Fix the consistency of pre-processing with yolov5 #293
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+ Coverage 94.01% 94.92% +0.91%
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zhiqwang
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Feb 4, 2022
| aug2 = out2[0].astype(np.float32) # uint8 to float32 | ||
| aug2 = np.transpose(aug2 / 255.0, [2, 0, 1]) | ||
| assert aug1.shape == aug2.shape | ||
| np.testing.assert_allclose(aug1, aug2, rtol=1e-4, atol=1e-2) |
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PyTorch's interpolate operator now only aligns with OpenCV for the float type, and the letterbox implemented by yolov5 operates on uint8, so the precision we set here is relatively low.
Check pytorch/pytorch#5580 (comment) for more details.
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Aligning the
YOLOTransformwith theletterboxin yolov5.Fortunately, the interpolation operator of PyTorch is aligned with that of OpenCV for the float type, however, PyTorch's
interpolatedoes not currently support integers type: pytorch/pytorch#5580 , a little loss of precision will occur here.https://github.com/zhiqwang/yolov5-rt-stack/blob/cd1a6ec7cda09de0dc92962a37ecb4f723a8dfeb/test/test_models_transform.py#L31-L53
Close #274 .