In [ ]:

    

import sys
import os
import dlib
import glob
import numpy as np
from skimage import io

cap = cv2.VideoCapture(0)


predictor_path = sys.argv[1]
face_rec_model_path = sys.argv[2]
faces_folder_path = sys.argv[3]

detector = dlib.get_frontal_face_detector()
sp = dlib.shape_predictor(predictor_path)
facerec = dlib.face_recognition_model_v1(face_rec_model_path)

win = dlib.image_window()

while (true):
    
    # Now process all the images
    for f in glob.glob(os.path.join(faces_folder_path, "*.jpg")):
    print("Processing file: {}".format(f))
    img = io.imread(f)

    win.clear_overlay()
    win.set_image(img)

    dets = detector(img, 1)
    print("Number of faces detected: {}".format(len(dets)))

    # Now process each face we found.
    for k, d in enumerate(dets):
        print("Detection {}: Left: {} Top: {} Right: {} Bottom: {}".format(
        k, d.left(), d.top(), d.right(), d.bottom()))
           # Get the landmarks/parts for the face in box d.
        shape = sp(img, d)
            # Draw the face landmarks on the screen so we can see what face is currently being processed.
        win.clear_overlay()
        win.add_overlay(d)
        win.add_overlay(shape)

        face_descriptor = facerec.compute_face_descriptor(img, shape)
        print(face_descriptor)