, 2)
)
@ -769,7 +769,7 @@ TEST_P(Eltwise, Accuracy)
throw SkipTestException("Test is disabled for Myriad target");
#endif
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE && numConv > 1)
throw SkipTestException("Test is disabled for DLIE backend");
#endif

115
modules/dnn/test/test_ie_models.cpp
View File

@ -21,9 +21,18 @@ static void initDLDTDataPath()
static bool initialized = false;
if (!initialized)
{
#if INF_ENGINE_RELEASE <= 2018050000
const char* dldtTestDataPath = getenv("INTEL_CVSDK_DIR");
if (dldtTestDataPath)
cvtest::addDataSearchPath(cv::utils::fs::join(dldtTestDataPath, "deployment_tools"));
cvtest::addDataSearchPath(dldtTestDataPath);
#else
const char* omzDataPath = getenv("OPENCV_OPEN_MODEL_ZOO_DATA_PATH");
if (omzDataPath)
cvtest::addDataSearchPath(omzDataPath);
const char* dnnDataPath = getenv("OPENCV_DNN_TEST_DATA_PATH");
if (dnnDataPath)
cvtest::addDataSearchPath(std::string(dnnDataPath) + "/omz_intel_models");
#endif
initialized = true;
}
#endif
@ -33,6 +42,76 @@ using namespace cv;
using namespace cv::dnn;
using namespace InferenceEngine;
struct OpenVINOModelTestCaseInfo
{
const char* modelPathFP32;
const char* modelPathFP16;
};
static const std::map<std::string, OpenVINOModelTestCaseInfo>& getOpenVINOTestModels()
{
static std::map<std::string, OpenVINOModelTestCaseInfo> g_models {
#if INF_ENGINE_RELEASE <= 2018050000
{ "age-gender-recognition-retail-0013", {
"deployment_tools/intel_models/age-gender-recognition-retail-0013/FP32/age-gender-recognition-retail-0013",
"deployment_tools/intel_models/age-gender-recognition-retail-0013/FP16/age-gender-recognition-retail-0013"
}},
{ "face-person-detection-retail-0002", {
"deployment_tools/intel_models/face-person-detection-retail-0002/FP32/face-person-detection-retail-0002",
"deployment_tools/intel_models/face-person-detection-retail-0002/FP16/face-person-detection-retail-0002"
}},
{ "head-pose-estimation-adas-0001", {
"deployment_tools/intel_models/head-pose-estimation-adas-0001/FP32/head-pose-estimation-adas-0001",
"deployment_tools/intel_models/head-pose-estimation-adas-0001/FP16/head-pose-estimation-adas-0001"
}},
{ "person-detection-retail-0002", {
"deployment_tools/intel_models/person-detection-retail-0002/FP32/person-detection-retail-0002",
"deployment_tools/intel_models/person-detection-retail-0002/FP16/person-detection-retail-0002"
}},
{ "vehicle-detection-adas-0002", {
"deployment_tools/intel_models/vehicle-detection-adas-0002/FP32/vehicle-detection-adas-0002",
"deployment_tools/intel_models/vehicle-detection-adas-0002/FP16/vehicle-detection-adas-0002"
}}
#else
// layout is defined by open_model_zoo/model_downloader
// Downloaded using these parameters for Open Model Zoo downloader (2019R1):
// ./downloader.py -o ${OPENCV_DNN_TEST_DATA_PATH}/omz_intel_models --cache_dir ${OPENCV_DNN_TEST_DATA_PATH}/.omz_cache/ \
// --name face-person-detection-retail-0002,face-person-detection-retail-0002-fp16,age-gender-recognition-retail-0013,age-gender-recognition-retail-0013-fp16,head-pose-estimation-adas-0001,head-pose-estimation-adas-0001-fp16,person-detection-retail-0002,person-detection-retail-0002-fp16,vehicle-detection-adas-0002,vehicle-detection-adas-0002-fp16
{ "age-gender-recognition-retail-0013", {
"Retail/object_attributes/age_gender/dldt/age-gender-recognition-retail-0013",
"Retail/object_attributes/age_gender/dldt/age-gender-recognition-retail-0013-fp16"
}},
{ "face-person-detection-retail-0002", {
"Retail/object_detection/face_pedestrian/rmnet-ssssd-2heads/0002/dldt/face-person-detection-retail-0002",
"Retail/object_detection/face_pedestrian/rmnet-ssssd-2heads/0002/dldt/face-person-detection-retail-0002-fp16"
}},
{ "head-pose-estimation-adas-0001", {
"Transportation/object_attributes/headpose/vanilla_cnn/dldt/head-pose-estimation-adas-0001",
"Transportation/object_attributes/headpose/vanilla_cnn/dldt/head-pose-estimation-adas-0001-fp16"
}},
{ "person-detection-retail-0002", {
"Retail/object_detection/pedestrian/hypernet-rfcn/0026/dldt/person-detection-retail-0002",
"Retail/object_detection/pedestrian/hypernet-rfcn/0026/dldt/person-detection-retail-0002-fp16"
}},
{ "vehicle-detection-adas-0002", {
"Transportation/object_detection/vehicle/mobilenet-reduced-ssd/dldt/vehicle-detection-adas-0002",
"Transportation/object_detection/vehicle/mobilenet-reduced-ssd/dldt/vehicle-detection-adas-0002-fp16"
}}
#endif
};
return g_models;
}
static const std::vector<std::string> getOpenVINOTestModelsList()
{
std::vector<std::string> result;
const std::map<std::string, OpenVINOModelTestCaseInfo>& models = getOpenVINOTestModels();
for (const auto& it : models)
result.push_back(it.first);
return result;
}
static inline void genData(const std::vector<size_t>& dims, Mat& m, Blob::Ptr& dataPtr)
{
std::vector<int> reversedDims(dims.begin(), dims.end());
@ -172,25 +251,23 @@ void runCV(Target target, const std::string& xmlPath, const std::string& binPath
}
}
typedef TestWithParam<tuple<Target, String> > DNNTestOpenVINO;
typedef TestWithParam<tuple<Target, std::string> > DNNTestOpenVINO;
TEST_P(DNNTestOpenVINO, models)
{
initDLDTDataPath();
Target target = (dnn::Target)(int)get<0>(GetParam());
std::string modelName = get<1>(GetParam());
std::string precision = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? "FP16" : "FP32";
std::string prefix;
bool isFP16 = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD);
#ifdef INF_ENGINE_RELEASE
#if INF_ENGINE_RELEASE <= 2018050000
prefix = utils::fs::join("intel_models",
utils::fs::join(modelName,
utils::fs::join(precision, modelName)));
#endif
#endif
const std::map<std::string, OpenVINOModelTestCaseInfo>& models = getOpenVINOTestModels();
const auto it = models.find(modelName);
ASSERT_TRUE(it != models.end()) << modelName;
OpenVINOModelTestCaseInfo modelInfo = it->second;
std::string modelPath = isFP16 ? modelInfo.modelPathFP16 : modelInfo.modelPathFP32;
initDLDTDataPath();
std::string xmlPath = findDataFile(prefix + ".xml");
std::string binPath = findDataFile(prefix + ".bin");
std::string xmlPath = findDataFile(modelPath + ".xml");
std::string binPath = findDataFile(modelPath + ".bin");
std::map<std::string, cv::Mat> inputsMap;
std::map<std::string, cv::Mat> ieOutputsMap, cvOutputsMap;
@ -210,16 +287,12 @@ TEST_P(DNNTestOpenVINO, models)
}
}
INSTANTIATE_TEST_CASE_P(/**/,
DNNTestOpenVINO,
Combine(testing::ValuesIn(getAvailableTargets(DNN_BACKEND_INFERENCE_ENGINE)),
testing::Values(
"age-gender-recognition-retail-0013",
"face-person-detection-retail-0002",
"head-pose-estimation-adas-0001",
"person-detection-retail-0002",
"vehicle-detection-adas-0002"
))
testing::ValuesIn(getOpenVINOTestModelsList())
)
);
}}

4
modules/dnn/test/test_layers.cpp
View File

@ -236,7 +236,7 @@ TEST_P(Test_Caffe_layers, Dropout)
TEST_P(Test_Caffe_layers, Concat)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is disabled for Myriad targets");
#endif
@ -247,7 +247,7 @@ TEST_P(Test_Caffe_layers, Concat)
TEST_P(Test_Caffe_layers, Fused_Concat)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE due negative_slope parameter");
#endif

2
modules/dnn/test/test_onnx_importer.cpp
View File

@ -319,7 +319,7 @@ TEST_P(Test_ONNX_nets, ResNet50v1)
TEST_P(Test_ONNX_nets, ResNet101_DUC_HDC)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#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

12
modules/dnn/test/test_tf_importer.cpp
View File

@ -140,7 +140,7 @@ TEST_P(Test_TensorFlow_layers, padding)
TEST_P(Test_TensorFlow_layers, padding_same)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE");
#endif
@ -197,7 +197,7 @@ TEST_P(Test_TensorFlow_layers, pooling)
TEST_P(Test_TensorFlow_layers, ave_pool_same)
{
// Reference output values are in range [-0.519531, 0.112976]
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X
)
@ -241,7 +241,7 @@ TEST_P(Test_TensorFlow_layers, reshape)
TEST_P(Test_TensorFlow_layers, flatten)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE");
#endif
@ -257,7 +257,7 @@ TEST_P(Test_TensorFlow_layers, flatten)
TEST_P(Test_TensorFlow_layers, unfused_flatten)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE");
#endif
@ -279,7 +279,7 @@ TEST_P(Test_TensorFlow_layers, leaky_relu)
TEST_P(Test_TensorFlow_layers, l2_normalize)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X
)
@ -587,7 +587,7 @@ TEST_P(Test_TensorFlow_layers, fp16_weights)
TEST_P(Test_TensorFlow_layers, fp16_padding_same)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE");
#endif