This is a Flask-based web application that allows users to upload an image of a handwritten digit (0–9), and it predicts the digit using a Convolutional Neural Network (CNN) trained on the MNIST dataset.

✨ Key Features

• Upload handwritten digit images (JPG, PNG, etc.)

• Processes the image using PIL and NumPy

• Predicts the digit using a .keras model trained on MNIST

• Displays top-10 class probabilities

• Lightweight Flask backend with HTML frontend

• Saves uploaded images in a dedicated /uploads folder (outside /static)

⚠️ Limitations

• Works best with clear handwritten digits

• Currently supports single-digit recognition only (0–9)

• Accuracy may decrease for noisy or distorted images

• No multi-user or persistent storage support

• Large image uploads may increase processing time

• Model trained only on the MNIST dataset

🔮 Future Improvements

• Multi-digit recognition support

• Real-time canvas drawing interface

• Higher-accuracy CNN architectures

• Mobile-friendly UI enhancements

• User history and prediction logs

• Cloud deployment with scalable inference

• Support for custom dataset training

• Explainable AI visualizations for predictions 

⚙️ How It Works

Image Processing Pipeline

• User uploads handwritten digit image

• Image resized to 28×28 grayscale

• Pixel normalization using NumPy

• CNN model processes image

• Model predicts digit probabilities

• Highest-confidence digit returned