| --- |
| license: other |
| license_name: ctw1500-research |
| license_link: https://github.com/open-mmlab/mmocr/blob/main/dataset_zoo/ctw1500/metafile.yml |
| tags: |
| - text-detection |
| - ocr |
| - scene-text |
| - mmocr |
| --- |
| |
| # 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 |
| hf download HB16888/CTW1500 --repo-type dataset --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 |
| [ModelScope](https://modelscope.cn/datasets/WangXinhan/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`). |
|
|
