Optical Character Recognition UI Software

This software implements the optical character recognition of carved text on the plaster sticks based on CTPN and CRNN implemented in Tensorflow, where the network architectures are inspired by MobileNet V1 and MobileNet V2.

Requirements

python3.5
tensorflow_gpu==1.8.0
PyQt==5.9.1
opencv_python==3.4.1
easydict==1.7
numpy==1.14.0
Cython==0.27.3
Pillow==5.0.0
PyYAML==3.12

Run software

A main program can be found in main.py. Before running the program, download a pretrained model from here. Put the downloaded model directory stickmobilev1 into directory detect/checkpoints/, and put the mobilev2 into recognize/checkpoints/.Then launch the program by:

python main.py

Example images

One shot recognition:

Training detection task:

Training recognition task:

References

Tian Z, Huang W, He T, et al. Detecting Text in Natural Image with Connectionist Text Proposal Network[J]. 2016:56-72.

Shi B, Bai X, Yao C. An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene Text Recognition[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2015, 39(11):2298-2304.

Howard A G, Zhu M, Chen B, et al. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications[J]. 2017.

Sandler M, Howard A, Zhu M, et al. MobileNetV2: Inverted Residuals and Linear Bottlenecks[J]. 2018.