MORAN: A Multi-Object Rectified Attention Network for Scene Text Recognition

MORAN is a network with rectification mechanism for general scene text recognition. The paper (accepted to appear in Pattern Recognition, 2019) in arXiv, online version is available now.

Here is a brief introduction in Chinese.

Improvements of MORAN v2:

More stable rectification network for one-stage training
Replace VGG backbone by ResNet
Use bidirectional decoder (a trick borrowed from ASTER)

Version	IIIT5K	SVT	IC03	IC13	SVT-P	CUTE80	IC15 (1811)	IC15 (2077)
MORAN v1 (curriculum training)*	91.2	88.3	95.0	92.4	76.1	77.4	74.7	68.8
MORAN v2 (one-stage training)	93.4	88.3	94.2	93.2	79.7	81.9	77.8	73.9

*The results of v1 were reported in our paper. If this project is helpful for your research, please cite our Pattern Recognition paper.

Requirements

(Welcome to develop MORAN together.)

Use pip to install the following libraries.

    pip install -r requirements.txt

Data Preparation

Please convert your own dataset to LMDB format by using the tool provided by @Baoguang Shi.

You can also download the training (NIPS 2014, CVPR 2016) and testing datasets prepared by us.

about 20G training datasets and testing datasets in LMDB format, password: l8em

The raw pictures of testing datasets can be found here.

Training and Testing

Modify the path to dataset folder in train_MORAN.sh:

	--train_nips path_to_dataset \
	--train_cvpr path_to_dataset \
	--valroot path_to_dataset \

And start training: (manually decrease the learning rate for your task)

	sh train_MORAN.sh

Demo

Download the model parameter file demo.pth.

BaiduYun (password: l8em)
Google Drive
OneDrive

Put it into root folder. Then, execute the demo.py for more visualizations.

	python demo.py

Citation

@article{cluo2019moran,
  author  = {Canjie Luo, Lianwen Jin, Zenghui Sun},
  title   = {MORAN: A Multi-Object Rectified Attention Network for Scene Text Recognition},
  journal = {Pattern Recognition}, 
  volume  = {}, 
  number  = {}, 
  pages   = {},
  year    = {2019}, 
}

Acknowledgment

The repo is developed based on @Jieru Mei's crnn.pytorch and @marvis' ocr_attention. Thanks for your contribution.

Attention

The project is only free for academic research purposes.

AlanNewImage/MORAN_v2