AI Face Mask Detection Project

Made by : Bhupendra Singh Hapawat — MCA - DIMS

A real-time computer vision application that detects whether a person is wearing a face mask using a Deep Learning model. This project is specifically configured to leverage the Apple Silicon M4 GPU for high-performance inference.

🛠️ Technologies Used (Stack)

• Hardware: Apple M4 Chip (Neural Engine & GPU Acceleration)
• Language: Python 3.12.12
• Machine Learning Framework: TensorFlow-MacOS & TensorFlow-Metal
• Computer Vision: OpenCV (cv2)
• Frontend Interface: Streamlit
• Deep Learning Model: MobileNet (via Google Teachable Machine)

🚀 Features

• Real-time Detection: Process video frames at 30+ FPS.
• M4 Optimization: Uses tensorflow-metal for hardware acceleration.
• Visual Feedback: Dynamic UI overlays (Green for Mask, Red for No Mask).
• Web Interface: Easy-to-use Streamlit browser tab.

📂 Project Structure

• app.py - The Streamlit web interface logic.
• main.py - The original core application logic.
• saved_model/ - The trained neural network weights.
• labels.txt - Classification labels.
• imgx1.png / imgx2.png - Project screenshots.

⚙️ Installation & Usage

1. Activate the environment:

   source myenv/bin/activate