my_simple_Dataset.py

import os
import torch
from torch.utils import data
from PIL import Image
from torchvision import transforms

class simpleDataset(data.Dataset):
    
    # initialise function of class
    def __init__(self, root, filenames, labels):
        # the data directory 
        self.root = root
        # the list of filename
        self.filenames = filenames
        # the list of label
        self.labels = labels

    # obtain the sample with the given index
    def __getitem__(self, index):
        # obtain filenames from list
        image_filename = self.filenames[index]
        # Load data and label
        image = Image.open(os.path.join(self.root, image_filename))
        label = self.labels[index]
        
        # output of Dataset must be tensor
        image = transforms.ToTensor()(image)
        label = torch.as_tensor(label, dtype=torch.int64)
        return image, label
    
    # the total number of samples (optional)
    def __len__(self):
        return len(self.filenames)