text: import face_recognition
  import cv2
  import numpy as np
  
  video_capture = cv2.VideoCapture(0)
  
  
  known_face_encodings = []
  known_face_names = [
      "Sitanshu"
  ]
  
  face_locations = []
  face_encodings = []
  face_names = []
  process_this_frame = True
  
  while True:
      ret, frame = video_capture.read()
      small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
      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 = "Unknown"
              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 *= 4
          right *= 4
          bottom *= 4
          left *= 4
  
          
          cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
  
          
          cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
          font = cv2.FONT_HERSHEY_DUPLEX
          cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)
      cv2.imshow('Video', frame)
      if cv2.waitKey(1) & 0xFF == ord('q'):
          break
  
  video_capture.release()
  cv2.destroyAllWindows()