PyTorch - Incorrect labeling using torchvision.datasets.ImageFolder

Question

I have structured my dataset in the following way:

dataset/train/0/456.jpg
dataset/train/1/456456.jpg
dataset/train/2/456.jpg
dataset/train/...

dataset/val/0/878.jpg
dataset/val/1/234.jpg
dataset/val/2/34554.jpg
dataset/val/...

So I used torchvision.datasets.ImageFolder to import my dataset to PyTorch. However, it seems like it is not giving the right label to the right image. I've added my code below:

data_transforms = {
    'train': transforms.Compose(
        [transforms.Resize((176,176)),
         transforms.RandomRotation((0,360)),
         transforms.RandomHorizontalFlip(),
         transforms.RandomVerticalFlip(),
         transforms.CenterCrop(128),         
         transforms.Grayscale(),
         transforms.ToTensor(),
         transforms.Normalize((0.5,0.5,0.5), (0.5,0.5,0.5))
    ]),
    'val': transforms.Compose(
        [transforms.Resize((128,128)),
         transforms.Grayscale(),
         transforms.ToTensor(),
         transforms.Normalize((0.5,0.5,0.5), (0.5,0.5,0.5))
    ]),
}

data_dir = 'dataset'
image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x),
                                          data_transforms[x])
                  for x in ['train', 'val']}
dataloaders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=4,
                                             shuffle=True, num_workers=4)
              for x in ['train', 'val']}
dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'val']}
class_names = image_datasets['train'].classes

device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")

I found out that the labels are wrong using the following function:

def imshow(img):
    img = img / 2 + 0.5
    npimg = img.numpy()
    plt.imshow(np.transpose(npimg, (1, 2, 0)))
    plt.show()

dataiter = iter(dataloaders['val'])
images, labels = dataiter.next()

imshow(torchvision.utils.make_grid(images))
print(labels)

Using the shown images and the labels, I manually checked whether they are correct. Unfortunately, the labels do not correspond to the images. Can someone tell me what I'm doing wrong?

Answer 1

Someone helped me out with this. ImageFolder creates its own internal labels. By printing image_datasets['train'].class_to_idx you can see what label is paired to what internal label. Using this dictionary, you can trace back the original label.

Answer 2

The ImageFolder API assumes that your data is in a "predefined" folder structure. Please check the below comment from PyTorch code or documentation @ https://pytorch.org/docs/stable/torchvision/datasets.html#imagefolder

A generic data loader where the images are arranged in this way: ::

root/dog/xxx.png
root/dog/xxy.png
root/dog/xxz.png

root/cat/123.png
root/cat/nsdf3.png
root/cat/asd932_.png

This means, you need to arrange your data under folders matching with your labels. In the above case there are 2 labels, cats & dogs.

Hope this helps!