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custom_vs_default_github_avatars.py

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+"""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(),
+            }