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Datasets:
psp-dada
/
ChartArena

Tasks:
Image-to-Text
Modalities:
Image
Formats:
imagefolder
Languages:
Chinese
English
Size:
1K - 10K
ArXiv:
Tags:
Chart-Parsing
Libraries:
Datasets
License:
Dataset card Data Studio Files
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1
ChartArena
File size: 4,081 Bytes
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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**.