Applying Transforms to a single image:

1

Following is my code:

from torchvision import datasets, models, transforms
import matplotlib.image as mpimg
import matplotlib.pyplot as plt

import torch



data_transforms = transforms.Compose([
        transforms.RandomResizedCrop(256),
        transforms.ToTensor(),
        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
        ])

img = mpimg.imread('dataset/train/cats/cat.1.jpg')
print(type(img))
print(len(img))
# img = img.astype(float)
# img = img.float()
print(img)
img = data_transforms(img)

Error Message:

Traceback (most recent call last):
  File "Image_Preprocessing.py", line 47, in <module>
    img = data_transforms(img)
  File "/home/debayon/anaconda3/envs/ENV2/lib/python3.7/site-packages/torchvision/transforms/transforms.py", line 61, in __call__
    img = t(img)
  File "/home/debayon/anaconda3/envs/ENV2/lib/python3.7/site-packages/torchvision/transforms/transforms.py", line 676, in __call__
    i, j, h, w = self.get_params(img, self.scale, self.ratio)
  File "/home/debayon/anaconda3/envs/ENV2/lib/python3.7/site-packages/torchvision/transforms/transforms.py", line 638, in get_params
    area = img.size[0] * img.size[1]
TypeError: 'int' object is not subscriptable

I am unable to understand why is that occuring and please tell how can I solve it?
Thank You.

1 Like
2

Your image seems to be a numpy array.
torchvision transformations work on PIL.Images, so either load the image directly via Image.open or convert it to a PIL.Image before passing it to the transformations.

9 Likes
3

Oh. Thank You so much. Lesson Learnt: "torchvision transformations work on PIL.Image s "

4 Likes
4

To be a bit more specific: “a lot of” torchvision’s transformation use PIL, while e.g. Normalize will work on tensors. :wink:

5 Likes
5

Just wonder why? Isn’t numpy image more common?

6

I think the major advantage is to reuse a common library for loading and processing images.
PIL is one of these libs, but I don’t know which requirements were used to pick it.

Note however that as of torchvision 0.8 transformations are now supported on tensors and torchvision ships with a native image loading utility. More details can be found in the release notes.

7

Thank you very much for quick responses, and background info is very helpful.

Still not direct support Numpy as input data format is a little bit strange for transform functions. For example, a project deal with both images and videos a lot, we use OpenCV for preprocessing.