import datasets
from description import description

_DESCRIPTION ="""Fetus Brain Abnormalities Images dataset"""

_CITATION = """
@misc{
    fetal-brain-abnormalities-ultrasound_dataset,
    title = { Fetal Brain Abnormalities Ultrasound Dataset },
    type = { Open Source Dataset },
    author = { Hritwik Trivedi },
    howpublished = { \url{ https://universe.roboflow.com/hritwik-trivedi-gkgrv/fetal-brain-abnormalities-ultrasound } },
    url = { https://universe.roboflow.com/hritwik-trivedi-gkgrv/fetal-brain-abnormalities-ultrasound },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { oct },
    note = { visited on 2024-03-12 },
}
"""

_URL = "https://huggingface.co/datasets/KBayoud/roboflow-fetus-head-abnormalities/resolve/main/images.tar.gz"

class FetusBrain(datasets.GeneratorBasedBuilder):

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    'text': datasets.Value('string'),
                    'image': datasets.Image(),
                }
            ),

            supervised_keys=None,
            homepage='https://huggingface.co/datasets/KBayoud/roboflow-fetus-head-abnormalities',
            citation=_CITATION,
        )
    

    def _split_generators(self, dl_manager):
        path = dl_manager.download_and_extract(_URL)
        image_iters = dl_manager.iter_archive(path)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "images": image_iters
                }
            ),
        ]
            
    def _generate_examples(self, images):
        idx = 0
        # iterate over the images 
        for filepath, image in images:
            yield idx, {
                'image': {'path': filepath, 'bytes': image.read()},
                'text': description[idx]
            }
            idx += 1