transforms.Resize() misidentified as attribute

I’m trying to resize my input images. They are pretty big (5312x2988) and I’m trying to shrink them.

This is my code. It’s based on the code in a tutorial:

import transforms as T

def get_transform(train):
    transforms = []
    # converts the image, a PIL image, into a PyTorch Tensor
    transforms.append(T.Resize((400*5312/2988,400)))  # *<-- this is where I added T.Resize()*
    if train:
        # during training, randomly flip the training images
        # and ground-truth for data augmentation
    return T.Compose(transforms)

This is the error message:

AttributeError Traceback (most recent call last)

in ()
1 model = torchvision.models.detection.fasterrcnn_resnet50_fpn(pretrained=True)
----> 2 dataset = four_chs(root = ‘/content/drive/MyDrive/four_chambers’, transforms = get_transform(train=True))
3 data_loader =
4 dataset, batch_size=1, shuffle=True, num_workers=2,
5 collate_fn=utils.collate_fn)

in get_transform(train)
8 # converts the image, a PIL image, into a PyTorch Tensor
9 transforms.append(T.ToTensor())
—> 10 transforms.append(T.Resize((360,360)))
11 if train:
12 # during training, randomly flip the training images

AttributeError: module ‘transforms’ has no attribute ‘Resize’

I suppose that I’ve coded transforms.Resize incorrectly if it’s being read as an attribute? I wrote that line the way I did because it seems to be the same format as T.ToTensor(). I don’t see the difference between applying ToTensor and Resize. Please tell me how should I code the transforms chunk to apply Resize to the tensors?

Could you try from torchvision import transforms ?

It looks like that worked. I have a different error now. lol. I’ll probably post about that in a few minutes.

Thanks for your help.