Hand Sentinel: Computer Vision Engine ✋🤖

Hand Sentinel is an advanced Computer Vision and Neural Network engine developed in Python. It utilizes robust Deep Learning models to dynamically map 21 articular nodes on both the left and right hands in real-time. By accurately classifying complete physical signs and complex gestures, the neural network acts as an automated trigger to execute and control media (video playback) without physical interfaces.

✨ Core Features & Architecture

• Bilateral Node Tracking: Precise, real-time spatial mapping of 42 total articular nodes (21 per hand) utilizing advanced neural network architectures.
• Gesture-Triggered Automation: Translates specific, complete physical signs into executable binary commands to instantly trigger and manage video playback.
• Low Latency Processing: Highly optimized for real-time execution and zero-lag rendering via OpenCV frame processing.
• Modular Engineering: Clean, scalable architecture strictly separated into core (AI engine), ui (interface), and assets (media and data) for seamless future integrations.

🗂️ Project Structure

The engine is built with a highly modular approach to ensure clean code and scalability:

hand-sentinel/
├── assets/       # Media files and output data
├── config/       # Global configurations and parameters
├── core/         # AI engine, node tracking, and neural network logic
├── ui/           # User interface components and visual OpenCV overlays
├── utils/        # Helper functions and isolated auxiliary scripts
├── main.py       # Main execution script
└── requirements.txt

🛠 Technologies Used

• Core Language: Python 3.x
• Computer Vision: OpenCV, MediaPipe (Hand Tracking Solutions)
• Machine Learning / AI: Integrated Neural Network logic for gesture classification
• Architecture: Modular component isolation and real-time data streaming.

🚀 Installation & Setup

To deploy the Hand Sentinel engine locally on a Windows environment:

1. Clone the repository:

git clone https://github.com/jp-software-dev/hand-sentinel.git

2. Navigate into the project directory:

cd hand-sentinel

3. Install the required dependencies:

pip install -r requirements.txt

4. Run the main engine:

python main.py

🎮 Usage: The "Scuba" Trigger

Once the engine is running and your webcam is active, Hand Sentinel will map your hand nodes in real-time.

To trigger the automated media response (Scuba Cat meme):

• Bring both hands into the camera frame.
• Place your hands over your mouth and raise one in the air, simulating a scuba mask.
• The neural network will instantly classify this physical sign and execute the video playback command without needing to touch the keyboard or mouse.