import logging

import torch
from PIL import Image
from torchvision import transforms

from library.utils import setup_logging

setup_logging()

logger = logging.getLogger(__name__)


class ImageLoadingDataset(torch.utils.data.Dataset):
    def __init__(self, image_paths):
        self.images = image_paths

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

    def __getitem__(self, idx):
        img_path = self.images[idx]

        try:
            image = Image.open(img_path).convert("RGB")
            # convert to tensor temporarily so dataloader will accept it
            tensor_pil = transforms.functional.pil_to_tensor(image)
        except Exception as e:
            logger.error(f"Could not load image path / 画像を読み込めません: {img_path}, error: {e}")
            return None

        return (tensor_pil, img_path)