GitHub - meijieru/crnn.pytorch: Convolutional recurrent network in pytorch (original) (raw)

Convolutional Recurrent Neural Network

This software implements the Convolutional Recurrent Neural Network (CRNN) in pytorch. Origin software could be found in crnn

Run demo

A demo program can be found in demo.py. Before running the demo, download a pretrained model from Baidu Netdisk or Dropbox. This pretrained model is converted from auther offered one by tool. Put the downloaded model file crnn.pth into directory data/. Then launch the demo by:

The demo reads an example image and recognizes its text content.

Example image:

Expected output: loading pretrained model from ./data/crnn.pth a-----v--a-i-l-a-bb-l-ee-- => available

Dependence

• warp_ctc_pytorch
• lmdb

Train a new model

1. Construct dataset following origin guide. If you want to train with variable length images (keep the origin ratio for example), please modify the tool/create_dataset.py and sort the image according to the text length.
2. Execute python train.py --adadelta --trainRoot {train_path} --valRoot {val_path} --cuda. Explore train.py for details.

Cite

@article{shi2016end, title={An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition}, author={Shi, Baoguang and Bai, Xiang and Yao, Cong}, journal={IEEE transactions on pattern analysis and machine intelligence}, volume={39}, number={11}, pages={2298--2304}, year={2016}, publisher={IEEE} }