Handwritten-Character-Recognition

Handwritten character recognition using keras. The model provided can also be used as a baseline model for applying transfer learning to attain better accuracy.

Installing Requirements

pip install -r requirements.txt

Pretrained Models

Pretrained Model trained on EMNIST dataset is present inside the models folder

The provided model achieves a testing accuracy of 92.43%

Train

Put the .mat file downloaded from the EMINST page inside data folder.

Training Parameters can be changed inside the src/constants.py

Also the model architecture can be changes from inside src/define_mode.py

python src/train.py  --data ./data/emnist-byclass.mat --start_from ./models/model.h5 

--data : path of the training data(.mat format)
--start_from : path of the pretrained models, to resume the training from pretrained model 

Prediction

To make a prediction on a test image:

python src/predict.py --data ./data/test/test.jpg--model ./models/model.h5

--model :  path of the trained model
--data  :  path of the image to make prediction on

Test

To evaluate the model on test data

python src/test.py --model models/model.h5 --data ./data/emnist-byclass.mat

--model : path of the trained model
--data  : path of the mat file