Face Recognition with DeepFace and OpenCV

This project demonstrates a simple face recognition system using DeepFace and OpenCV. The system captures video from a webcam, processes each frame to check for a match against a reference image, and displays the result on the video feed.

Requirements

• Python 3.x
• OpenCV
• DeepFace

You can install the required packages using pip:

pip install opencv-python deepface

Project Structure

Facial-Recognition-Software/
│
├── reference.jpg
├── reference2.jpg
├── main.py
├── facial_recognition.jpg
└── README.md

• reference.jpg: Image used for face comparison.
• main.py: The main script for the face recognition system.

Usage

1. Place Your Reference Image:

   • Ensure that reference.jpg is present in the same directory as main.py. This image will be used for face matching.

2. Run the Script:

   Execute the script using Python:

   python main.py

3. Interaction:

   • The script opens a webcam feed.
   • It checks every 30 frames to see if the face in the frame matches the reference image.
   • If a match is found, the text "MATCH!" is displayed in green; otherwise, "NO MATCH!" is displayed in red.
   • Press q to quit the application.

Code

import threading
import cv2
from deepface import DeepFace

cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)

cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)

counter = 0
face_match = False
reference_img = cv2.imread('reference.jpg')
lock = threading.Lock()

def check_face(frame):
    global face_match
    try:
        result = DeepFace.verify(frame, reference_img.copy())['verified']
        with lock:
            face_match = result
    except ValueError:
        with lock:
            face_match = False

while True:
    ret, frame = cap.read()

    if ret:
        if counter % 30 == 0:
            try:
                threading.Thread(target=check_face, args=(frame.copy(),)).start()
            except ValueError:
                pass
        counter += 1
        
        with lock:
            if face_match:
                cv2.putText(frame, 'MATCH!', (20, 450), cv2.FONT_HERSHEY_SIMPLEX, 2, (0, 255, 0), 3)
            else:
                cv2.putText(frame, 'NO MATCH!', (20, 450), cv2.FONT_HERSHEY_SIMPLEX, 2, (0, 0, 255), 3)

        cv2.imshow('video', frame)

    key = cv2.waitKey(1)
    if key == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

Notes

• Make sure you have a working webcam and the reference.jpg image for the face comparison.
• Adjust the webcam resolution and frame rate settings as needed.
• This script is for educational purposes and may require adjustments for production use.

License

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

This README provides clear instructions on setting up and running your face recognition system, including a description of the project, how to use it, and the full code.