import json

import datasets
from datasets.tasks import QuestionAnsweringExtractive


logger = datasets.logging.get_logger(__name__)

_URL = "https://huggingface.co/datasets/jaradat/pidray-semantics/resolve/main/pixel_values.tar.gz"
_URL2 = "https://huggingface.co/datasets/jaradat/pidray-semantics/resolve/main/label.tar.gz"
                      
class pidraySemantics(datasets.GeneratorBasedBuilder):

    def _info(self):
        return datasets.DatasetInfo(
            features=datasets.Features(
                {
                    #"text": datasets.Value("string"),
                    "pixel_values": datasets.Image(),
                    "label": datasets.Image(),
                }
            ),
            # No default supervised_keys (as we have to pass both question
            # and context as input).
            supervised_keys=None,
            homepage="https://huggingface.co/datasets/jaradat/pidray-semantics",

        )

    def _split_generators(self, dl_manager):
        path = dl_manager.download(_URL)
        image_iters = dl_manager.iter_archive(path)

        
        path2 = dl_manager.download(_URL2)
        label_iters = dl_manager.iter_archive(path2)

        return [
            datasets.SplitGenerator(
            name=datasets.Split.TRAIN, 
            gen_kwargs={
                "images": image_iters,
                "label": label_iters
                }
            ),
            
        ]

    def _generate_examples(self, images, label):
        idx = 0
        # iterate through images
        
        for (filepath, image), (filepath2, image2) in zip(images, label):
                        
            yield idx, {
                "pixel_values": {"path": filepath, "bytes": image.read()},
                "label": {"path": filepath2, "bytes": image2.read()},
            }
            idx += 1