ai2dcaption

• Description:

This dataset is primarily based off the AI2D Dataset (see here).

See Section 4.1 of our paper for the AI2D-Caption dataset annotation process.

• Homepage: https://huggingface.co/datasets/abhayzala/AI2D-Caption

• Source code: tfds.datasets.ai2dcaption.Builder

• Versions:

  • 1.0.0 (default): Initial release.

• Download size: Unknown size

• Dataset size: 2.01 GiB

• Auto-cached (documentation): No

• Splits:

• Feature structure:

FeaturesDict({
    'caption': Text(shape=(), dtype=string),
    'entities': Sequence({
        'bounds': BBoxFeature(shape=(4,), dtype=float32),
        'cat': ClassLabel(shape=(), dtype=int64, num_classes=10),
        'from': Text(shape=(), dtype=string),
        'id': Text(shape=(), dtype=string),
        'label': Text(shape=(), dtype=string),
        'to': Text(shape=(), dtype=string),
        'type': ClassLabel(shape=(), dtype=int64, num_classes=5),
    }),
    'image': Image(shape=(None, None, 3), dtype=uint8, description=The image of the diagram.),
    'image_filename': Text(shape=(), dtype=string),
    'layout': ClassLabel(shape=(), dtype=int64, num_classes=7),
    'relationships': Sequence(Text(shape=(), dtype=string)),
    'topic': ClassLabel(shape=(), dtype=int64, num_classes=4),
})

• Feature documentation:

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

• Citation:

@inproceedings{Zala2024DiagrammerGPT,
        author = {Abhay Zala and Han Lin and Jaemin Cho and Mohit Bansal},
        title = {DiagrammerGPT: Generating Open-Domain, Open-Platform Diagrams via LLM Planning},
        year = {2024},
        booktitle = {COLM},
}