https://github.com/karan-malik/digitrecognition

Using Deep Learning to recognize Handwritten Digits (MNIST) and hosted using Flask
https://github.com/karan-malik/digitrecognition

cnn cnn-keras convnet convolutional-neural-networks css deep-learning deep-neural-networks deeplearning flask flask-application html html5 keras machine-learning mnist-classification mnist-handwriting-recognition python python3

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Using Deep Learning to recognize Handwritten Digits (MNIST) and hosted using Flask

• Host: GitHub
• URL: https://github.com/karan-malik/digitrecognition
• Owner: Karan-Malik
• Created: 2020-07-08T15:35:06.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2023-02-16T02:21:52.000Z (almost 2 years ago)
• Last Synced: 2023-03-05T15:09:53.725Z (almost 2 years ago)
• Topics: cnn, cnn-keras, convnet, convolutional-neural-networks, css, deep-learning, deep-neural-networks, deeplearning, flask, flask-application, html, html5, keras, machine-learning, mnist-classification, mnist-handwriting-recognition, python, python3
• Language: Python
• Homepage:
• Size: 755 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 9
• Metadata Files:
  • Readme: README.md

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README

        
# DigitRecognition

Using Deep Learning to recognize Handwritten Digits (MNIST)

## User Interface

Main Screen

![image](UI/main.JPG)

Prediction Screen

![image](UI/predict.JPG)

## About This Project

This repository contains a self-made Convolutional Neural Network, implemented using Keras, an open source neural network library in Python. It uses this Deep Learning model

to identify the handwritten digit in the image uploaded to it. It is hosted using Flask, a Python Web Development Framework.

It has a **training accuracy of 99.24%** and a **test accuracy of 99.21%**

The complete model is available in 'digit recognition.py'.

## Dataset

The dataset used is the popular MNIST Handwritten Digit Dataset, available on this [link](http://yann.lecun.com/exdb/mnist/). It is also available as a pre-installed dataset

in Keras and can be used as shown in 'digit recognition.py'.

## How to Use

1. Clone this repository onto your system. On Command Prompt, run the following command:

```

git clone https://github.com/Karan-Malik/DigitRecognition.git

```

2. Change your directory to MovieHype:

```

cd DigitRecognition

```

3. Then run the follwing commands to run the application:

```

set FLASK_APP=digit.py

flask run

```

4. Enter the url provided after running the previous commands into your web browser

### The website is now ready to use!