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Merge pull request #13932 from l-bat:MyriadX_master_dldt

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* Fix precision in tests for MyriadX

* Fix ONNX tests

* Add output range in ONNX tests

* Skip tests on Myriad OpenVINO 2018R5

* Add detect MyriadX

* Add detect MyriadX on OpenVINO R5

* Skip tests on Myriad next version of OpenVINO

* dnn(ie): VPU type from environment variable

* dnn(test): validate VPU type

* dnn(test): update DLIE test skip conditions
This commit is contained in:
Lubov Batanina
2019-03-29 16:42:58 +03:00
committed by Alexander Alekhin
parent 982e6fc721
commit 7d3d6bc4e2
19 changed files with 1024 additions and 417 deletions
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modules/dnn/test/test_tf_importer.cpp
+124 -28
View File
@@ -2,7 +2,7 @@
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
// Copyright (C) 2017, Intel Corporation, all rights reserved.
// Copyright (C) 2017-2019, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
/*
@@ -133,12 +133,27 @@ TEST_P(Test_TensorFlow_layers, conv)
TEST_P(Test_TensorFlow_layers, padding)
{
runTensorFlowNet("padding_same");
runTensorFlowNet("padding_valid");
runTensorFlowNet("spatial_padding");
runTensorFlowNet("keras_pad_concat");
}
TEST_P(Test_TensorFlow_layers, padding_same)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE");
#endif
#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
// Reference output values are in range [0.0006, 2.798]
runTensorFlowNet("padding_same");
}
TEST_P(Test_TensorFlow_layers, eltwise)
{
runTensorFlowNet("eltwise_add_mul");
@@ -181,6 +196,13 @@ TEST_P(Test_TensorFlow_layers, pooling)
// TODO: fix tests and replace to 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 (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
runTensorFlowNet("ave_pool_same");
}
@@ -200,8 +222,11 @@ TEST_P(Test_TensorFlow_layers, matmul)
if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16)
throw SkipTestException("");
runTensorFlowNet("matmul");
runTensorFlowNet("nhwc_reshape_matmul");
runTensorFlowNet("nhwc_transpose_reshape_matmul");
// Reference output values are in range [-5.688, 4.484]
double l1 = target == DNN_TARGET_MYRIAD ? 6.1e-3 : default_l1;
runTensorFlowNet("nhwc_reshape_matmul", false, l1);
}
TEST_P(Test_TensorFlow_layers, reshape)
@@ -216,26 +241,36 @@ TEST_P(Test_TensorFlow_layers, reshape)
TEST_P(Test_TensorFlow_layers, flatten)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE &&
(target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD))
throw SkipTestException("");
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE");
#endif
#if defined(INF_ENGINE_RELEASE)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_2
)
throw SkipTestException("Test is disabled for Myriad2");
#endif
runTensorFlowNet("flatten", true);
}
TEST_P(Test_TensorFlow_layers, unfused_flatten)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE &&
(target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
throw SkipTestException("");
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE");
#endif
runTensorFlowNet("unfused_flatten");
runTensorFlowNet("unfused_flatten_unknown_batch");
}
TEST_P(Test_TensorFlow_layers, leaky_relu)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE >= 2018050000
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2018050000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL)
throw SkipTestException("");
throw SkipTestException("Test is disabled for DLIE/OCL target (OpenVINO 2018R5)");
#endif
runTensorFlowNet("leaky_relu_order1");
runTensorFlowNet("leaky_relu_order2");
@@ -244,14 +279,30 @@ 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 (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
runTensorFlowNet("l2_normalize");
}
// TODO: fix it and add to l2_normalize
TEST_P(Test_TensorFlow_layers, l2_normalize_3d)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target != DNN_TARGET_CPU)
throw SkipTestException("");
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2018050000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE
&& (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16)
)
throw SkipTestException("Test is disabled for DLIE for OpenCL 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
runTensorFlowNet("l2_normalize_3d");
}
@@ -300,6 +351,13 @@ TEST_P(Test_TensorFlow_nets, MobileNet_SSD)
TEST_P(Test_TensorFlow_nets, Inception_v2_SSD)
{
#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
checkBackend();
std::string proto = findDataFile("dnn/ssd_inception_v2_coco_2017_11_17.pbtxt", false);
std::string model = findDataFile("dnn/ssd_inception_v2_coco_2017_11_17.pb", false);
@@ -320,6 +378,7 @@ TEST_P(Test_TensorFlow_nets, Inception_v2_SSD)
0, 3, 0.75838411, 0.44668293, 0.45907149, 0.49459291, 0.52197015,
0, 10, 0.95932811, 0.38349164, 0.32528657, 0.40387636, 0.39165527,
0, 10, 0.93973452, 0.66561931, 0.37841269, 0.68074018, 0.42907384);
double scoreDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.0097 : default_l1;
double iouDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.09 : default_lInf;
normAssertDetections(ref, out, "", 0.5, scoreDiff, iouDiff);
@@ -329,6 +388,13 @@ TEST_P(Test_TensorFlow_nets, MobileNet_v1_SSD)
{
checkBackend();
#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
std::string model = findDataFile("dnn/ssd_mobilenet_v1_coco_2017_11_17.pb", false);
std::string proto = findDataFile("dnn/ssd_mobilenet_v1_coco_2017_11_17.pbtxt", false);
@@ -354,7 +420,7 @@ TEST_P(Test_TensorFlow_nets, Faster_RCNN)
"faster_rcnn_resnet50_coco_2018_01_28"};
checkBackend();
if ((backend == DNN_BACKEND_INFERENCE_ENGINE && target != DNN_TARGET_CPU) ||
if ((backend == DNN_BACKEND_INFERENCE_ENGINE) ||
(backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16))
throw SkipTestException("");
@@ -380,10 +446,11 @@ TEST_P(Test_TensorFlow_nets, Faster_RCNN)
TEST_P(Test_TensorFlow_nets, MobileNet_v1_SSD_PPN)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE >= 2018050000
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2018050000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
throw SkipTestException("Unstable test case");
throw SkipTestException("Test is disabled for DLIE OpenCL targets in OpenVINO 2018R5");
#endif
checkBackend();
std::string proto = findDataFile("dnn/ssd_mobilenet_v1_ppn_coco.pbtxt", false);
std::string model = findDataFile("dnn/ssd_mobilenet_v1_ppn_coco.pb", false);
@@ -399,9 +466,9 @@ TEST_P(Test_TensorFlow_nets, MobileNet_v1_SSD_PPN)
net.setInput(blob);
Mat out = net.forward();
double scoreDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.011 : 1.1e-5;
double iouDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.021 : default_lInf;
normAssertDetections(ref, out, "", 0.4, scoreDiff, iouDiff);
double scoreDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.048 : 1.1e-5;
double iouDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.058 : default_lInf;
normAssertDetections(ref, out, "", 0.45, scoreDiff, iouDiff);
}
TEST_P(Test_TensorFlow_nets, opencv_face_detector_uint8)
@@ -444,7 +511,13 @@ TEST_P(Test_TensorFlow_nets, opencv_face_detector_uint8)
// np.save('east_text_detection.geometry.npy', geometry)
TEST_P(Test_TensorFlow_nets, EAST_text_detection)
{
#if defined(INF_ENGINE_RELEASE)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is disabled for Myriad targets");
#endif
checkBackend();
std::string netPath = findDataFile("dnn/frozen_east_text_detection.pb", false);
std::string imgPath = findDataFile("cv/ximgproc/sources/08.png", false);
std::string refScoresPath = findDataFile("dnn/east_text_detection.scores.npy", false);
@@ -478,8 +551,8 @@ TEST_P(Test_TensorFlow_nets, EAST_text_detection)
}
else if (target == DNN_TARGET_MYRIAD)
{
lInf_scores = 0.214;
l1_geometry = 0.47; lInf_geometry = 15.34;
lInf_scores = 0.41;
l1_geometry = 0.28; lInf_geometry = 5.94;
}
else
{
@@ -493,17 +566,40 @@ INSTANTIATE_TEST_CASE_P(/**/, Test_TensorFlow_nets, dnnBackendsAndTargets());
TEST_P(Test_TensorFlow_layers, fp16_weights)
{
const float l1 = 0.00071;
const float lInf = 0.012;
float l1 = 0.00078;
float lInf = 0.012;
runTensorFlowNet("fp16_single_conv", false, l1, lInf);
runTensorFlowNet("fp16_deconvolution", false, l1, lInf);
runTensorFlowNet("fp16_max_pool_odd_same", false, l1, lInf);
runTensorFlowNet("fp16_padding_valid", false, l1, lInf);
runTensorFlowNet("fp16_eltwise_add_mul", false, l1, lInf);
runTensorFlowNet("fp16_max_pool_odd_valid", false, l1, lInf);
runTensorFlowNet("fp16_max_pool_even", false, l1, lInf);
runTensorFlowNet("fp16_padding_same", false, l1, lInf);
runTensorFlowNet("fp16_pad_and_concat", false, l1, lInf);
runTensorFlowNet("fp16_padding_valid", false, l1, lInf);
// Reference output values are in range [0.0889, 1.651]
runTensorFlowNet("fp16_max_pool_even", false, (target == DNN_TARGET_MYRIAD) ? 0.003 : l1, lInf);
if (target == DNN_TARGET_MYRIAD) {
l1 = 0.0041;
lInf = 0.024;
}
// Reference output values are in range [0, 10.75]
runTensorFlowNet("fp16_deconvolution", false, l1, lInf);
// Reference output values are in range [0.418, 2.297]
runTensorFlowNet("fp16_max_pool_odd_valid", false, l1, lInf);
}
TEST_P(Test_TensorFlow_layers, fp16_padding_same)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2018050000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE");
#endif
#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
// Reference output values are in range [-3.504, -0.002]
runTensorFlowNet("fp16_padding_same", false, 6e-4, 4e-3);
}
TEST_P(Test_TensorFlow_layers, defun)