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dnn(test): fix Test_Model.Keypoints* tests

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This commit is contained in:
Alexander Alekhin 2019-12-16 17:43:06 +03:00
parent ba7b0f4c54
commit 2c0d9fa81f
1 changed files with 18 additions and 3 deletions
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21
modules/dnn/test/test_model.cpp
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@ -83,6 +83,9 @@ public:
model.setInputSize(size).setInputMean(mean).setInputScale(scale) model.setInputSize(size).setInputMean(mean).setInputScale(scale)
.setInputSwapRB(swapRB).setInputCrop(crop); .setInputSwapRB(swapRB).setInputCrop(crop);
model.setPreferableBackend(backend);
model.setPreferableTarget(target);
points = model.estimate(frame, 0.5); points = model.estimate(frame, 0.5);
Mat out = Mat(points).reshape(1); Mat out = Mat(points).reshape(1);
@ -242,8 +245,15 @@ TEST_P(Test_Model, DetectionMobilenetSSD)
TEST_P(Test_Model, Keypoints_pose) TEST_P(Test_Model, Keypoints_pose)
{ {
if (target == DNN_TARGET_OPENCL_FP16)
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16);
#ifdef HAVE_INF_ENGINE
if (target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
Mat inp = imread(_tf("pose.png")); Mat inp = imread(_tf("pose.png"));
std::string weights = _tf("lightweight_pose_estimation.onnx"); std::string weights = _tf("onnx/models/lightweight_pose_estimation.onnx");
Mat exp = blobFromNPY(_tf("keypoints_exp.npy")); Mat exp = blobFromNPY(_tf("keypoints_exp.npy"));
@ -258,12 +268,17 @@ TEST_P(Test_Model, Keypoints_pose)
TEST_P(Test_Model, Keypoints_face) TEST_P(Test_Model, Keypoints_face)
{ {
#if defined(INF_ENGINE_RELEASE)
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
Mat inp = imread(_tf("gray_face.png"), 0); Mat inp = imread(_tf("gray_face.png"), 0);
std::string weights = _tf("facial_keypoints.onnx"); std::string weights = _tf("onnx/models/facial_keypoints.onnx");
Mat exp = blobFromNPY(_tf("facial_keypoints_exp.npy")); Mat exp = blobFromNPY(_tf("facial_keypoints_exp.npy"));
Size size{224, 224}; Size size{224, 224};
float norm = 1e-4; float norm = (target == DNN_TARGET_OPENCL_FP16) ? 5e-3 : 1e-4;
double scale = 1.0/255; double scale = 1.0/255;
Scalar mean = Scalar(); Scalar mean = Scalar();
bool swapRB = false; bool swapRB = false;