This is for per iteration image scaling. Would a better idea be to define a custom collate function for the dataloader where it does the scaling there? There’s also a bunch of auxillary things such as multiplying scaling factors to ground truth optical flow which I also have to intergrate into it.
The main problem I am having is that I am always getting divergence between training and validation accuracy for segmentation and one of the augmentations I am missing from the paper I’m branching from is random scaling. I’m very memory limited with only a 1070Ti so I operate at a significantly lower resolution and batch size compared to what the literature had which had a bunch of V100’s…could this also be a significant contributing factor?
Example output from cityscapes validation set below:
E30_42560×991 330 KB