Handwritten Digit Recognition System

This project provides a Flask-based RESTful API for real-time handwritten digit recognition using a CNN model trained on the MNIST dataset.

Features

• Upload an image of a handwritten digit for real-time recognition.
• Deployed on AWS EC2 for global accessibility.
• Future enhancements: alphanumeric recognition, mobile integration, and real-time handwriting conversion.

Setup and Installation

1. Clone the repository:

   git clone https://github.com/Bit-Nest/deci-engine.git
   
   

2. Repository Structure

   flask-app/
   │
   ├── app.py                 # Main Flask application
   ├── model.h5               # Your machine learning model weights
   ├── model.json             # Your model architecture
   ├── templates/             # HTML templates
   │   └── index.html
   │   └── result.html
   ├── requirements.txt       # Python dependencies
   └── venv/                  # Virtual environment
   

3. Install dependencies:

    pip install -r requirements.txt
   
   

4. Run the Flask app:

    python app.py
   

5. Access the API at

      http://127.0.0.1:5000/predict.
   

6.Future Work

• Alphanumeric character recognition.
• Mobile application integration.
• Real-time handwriting conversion.