PyTorch Image File Paths With Dataset Dataloader

pytorch_image_folder_with_file_paths.py

import torch
import torchvision
from torchvision import datasets, transforms

transforms = transforms.Compose([
  transforms.Resize((64,64)),
  transforms.ToTensor()
])

class ImageFolderWithPaths(torchvision.datasets.ImageFolder)):
    """Custom dataset that includes image file paths. Extends
    torchvision.datasets.ImageFolder
    """

    # override the __getitem__ method. this is the method that dataloader calls
    def __getitem__(self, index):
        # this is what ImageFolder normally returns 
        original_tuple = super(ImageFolderWithPaths, self).__getitem__(index)
        # the image file path
        path = self.imgs[index][0]
        # make a new tuple that includes original and the path
        tuple_with_path = (original_tuple + (path,))
        return tuple_with_path

# EXAMPLE USAGE:
# instantiate the dataset and dataloader
# data_dir = './dog_vs_cat/'
# data_dir = './dog_vs_cat/train/'
data_dir = "your/data_dir/here"
dataset = ImageFolderWithPaths(data_dir, transform=transforms) # our custom dataset
dataloader = torch.utils.DataLoader(dataset)

# iterate over data
for inputs, labels, paths in dataloader:
    # use the above variables freely
    print(inputs, labels, paths)