https://github.com/soumik12345/kinect-vision

A computer vision based gesture detection system that automatically detects the number of fingers as a hand gesture and enables you to control simple button pressing games using you hand gestures.
https://github.com/soumik12345/kinect-vision

computer-vision gaming gesture-recognition opencv opencv3-python python-3 sign-language-recognition-system

Last synced: 2 months ago
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A computer vision based gesture detection system that automatically detects the number of fingers as a hand gesture and enables you to control simple button pressing games using you hand gestures.

• Host: GitHub
• URL: https://github.com/soumik12345/kinect-vision
• Owner: soumik12345
• Created: 2018-12-18T19:36:45.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2020-05-03T13:22:41.000Z (over 4 years ago)
• Last Synced: 2024-10-24T14:27:58.257Z (2 months ago)
• Topics: computer-vision, gaming, gesture-recognition, opencv, opencv3-python, python-3, sign-language-recognition-system
• Language: Jupyter Notebook
• Homepage:
• Size: 26.1 MB
• Stars: 53
• Watchers: 3
• Forks: 13
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
# Kinect-Vision

[![HitCount](http://hits.dwyl.com/soumik12345/Kinect-Vision.svg)](http://hits.dwyl.com/soumik12345/Kinect-Vision)

A computer vision based gesture detection system that automatically detects the number of fingers as a hand gesture and enables you to control simple button pressing games using you hand gestures. Currently the system has been tested on the [**T-Rex Runner** game](http://www.trex-game.skipser.com/).



## Installation

1. Clone the repo using `git clone https://github.com/soumik12345/Kinect-Vision`

2. Use `cd Kinect-Vision` to get inside the folder

3. Create a new conda environment using `conda create --name kinect_vision`

4. Activate the environment using `activate kinect_vision`

5. Install the requirements using `pip install -r requirements.txt`

## Run The Program

1. Run the program using `python3 main.py` or `python main.py` or `ipython main.py`

2. Select the Camera port (choose `0` if you are using a laptop)

3. Tune the upper and lower thresholds using the trackbars unless the gestures are being detected accurately enough. Ideally the lower threshold is around `130` and the upper threshold is `255`.

4. Once the detection is working satisfactorily, switch on `Game On` and open the game window

5. If you want to change the control scheme, you can do so by editing the `config.json` file.

## Demo