message: dnn(test): fix Test_Model.Keypoints* tests
diff: @@ -83,6 +83,9 @@ public:
  model.setInputSize(size).setInputMean(mean).setInputScale(scale)
  .setInputSwapRB(swapRB).setInputCrop(crop);
  + model.setPreferableBackend(backend);
  + model.setPreferableTarget(target);
  +
  points = model.estimate(frame, 0.5);
  Mat out = Mat(points).reshape(1);
  @@ -242,8 +245,15 @@ TEST_P(Test_Model, DetectionMobilenetSSD)
  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"));
  - 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"));
  @@ -258,12 +268,17 @@ TEST_P(Test_Model, Keypoints_pose)
  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);
  - std::string weights = _tf("facial_keypoints.onnx");
  + std::string weights = _tf("onnx/models/facial_keypoints.onnx");
  Mat exp = blobFromNPY(_tf("facial_keypoints_exp.npy"));
  Size size{224, 224};
  - float norm = 1e-4;
  + float norm = (target == DNN_TARGET_OPENCL_FP16) ? 5e-3 : 1e-4;
  double scale = 1.0/255;
  Scalar mean = Scalar();
  bool swapRB = false;
  