import os
from loguru import logger

from PIL import Image
from torch.utils.data import Dataset


class CounterAnimal(Dataset):
    """Dataset to load the CounterAnimal dataset with ImageNet labels."""

    def __init__(self, base_path, mode, transform=None, target_transform=None, train=False):
        """Create the dataset.

        Args:
            base_path (str): path to the base folder (the one where the class folders are in)
            mode (str): mode/variant of the dataset (common/counter)
            transform: Image augmentation
            target_transform: label augmentation
            train: train or test set. Train set is not supported
        """
        super().__init__()
        self.base = base_path
        assert mode in ["counter", "common"], f"Supported modes are counter and common, but got '{mode}'"
        assert not train, "CounterAnimal only consists of test data, not training data."
        self.transform = transform
        self.target_transform = target_transform

        self.index = []
        for class_folder in os.listdir(self.base):
            if not os.path.isdir(os.path.join(self.base, class_folder)):
                continue
            # print(f"looking in folder {class_folder}")
            class_idx = int(class_folder.split(" ")[0])
            for variant_folder in os.listdir(os.path.join(self.base, class_folder)):
                # print(f"\tlooking in variant {variant_folder}")
                if not variant_folder.startswith(mode):
                    # print("\t\tskip")
                    continue

                _folder = os.path.join(self.base, class_folder, variant_folder)
                # print(f"\t\tadding {len(os.listdir(_folder))} files to index")
                for file in os.listdir(_folder):
                    if file.lower().split(".")[-1] in ["jpg", "jpeg", "png"]:
                        self.index.append((os.path.join(_folder, file), class_idx))

        # print(f"loaded {len(self.index)} images into the index: {self.index[:5]}...")
        assert len(self.index) > 0, "did not find any images :("

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

    def __getitem__(self, idx):
        path, label = self.index[idx]

        img = Image.open(path).convert("RGB")

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

        if self.target_transform:
            label = self.target_transform(label)

        return img, label