hand-gesture-recognition_mediapipe

The aim of this Project is to detect and recognise the most common Hand Gestures expressed in Online Learning using Python and MediaPipe.

https://github.com/aminefarez/hand-gesture-recognition_mediapipe

Science Score: 44.0%

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CITATION.cff file
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Low similarity (8.8%) to scientific vocabulary

Keywords

gesture-recognition hand-tracking online-learning

Last synced: 6 months ago · JSON representation ·

Repository

The aim of this Project is to detect and recognise the most common Hand Gestures expressed in Online Learning using Python and MediaPipe.

Basic Info

Host: GitHub
Owner: aminefarez
License: apache-2.0
Language: Python
Default Branch: main
Homepage:
Size: 420 KB

Statistics

Stars: 1
Watchers: 1
Forks: 0
Open Issues: 0
Releases: 0

Topics

gesture-recognition hand-tracking online-learning

Created about 4 years ago · Last pushed almost 4 years ago

Metadata Files

Readme License Citation

Hand Gesture Recognition for Online Learning using MediaPipe

The aim of this Project is to detect and recognise the most common Hand Gestures expressed in Online Learning using Python and MediaPipe. The model is trained to Recognize 4 Gestures expressing: 'Tiredness', 'Sickness', 'Critical Thinking' and 'Asking Questions' as demonstrated below:

alt text

The repository includes:

Source code of Hand Gesture Recognition based on MediaPipe with pre-trained encodings for the 4 Gestures of Interest.
Training code to be used to train on your own dataset.

The code is documented and designed to be easy to extend. If you use it in your research, please consider citing this repository (bibtex below).

Prerequisites

The libraries needed can be found in the requirements.txt file, they can be installed using:

```

pip install -r requirements.txt

``` Or if you're using Google Colab:

```

!pip install -r requirements.txt

```

Getting Started

hand_recognition.py Is the easiest way to start. It shows an example of using a pre-trained model to be used on a Video or Webcam Input.
hand_training.py shows how to train the model on your own dataset.

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Farez"
  given-names: "Mohammed"
title: "Hand Gesture Recognition for Online Learning using MediaPipe"
version: 1.0
date-released: 2021-12-18
url: "https://github.com/aminefarez/Hand-Gesture-Recognition_MediaPipe"

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