models/text_recognition_crnn/README.md

# CRNN

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

Note:
- Model source:
    - `text_recognition_CRNN_EN_2021sep.onnx`: https://docs.opencv.org/4.5.2/d9/d1e/tutorial_dnn_OCR.html (CRNN_VGG_BiLSTM_CTC.onnx)
    - `text_recognition_CRNN_CN_2021nov.onnx`: https://docs.opencv.org/4.5.2/d4/d43/tutorial_dnn_text_spotting.html (crnn_cs_CN.onnx)
- `text_recognition_CRNN_EN_2021sep.onnx` can detect digits (0\~9) and letters (return lowercase letters a\~z) (view `charset_36_EN.txt` for details).
- `text_recognition_CRNN_CN_2021nov.onnx` can detect digits (0\~9), upper/lower-case letters (a\~z and A\~Z), some Chinese characters and some special characters (view `charset_3944_CN.txt` for details).
- For details on training this model series, please visit https://github.com/zihaomu/deep-text-recognition-benchmark.

## Demo

***NOTE***:
- This demo uses [text_detection_db](../text_detection_db) as text detector.
- Selected model must match with the charset:
    - Try `text_recognition_CRNN_EN_2021sep.onnx` with `charset_36_EN.txt`.
    - Try `text_recognition_CRNN_CN_2021sep.onnx` with `charset_3944_CN.txt`.

Run the demo detecting English:
```shell
# detect on camera input
python demo.py
# detect on an image
python demo.py --input /path/to/image
```

Run the demo detecting Chinese:
```shell
# detect on camera input
python demo.py --model text_recognition_CRNN_CN_2021nov.onnx --charset charset_3944_CN.txt
# detect on an image
python demo.py --input /path/to/image --model text_recognition_CRNN_CN_2021nov.onnx --charset charset_3944_CN.txt
```

### Examples

![CRNNCTC](./examples/CRNNCTC.gif)

![demo](./examples/demo.jpg)

## License

All files in this directory are licensed under [Apache 2.0 License](./LICENSE).

## Reference

- https://arxiv.org/abs/1507.05717
- https://github.com/bgshih/crnn
- https://github.com/meijieru/crnn.pytorch
- https://github.com/zihaomu/deep-text-recognition-benchmark
- https://docs.opencv.org/4.5.2/d9/d1e/tutorial_dnn_OCR.html