import os

from PIL import Image

from torch.utils.data import Dataset

import numpy as np

class ChestDataset(Dataset):

    def __init__(self, image_dir, mask_dir, transform=None):

        super(ChestDataset, self).__init__()

        self.image_dir = image_dir

        self.mask_dir = mask_dir

        self.transform = transform

        self.images = os.listdir(image_dir)

        self.masked_images = os.listdir(mask_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.masked_images[index])

        image = np.array(Image.open(img_path).convert('RGB'), dtype=np.float32)

        mask = np.array(Image.open(mask_path).convert('L'), dtype=np.float32)

        #mask[mask == 255.0] = 1.0

        if self.transform is not None:

            augmentation = self.transform(image=image, mask=mask)

            image = augmentation['image']

            mask = augmentation['mask']

        return image, mask