Real_time_face_detection

Real-Time Face Recognition System

Overview

This project implements a real-time face recognition system using OpenCV and the face_recognition library. The system detects faces from a video stream, recognizes previously seen faces, and displays metadata about each recognized face. It supports both Raspberry Pi cameras and USB webcams.

Features

Real-time face detection and recognition
Save and load known faces and their metadata
Display metadata such as first seen time, last seen time, and visit count
Handles both Raspberry Pi camera modules and USB webcams

Requirements

Python 3.x
OpenCV
face_recognition library
NumPy

Installation

Clone the repository:

git clone https://github.com/yourusername/face-recognition-system.git
cd face-recognition-system

Install the required Python packages:
```
pip install -r requirements.txt
```
If you're using a Raspberry Pi camera, ensure you have the necessary libraries for gstreamer installed:
```
sudo apt-get install libgstreamer1.0-dev
```

Usage

Ensure you have a camera connected to your system.
Run the script:
```
python face_recognition_system.py
```
The system will start capturing video and recognizing faces. Press q to quit.

Configuration

To switch between using a Raspberry Pi camera and a USB webcam, change the USING_RPI_CAMERA_MODULE variable at the beginning of the script:
```
USING_RPI_CAMERA_MODULE = False  # Set to True if using a Raspberry Pi camera module
```

Functions

`save_known_faces()`

Saves known face encodings and metadata to a file (known_faces.dat).

`load_known_faces()`

Loads known face encodings and metadata from a file (known_faces.dat).

`get_jetson_gstreamer_source(capture_width, capture_height, display_width, display_height, framerate, flip_method)`

Returns a gstreamer pipeline string for capturing video from a Raspberry Pi camera on a Jetson Nano.

`register_new_face(face_encoding, face_image)`

Registers a new face encoding and its associated metadata.

`lookup_known_face(face_encoding)`

Looks up a face encoding in the list of known faces and returns its metadata if found.

`main_loop()`

Main loop for capturing video, detecting faces, recognizing faces, and displaying the results.

Acknowledgements

This project was developed by Zaryab Rahman. It is based on the face_recognition library and OpenCV.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Finding-mll / Real_time_face_detection