cunhafh

import os
import cv2
import numpy as np
import dlib

# Load the descriptors
descriptors = np.load(r"C:\Users\felipe.cunha\Documents\venv\cv2\CelebrityDoppelganger\descriptors.npy",
                      allow_pickle=True)

# Rearrange data, each 128 items corresponds to one image descriptor

cunhafh

import os
from urllib.error import HTTPError, URLError
import dlib
import cv2
import numpy as np
import urllib.request
from socket import timeout

def enroll(im, face):
    status = "pass"

cunhafh

import cv2
import dlib


def faceLandmarks(im):

    # Path for the detection model, you can download it from here: https://github.com/italojs/facial-landmarks-recognition/blob/master/shape_predictor_68_face_landmarks.dat
    PREDICTOR_PATH = r"C:\Users\felipe.cunha\Documents\venv\cv2\week1-pyton\data\models\shape_predictor_68_face_landmarks.dat"
    
    # Create object to detect the face

cunhafh

import cv2
import dlib
import faceBlendCommon as face
import numpy as np

# Load Image
im = cv2.imread("cv2/images/girl.jpg")

# Detect face landmarks
PREDICTOR_PATH = r"C:\Users\felipe.cunha\Documents\venv\cv2\week1-pyton\data\models\shape_predictor_68_face_landmarks.dat"

cunhafh

$ python3.6 -m venv venv
$ source venv/bin/activate
(venv)$ pip install pylivetrader