import datasets
import tarfile
import os

_CITATION = """\
@InProceedings{huggingface:dataset,
title = {Bee-wings-large},
author={Slawek Maciura},
year={2023}
}
"""

_DESCRIPTION = """\
Random Small 
"""
_HOMEPAGE = ""

_LICENSE = ""

_REPO = "https://huggingface.co/datasets/smaciu/bee-wings-large"


class ImageSet(datasets.GeneratorBasedBuilder):
    """Small sample of image-text pairs"""

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    'file_name': datasets.Value('string'),
                    'image': datasets.Image(),
                    'label': datasets.Value("string"),
                }
            ),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        images_archive = dl_manager.download(f"{_REPO}/resolve/main/bee-wings-large.tar")
     
        
        image_iters = dl_manager.iter_archive(images_archive)
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN,gen_kwargs={"images": image_iters}),
        ]

    def _generate_examples(self, images):
        """ This function returns the examples in the raw (text) form."""
    
        for idx, (filepath, image) in enumerate(images):
            
            
            filename = os.path.basename(filepath)  # Get the file name from the path
            description = filename[:2]
            yield idx, {
                "file_name": filename,
                "image": {"path": filepath, "bytes": image.read()},
                "label": description,
            }