The Original Dataset contains Handwritten Bangla Characters and Digits. Here, only the Handwritten Digits have been taken into consideration. The dataset used here is available here.
- Open CMD/Terminal and clone the repository using the command :
git clone git@github.com:ayan-cs/banglalekha-numerals-classification - Download the BanglaLekha Numerals dataset from the given link above and extract inside the repository folder. It is recommended not to make any change to the dataset folder.
- Preprocess the data by executing the
Data_Preparation.ipynbnotebook. This should create a folder Preprocessed_Dataset containing Train and Validation splits. - Configure
train_config.yamlfile. - Run the script on CMD/Terminal :
python main.py train - The trained model will be available inside Checkpoints folder and the plots will be saved inside Plots & Outputs folder.
- Open CMD/Terminal and clone the repository using the command :
git clone git@github.com:ayan-cs/banglalekha-numerals-classification - Make sure the data is preprocessed.
- Configure
inference_config.yamlfile. For demo, one trained ResNet-34 model has been provided. - Open CMD/Terminal, run the command :
python main.py inference - The outputs will be available inside the Plots & Outputs folder.