__base__

Recognition Base Model

1. Introduction

This code repository contains an implementation of (CRNN:An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition)(TPAMI) and (Res-Bilstm-Attn:What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis) (ICCV 2019).

2. Preparing Dataset

Train Dataset

Dataset	Samples	Description	Release
MJSynth	8919257	Scene text recognition synthetic data set	Link
SynText	7266164	A synthesized by scene text dataset, and the text is cropped from the large image	Link

Validation Dataset

Testset	Instance Number	Note
IIIT5K	3000	regular
SVT	647	regular
IC03_860	860	regular
IC13_857	857	regular
IC15_1811	1811	irregular
SVTP	645	irregular
CUTE80	288	irregular

Test Dataset

Testset	Instance Number	Note
IIIT5K	3000	regular
SVT	647	regular
IC03_860	860	regular
IC13_857	857	regular
IC15_1811	1811	irregular
SVTP	645	irregular
CUTE80	288	irregular

3. Getting Started

Preparation

A quick start is to use above lmdb-formatted datasets that contain the full benchmarks for scene text recognition tasks as belows.

Data Type: LMDB

File storage format:
   |-- train           
   |   |-- MJ
   |   |-- ST
   |-- validation
   |   |-- mixture
   |-- evaluation
   |   |-- mixture

Training

Run the following bash command in the command line,

cd .
bash ./train_script/train_att.sh 

cd .
bash ./train_script/train_crnn.sh 

We provide the implementation of online validation. If you want to close it to save training time, you may modify the startup script to add --no-validate command.

Evaluation

cd .
bash ./train.sh

4. Results

Evaluation

Methods	Regular Text				Irregular Text			Download
Name	IIIT5K	SVT	IC03	IC13	IC15	SVTP	CUTE80	Config	Model
CRNN(Report)	86.2	86.0	94.4	92.6	73.6	76.0	72.2	-	-
CRNN	93.3	87.5	92.6	92.4	78.1	78.9	80.6	Config	pth BaiduYunPan (Code:yc98), Google Drive
Attention(Report)	86.6	86.2	94.1	92.8	75.6	76.4	72.6	-	-
Attention	94.5	89.0	94.5	94.1	81.7	82.5	81.9	Config	pth BaiduYunPan (Code:mdtf), Google Drive

Visualization

Here is the picture for result visualization.

Citation

@article{CRNN,
  author={Baoguang Shi and Xiang Bai and Cong Yao},
  title={An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene Text Recognition},
  journal={TPAMI},
  volume={39},
  number={11},
  pages={2298--2304},
  year={2017},
}

@inproceedings{Wrong,
  author={Jeonghun Baek and Geewook Kim and Junyeop Lee and Sungrae Park and Dongyoon Han and Sangdoo Yun and Seong Joon Oh and Hwalsuk Lee},
  title={What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis},
  booktitle={ICCV 2019},
  pages={4714--4722},
  publisher={{IEEE}},
  year={2019},
}

License

This project is released under the Apache 2.0 license

Copyright

If there is any suggestion and problem, please feel free to contact the author with jianghui11@hikvision.com or chengzhanzhan@hikvision.com.