import os
import torch

import datasets
from pycocotools.coco import COCO

_DESCRIPTION = """\
    Watermark Dataset
"""

_VERSION = datasets.Version("1.0.0")

_REPO = "data"# "https://huggingface.co/datasets/bastienp/visible-watermark-pita/raw/main/data"
_URLS = {"train": f"{_REPO}/train.zip", "valid": f"{_REPO}/valid.zip"}

_CATEGORIES = ["watermark"]

class WatermarkPita(datasets.GeneratorBasedBuilder):
    """Watermark Dataset"""

    VERSION = datasets.Version("1.0.0")

    def _info(self):
        return datasets.DatasetInfo(
            features=datasets.Features(
                {
                    "image": datasets.Image(),
                    "objects": datasets.Sequence({
                        "label": datasets.ClassLabel(names=_CATEGORIES),
                        "bbox": datasets.Sequence(datasets.Value("int32"), length=4)
                    }),
                }
            ),
    
            description=_DESCRIPTION,
        )

    def _split_generators(self, dl_manager):
        return 

    def _generate_examples(self, images, metadata_path):