dataset.py

from torch.utils.data import Dataset
import os 
from PIL import Image
import numpy as np
import torch

class Cardataset(Dataset):
    def __init__(self,image_dir ,mask_dir,transform=None):
        self.image_dir = image_dir 
        self.mask_dir = mask_dir 
        self.transform = transform
        self.images = os.listdir(image_dir)

    def __len__(self):
        return len(self.images)
    
    def __getitem__(self,index):
        img_path =os.path.join(self.image_dir, self.images[index])
        mask_path = os.path.join(self.mask_dir,self.images[index].replace(".jpg","_mask.gif"))
        image = np.array(Image.open(img_path).convert("RGB"))
        mask = np.array(Image.open(mask_path).convert("L"))
        mask[mask == 255.0] = 1.0

        if self.transform is not None:
            augmentations = self.transform(image=image,mask = mask)
            image = augmentations["image"]
            mask = augmentations["mask"]
            mask = torch.unsqueeze(mask, 0)
            mask = mask.type(torch.float32)
        return image,mask