Question

21.5. 摄像头识别人脸

import face_recognition
import cv2
import numpy as np

# Get a reference to webcam #0 (the default one)
video_capture = cv2.VideoCapture(1)

# Load a sample picture and learn how to recognize it.
image = face_recognition.load_image_file("me.jpg")
known_face_encodings = face_recognition.face_encodings(image)[0]

while True:
    # Grab a single frame of video
    ret, frame = video_capture.read()

    # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
    rgb_frame = frame[:, :, ::-1]

    # Find all the faces and face enqcodings in the frame of video
    face_locations = face_recognition.face_locations(rgb_frame)
    face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)

    # Loop through each face in this frame of video
    for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):
        # See if the face is a match for the known face(s)
        matches = face_recognition.compare_faces(
            [known_face_encodings], face_encoding)

        name = "Unknown"

        if matches[0] == True:
            print("It's a picture of me!")
        else:
            print("It's not a picture of me!")

        # Or instead, 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 = 'netkiller'

        # Draw a box around the face
        cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)

        # Draw a label with a name below the face
        cv2.rectangle(frame, (left, bottom - 35),
                      (right, bottom), (0, 0, 255), cv2.FILLED)
        font = cv2.FONT_HERSHEY_DUPLEX
        cv2.putText(frame, name, (left + 6, bottom - 6),
                    font, 1.0, (255, 255, 255), 1)

    # Display the resulting image
    cv2.imshow('Video', frame)

    # Hit 'q' on the keyboard to quit!
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release handle to the webcam
video_capture.release()
cv2.destroyAllWindows()