| """Custom vs. default GitHub avatars dataset""" |
|
|
| from pathlib import Path |
| from typing import List |
|
|
| import datasets |
| from datasets.tasks import ImageClassification |
|
|
|
|
| logger = datasets.logging.get_logger(__name__) |
|
|
| _URL = "https://huggingface.co/datasets/codecrafters/github-avatars/resolve/main/custom-and-default-avatars.zip" |
|
|
| _HOMEPAGE = "https://codecrafters.io" |
|
|
| _DESCRIPTION = "A dataset of custom vs. default GitHub avatars" |
|
|
|
|
| class CatsVsDogs(datasets.GeneratorBasedBuilder): |
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features( |
| { |
| "image": datasets.Image(), |
| "labels": datasets.features.ClassLabel(names=["custom", "default"]), |
| } |
| ), |
| supervised_keys=("image", "labels"), |
| task_templates=[ |
| ImageClassification(image_column="image", label_column="labels") |
| ], |
| homepage=_HOMEPAGE, |
| ) |
|
|
| def _split_generators( |
| self, dl_manager: datasets.DownloadManager |
| ) -> List[datasets.SplitGenerator]: |
| images_path = ( |
| Path(dl_manager.download_and_extract(_URL)) / "custom-and-default-avatars" |
| ) |
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, gen_kwargs={"images_path": images_path} |
| ), |
| ] |
|
|
| def _generate_examples(self, images_path): |
| logger.info("generating examples from = %s", images_path) |
| for i, filepath in enumerate(images_path.glob("**/*.png")): |
| yield str(i), { |
| "image": str(filepath), |
| "labels": filepath.parent.name.lower(), |
| } |
|
|