main2.py

import cv2
import face_recognition
import numpy as np
import os

# Load known faces
known_face_encodings = []
known_face_names = []

# Load images from the 'images' directory
for filename in os.listdir('images'):
    if filename.endswith('.jpg') or filename.endswith('.png'):
        image_path = os.path.join('images', filename)
        image = face_recognition.load_image_file(image_path)
        encoding = face_recognition.face_encodings(image)[0]
        known_face_encodings.append(encoding)
        known_face_names.append(os.path.splitext(filename)[0])  # Get the name without the extension

# Initialize video capture
video_capture = cv2.VideoCapture(0)  # Use 0 for the default camera

while True:
    # Capture frame-by-frame
    ret, frame = video_capture.read()

    # Convert the image from BGR to RGB
    rgb_frame = frame[:, :, ::-1]

    # Find all the faces and face encodings in the current frame
    face_locations = face_recognition.face_locations(rgb_frame)
    face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)

    # Loop through each face found in the frame
    for face_encoding, face_location in zip(face_encodings, face_locations):
        # Compare the found face with known faces
        matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
        name = "Unknown"

        # Use the known face with the smallest distance to the new face
        face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
        best_match_index = np.argmin(face_distances)
        if matches[best_match_index]:
            name = known_face_names[best_match_index]

        # Draw a rectangle around the face
        top, right, bottom, left = face_location
        cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
        cv2.putText(frame, name, (left, top - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2)

    # Display the resulting frame
    cv2.imshow('Face Recognition', frame)

    # Break the loop when 'q' key is pressed
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release the video capture
video_capture.release()
cv2.destroyAllWindows()