I have grayscale videos from 3 different classes.
I’d like to build a 3d conv network that would analyse a collection of frames (not necessarily concurrent) from each video and classify the video based on them.
Each class has its own folder. Within the folder, frames are named as follows: VidName_FrameNum (E4FG89_1 for the first frame, E4FG89_2 for the second and so on)
I’d like to get a samples of specific frames from a batch of videos.
I don’t know which will work best, so I need to be able to customise it. For example, get frames (1,5,10,15) or (3,10,17) or (1,3,5,7,9,11,13) etc.
I think the output tensor dimensions should look like (n_sets, n_frames, n_rows, n_cols)
Is there something built into pytorch to achieve this? how should i go about it?