Skip to content

kyle-lyk/handwrittendigit-recognition

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

11 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Hand Written Digit Recognition

Description

This is a Flask web application project for hand-written digit recognition, utilizing a TensorFlow-based Convolutional Neural Network (CNN) model. The app enables users to draw a digit on a canvas using their mouse or touch input and then predicts the drawn digit using the trained CNN model. The app also displays a probability graph, indicating the model's confidence in its prediction within the range of 0 to 9.

Table of Contents

Installation

To run this project, follow these steps:

  1. Clone the repository:

    git clone [repository_url]
    cd flask-project
    
  2. Create a virtual environment (optional, but recommended):

    python -m venv venv
    source venv/bin/activate   # For Windows, use: venv\Scripts\activate
    
  3. Install the dependencies:

    pip install -r requirements.txt
    
  4. Run the Flask application:

    python app.py
    

Usage

After running the Flask application, open your web browser and go to http://localhost:5000 to access the web application.

Demo

Demo GIF

About

Tensorflow CNN, Flask

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published