Datasets:
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
- Downloads last month
- 8