Handigits

📝 Description

The goal of this project was to make a deep learning model that could recognize hand signs digits, no matter the environment.

Tip

NEW: The project now uses Neuralnetlib, my own deep learning framework instead of TensorFlow and Keras!

Every information you need is in the source code, but here are some important points:

• The dataset used is: Sign-Language-Digits-Dataset
• The library I use to detect the hand is: mediapipe

I don't think this project deserves a bigger README, like my other projects.

It was primarily made for fun and to learn more about real-time processing and deep learning.

🎥 Demo

💡 How to use

Prerequisites

• Python 3.7.0+

Get a copy of the Project. Assuming you have git installed, open your Terminal and enter:

git clone 'https://github.com/marcpinet/handigits'

To install all needed requirements run the following command in the project directory:

pip install -r requirements.txt

Running

After that, you can proceed to start the program by running main.py.

🐛 Known issues

• Nothing yet!

🥅 TO-DO List

• Nothing yet!

✍️ Authors

• Marc Pinet - Initial work - marcpinet

📃 License

This project is licensed under the MIT License - see the LICENSE.md file for details