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Code Packages Releases Wiki Activity

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

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This commit is contained in:
Alexander Alekhin
2019-10-05 15:45:31 +00:00
parent c54753c185 98fc098216
commit 626bfbf309
23 changed files with 222 additions and 98 deletions
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modules/dnn/misc/python/test/test_dnn.py
+9
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@@ -64,11 +64,19 @@ def printParams(backend, target):
testdata_required = bool(os.environ.get('OPENCV_DNN_TEST_REQUIRE_TESTDATA', False))
g_dnnBackendsAndTargets = None
class dnn_test(NewOpenCVTests):
def setUp(self):
super(dnn_test, self).setUp()
global g_dnnBackendsAndTargets
if g_dnnBackendsAndTargets is None:
g_dnnBackendsAndTargets = self.initBackendsAndTargets()
self.dnnBackendsAndTargets = g_dnnBackendsAndTargets
def initBackendsAndTargets(self):
self.dnnBackendsAndTargets = [
[cv.dnn.DNN_BACKEND_OPENCV, cv.dnn.DNN_TARGET_CPU],
]
@@ -86,6 +94,7 @@ class dnn_test(NewOpenCVTests):
self.dnnBackendsAndTargets.append([cv.dnn.DNN_BACKEND_INFERENCE_ENGINE, cv.dnn.DNN_TARGET_OPENCL])
if self.checkIETarget(cv.dnn.DNN_BACKEND_INFERENCE_ENGINE, cv.dnn.DNN_TARGET_OPENCL_FP16):
self.dnnBackendsAndTargets.append([cv.dnn.DNN_BACKEND_INFERENCE_ENGINE, cv.dnn.DNN_TARGET_OPENCL_FP16])
return self.dnnBackendsAndTargets
def find_dnn_file(self, filename, required=True):
if not required:
modules/dnn/src/layers/pooling_layer.cpp
+2
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@@ -163,6 +163,8 @@ public:
{
if (backendId == DNN_BACKEND_INFERENCE_ENGINE)
{
if (computeMaxIdx)
return false;
#ifdef HAVE_INF_ENGINE
if (kernel_size.size() == 3)
return preferableTarget == DNN_TARGET_CPU;
modules/dnn/src/op_inf_engine.hpp
+3 -2
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@@ -22,10 +22,11 @@
#define INF_ENGINE_RELEASE_2018R5 2018050000
#define INF_ENGINE_RELEASE_2019R1 2019010000
#define INF_ENGINE_RELEASE_2019R2 2019020000
#define INF_ENGINE_RELEASE_2019R3 2019030000
#ifndef INF_ENGINE_RELEASE
#warning("IE version have not been provided via command-line. Using 2019R2 by default")
#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2019R2
#warning("IE version have not been provided via command-line. Using 2019R3 by default")
#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2019R3
#endif
#define INF_ENGINE_VER_MAJOR_GT(ver) (((INF_ENGINE_RELEASE) / 10000) > ((ver) / 10000))
modules/dnn/test/test_common.hpp
+1
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@@ -19,6 +19,7 @@
#define CV_TEST_TAG_DNN_SKIP_IE_2019R1 "dnn_skip_ie_2019r1"
#define CV_TEST_TAG_DNN_SKIP_IE_2019R1_1 "dnn_skip_ie_2019r1_1"
#define CV_TEST_TAG_DNN_SKIP_IE_2019R2 "dnn_skip_ie_2019r2"
#define CV_TEST_TAG_DNN_SKIP_IE_2019R3 "dnn_skip_ie_2019r3"
#define CV_TEST_TAG_DNN_SKIP_IE_OPENCL "dnn_skip_ie_ocl"
#define CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16 "dnn_skip_ie_ocl_fp16"
#define CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_2 "dnn_skip_ie_myriad2"
modules/dnn/test/test_common.impl.hpp
+2
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@@ -324,6 +324,8 @@ void initDNNTests()
# endif
#elif INF_ENGINE_VER_MAJOR_EQ(2019020000)
CV_TEST_TAG_DNN_SKIP_IE_2019R2,
#elif INF_ENGINE_VER_MAJOR_EQ(2019030000)
CV_TEST_TAG_DNN_SKIP_IE_2019R3,
#endif
CV_TEST_TAG_DNN_SKIP_IE
);
modules/dnn/test/test_halide_layers.cpp
+2 -2
View File
@@ -554,9 +554,9 @@ TEST_P(ReLU, Accuracy)
Backend backendId = get<0>(get<1>(GetParam()));
Target targetId = get<1>(get<1>(GetParam()));
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019020000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019020000)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_MYRIAD && negativeSlope < 0)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_2019R3, CV_TEST_TAG_DNN_SKIP_IE_2019R2, CV_TEST_TAG_DNN_SKIP_IE);
#endif
LayerParams lp;
modules/dnn/test/test_onnx_importer.cpp
+13 -4
View File
@@ -86,8 +86,8 @@ TEST_P(Test_ONNX_layers, InstanceNorm)
TEST_P(Test_ONNX_layers, MaxPooling)
{
testONNXModels("maxpooling");
testONNXModels("two_maxpooling");
testONNXModels("maxpooling", npy, 0, 0, false, false);
testONNXModels("two_maxpooling", npy, 0, 0, false, false);
}
TEST_P(Test_ONNX_layers, Convolution)
@@ -212,7 +212,7 @@ TEST_P(Test_ONNX_layers, MaxPooling3D)
#endif
if (target != DNN_TARGET_CPU)
throw SkipTestException("Only CPU is supported");
testONNXModels("max_pool3d");
testONNXModels("max_pool3d", npy, 0, 0, false, false);
}
TEST_P(Test_ONNX_layers, AvePooling3D)
@@ -422,13 +422,22 @@ TEST_P(Test_ONNX_nets, Googlenet)
TEST_P(Test_ONNX_nets, CaffeNet)
{
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019030000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, CV_TEST_TAG_DNN_SKIP_IE_2019R3);
#endif
testONNXModels("caffenet", pb);
}
TEST_P(Test_ONNX_nets, RCNN_ILSVRC13)
{
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019030000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, CV_TEST_TAG_DNN_SKIP_IE_2019R3);
#endif
// Reference output values are in range [-4.992, -1.161]
testONNXModels("rcnn_ilsvrc13", pb, 0.0045);
}
modules/dnn/test/test_tf_importer.cpp
+3 -3
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@@ -146,13 +146,13 @@ TEST_P(Test_TensorFlow_layers, padding)
runTensorFlowNet("padding_valid");
runTensorFlowNet("spatial_padding");
runTensorFlowNet("mirror_pad");
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019020000)
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019020000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
{
if (target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_2019R3, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
if (target == DNN_TARGET_OPENCL_FP16)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_2019R3, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
}
#endif
runTensorFlowNet("keras_pad_concat");
modules/dnn/test/test_torch_importer.cpp
+9 -3
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@@ -337,9 +337,15 @@ TEST_P(Test_Torch_nets, ENet_accuracy)
{
applyTestTag(target == DNN_TARGET_CPU ? "" : CV_TEST_TAG_MEMORY_512MB);
checkBackend();
if (backend == DNN_BACKEND_INFERENCE_ENGINE ||
(backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16))
applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16);
if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16)
throw SkipTestException("");
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target != DNN_TARGET_CPU)
{
if (target == DNN_TARGET_OPENCL_FP16) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16);
if (target == DNN_TARGET_OPENCL) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL);
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD);
throw SkipTestException("");
}
Net net;
{