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dnn: small fix in pose estimation model

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This commit is contained in:
berak
2020-01-27 17:17:11 +01:00
parent 5d01821d9f
commit 4fdf4d380c
2 changed files with 10 additions and 4 deletions
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modules/dnn/test/test_model.cpp
+9 -3
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@@ -273,9 +273,15 @@ TEST_P(Test_Model, Keypoints_pose)
#endif
Mat inp = imread(_tf("pose.png"));
std::string weights = _tf("onnx/models/lightweight_pose_estimation.onnx", false);
Mat exp = blobFromNPY(_tf("keypoints_exp.npy"));
std::string weights = _tf("onnx/models/lightweight_pose_estimation_201912.onnx", false);
float kpdata[] = {
237.65625f, 78.25f, 237.65625f, 136.9375f,
190.125f, 136.9375f, 142.59375f, 195.625f, 79.21875f, 176.0625f, 285.1875f, 117.375f,
348.5625f, 195.625f, 396.09375f, 176.0625f, 205.96875f, 313.0f, 205.96875f, 430.375f,
205.96875f, 528.1875f, 269.34375f, 293.4375f, 253.5f, 430.375f, 237.65625f, 528.1875f,
221.8125f, 58.6875f, 253.5f, 58.6875f, 205.96875f, 78.25f, 253.5f, 58.6875f
};
Mat exp(18, 2, CV_32FC1, kpdata);
Size size{256, 256};
float norm = 1e-4;