old_contents: # -*- coding: utf-8 -*-
  """
  Spyder Editor
  
  This is a temporary script file.
  """
  import face_recognition
  import cv2
  import csv
  import numpy as np
  from datetime import datetime
  
  # Get a reference to webcam #0 (the default one)
  video_capture = cv2.VideoCapture(0)
  
  # Load a sample picture and learn how to recognize it.
  #for windows
  #obama_image = face_recognition.load_image_file(".\dataset\\Jason\\1.jpg")
  
  #for linuxe
  obama_image = face_recognition.load_image_file("./dataset/dahang/1.jpg")
  
  obama_face_encoding = face_recognition.face_encodings(obama_image)[0]
  print(obama_face_encoding)
  
  # Initialize some variables
  face_locations = []
  face_encodings = []
  face_names = []
  process_this_frame = True
  
  while True:
  
      time_start = datetime.now()  #get the start time
  
      # Grab a single frame of video
      ret, frame = video_capture.read()
  
      # Resize frame of video to 1/4 size for faster face recognition processing
      small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
  
      # Only process every other frame of video to save time
      if process_this_frame:
          # Find all the faces and face encodings in the current frame of video
          
          locationimg = face_recognition.face_locations(frame)  # top right bottom left  171, 468, 439, 200
  
          if locationimg:
              copyframe = frame.copy();  
              print("detect location:",locationimg)
              cv2.rectangle(frame,(locationimg[0][3],locationimg[0][0]),(locationimg[0][1],locationimg[0][2]),(255,0,0),5)
              
              # record the pic
              if cv2.waitKey(1) & 0xFF == ord('r'):
                  cv2.imwrite("new.jpg", copyframe)
  
          cv2.imshow('Video', frame)
  
      process_this_frame = not process_this_frame
  
      # Hit 'q' on the keyboard to quit!
      if cv2.waitKey(1) & 0xFF == ord('q'):
          break
  
      time_end = datetime.now()  #get the end time
  
      time_cost = time_end - time_start
      print("time cost for detection:", (time_cost.microseconds / 1000.0) )
  
  # Release handle to the webcam
  video_capture.release()
  cv2.destroyAllWindows()
  
new_contents: # -*- coding: utf-8 -*-
  """
  Spyder Editor
  
  This is a temporary script file.
  """
  import face_recognition
  import cv2
  import csv
  import numpy as np
  from datetime import datetime
  import os,sys
  
  # Get a reference to webcam #0 (the default one)
  video_capture = cv2.VideoCapture(0)
  
  # Initialize some variables
  face_locations = []
  face_encodings = []
  face_names = []
  process_this_frame = True
  frame_count = 0
  
  #get the name of the person
  #print(sys.argv[:])
  name_person = sys.argv[1]
  #print(name_person)
  #create the new folder path
  img_person_path = "./dataset/"+name_person
  if not os.path.isdir(img_person_path):
      os.mkdir(img_person_path) 
  
  while True:
  
      time_start = datetime.now()  #get the start time
  
      # Grab a single frame of video
      ret, frame = video_capture.read()
      copyframe = frame.copy()
      # Resize frame of video to 1/4 size for faster face recognition processing
      small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
  
      # Only process every other frame of video to save time
      if process_this_frame:
          # Find all the faces and face encodings in the current frame of video
          
          locationimg = face_recognition.face_locations(frame)  # top right bottom left  171, 468, 439, 200
  
          if locationimg:
              copyframe = frame.copy()
              print("detect location:",locationimg)
              cv2.rectangle(frame,(locationimg[0][3],locationimg[0][0]),(locationimg[0][1],locationimg[0][2]),(255,0,0),5)
              
              # record the pic
              if cv2.waitKey(1) & 0xFF == ord('r'):
                  cv2.imwrite("new.jpg", copyframe)
  
          cv2.imshow('Video', frame)
  
      process_this_frame = not process_this_frame
  
      #write the frame images
      cv2.imwrite(img_person_path+"/"+str(frame_count)+".jpg", copyframe)
      frame_count+=1
  
      # Hit 'q' on the keyboard to quit!
      if cv2.waitKey(1) & 0xFF == ord('q'):
          break
  
      time_end = datetime.now()  #get the end time
  
      time_cost = time_end - time_start
      print("time cost for detection:", (time_cost.microseconds / 1000.0) )
  
  # Release handle to the webcam
  video_capture.release()
  cv2.destroyAllWindows()
  
subject: add the imgs collection code for args input