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MNIST Digit Classifier

This is a simple web-based digit recognition app using a trained Keras model and Flask for the backend. Users can draw a digit (0–9) in the browser, and the model will predict the number in real time. This is an introductory project for me to explore neural networks and deep learning for a common problem.

Model taken from here.

Features

  • Draw digits on a web canvas
  • Classify handwritten digits (0–9) using a Convolutional Neural Network (CNN) trained on the MNIST dataset
  • Real-time predictions using a Flask API
  • Lightweight and easy to set up

Technologies Used

  • Python
  • TensorFlow / Keras
  • Flask
  • HTML + CSS + JavaScript (frontend)
  • Pillow (PIL) for image processing
  • NumPy

Installation

1. Clone the Repository

git clone https://github.com/your-username/mnist-digit-classifier.git
cd mnist-digit-classifier

2. Install Required Libraries

Open your terminal or command prompt and run:

pip install flask tensorflow pillow numpy

3. Click run on app.py

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