chore: add builder

how2sign-clips.py

@@ -0,0 +1,122 @@
+# Copyright 2023 Thinh T. Duong
+import os
+import datasets
+
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_CITATION = """
+
+"""
+_DESCRIPTION = """
+    This dataset contain short clips of Vietnamese speakers.
+"""
+_HOMEPAGE = "https://how2sign.github.io/index.html"
+_REPO_URL = "https://huggingface.co/VieSignLang/how2sign-clips/resolve/main"
+_URLS = {
+    "meta": f"{_REPO_URL}/metadata/" + "{split}.parquet",
+    "video": f"{_REPO_URL}/videos/" + "{type}/{split}.zip",
+}
+
+
+class How2SignClipsConfig(datasets.BuilderConfig):
+    """Vietnamese Speaker Clip configuration."""
+
+    def __init__(self, name, **kwargs):
+        """
+        :param name:    Name of subset.
+        :param kwargs:  Arguments.
+        """
+        super(How2SignClipsConfig, self).__init__(
+            name=name,
+            version=datasets.Version("1.0.0"),
+            description=_DESCRIPTION,
+            **kwargs,
+        )
+
+
+class How2SignClips(datasets.GeneratorBasedBuilder):
+    """Vietnamese Speaker Clip dataset."""
+    BUILDER_CONFIGS = [
+        How2SignClipsConfig(name="rgb"),
+        How2SignClipsConfig(name="keypoints"),
+    ]
+    DEFAULT_CONFIG_NAME = "rgb"
+
+    def _info(self) -> datasets.DatasetInfo:
+        features = datasets.Features({
+            "id": datasets.Value("string"),
+            "type": datasets.Value("string"),
+            "view": datasets.Value("string"),
+            "text": datasets.Value("string"),
+            "video": datasets.Value("large_binary"),
+        })
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(
+        self, dl_manager: datasets.DownloadManager
+    ) -> list[datasets.SplitGenerator]:
+        """
+        Get splits.
+        :param dl_manager:  Download manager.
+        :return:            Splits.
+        """
+        split_dict = {
+            "train": datasets.Split.TRAIN,
+            "test": datasets.Split.TEST,
+            "val": datasets.Split.VALIDATION,
+        }
+
+        return [
+            datasets.SplitGenerator(
+                name=name,
+                gen_kwargs={
+                    "metadata_path": dl_manager.download(
+                        _URLS["meta"].format(split=split)
+                    ),
+                    "video_dir": dl_manager.download_and_extract(
+                        _URLS["video"].format(
+                            type=self.config.name,
+                            split=split
+                        )
+                    ),
+                },
+            )
+            for split, name in split_dict.items()
+        ]
+
+    def _generate_examples(
+        self, metadata_paths: str,
+        video_dir: str,
+    ) -> tuple[int, dict]:
+        """
+        Generate examples from metadata.
+        :param metadata_path:       Path to metadata.
+        :param visual_dir:          Directory of visual data.
+        :yield:                     Example.
+        """
+        dataset = datasets.load_dataset(
+            "parquet",
+            data_files=metadata_paths,
+            split="train",
+        )
+        for i, sample in enumerate(dataset):
+            video_path = os.path.join(video_dir, sample["id"] + ".mp4")
+            yield i, {
+                "id": sample["id"],
+                "type": sample["type"],
+                "view": sample["view"],
+                "text": sample["text"],
+                "video": self.__get_binary_data(video_path),
+            }
+
+    def __get_binary_data(self, path):
+        with open(path, "rb") as f:
+            return f.read()