Handwritten Digit Recognition

Overview

This project features two main components:

1. Model Training: A Convolutional Neural Network (CNN) trained on the MNIST dataset to recognize handwritten digits.
2. Interactive Drawing Application: A pygame application that allows users to draw digits and predicts them using the trained model.

Components

• Model Training Script: Trains a CNN on the MNIST dataset and saves the best model.
• Drawing Application: Uses pygame to capture user drawings, preprocesses them, and predicts the digit using the trained model.

Requirements

• Python 3.x
• Libraries: numpy, matplotlib, keras, tensorflow, pygame, opencv-python

Installation

Install the required libraries with: pip install numpy matplotlib keras tensorflow pygame opencv-python

Running the Project

1. Train the Model: Save and run the model training script: python train_model.py

2. Run the Drawing Application: Save and run the interactive drawing script: python digit_recognition.py