Apply different Transform (Data Augmentation) to Train and Validation

vision
6

Hi gregunz, apologize for late reply.
You code is great, but it needs to change a bit in ‘getitem’ to access iamges and labels in my case.
I have used your code and the code here Using ImageFolder, random_split with multiple transforms.

The resulting code coulde work for me. Let me know if my I did it correctly. You can refine this code if there are any mistakes and then I will accept it as a solution.

class MapDataset(torch.utils.data.Dataset):
    """
    Given a dataset, creates a dataset which applies a mapping function
    to its items (lazily, only when an item is called).

    Note that data is not cloned/copied from the initial dataset.
    """

    def __init__(self, dataset, map_fn):
        self.dataset = dataset
        self.map = map_fn

    def __getitem__(self, index):
        if self.map:     
            x = self.map(self.dataset[index][0]) 
        else:     
            x = self.dataset[index][0]  # image
        y = self.dataset[index][1]   # label      
        return x, y

    def __len__(self):
        return len(self.dataset)
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