|
|
| 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( |
| { |
| |
| "pixel_values": datasets.Image(), |
| "label": datasets.Image(), |
| } |
| ), |
| |
| |
| 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 |
| |
| |
| 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 |
|
|