text: import numpy as np
  import cv2
  
  
  face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
  eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
  smile_cascade = cv2.CascadeClassifier('haarcascade_smile.xml')
  
  # cap = cv2.VideoCapture(0)
  cap = cv2.VideoCapture('http://192.168.55.6:8080/video')
  x = 1
  
  cap3 = cap.get(3)
  cap4 = cap.get(4)
  
  print('cap {} {}'.format(cap3, cap4))
  
  
  print('cap {} {}'.format(cap3, cap4))
  while(True):
      # Capture frame-by-frame
      ret, frame = cap.read()
  
      if (x == 1):
  
          # print(frame)
          x += 1
  
      # Our operations on the frame come here
      gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
      faces = face_cascade.detectMultiScale(gray, 1.3, 5)
      for (x, y, w, h) in faces:
          cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
          roi_gray = gray[y:y+h, x:x+w]
          roi_color = frame[y:y+h, x:x+w]
          # print('\n\n new ')
          # print(roi_gray)
          eyes = eye_cascade.detectMultiScale(roi_gray)
          for (ex, ey, ew, eh) in eyes:
              cv2.rectangle(roi_color, (ex, ey), (ex+ew, ey+eh), (0, 255, 0), 2)
          smile = smile_cascade.detectMultiScale(roi_gray)
          # for (ex, ey, ew, eh) in smile:
          #     cv2.rectangle(roi_color, (ex, ey), (ex+ew, ey+eh), (0, 255, 0), 2)
  
      # Display the resulting frame
  
      cv2.imshow('frame', frame)
      # cv2.imshow('foo', gray)
      if cv2.waitKey(1) & 0xFF == ord('q'):
          break
  
  # When everything done, release the capture
  cap.release()
  cv2.destroyAllWindows()
  