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mtl-text-recognition

multi-task learning for text recognition with joint ctc-attention.

Update features

  • support variable length of squence training and inference (fixed height).
  • Chinese character recognition.
  • Joint CTC-Attention



Getting Started

Dependency

  • This work was tested with PyTorch 1.1.0, CUDA 9.0, python 3.6 and centos7
  • requirements : pytorch, lmdb, pillow, torchvision, nltk, natsort
pip3 install torch==1.1.0
pip3 install lmdb pillow torchvision nltk natsort

Run demo with pretrained model(中文+英文字符版本，使用config中的chn.txt文件)

  1. Download pretrained model(crnn) from baidu code:un8d
    pretrained crnn model configuration:
--output_channel 512 \
--hidden_size 256 \
--Transformation None \
--FeatureExtraction ResNet \
--SequenceModeling BiLSTM \
--Prediction CTC

run demo with pretrained mdoel.

# change config.py file and run:
CUDA_VISIBLE_DEVICES=0 python3 infer.py ${image_path}
  1. CTC-Attention pretrained model will release later.

prediction results

demo images None-ResNet512-BiLSTM256-CTC None-ResNet768-BiLSTM384-CTC
同达电动车配件 同达电动车配件
微信14987227 微信14987227
快乐大本营20190629期:张艺兴李荣浩惊喜同台合唱彭昱畅破音三连引 快乐大本营20190629期:张艺兴李荣浩惊喜同台合唱彭昱畅破音三连引
每周三中午12:00 每周三中午12-00
整套征兵甄别程序的一个部分 整套征兵甄别程序的一个部分
再热烈的鼓掌 再热烈的鼓掌
厂外恒升拆车件 广州恒升拆车件
我想说你为什么 我想说你为什么
我抱吧他在你怀里一直在哭 我抱吧他在你怀里一直在哭
如果没有这个阿姨的话 如果没有这个阿姨的话
因为我觉得有你了我才有安全感 因为我觉得有你了我才有安全感
丫OUI<U YOUKU
麦油娜孕其智商下线 轰迪娜马期智商下线
因为后一仁看《《二》的巡演 团为册长加看飞广海》的巡演
铂爵 铂爵
婆婆担心张晋怒斥蔡少芬 婆婆担心张晋怒斥蔡少芬
若风作为队长带队获得/PL5总冠军 若风作为队长带队获得/PL5总冠军
向佐向郭碧婷求婚戊功 向佐向郭碧婷求婚成功
严屹宽骨亲 严屹宽母宗
哇品会 唯品会
YOUI<U独播 YOUKU独播

Training and evaluation

  1. Train CRNN model
CUDA_VISIBLE_DEVICES=0 python train.py \
	--train_data data/synch/lmdb_train \
	--valid_data data/synch/lmdb_val \
	--select_data / --batch_ratio 1 \
	--sensitive \
  	--num_iter 400000 \
  	--output_channel 512 \
  	--hidden_size 256 \
	--Transformation None \
  	--FeatureExtraction ResNet \
  	--SequenceModeling BiLSTM \
  	--Prediction CTC \
  	--experiment_name none_resnet_bilstm_ctc \
  	--continue_model saved_models/pretrained_model.pth
  1. Train CTC-Attention model
CUDA_VISIBLE_DEVICES=0 python train.py \
	--train_data data/synch/lmdb_train \
	--valid_data data/synch/lmdb_val \
	--select_data / --batch_ratio 1 \
  	--sensitive \
  	--num_iter 400000 \
  	--output_channel 512 \
	--hidden_size 256 \
	--Transformation None \
  	--FeatureExtraction ResNet \
  	--SequenceModeling BiLSTM \
  	--Prediction CTC \
  	--mtl \
  	--without_prediction \
  	--experiment_name none_resnet_bilstm_ctc \
  	--continue_model saved_models/pretrained_model.pth

Acknowledgements

  1. This implementation has mainly been based on this great repository: deep-text-recognition-benchmark
  2. SynthText Generation has mainly been based on TextRecognitionDataGenerator