$ pip install -r requirements.txt
$ py predict.py

Everything is okay. Let's predict the demo images.

the result will be saved in output.txt file

demo_data\public_test_img_0.jpg BO
demo_data\public_test_img_1.jpg Nhoàm
demo_data\public_test_img_2.jpg NGỰC
demo_data\public_test_img_3.jpg chương

This is a Pytorch implementation of a Deep Neural Network for scene text recognition. It is based on the paper "An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition (2016), Baoguang Shi et al.".

Blog article with more info: https://ycc.idv.tw/crnn-ctc.html

This model is trained on the dataset provided by HaNoi University of science and technology.

To train your own model, you must prepare your data like this structure

├───data_set
│   │   train_gt.txt
│   │
│   └───New_train
│           train_img_0.jpg
│           train_img_1.jpg
│           train_img_2.jpg

You could adjust hyper-parameters in ./src/config.py.

And train crnn models,

$ python vietnamese_writting\main.ipynb

PThis project is built upon the work of crnn-pytorch