get_facenet_masknet.py

def get_facenet_masknet():
    
    ap = argparse.ArgumentParser()
    ap.add_argument("-f", "--face", type=str,
                    default="face_detector",
                    help="path to face detector model directory")
    ap.add_argument("-m", "--model", type=str,
                    default="mask_detector.model",
                    help="path to trained face mask detector model")
    ap.add_argument("-c", "--confidence", type=float, default=0.5,
                    help="minimum probability to filter weak detections")
    args = vars(ap.parse_args())

    # load our serialized face detector model from disk
    print("[INFO] loading face detector model...")
    # prototxtPath = os.path.sep.join([args["face"], "deploy.prototxt"])
    prototxtPath = (
        '/Users/USER/Documents/DroneProjects/facemaskdetection/face_detector/deploy.prototxt')
    # weightsPath = os.path.sep.join([args["face"],
    #                                 "res10_300x300_ssd_iter_140000.caffemodel"])
    weightsPath = (
        '/Users/USER/Documents/DroneProjects/facemaskdetection/face_detector/res10_300x300_ssd_iter_140000.caffemodel')
    faceNet = cv2.dnn.readNet(prototxtPath, weightsPath)

    # load the face mask detector model from disk
    print("[INFO] loading face mask detector model...")
    maskNet = load_model(
        '/Users/USER/Documents/DroneProjects/facemaskdetection/mask_detector.model')
    return(faceNet, maskNet, args)