Khmer Alphabet Handwriting CNN

This README provides instructions on how to set up and run a Flask application for the Khmer Alphabet CNN project, as well as information on training the model.

Prerequisites

• Python 3.9
• pip
• Docker (optional, if you choose to run via Docker)

Getting Started

1. Clone the Repository

First, clone the repository to your local machine:

git clone git@github.com:vvvey/khmer-alphabet-cnn.git
cd khmer-alphabet-cnn

2. Install Dependencies

To install the required Python packages, run:

pip install -r requirements.txt

3. Run the Flask Application

You can run the Flask application in one of two ways:

Option A: Run Locally

Start the Flask application using the following command:

python app.py

The application should be running on http://localhost:5000

Option B: Run Using Docker

If you prefer to run the application using Docker, you can build and run it with the following commands:

1. Build the Docker image

docker build -t khmer-cnn .

2. Run the Docker container:

docker run -d -p 5000:80 --name khmer-cnn khmer-cnn

In this case, the application will also be available at http://localhost:5000

4. Train the Model

To train the model, use the model.pynb Jupyter notebook. This notebook will save the trained model to my_model.h5 and the label encoder to label_encoder.pkl.

You can run the notebook using Jupyter Notebook:

model.ipynb

5. Model Performance

The pretrained model has achieved a test accuracy of 95% .

Notes

• Ensure the necessary system dependencies for running Flask and Docker are installed.
• If you make any changes to the model or requirements, remember to rebuild the Docker image.

License

This project is licensed under the MIT License - see the LICENSE file for details.