README.md

attention-ocr.pytorch:Encoder+Decoder+attention model

This repository implements the the encoder and decoder model with attention model for OCR, the encoder uses CNN+Bi-LSTM, the decoder uses GRU. This repository is modified from https://github.com/meijieru/crnn.pytorch
Earlier I had an open source version, but had some problems identifying images of fixed width. Recently I modified the model to support image recognition with variable width. The function is the same as CRNN. Due to the time problem, there is no pre-training model this time, which will be updated later.

requirements

pytorch 0.4.1
opencv_python

cd Attention_ocr.pytorch
pip install -r requirements.txt

Test

pretrained model coming soon

Train

  1. Here i choose a small dataset from Synthetic_Chinese_String_Dataset, about 270000+ images for training, 20000 images for testing. download the image data from Baidu
  2. the train_list.txt and test_list.txt are created as the follow form:
# path/to/image_name.jpg label
path/AttentionData/50843500_2726670787.jpg 情笼罩在他们满是沧桑
path/AttentionData/57724421_3902051606.jpg 心态的松弛决定了比赛
path/AttentionData/52041437_3766953320.jpg 虾的鲜美自是不可待言
  1. change the trainlist and vallist parameter in train.py, and start train
cd Attention_ocr.pytorch
python train.py --trainlist ./data/ch_train.txt --vallist ./data/ch_test.txt

then you can see in the terminel as follow: attentionocr there uses the decoderV2 model for decoder.

The previous version

git checkout AttentionOcrV1

Reference

  1. crnn.pytorch
  2. Attention-OCR
  3. Seq2Seq-PyTorch
  4. caffe_ocr

TO DO

  • change LSTM to Conv1D, it can greatly accelerate the inference
  • change the cnn bone model with inception net, densenet
  • realize the decoder with transformer model

项目简介

🚀 Github 镜像仓库 🚀

源项目地址

https://github.com/chenjun2hao/attention_ocr.pytorch

发行版本

当前项目没有发行版本

贡献者 8

开发语言

  • Python 100.0 %