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• Revision 4bbd95512a : Dynamic resize for real-time : source scaling Use faster scaling on source. Cha

  9 juillet 2015, par Marco

  Changed Paths :
   Modify /vp9/encoder/vp9_encoder.c

  
   Modify /vp9/encoder/vp9_encoder.h

  
  
  Dynamic resize for real-time : source scaling

  Use faster scaling on source.

  Change-Id : I968df97239a86834c96126b86832d3d6d0875a53

• Real Time indoor streaming and music mixing

  9 novembre 2015, par Saneet

  I am working on this project where we are doing a live performance with about 6 musicians placed away from each other in a big space. The audience will be wearing their headphones and as they move around we want them to hear different kinds of effects in different areas of the place. For calculating the position of users we are using bluetooth beacons. We’re expecting around a 100 users and we can’t have a latency of more than 2 seconds.

  Is such kind of a setup possible ?

  The current way we’re thinking of implementing this is that we’ll divide the place into about 30 different sections.
  For the server we’ll take the input from all the musicians and mix a different stream for every section and stream it on a local WLAN using the RTP protocol.
  We’ll have Android and iOS apps that will locate the users using Bluetooth beacons and switch the live streams accordingly.

  Presonus Studio One music mixer - Can have multiple channels that can be output to devices. 30 channels.
  Virtual Audio Cable - Used to create virtual devices that will get the output from the channels. 30 devices.
  FFMpeg streaming - Used to create an RTP stream for each of the devices. 30 streams.

  Is this a good idea ? Are there other ways of doing this ?
  Any help will be appreciated.

• ffmpeg real-time buffer too full or near too full frame dropped, I even tried increasing rtbufsize. What could be going wrong ?

  21 mai 2024, par Ali Azlan

  We have a software where we capture the stream from the camera connected to the laptop or device using ffmpeg python,

  


                   ffmpeg
                .input(video, s='640x480', **self.args) //tried with rtbufsize=1000M (enough I suupose/ also sometimes the error does not occur even on default rtbufsize which is around 3MB)
                .output('pipe:', format='rawvideo', pix_fmt='rgb24')
                .overwrite_output()
                .run_async(pipe_stdout=True) 


  


  majority of the times when I start the software like the software is still initiating we receive the following error, I have also received this error when the software has initiated fully and completely and it is running from a long time like after 12hrs or more.

  


  


  Error : [dshow @ 000002248916e240] real-time buffer [Integrated
Camera] [video input] too full or near too full (80% of size : 3041280
[rtbufsize parameter]) ! frame dropped !
Last message repeated 1 times [dshow @ 000002248916e240] real-time buffer [Integrated Camera] [video input] too full or near too full
(101% of size : 3041280 [rtbufsize parameter]) ! frame dropped !

  


  


  What are the things we possibly might be doing wrong ?

  


  Edit 1 :

  


  below is the code to consume the frame captured in the video using ffmpeg

  


      def frame_reader(self):
    while True:
        in_bytes = self.process.stdout.read(self.width * self.height * 3)
        if not in_bytes:
            break
        try:
            in_frame = (
                np
                    .frombuffer(in_bytes, np.uint8)
                    .reshape([self.height, self.width, 3])
            )
            frame = cv2.resize(in_frame, (640, 480))
            frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
        except Exception as e:
            logger.error(e, exc_info=True)
            in_frame = (
                np
                    .frombuffer(in_bytes, np.uint8)
            )

        if not self.q.empty():
            try:
                self.q.get_nowait()
            except queue.Empty:
                pass
        self.q.put(frame)