Face_recognition.py

from keras_facenet import FaceNet
import cv2
import numpy as np
from mtcnn import MTCNN
import os
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"


# Load FaceNet model and MTCNN for face detection
embedder = FaceNet()
detector = MTCNN()

# Open webcam
cap = cv2.VideoCapture(0)

while cap.isOpened():
    ret, frame = cap.read()
    if not ret:
        break

    # Detect faces
    faces = detector.detect_faces(frame)
    for face in faces:
        x, y, width, height = face['box']
        x2, y2 = x + width, y + height

        # Extract face
        face_crop = frame[y:y2, x:x2]

        # Convert to FaceNet embedding
        face_crop = cv2.resize(face_crop, (160, 160))
        face_crop = np.expand_dims(face_crop, axis=0)
        embedding = embedder.embeddings(face_crop)

        # Draw box
        cv2.rectangle(frame, (x, y), (x2, y2), (255, 0, 0), 2)
        cv2.putText(frame, "Face Detected", (x, y - 10),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 2)

    cv2.imshow("Face Recognition", frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()