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Graph Dataset: Image, LabelMe, and OBB

This dataset contains graph/chart images paired with LabelMe JSON polygon annotations and OBB text annotations. Rows are reproducibly divided into 80% training and 20% validation splits.

Dataset Summary

Metric Count
Matched image/LabelMe/OBB rows 6442
Train rows 5154
Validation rows 1288
Source image files 6442
Source LabelMe JSON files 6442
Source OBB text files 6442
Train row groups 52
Validation row groups 13
Combined parquet size 2194.49 MB

Columns

Column Type Description
image_name string Source filename without extension
image image Image decoded by Hugging Face Datasets
labelme string LabelMe annotation serialized as JSON
obb string OBB annotation text from the matching .txt file

Load the Dataset

import json

from datasets import load_dataset

dataset = load_dataset(
    "parquet",
    data_files={
        "train": "data/train.parquet",
        "validation": "data/validation.parquet",
    },
)
row = dataset["train"][0]
image = row["image"]
labelme = json.loads(row["labelme"])
obb_lines = row["obb"].splitlines()

The parquet file is written in bounded row groups by create_hf_parquet_dataset.py to avoid constructing the complete image dataset in memory during export.

Last updated: 2026-05-25

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