Brightness Control With Hand Detection OpenCV Python – The screen-brightness-control library is used to control the screen’s brightness.
There is only one class and a few functions in the screen-brightness-control library.
Brightness Control With Hand Detection In Python: Project Details and Technology
| Project Name: | Brightness Control With Hand Detection Project In Python With Source Code |
| Abstract | Brightness Control With Hand Detection Python OpenCV – The screen-brightness-control library is used to control the screen’s brightness |
| Language/s Used: | Python Deep Learning |
| Python version (Recommended): | 3.8/3.9 |
| Database: | None |
| Type: | Desktop Application |
| Developer: | Source Code Hero |
| Updates: | 0 |
Brightness Control With Hand Detection OpenCV Python: About the project
This Brightness Control With Hand Detection OpenCV Python With Source Code was created with Python OpenCV. In this Python OpenCV Project With Source Code, we will build a Brightness Controller with OpenCV to control the computer’s brightness.
Building a Brightness Controller with OpenCV can be accomplished in just 3 simple steps:
- Step 1. Detect Hand landmarks
- Step 2. Calculate the distance between the thumb tip and index fingertip.
- Step 3. Map the distance of the thumb tip and index fingertip with volume range. In my case, the distance between thumb tip and index fingertip was within the range of 15 – 220 and the volume range was from 0 – 100.
This Brightness Control With Hand Detection In Python also includes a downloadable Python Project With Source Code for free, just find the downloadable source code below and click to start downloading.
To start executing this project, make sure that you have installed Python on your computer.
Brightness Control With Hand Detection OpenCV Python Source Code: Steps on how to run the project
Time needed: 5 minutes
These are the steps on how to run Brightness Control With Hand Detection OpenCV Python Source Code
- Step 1: Download Source Code
First, download the provided source code below.
- Step 2: Extract File
Next, after the download is finished extract the zip file.
- Step 3: Import the project to your PyCharm IDE.
Next, import the source code you’ve downloaded to your PyCharm IDE.
- Step 4: Install all Libraries.
Next, install all libraries given below.
- Step 5: Open cmd.
Next, click the folder directory of the project and type cmd.
- Step 6: Run Project.
Lastly, run the project with the command “py main.py”
Download the Source Code below
Summary
Gesture recognition helps computers to understand human body language.
This helps to build a more potent link between humans and machines, rather than just the basic text user interfaces or graphical user interfaces (GUIs).
In this project for gesture recognition, the human body’s motions are read by a computer camera.
The computer then makes use of this data as input to handle applications.
This Python OpenCV Project also includes a downloadable source code for free.
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Inquiries
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