How can I apply transformations like, Resize, CenterCrop, RandomCrop, RandomHorizontalFlip etc… to a read video, of type torch.tensor with four dimensions -> (channels, frames, height, width). (Its okay if I’d have to reshape this…)
You could create custom transformations, which would apply the
torchvision.transforms in a loop on each sample (or rewrite the transformations so that they would work on batched inputs).
torchvision has some internal video transforms. Since the API isn’t finalized, this code might break and shouldn’t be used, if you rely on backwards compatibility.
Don’t know if you are still looking for a solution, might be this will help GitHub - facebookresearch/pytorchvideo: A deep learning library for video understanding research.
Yup I’ve also recently discovered this… and its awesome
Thanks for your time.