Scene Text-Spotting based on PSEnet+CRNN

Pytorch implementation of an end to end Text-Spotter with a PSEnet text detector and CRNN text recognizer. We plan to grow this repository into an open research platform for multi-lingual text detection and recognition from natural scene images, targeted towards low-resource languages.

Requirements

• Python 3.6.5
• Pytorch 1.0.1
• pyclipper
• Polygon 3.0.8
• OpenCV 3.4.1

Testing

• Download the trained CRNN and PSEnet models from the links provided below.
• Copy paths of the models and paste them in params.py
• run end-end.py

python end-end.py --img [path to image]

Pre-trained Models

Both PSEnet and CRNN pre-trained models can be found here: gdrive

• the PSEnet model is a multi-lingual text detector, trained on MLT 2019. Works quite well!
• the CRNN recognizes Hindi right now. this one is quite moody :( More coming soon!

Download the models in models/ directory and modify params.py if required.

Samples

Contributors

• Azhar Shaikh, PES University LinkedIn
• Nishant Sinha, OffNote Labs

Work done as part of Internship with OffNote Labs.

References

1. https://github.com/whai362/PSENet
2. https://github.com/Holmeyoung/crnn-pytorch

If this repository helps you, please star it. Thank you!