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I see your point. The idea of this try-except block is that if we fail to produce keypoints for some reason, we will skip this sample since it cannot be used for training. Is there a a reason why you need this failed sample without keypoint annotations?
It failed due to numpy alias changes (I opened an issue for that. I guess defining the exact exception instead of a broad except may be the solution here.
The following try-except block is incorrect and may cause no data being saved if the code fails partway.
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