| | import json |
| | import datasets |
| | import datetime |
| |
|
| | _CITATION = """ |
| | @inproceedings{zellersluhessel2021merlot, |
| | title={MERLOT: Multimodal Neural Script Knowledge Models}, |
| | author={Zellers, Rowan and Lu, Ximing and Hessel, Jack and Yu, Youngjae and Park, Jae Sung and Cao, Jize and Farhadi, Ali and Choi, Yejin}, |
| | booktitle={Advances in Neural Information Processing Systems 34}, |
| | year={2021} |
| | } |
| | """ |
| |
|
| | _DESCRIPTION = """\ |
| | YT-Temporal-180M, a large and diverse dataset of 6 million videos (spanning 180M extracted frames) |
| | that covers diverse topics. |
| | """ |
| |
|
| | _URL_BASE = "https://rowanzellers.com/merlot/#data" |
| |
|
| | url_numbers = ["00" + str(i) if i < 10 else "0" + str(i) for i in range(100)] |
| | _DL_URLS = [ |
| | f"https://storage.googleapis.com/merlot/yttemporal180m/yttemporal180m_{num}of100.jsonl.gz" |
| | for num in url_numbers |
| | ] |
| |
|
| |
|
| | def json_serializer(o): |
| | if isinstance(o, datetime): |
| | return str(o) |
| |
|
| | raise TypeError(f"Object of type {o.__class__.__name__} is not JSON serializable") |
| |
|
| |
|
| | class yttemporal180mConfig(datasets.BuilderConfig): |
| | """BuilderConfig for ActivityNet Captions.""" |
| |
|
| | def __init__(self, **kwargs): |
| | super(yttemporal180mConfig, self).__init__( |
| | version=datasets.Version("2.1.0", ""), **kwargs |
| | ) |
| |
|
| |
|
| | class yttemporal180m(datasets.GeneratorBasedBuilder): |
| |
|
| | DEFAULT_CONFIG_NAME = "default" |
| | BUILDER_CONFIGS = [ |
| | yttemporal180mConfig( |
| | name="default", description="Default full yttemporal180m dataset" |
| | ), |
| | ] |
| |
|
| | def _info(self): |
| | return datasets.DatasetInfo( |
| | description=_DESCRIPTION, |
| | features=datasets.Features( |
| | { |
| | "video_id": datasets.Value("string"), |
| | "video_url": datasets.Value("string"), |
| | "caption": datasets.Value("string"), |
| | "timestamp_start": datasets.Value("float32"), |
| | "timestamp_stop": datasets.Value("float32"), |
| | "meta": datasets.Value("string"), |
| | } |
| | ), |
| | supervised_keys=None, |
| | homepage=_URL_BASE, |
| | citation=_CITATION, |
| | ) |
| |
|
| | def _split_generators(self, dl_manager): |
| | archive_paths = [dl_manager.download_and_extract(url) for url in _DL_URLS] |
| |
|
| | train_split = [ |
| | datasets.SplitGenerator( |
| | name=datasets.Split.TRAIN, |
| | gen_kwargs={"jsonl_files": archive_paths}, |
| | ) |
| | ] |
| |
|
| | return train_split |
| |
|
| | def _generate_examples(self, jsonl_files): |
| | """This function returns the examples.""" |
| | idx = 0 |
| | for file in jsonl_files: |
| | with open(file, encoding="utf-8") as jsonl_file: |
| | json_list = list(jsonl_file) |
| | for json_str in json_list: |
| | infos = json.loads(json_str) |
| |
|
| | id = infos["info"]["display_id"] |
| | url = "https://www.youtube.com/watch?v=" + id |
| |
|
| | |
| | max_sec_per_segment = 15 |
| | last_caption_timestamp = infos["subtitles"][-1]["time"] |
| | num_chunks = ( |
| | int(divmod(last_caption_timestamp, max_sec_per_segment)[0]) + 1 |
| | ) |
| | time_chunks = [ |
| | i * max_sec_per_segment for i in range(num_chunks + 1) |
| | ] |
| | time_chunk_idx = 0 |
| | caption = "" |
| | for el in infos["subtitles"]: |
| | if ( |
| | el["time"] > time_chunks[time_chunk_idx + 1] |
| | or el["time"] == last_caption_timestamp |
| | ): |
| | timestamp_start = float(time_chunks[time_chunk_idx]) |
| | timestamp_stop = float(time_chunks[time_chunk_idx + 1]) |
| | time_chunk_idx += 1 |
| |
|
| | metadata_dict = { |
| | "asr_info": infos["denoised"], |
| | "info": infos["info"], |
| | "subtitles": infos["subtitles"], |
| | "title": infos["info"]["title"], |
| | } |
| | yield idx, { |
| | "video_id": id, |
| | "video_url": url, |
| | "caption": caption, |
| | "timestamp_start": timestamp_start, |
| | "timestamp_stop": timestamp_stop |
| | if el["time"] != last_caption_timestamp |
| | else last_caption_timestamp, |
| | "meta": json.dumps( |
| | metadata_dict, default=json_serializer, indent=2 |
| | ), |
| | } |
| | idx += 1 |
| | caption = "" |
| | else: |
| | caption += el["word"] + " " |
| |
|
