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3rdparty/opencv-4.5.4/samples/python/video_threaded.py 2.35 KB
f4334277   Hu Chunming   提交3rdparty
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  #!/usr/bin/env python
  
  '''
  Multithreaded video processing sample.
  Usage:
     video_threaded.py {<video device number>|<video file name>}
  
     Shows how python threading capabilities can be used
     to organize parallel captured frame processing pipeline
     for smoother playback.
  
  Keyboard shortcuts:
  
     ESC - exit
     space - switch between multi and single threaded processing
  '''
  
  # Python 2/3 compatibility
  from __future__ import print_function
  
  import numpy as np
  import cv2 as cv
  
  from multiprocessing.pool import ThreadPool
  from collections import deque
  
  from common import clock, draw_str, StatValue
  import video
  
  
  class DummyTask:
      def __init__(self, data):
          self.data = data
      def ready(self):
          return True
      def get(self):
          return self.data
  
  def main():
      import sys
  
      try:
          fn = sys.argv[1]
      except:
          fn = 0
      cap = video.create_capture(fn)
  
  
      def process_frame(frame, t0):
          # some intensive computation...
          frame = cv.medianBlur(frame, 19)
          frame = cv.medianBlur(frame, 19)
          return frame, t0
  
      threadn = cv.getNumberOfCPUs()
      pool = ThreadPool(processes = threadn)
      pending = deque()
  
      threaded_mode = True
  
      latency = StatValue()
      frame_interval = StatValue()
      last_frame_time = clock()
      while True:
          while len(pending) > 0 and pending[0].ready():
              res, t0 = pending.popleft().get()
              latency.update(clock() - t0)
              draw_str(res, (20, 20), "threaded      :  " + str(threaded_mode))
              draw_str(res, (20, 40), "latency        :  %.1f ms" % (latency.value*1000))
              draw_str(res, (20, 60), "frame interval :  %.1f ms" % (frame_interval.value*1000))
              cv.imshow('threaded video', res)
          if len(pending) < threadn:
              _ret, frame = cap.read()
              t = clock()
              frame_interval.update(t - last_frame_time)
              last_frame_time = t
              if threaded_mode:
                  task = pool.apply_async(process_frame, (frame.copy(), t))
              else:
                  task = DummyTask(process_frame(frame, t))
              pending.append(task)
          ch = cv.waitKey(1)
          if ch == ord(' '):
              threaded_mode = not threaded_mode
          if ch == 27:
              break
  
      print('Done')
  
  
  if __name__ == '__main__':
      print(__doc__)
      main()
      cv.destroyAllWindows()