ChartArena / README.md
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---
license: apache-2.0
task_categories:
- image-to-text
language:
- zh
- en
tags:
- Chart-Parsing
pretty_name: ChartArena
size_categories:
- 1K<n<10K
---
# ChartArena <!-- omit in toc -->
**A Comprehensive Bilingual Benchmark for General Chart Parsing across Families, Scenarios, and Formats**
<p align="center">
<a href="https://github.com/pspdada/ChartArena">Github Repo</a>
<a href="https://arxiv.org/abs/2606.01348">Paper</a>
</p>
## Overview <!-- omit in toc -->
**ChartArena** is a bilingual benchmark for evaluating the **chart parsing** capabilities of vision-language models. It covers the full difficulty spectrum of real-world charts, spanning eight chart families across three visual scenarios and two languages.
<table align="center">
<p align="center">
<img src="docs/figures/ChartArena_overview.jpg" width="80%" />
</p>
</table>
## Contents <!-- omit in toc -->
- [Statistics](#statistics)
- [Dataset Structure](#dataset-structure)
- [Data Format](#data-format)
- [Usage](#usage)
- [Citation](#citation)
- [License](#license)
## Statistics
| Item | Details |
| ---------------- | --------------------------------------------------------------------- |
| Chart Families | 8 (bar, line, pie, radar, box plot, combination, flowchart, mind map) |
| Visual Scenarios | 3 (digital, printed, hand-drawn) |
| Languages | 2 (Chinese, English) |
Chart families
| Family | Bar | Line | Pie | Radar | Box Plot | Combination | Flowchart | Mind Map |
| -------- | ------- | ------- | ------- | ------- | -------- | ----------- | ------------ | ------------ |
| Category | Numeric | Numeric | Numeric | Numeric | Numeric | Numeric | Diagrammatic | Diagrammatic |
Visual scenarios
| Scenario | Description |
| ----------------- | ------------------------------------------ |
| Digital Rendering | Charts rendered directly as digital images |
| Printed Photo | Photos of printed charts |
| Hand-drawn Photo | Photos of hand-drawn charts |
Languages
Bilingual: **Chinese (ZH)** and **English (EN)**
## Dataset Structure
```
data/
├── ChartArena.jsonl # annotations for all samples
└── images/
```
## Data Format
Each line of `ChartArena.jsonl` is a JSON object:
```json
{
"img_path": "images/xxx.png",
"chart_type": "柱状图",
"img_type": "电子印刷",
"lang_type": "中文",
"anno": "..."
}
```
| Field | Type | Description |
| ------------ | ------ | ------------------------------------------------------------------------------------------------ |
| `img_path` | string | Relative path from `data/`; also serves as the unique sample key |
| `chart_type` | string | Chart family in Chinese (e.g. `柱状图` = bar, `流程图` = flowchart) |
| `img_type` | string | Visual scenario in Chinese (`电子印刷` = digital, `印刷照片` = printed, `手绘照片` = hand-drawn) |
| `lang_type` | string | Language of chart content (`中文` = Chinese, `英文` = English) |
| `anno` | string | Ground-truth annotation |
## Usage
Please refer to the [Github repository](https://github.com/pspdada/ChartArena) for inference and evaluation scripts.
```bash
# Quick start
git clone https://github.com/pspdada/ChartArena
cd ChartArena
pip install -r requirements.txt
# Run inference
python infer.py --api_type openai_compat --model_name <model> --base_url <url>
# Score
python judge.py
# Generate analysis report
python analyze.py
```
## Citation
```bibtex
% (coming soon)
```
## License
This dataset is released for **research purposes only**.