I am using PyTorch for semantic segmentation, But I am facing a problem, because I am use  images , and their  masks/labels . I want to perform data augmentation such as RandomHorizontalFlip, and RandomCrop, etc.
Here is my code, please check and let me know, how I can embed the following operations in the provided code.

import torchvision.transforms.functional as F
class ToTensor(object):
def call(self, sample):
image, label = sample[‘image’], sample[‘label’]
return {‘image’: F.to_tensor(image), ‘label’: F.to_tensor(label)}
my_transform = transforms.Compose([ ToTensor() ])
dataset = Mydataset(image_dir, label_dir, transform = my_transform)
Print dataset output
dataset[1]

Output

{‘image’: tensor([[[0.0824, 0.0824, 0.0824,  …, 0.0824, 0.0824, 0.0824],
[0.0824, 0.0824, 0.0824,  …, 0.0824, 0.0824, 0.0824],
[0.0824, 0.0824, 0.0824,  …, 0.0824, 0.0824, 0.0824],
…,
[0.0902, 0.0902, 0.0902,  …, 0.0824, 0.0824, 0.0824],
[0.0824, 0.0824, 0.0824,  …, 0.0824, 0.0824, 0.0824],
[0.0745, 0.0745, 0.0745,  …, 0.0824, 0.0824, 0.0824]],
     [[0.0824, 0.0824, 0.0824,  ..., 0.0824, 0.0824, 0.0824],
      [0.0824, 0.0824, 0.0824,  ..., 0.0824, 0.0824, 0.0824],
      [0.0824, 0.0824, 0.0824,  ..., 0.0824, 0.0824, 0.0824],
      ...,
      [0.0902, 0.0902, 0.0902,  ..., 0.0824, 0.0824, 0.0824],
      [0.0824, 0.0824, 0.0824,  ..., 0.0824, 0.0824, 0.0824],
      [0.0745, 0.0745, 0.0745,  ..., 0.0824, 0.0824, 0.0824]],

     [[0.0824, 0.0824, 0.0824,  ..., 0.0824, 0.0824, 0.0824],
      [0.0824, 0.0824, 0.0824,  ..., 0.0824, 0.0824, 0.0824],
      [0.0824, 0.0824, 0.0824,  ..., 0.0824, 0.0824, 0.0824],
      ...,
      [0.0902, 0.0902, 0.0902,  ..., 0.0824, 0.0824, 0.0824],
      [0.0824, 0.0824, 0.0824,  ..., 0.0824, 0.0824, 0.0824],
      [0.0745, 0.0745, 0.0745,  ..., 0.0824, 0.0824, 0.0824]]]),

‘label’: tensor([[[0.0824, 0.0824, 0.0824,  …, 0.0824, 0.0824, 0.0824],
[0.0824, 0.0824, 0.0824,  …, 0.0824, 0.0824, 0.0824],
[0.0824, 0.0824, 0.0824,  …, 0.0824, 0.0824, 0.0824],
…,
[0.0902, 0.0902, 0.0902,  …, 0.0824, 0.0824, 0.0824],
[0.0824, 0.0824, 0.0824,  …, 0.0824, 0.0824, 0.0824],
[0.0745, 0.0745, 0.0745,  …, 0.0824, 0.0824, 0.0824]]])}