Definitely! Let me know if you need any other details. And thanks again for working with me on figuring this out.
Here’s the entire code for my custom Dataset class:
# Create custom Dataset class
class CameraCatalogueDataset(Dataset):
    """
    Camera Catalogue dataset.
    """
    def __init__(self, csv_file, data_folder, transform=None):
        """
        Args:
            csv_file (string): Path to the csv file with annotations.
            data_folder (string): Directory with all the images.
            transform (callable, optional): Optional transform to be applied
                on a sample.
        """
        self.labels_frame = pd.read_csv(csv_file)
        self.data_folder = data_folder
        self.transform = transform
        self.labels = self.labels_frame.Label.unique()
        self.label_counts = self.labels_frame.Label.value_counts()
        self.num_classes = len(self.labels)

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

    def __getitem__(self, idx):
        image_name = data_folder / self.labels_frame.iloc[idx, 0]
        image = Image.open(image_name)
        image_label = self.labels_frame.iloc[idx, 1]

        if self.transform:
            image = self.transform(image)

        return image, image_label