Digit Recognition

Description

Table of Contents

• General Information
• Features
• Dataset
• Setup
• Project requirements/dependencies
• Extentions for Vscode
• Installations
• Acknowledgements
• Contact

General Information:

• This project is a Python-based application for identifying handwritten digits using machine learning techniques.
• It utilizes a trained model to accurately predict the digit from an input image.
• CNN based approach

Features:

1. Accurately recognizes handwritten digits (0-9).
2. Easy-to-use interface for both single and batch digit recognition.
3. Provides confidence scores for each prediction.

Dataset:

• MNIST dataset

Setup:-

Project requirements/dependencies:

• Python version 3.9.6

• Visual Studio Code version 1.60.2

Extentions for Vscode:

• Python

Installations:

-clone the repository in your local machine

• pip install the keras library
• run the application using 'python gui_digit_recognizer.py'

We are good to go

How to access the application:

Directly run the gui_digit_recognizer file in VSCode(Python 3.9 64 bit)

Give the input data to predict the value to the model

Acknowledgements

Mnist dataset

DataFlair

Contact

Created by R JOEL SHARON