$ 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