face_recognition_webcam.py

import argparse
import sys
import time

import cv2
import os
import face
import datetime



def add_overlays(frame, faces, frame_rate):
    if faces is not None:
        for face in faces:
            face_bb = face.bounding_box.astype(int)
            cv2.rectangle(frame,
                          (face_bb[0], face_bb[1]), (face_bb[2], face_bb[3]),
                          (0, 255, 0), 2)
            if face.name is not None:
                cv2.putText(frame, face.name, (face_bb[0], face_bb[3]),
                            cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0),
                            thickness=2, lineType=2)

    cv2.putText(frame, str(frame_rate) + " fps", (10, 30),
                cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0),
                thickness=2, lineType=2)
    return frame


def main(args):
    frame_interval = 30  
    fps_display_interval = 5 
    frame_rate = 0
    frame_count = 0

    if args.debug:
        face.debug = True

    video_capture = cv2.VideoCapture(0)
    video_capture.set(cv2.CAP_PROP_FRAME_WIDTH, 320)
    video_capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 240)
    video_capture.set(cv2.CAP_PROP_FPS, 30)

    facenet_model_checkpoint = os.path.dirname(__file__) + args.model
    classifier_model = os.path.dirname(__file__) + args.classifier
    face_recognition = face.Recognition(facenet_model_checkpoint, classifier_model, min_face_size=20)
    start_time = time.time()

    while True:
        # Capture frame-by-frame
        ret, frame = video_capture.read()
        if ret == 0:
            print("Error")
            return

        faces = face_recognition.identify(frame)

        if (frame_count % frame_interval) == 0:
            end_time = time.time()
            if (end_time - start_time) > fps_display_interval:
                frame_rate = int(frame_count / (end_time - start_time))
                start_time = time.time()
                frame_count = 0

        new_frame = add_overlays(frame.copy(), faces, frame_rate)

        frame_count += 1
        cv2.imshow("Face Recognition", new_frame)

        keyPressed = cv2.waitKey(1) & 0xFF
        if keyPressed == 27: 
            break

    video_capture.release()
    cv2.destroyAllWindows()


def parse_arguments(argv):
    parser = argparse.ArgumentParser()

    parser.add_argument('--debug', action='store_true',
                        help='Enable some debug outputs.')
    parser.add_argument('--model', help='Model to use.', required=True)
    parser.add_argument('--classifier', help='Classifier to use.', required=True)
    return parser.parse_args(argv)


if __name__ == '__main__':
    main(parse_arguments(sys.argv[1:]))