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Merge branch 4.x

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This commit is contained in:
Alexander Smorkalov
2023-10-16 21:25:56 +03:00
parent d789cb459c 2f63c58380
commit 97620c053f
221 changed files with 3584 additions and 2215 deletions
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modules/dnn/test/test_backends.cpp
+11 -3
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@@ -151,10 +151,12 @@ TEST_P(DNNTestNetwork, ENet)
{
applyTestTag(target == DNN_TARGET_CPU ? "" : CV_TEST_TAG_MEMORY_512MB);
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2023000000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER);
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);
#endif
if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16)
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16);
if (backend == DNN_BACKEND_CUDA && target == DNN_TARGET_CUDA_FP16)
@@ -482,7 +484,7 @@ TEST_P(DNNTestNetwork, FastNeuralStyle_eccv16)
Mat img = imread(findDataFile("dnn/googlenet_1.png"));
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 = 2e-4, lInf = 2e-3;
float l1 = 2e-4, lInf = 2.4e-3;
if (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD)
{
l1 = 0.4;
@@ -875,8 +877,12 @@ TEST_P(MaxPooling, Accuracy)
Target targetId = get<1>(get<5>(GetParam()));
// https://github.com/openvinotoolkit/openvino/issues/18731
if (backendId == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && stride != Size(1, 1))
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);
if (backendId == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && stride != Size(1, 1)) {
int ow = ceil(static_cast<float>(inSize.width + 2 * pad.width - kernel.width) / stride.width);
int oh = ceil(static_cast<float>(inSize.height + 2 * pad.height - kernel.height) / stride.height);
if (ow * stride.width >= inSize.width + pad.width || oh * stride.height >= inSize.height + pad.height)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);
}
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && targetId == DNN_TARGET_MYRIAD
@@ -1026,10 +1032,12 @@ INSTANTIATE_TEST_CASE_P(Layer_Test_Backends, SoftMax, testing::Combine(
//////////////////////////////////////////////////////////////////////////////
TEST_P(Test_layers_backends, MaxPoolUnpool)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LT(2023000000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER);
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);
#endif
LayerParams pool;
pool.set("pool", "max");