Hii, I built a custom data class for video dataset (I know about nvvl but can’t use it rn).
Different videos may have different number of frames. During validation I slide across videos in following manner ->
First 120 frames from all, next 120 frames from all and so one. But once a this slides window covers the smallest video entirely as I cannot return 0 dimensional tensor, I have to send 8 frames from that video again and again until sliding window gets over for the largest video. This means that I validate of same set of frames (from smaller videos multiple times).
So I thought of storing attributes containing which video has finished and to ignore such cases. But it doesnt work thanks to multiprocessing.
Any suggestions,  (I AM OPEN TO COMPLETELY DIFFERENT APPROACH AS WELL)