This web application allows users to draw a single digit on a canvas, and the model will predict the digit.
The project demonstrates how to integrate a Flask backend with a simple frontend for digit recognition. It covers:
- Sending user input (a drawn digit) from the webpage to the backend.
- Using a trained model to make predictions.
- Displaying the prediction result on the webpage.
The digit recognition model is built using Keras and trained on the MNIST dataset. You can easily replace it with your own model (saved with the .keras extension).
- Draw or Upload: Users can either draw a digit on the canvas or upload an image.
- Prediction: The model predicts the digit based on user input and displays the result on the webpage.
- Customizable: You can replace the pre-trained model with your own for different datasets.
The input image undergoes several preprocessing steps to match the format expected by the model (28x28 grayscale). Future optimizations are planned to improve accuracy and speed.
- Clone or download the repository.
- Install the required dependencies (see requirements.txt).
- Run the Flask app:
python app.py - Open the webpage in your browser and start drawing a digit or upload an image for prediction.
