---
title: CTW1500
canonical_url: "https://www.modelscope.cn/datasets/WangXinhan/CTW1500"
md_url: "https://www.modelscope.cn/datasets/WangXinhan/CTW1500.md"
repository: WangXinhan/CTW1500
last_updated: 2026-08-23
license: other
downloads: 24
stars: 0
---

# CTW1500

> CTW1500 - WangXinhan 在 ModelScope 开源的数据集。CTW1500 (MMOCR format)

WangXinhan/CTW1500 是 ModelScope 魔搭社区上的数据集，采用 other 许可。

- **Repository**: WangXinhan/CTW1500
- **License**: other
- **Downloads**: 24
- **Stars**: 0
- **Last updated**: 2026-08-23

Source: https://www.modelscope.cn/datasets/WangXinhan/CTW1500

---

# CTW1500 (MMOCR format)

[CTW1500](https://github.com/Yuliang-Liu/Curve-Text-Detector) is a curve
scene text detection benchmark with 1,000 training and 500 test images. The
official download links (Box / CloudStor) are currently unreliable, so this
repository re-hosts the dataset **already prepared in
[MMOCR](https://github.com/open-mmlab/mmocr) format** for convenience.

## Contents

`ctw1500_mmocr.zip` unpacks to:

```text
ctw1500/
├── textdet_imgs/
│   ├── train/          # 1000 images
│   └── test/           # 500 images
├── textdet_train.json  # MMOCR textdet training annotations
└── textdet_test.json   # MMOCR textdet test annotations
```

## Usage

```bash
pip install modelscope
modelscope download --dataset WangXinhan/CTW1500 --local_dir ./ctw1500_dl
unzip ctw1500_dl/ctw1500_mmocr.zip -d data/
```

Then point MMOCR configs at `data/ctw1500` (the default
`data_root='data/ctw1500'` in the textdet configs works out of the box).

The same archive is mirrored on
[HuggingFace](https://huggingface.co/datasets/HB16888/CTW1500).

## License

The dataset is provided for academic research purposes, following the
original CTW1500 release terms. The preparation pipeline is the one shipped
with MMOCR (`tools/dataset_converters/prepare_dataset.py ctw1500 --task
textdet`).