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camera.py

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+import ast
+
+import datasets as ds
+import pandas as pd
+
+_DESCRIPTION = """\
+CAMERA (CyberAgent Multimodal Evaluation for Ad Text GeneRAtion) is the Japanese ad text generation dataset.
+"""
+
+_CITATION = """\
+@misc{mita2024striking,
+    title={Striking Gold in Advertising: Standardization and Exploration of Ad Text Generation},
+    author={Masato Mita and Soichiro Murakami and Akihiko Kato and Peinan Zhang},
+    year={2024},
+    eprint={2309.12030},
+    archivePrefix={arXiv},
+    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.'}
+}
+"""
+
+_HOMEPAGE = "https://github.com/CyberAgentAILab/camera"
+
+_LICENSE = """\
+This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
+"""
+
+_URLS = {
+    "without-lp-images": "https://storage.googleapis.com/camera-public/camera-v2.2-minimal.tar.gz",
+    "with-lp-images": "https://storage.googleapis.com/camera-public/camera-v2.2.tar.gz",
+}
+
+_DESCRIPTION = {
+    "without-lp-images": "The CAMERA dataset w/o LP images (ver.2.2.0)",
+    "with-lp-images": "The CAMERA dataset w/ LP images (ver.2.2.0)",
+}
+
+_VERSION = ds.Version("2.2.0", "")
+
+
+class CameraConfig(ds.BuilderConfig):
+    def __init__(self, name: str, version: ds.Version = _VERSION, **kwargs):
+        super().__init__(
+            name=name,
+            description=_DESCRIPTION[name],
+            version=version,
+            **kwargs,
+        )
+
+
+class CameraDataset(ds.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [CameraConfig(name="without-lp-images")]
+
+    DEFAULT_CONFIG_NAME = "without-lp-images"
+
+    def _info(self) -> ds.DatasetInfo:
+        features = ds.Features(
+            {
+                "asset_id": ds.Value("int64"),
+                "kw": ds.Value("string"),
+                "lp_meta_description": ds.Value("string"),
+                "title_org": ds.Value("string"),
+                "title_ne1": ds.Value("string"),
+                "title_ne2": ds.Value("string"),
+                "title_ne3": ds.Value("string"),
+                "domain": ds.Value("string"),
+                "parsed_full_text_annotation": ds.Sequence(
+                    {
+                        "text": ds.Value("string"),
+                        "xmax": ds.Value("int64"),
+                        "xmin": ds.Value("int64"),
+                        "ymax": ds.Value("int64"),
+                        "ymin": ds.Value("int64"),
+                    }
+                ),
+            }
+        )
+
+        if self.config.name == "with-lp-images":
+            features["lp_image"] = ds.Image()
+
+        return ds.DatasetInfo(
+            description=_DESCRIPTION,
+            citation=_CITATION,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            features=features,
+        )
+
+    def _split_generators(self, dl_manager: ds.DownloadManager):
+        base_dir = dl_manager.download_and_extract(_URLS[self.config.name])
+        lp_image_dir: str | None = None
+
+        if self.config.name == "without-lp-images":
+            data_dir = f"{base_dir}/camera-v2.2-minimal"
+        elif self.config.name == "with-lp-images":
+            data_dir = f"{base_dir}/camera-v2.2"
+            lp_image_dir = f"{data_dir}/lp-screenshot"
+        else:
+            raise ValueError(f"Invalid config name: {self.config.name}")
+
+        return [
+            ds.SplitGenerator(
+                name=ds.Split.TRAIN,
+                gen_kwargs={
+                    "file": f"{data_dir}/train.csv",
+                    "lp_image_dir": lp_image_dir,
+                },
+            ),
+            ds.SplitGenerator(
+                name=ds.Split.VALIDATION,
+                gen_kwargs={
+                    "file": f"{data_dir}/dev.csv",
+                    "lp_image_dir": lp_image_dir,
+                },
+            ),
+            ds.SplitGenerator(
+                name=ds.Split.TEST,
+                gen_kwargs={
+                    "file_name": f"{data_dir}/test.csv",
+                    "lp_image_dir": lp_image_dir,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, file: str, lp_image_dir: str | None = None):
+        df = pd.read_csv(file)
+        for i, data_dict in enumerate(df.to_dict("records")):
+            asset_id = data_dict["asset_id"]
+            example_dict = {
+                "asset_id": asset_id,
+                "kw": data_dict["kw"],
+                "lp_meta_description": data_dict["lp_meta_description"],
+                "title_org": data_dict["title_org"],
+                "title_ne1": data_dict.get("title_ne1", ""),
+                "title_ne2": data_dict.get("title_ne2", ""),
+                "title_ne3": data_dict.get("title_ne3", ""),
+                "domain": data_dict.get("domain", ""),
+                "parsed_full_text_annotation": ast.literal_eval(
+                    data_dict["parsed_full_text_annotation"]
+                ),
+            }
+
+            if self.config.name == "with-lp-images" and lp_image_dir is not None:
+                file_name = f"screen-1200-{asset_id}.png"
+                example_dict["lp_image"] = f"{lp_image_dir}/{file_name}"
+
+            yield i, example_dict