Datasets:
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9c62b41
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Parent(s):
9ca1529
Delete loading script
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camera.py
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import ast
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import datasets as ds
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import pandas as pd
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_DESCRIPTION = """\
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CAMERA (CyberAgent Multimodal Evaluation for Ad Text GeneRAtion) is the Japanese ad text generation dataset.
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"""
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_CITATION = """\
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@misc{mita2024striking,
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title={Striking Gold in Advertising: Standardization and Exploration of Ad Text Generation},
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author={Masato Mita and Soichiro Murakami and Akihiko Kato and Peinan Zhang},
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year={2024},
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eprint={2309.12030},
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archivePrefix={arXiv},
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primaryClass={id='cs.CL' full_name='Computation and Language' is_active=True alt_name='cmp-lg' in_archive='cs' is_general=False description='Covers natural language processing. Roughly includes material in ACM Subject Class I.2.7. Note that work on artificial languages (programming languages, logics, formal systems) that does not explicitly address natural-language issues broadly construed (natural-language processing, computational linguistics, speech, text retrieval, etc.) is not appropriate for this area.'}
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}
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"""
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_HOMEPAGE = "https://github.com/CyberAgentAILab/camera"
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_LICENSE = """\
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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"""
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_URLS = {
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"without-lp-images": "https://storage.googleapis.com/camera-public/camera-v2.2-minimal.tar.gz",
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"with-lp-images": "https://storage.googleapis.com/camera-public/camera-v2.2.tar.gz",
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}
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_DESCRIPTION = {
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"without-lp-images": "The CAMERA dataset w/o LP images (ver.2.2.0)",
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"with-lp-images": "The CAMERA dataset w/ LP images (ver.2.2.0)",
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}
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_VERSION = ds.Version("2.2.0", "")
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class CameraConfig(ds.BuilderConfig):
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def __init__(self, name: str, version: ds.Version = _VERSION, **kwargs):
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super().__init__(
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name=name,
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description=_DESCRIPTION[name],
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version=version,
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**kwargs,
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)
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class CameraDataset(ds.GeneratorBasedBuilder):
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BUILDER_CONFIGS = [CameraConfig(name="with-lp-images")]
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DEFAULT_CONFIG_NAME = "with-lp-images"
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def _info(self) -> ds.DatasetInfo:
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features = ds.Features(
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{
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"asset_id": ds.Value("int64"),
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"kw": ds.Value("string"),
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"lp_meta_description": ds.Value("string"),
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"title_org": ds.Value("string"),
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"title_ne1": ds.Value("string"),
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"title_ne2": ds.Value("string"),
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"title_ne3": ds.Value("string"),
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"domain": ds.Value("string"),
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"parsed_full_text_annotation": ds.Sequence(
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{
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"text": ds.Value("string"),
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"xmax": ds.Value("int64"),
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"xmin": ds.Value("int64"),
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"ymax": ds.Value("int64"),
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"ymin": ds.Value("int64"),
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}
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),
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}
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)
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if self.config.name == "with-lp-images":
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features["lp_image"] = ds.Image()
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return ds.DatasetInfo(
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description=_DESCRIPTION,
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citation=_CITATION,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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features=features,
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)
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def _split_generators(self, dl_manager: ds.DownloadManager):
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base_dir = dl_manager.download_and_extract(_URLS[self.config.name])
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lp_image_dir: str | None = None
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if self.config.name == "without-lp-images":
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data_dir = f"{base_dir}/camera-v2.2-minimal"
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elif self.config.name == "with-lp-images":
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data_dir = f"{base_dir}/camera-v2.2"
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lp_image_dir = f"{data_dir}/lp-screenshot"
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else:
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raise ValueError(f"Invalid config name: {self.config.name}")
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return [
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ds.SplitGenerator(
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name=ds.Split.TRAIN,
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gen_kwargs={
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"file": f"{data_dir}/train.csv",
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"lp_image_dir": lp_image_dir,
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},
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),
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ds.SplitGenerator(
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name=ds.Split.VALIDATION,
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gen_kwargs={
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"file": f"{data_dir}/dev.csv",
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"lp_image_dir": lp_image_dir,
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},
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),
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ds.SplitGenerator(
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name=ds.Split.TEST,
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gen_kwargs={
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"file": f"{data_dir}/test.csv",
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"lp_image_dir": lp_image_dir,
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},
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),
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]
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def _generate_examples(self, file: str, lp_image_dir: str | None = None):
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df = pd.read_csv(file)
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for i, data_dict in enumerate(df.to_dict("records")):
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asset_id = data_dict["asset_id"]
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example_dict = {
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"asset_id": asset_id,
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"kw": data_dict["kw"],
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"lp_meta_description": data_dict["lp_meta_description"],
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"title_org": data_dict["title_org"],
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"title_ne1": data_dict.get("title_ne1", ""),
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"title_ne2": data_dict.get("title_ne2", ""),
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"title_ne3": data_dict.get("title_ne3", ""),
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"domain": data_dict.get("domain", ""),
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"parsed_full_text_annotation": ast.literal_eval(
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data_dict["parsed_full_text_annotation"]
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),
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}
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if self.config.name == "with-lp-images" and lp_image_dir is not None:
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file_name = f"screen-1200-{asset_id}.png"
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example_dict["lp_image"] = f"{lp_image_dir}/{file_name}"
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yield i, example_dict
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