Delete how2sign-clips.py

how2sign-clips.py

@@ -1,164 +0,0 @@
-# Copyright 2023 Thinh T. Duong
-import os
-import datasets
-from glob import glob
-
-
-logger = datasets.logging.get_logger(__name__)
-
-
-_CITATION = """
-
-"""
-_DESCRIPTION = """
-"""
-_HOMEPAGE = "https://how2sign.github.io/index.html"
-_REPO_URL = "https://huggingface.co/datasets/VieSignLang/how2sign-clips/resolve/main"
-_URLS = {
-    "meta": f"{_REPO_URL}/metadata/" + "sharded_how2sign_realigned_{split}.parquet",
-    "video": f"{_REPO_URL}/videos/" + "{type}/{split}/*/*.zip",
-}
-
-
-class How2SignClipsConfig(datasets.BuilderConfig):
-    """How2Sign 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):
-    """How2Sign dataset."""
-    BUILDER_CONFIGS = [
-        How2SignClipsConfig(name="rgb"),
-        # How2SignClipsConfig(name="keypoints"),
-    ]
-    DEFAULT_CONFIG_NAME = "rgb"
-
-    def _info(self) -> datasets.DatasetInfo:
-        features = datasets.Features({
-            "VIDEO_ID": datasets.Value("string"),
-            "VIDEO_NAME": datasets.Value("string"),
-            "SENTENCE_ID": datasets.Value("string"),
-            "SENTENCE_NAME": datasets.Value("string"),
-            "START_REALIGNED": datasets.Value("float64"),
-            "END_REALIGNED": datasets.Value("float64"),
-            "SENTENCE": datasets.Value("string"),
-            "VIDEO": datasets.Value("large_binary"),
-        })
-        # 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": {
-                "name": datasets.Split.TRAIN,
-                "num_shards": 32,
-            },
-            "test": {
-                "name": datasets.Split.TEST,
-                "num_shards": 3,
-            },
-            "val": {
-                "name": datasets.Split.VALIDATION,
-                "num_shards": 2,
-            },
-        }
-
-        return [
-            datasets.SplitGenerator(
-                name=info["name"],
-                gen_kwargs={
-                    "metadata_path": dl_manager.download(
-                        _URLS["meta"].format(split=split)
-                    ),
-                    "video_dirs": dl_manager.download_and_extract(
-                        glob(
-                            _URLS["video"].format(
-                                type=self.config.name,
-                                split=split
-                            )
-                        )
-                    ),
-                    "num_shards": info["num_shards"],
-                },
-            )
-            for split, info in split_dict.items()
-        ]
-
-    def _generate_examples(
-        self, metadata_path: str,
-        video_dirs: list[str],
-        num_shards: int,
-    ) -> tuple[int, dict]:
-        """
-        Generate examples from metadata.
-        :param metadata_path:       Path to metadata.
-        :param visual_dirs:         Directories of videos.
-        :param num_shards:          Number of shards.
-        :yield:                     Example.
-        """
-        dataset = datasets.load_dataset(
-            "parquet",
-            data_files=metadata_path,
-            split="train",
-        )
-        for i, sample in enumerate(dataset):
-            shard_idx = sample["shard"]
-            for video_dir in video_dirs:
-                video_path = os.path.join(
-                    video_dir,
-                    f"shard_{shard_idx:03d}_{num_shards:03d}",
-                    sample["SENTENCE_NAME"] + ".mp4",
-                    # sample["id"] + ".mp4",
-                )
-                if os.path.exists(video_path):
-                    yield i, {
-                        "VIDEO_ID": sample["VIDEO_ID"],
-                        "VIDEO_NAME": sample["VIDEO_NAME"],
-                        "SENTENCE_ID": sample["SENTENCE_ID"],
-                        "SENTENCE_NAME": sample["SENTENCE_NAME"],
-                        "START_REALIGNED": sample["START_REALIGNED"],
-                        "END_REALIGNED": sample["END_REALIGNED"],
-                        "SENTENCE": sample["SENTENCE"],
-                        "VIDEO": self.__get_binary_data(video_path),
-                    }
-                    # 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()