!pip install --upgrade face_recognition
!pip install --upgrade opencv-python

!wget -O pic.jpg 'https://media.licdn.com/dms/image/C4D03AQHDsuwJf6rX0w/profile-displayphoto-shrink_200_200/0?e=1574899200&v=beta&t=Ny70D9QQIWbtkZGngLPn2yPih10tf0W-m6qwHM3NtXQ'
!wget -O um.jpg 'https://media.licdn.com/dms/image/C4E03AQER_p7M5KxsMw/profile-displayphoto-shrink_200_200/0?e=1574294400&v=beta&t=nUNTUUbJYwrUekQK2o3_F-uUDZbY3nHOgSqvW5G2MTQ'
!wget -O leit.jpg 'https://media.licdn.com/dms/image/C4D03AQHPH83HedAaMw/profile-displayphoto-shrink_800_800/0?e=1575504000&v=beta&t=dGiBrL7-a4QJjelFfBCQJ6pdeQpXhulQt1dBiY24xF4'
!wget -O mig.jpg 'https://media.licdn.com/dms/image/C4D03AQHtodjy_hpn5Q/profile-displayphoto-shrink_800_800/0?e=1575504000&v=beta&t=ATugj3q6zDn8W9cW4T3YGuP5kYdmkuGopq1PO3TJb-c'
!ls -la

import face_recognition
import cv2
import numpy as np

from IPython.display import display, Javascript, Image, clear_output
from google.colab.output import eval_js
from google.colab.patches import cv2_imshow
import urllib

def take_photo(filename='photo.jpg', quality=0.4):
  js = Javascript('''
    async function takePhoto(quality) {
      const div = document.createElement('div');

      const video = document.createElement('video');
      video.style.display = 'block';
      const stream = await navigator.mediaDevices.getUserMedia({video: true});

      document.body.appendChild(div);
      div.appendChild(video);
      video.srcObject = stream;
      await video.play();

      // Resize the output to fit the video element.
      google.colab.output.setIframeHeight(document.documentElement.scrollHeight, true);

      const canvas = document.createElement('canvas');
      canvas.width = video.videoWidth;
      canvas.height = video.videoHeight;
      canvas.getContext('2d').drawImage(video, 0, 0);
      stream.getVideoTracks()[0].stop();
      div.remove();
      return canvas.toDataURL('image/jpeg', quality);
    }
    ''')
  display(js)
  data = eval_js('takePhoto({})'.format(quality))
  resp = urllib.request.urlopen(data)
  image = np.asarray(bytearray(resp.read()), dtype="uint8")
  image = cv2.imdecode(image, cv2.IMREAD_COLOR)

  return image

cam_image = face_recognition.load_image_file("pic.jpg")
cam_image_two = face_recognition.load_image_file("um.jpg")
cam_image_three = face_recognition.load_image_file("leit.jpg")
cam_image_four = face_recognition.load_image_file("mig.jpg")
cam_face_encoding = face_recognition.face_encodings(cam_image)[0]
cam_face_encoding_two = face_recognition.face_encodings(cam_image_two)[0]
cam_face_encoding_three = face_recognition.face_encodings(cam_image_three)[0]
cam_face_encoding_four = face_recognition.face_encodings(cam_image_four)[0]

known_face_encodings = [
    cam_face_encoding,
    cam_face_encoding_two,
    cam_face_encoding_three,
    cam_face_encoding_four
]
known_face_names = [
    "Polillo",
    "1berto",
    "Big Milk",
    "Bunny"
]

face_locations = []
face_encodings = []
face_names = []
process_this_frame = True
first = True

filename = 'result.jpg'
scale = 6

while True:
    frame = take_photo()

    small_frame = cv2.resize(frame, (0, 0), fx=1/scale, fy=1/scale)

    rgb_small_frame = small_frame[:, :, ::-1]

    if process_this_frame:
        face_locations = face_recognition.face_locations(rgb_small_frame)
        face_encodings = face_recognition.face_encodings(rgb_small_frame, face_locations)

        face_names = []
        for face_encoding in face_encodings:
            matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
            name = "Capybara"

            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]

            face_names.append(name)

    process_this_frame = not process_this_frame

    for (top, right, bottom, left), name in zip(face_locations, face_names):
        top *= scale
        right *= scale
        bottom *= scale
        left *= scale

        if name == "Polillo":
          cv2.rectangle(frame, (left, top), (right, bottom), (100, 0, 100), 2)
        elif name == "1berto":
          cv2.rectangle(frame, (left, top), (right, bottom), (100, 0, 100), 2)
        # cv2.circle(frame, (left, top), 5, (100, 0, 100), 1)

        cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (100, 0, 100), cv2.FILLED)
        font = cv2.FONT_HERSHEY_DUPLEX
        cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)
        
    clear_output()
    cv2_imshow(frame)