"train.ipynb" is for training the model. It uses "csv_loader.py" to load the dataset and "Model.py" to load the model. "draw_and_detect.py" takes mouse input and predicts the character using the trained model.
The model has obtained 97.82% validation accuracy and 97.3% testing accuracy on the CMATERdb dataset (231 character class) and 96.18% validation accuracy and 96.13% testing accuracy on the Ekush dataset (122 character class).