FaceRecognitionSample.py

FaceRecognitionSample.py

import face_recognition
import cv2
import numpy as np

def LoadFaces():
    bruno_image = face_recognition.load_image_file("d:\Faces\Bruno1.jpg")
    bruno_face_encoding = face_recognition.face_encodings(bruno_image)[0]
    valentino_image = face_recognition.load_image_file("d:\Faces\Valen1.jpg")
    valentino_face_encoding = face_recognition.face_encodings(valentino_image)[0]

    known_face_encodings = [
        bruno_face_encoding,
        valentino_face_encoding
        ]
    known_face_names = [
        "Bruno",
        "Valentino"
    ]

    return known_face_encodings, known_face_names;

video_capture = cv2.VideoCapture(0)

known_face_encodings, known_face_names = LoadFaces()

while True:
    ret, frame = video_capture.read()
    rgb_frame = frame[:, :, ::-1]

    face_locations = face_recognition.face_locations(rgb_frame)
    face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)

    for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):
        matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
        name = "Unknown"
        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]
        cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
        cv2.rectangle(frame, (left, bottom - 25), (right, bottom), (0, 0, 255), cv2.FILLED)
        font = cv2.FONT_HERSHEY_COMPLEX_SMALL
        cv2.putText(frame, name, (left + 6, bottom - 6), font, 0.7, (255, 255, 255), 1)
    cv2.imshow('Video', frame)

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

video_capture.release()
cv2.destroyAllWindows()