VietnameseOCR

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VietnameseOCR - Vietnamese Optical Character Recognition

Apply Deep Learning ( CNN networks ) to train a model uses for recognizing Vietnamese characters, it works well with Latin characters.

Dataset in big image ( 10.000 samples, 2800 x 2800 pixel)

Requirements

python 3.6.5
tensorflow
PIL

Model Summary

Results

Training...

......
Epoch: 38 cost = 0.312853018
Epoch: 39 cost = 0.298816641
Epoch: 40 cost = 0.293328794

Evaluation
------------------------------
Test Accuracy: 0.974867469544

Training

Prepare dataset for training

git clone https://github.com/miendinh/VietnameseOCR.git
cd VietnameseOCR/data/train/characters
unzip dataset.zip

Let's train.

python train.py

Create you own dataset

Prepare fonts for generating text-image

• You could add more fonts

cd VietnameseOCR/data/train/characters
unzip google.zip
unzip win.zip

Create font list, then save it in fonts.list

source ./list.sh

Generate Text Image Dataset

python generate_data.py

Play with pretrained model

• All pretrained weights of model is save to file vocr.brain
• Let's test with random character in dataset

python predict.py

Further working

• [x] Character classification.
• [ ] Dataset augmentation.
• [ ] Improve accuracy.
• [ ] Text location.
• [ ] Text recognition.
• [ ] Apply NLP for spell checking.

References

1. STN-OCR: A single Neural Network for Text Detection and Text Recognition
2. Automatic Dataset Augmentation
3. VGG16 implementation in TensorFlow
4. Vietnamese Dict (VietOCR3)

Author mien.hust [at] gmail [dot] com