| |
| 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"), |
| |
| ] |
| 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"), |
| }) |
| |
| |
| |
| |
| |
| |
| |
|
|
| 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", |
| |
| ) |
| 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), |
| } |
| |
| |
| |
| |
| |
| |
| |
|
|
| def __get_binary_data(self, path): |
| with open(path, "rb") as f: |
| return f.read() |
|
|
