Comments (4)
Hello,
the predict method converts the image into RGB. So it's okay, to pass a BGR array.
https://github.com/thohemp/6DRepNet/blob/master/sixdrepnet/regressor.py#L67
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Hello,
Thanks for your reply. I have already seen that in the code. The problem is the line above (https://github.com/thohemp/6DRepNet/blob/master/sixdrepnet/regressor.py#L66):
img = Image.fromarray(img)
that, I think, by default, converts an array with three channels into an RGB PIL image as it does not now which channel is what color. Thus img
is already an RGB PIL image but with its R and B channels inverted. Convertimg it to an RGB PIL image should not invert its channels. Though I might be wrong. If I have some time today, I will add some print function around the code to check if I am correct or not
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You are correct, I just tested it. Swapping channels before using PIL should fix this:
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
Thanks!
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Thanks for checking this and happy that helped fix a bug at the end!
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Related Issues (20)
- Pip install failed HOT 4
- quick start version will install torch-cpu automaticlly HOT 1
- BIWI Dataset HOT 7
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- may i ask how does the performance compare with 3ddfav2?
- is there possible to provide a smaller version? HOT 3
- what the difference between those different pretain models?
- Import error with pip package HOT 9
- Reference System
- Finetuning the model HOT 1
- Why did you set up the scheduler as MultiStepLR=False? HOT 2
- please tell me where 'output/snapshots/1.pth' in test.py HOT 6
- Using your own trained weight files, the test results lose a lot
- Getting different results using your code and your fine_tuned model for BIWI.
- Is there a way to run this model on Apple M1 that doesn't have CUDA support? HOT 2
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- module 'utils' has no attribute 'compute_rotation_matrix_from_ortho6d' HOT 3
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