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• ffmpeg command to copy raw data into MP4 hangs and never finishes

  28 mai 2019, par James Adams

  I am running an ffmpeg command to copy raw H.265 data into an MP4 file and the command never completes. The file isn’t large, just 10 seconds worth of data. Here’s the command I’m running :

  $ ffmpeg -rtsp_transport tcp -i rtsp://user:pass@71.185.124.195:554/c1/b1558830329/e1558830339/replay/ -vcodec copy -y test_clip.mp4

  I then get output like this :

  ffmpeg version 3.4.6-0ubuntu0.18.04.1 Copyright (c) 2000-2019 the FFmpeg developers
  
    built with gcc 7 (Ubuntu 7.3.0-16ubuntu3)
  
    configuration: --prefix=/usr --extra-version=0ubuntu0.18.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --enable-gpl --disable-stripping --enable-avresample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librubberband --enable-librsvg --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-omx --enable-openal --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libopencv --enable-libx264 --enable-shared
  
    libavutil      55. 78.100 / 55. 78.100
  
    libavcodec     57.107.100 / 57.107.100
  
    libavformat    57. 83.100 / 57. 83.100
  
    libavdevice    57. 10.100 / 57. 10.100
  
    libavfilter     6.107.100 /  6.107.100
  
    libavresample   3.  7.  0 /  3.  7.  0
  
    libswscale      4.  8.100 /  4.  8.100
  
    libswresample   2.  9.100 /  2.  9.100
  
    libpostproc    54.  7.100 / 54.  7.100
  
  Guessed Channel Layout for Input Stream #0.1 : mono
  
  Input #0, rtsp, from 'rtsp://user:pass@71.85.104.195:554/c1/b1558830329/e1558830339/replay/':
  
    Metadata:
  
      title           : ONVIF RTSP Server
  
    Duration: N/A, start: 0.000000, bitrate: N/A
  
      Stream #0:0: Video: h264 (High), yuvj420p(pc, bt709, progressive), 1920x1080, 30 fps, 30 tbr, 90k tbn, 60 tbc
  
      Stream #0:1: Audio: pcm_mulaw, 8000 Hz, mono, s16, 64 kb/s
  
  Stream mapping:
  
    Stream #0:0 -> #0:0 (copy)
  
    Stream #0:1 -> #0:1 (pcm_mulaw (native) -> aac (native))
  
  Press [q] to stop, [?] for help
  
  [aac @ 0x55b71ce31900] Too many bits 8832.000000 > 6144 per frame requested, clamping to max
  
  Output #0, mp4, to 'test_clip.mp4':
  
    Metadata:
  
      title           : ONVIF RTSP Server
  
      encoder         : Lavf57.83.100
  
      Stream #0:0: Video: h264 (High) (avc1 / 0x31637661), yuvj420p(pc, bt709, progressive), 1920x1080, q=2-31, 30 fps, 30 tbr, 90k tbn, 90k tbc
  
      Stream #0:1: Audio: aac (LC) (mp4a / 0x6134706D), 8000 Hz, mono, fltp, 48 kb/s
  
      Metadata:
  
        encoder         : Lavc57.107.100 aac
  
  [mp4 @ 0x55b71ce17e00] Non-monotonous DTS in output stream 0:0; previous: 18000, current: 3000; changing to 18001. This may result in incorrect timestamps in the output file.
  
  [mp4 @ 0x55b71ce17e00] Non-monotonous DTS in output stream 0:0; previous: 18001, current: 6000; changing to 18002. This may result in incorrect timestamps in the output file.
  
  [mp4 @ 0x55b71ce17e00] Non-monotonous DTS in output stream 0:0; previous: 18002, current: 9000; changing to 18003. This may result in incorrect timestamps in the output file.
  
  [mp4 @ 0x55b71ce17e00] Non-monotonous DTS in output stream 0:0; previous: 18003, current: 12000; changing to 18004. This may result in incorrect timestamps in the output file.
  
  [mp4 @ 0x55b71ce17e00] Non-monotonous DTS in output stream 0:0; previous: 18004, current: 15000; changing to 18005. This may result in incorrect timestamps in the output file.
  
  [mp4 @ 0x55b71ce17e00] Non-monotonous DTS in output stream 0:0; previous: 18005, current: 18000; changing to 18006. This may result in incorrect timestamps in the output file.
  
  frame=   44 fps=0.0 q=-1.0 size=     256kB time=00:00:01.43 bitrate=1463.4kbits/frame=   60 fps= 57 q=-1.0 size=     512kB time=00:00:01.96 bitrate=2132.9kbits/frame=   76 fps= 48 q=-1.0 size=     768kB time=00:00:02.50 bitrate=2516.7kbits/frame=   92 fps= 44 q=-1.0 size=    1024kB time=00:00:03.03 bitrate=2765.6kbits/frame=  108 fps= 41 q=-1.0 size=    1024kB time=00:00:03.56 bitrate=2352.0kbits/[NULL @ 0x55b71cdfa540] SEI type 5 size 2208 truncated at 1944
  
  frame=  123 fps= 39 q=-1.0 size=    1280kB time=00:00:04.06 bitrate=2578.6kbits/frame=  139 fps= 38 q=-1.0 size=    1536kB time=00:00:04.60 bitrate=2735.5kbits/frame=  155 fps= 37 q=-1.0 size=    1536kB time=00:00:05.13 bitrate=2451.3kbits/frame=  171 fps= 36 q=-1.0 size=    1792kB time=00:00:05.66 bitrate=2590.7kbits/frame=  187 fps= 36 q=-1.0 size=    2048kB time=00:00:06.20 bitrate=2706.1kbits/frame=  203 fps= 35 q=-1.0 size=    2304kB time=00:00:06.73 bitrate=2803.2kbits/frame=  219 fps= 35 q=-1.0 size=    2304kB time=00:00:07.26 bitrate=2597.4kbits/frame=  235 fps= 34 q=-1.0 size=    2560kB time=00:00:07.80 bitrate=2688.7kbits/frame=  246 fps= 33 q=-1.0 size=    2560kB time=00:00:08.16 bitrate=2568.0kbits/frame=  267 fps= 34 q=-1.0 size=    3072kB time=00:00:08.86 bitrate=2838.3kbits/frame=  282 fps= 34 q=-1.0 size=    3072kB time=00:00:09.36 bitrate=2686.8kbits/frame=  298 fps= 33 q=-1.0 size=    3328kB time=00:00:09.90 bitrate=2753.9kbits/frame=  314 fps= 33 q=-1.0 size=    3328kB time=00:00:10.43 bitrate=2613.1kbits/^Cspeed=1.11x    

  The command never completes and I need to kill it using Ctrl-C.

  I have also tried adding the options -nostdin -loglevel error and appending this to the end of the command : > /dev/null 2>&1 < /dev/null but to no avail.

  I am testing the above since it mimics the actual code I’m developing which utilizes a Python package that wraps calls to ffmpeg. The Python code below works well on a laptop but hangs on EC2 (both are Ubuntu 18.04) :

  import argparse
  
  import datetime
  
  import ffmpeg
  
  
  
  
  
  # ------------------------------------------------------------------------------
  
  if __name__ == "__main__":
  
  
  
      # USAGE
  
      # $ python collect_and_store.py --rtsp rtsp://user:pass1@71.85.125.110:554 \
  
      #       --duration 30 --count 10
  
  
  
      # construct the argument parser and parse the arguments
  
      args_parser = argparse.ArgumentParser()
  
      args_parser.add_argument("--rtsp",
  
                               required=True,
  
                               type=str,
  
                               help="RTSP URL for video stream")
  
      args_parser.add_argument("--duration",
  
                               required=True,
  
                               type=int,
  
                               help="duration of saved clips (in seconds)")
  
      args_parser.add_argument("--count",
  
                               required=True,
  
                               type=int,
  
                               help="number of clips to save")
  
      args = vars(args_parser.parse_args())
  
  
  
      # sanity check for some of the arguments
  
      if not args["rtsp"].lower().startswith("rtsp://"):
  
          raise ValueError("Invalid input URL -- only RTSP supported")
  
  
  
      seconds_per_clip = args["duration"]
  
      start = int(datetime.datetime.now().strftime("%s"))
  
      end = start + seconds_per_clip
  
      number_of_files_to_collect = args["count"]
  
  
  
      while number_of_files_to_collect > 0:
  
  
  
          # build URL with start and end times
  
          # NOTE URL is for Uniview RTSP, add options for other camera types
  
          url = args["rtsp"] + f"/c1/b{start}/e{end}/replay/"
  
  
  
          # file where we'll write clip data
  
          temp_file = f"clip_b{start}_e{end}.mp4"
  
  
  
          # create the equivalent of the ffmpeg command:
  
          # $ ffmpeg -i  -vcodec copy -y -rtsp_transport tcp 
  
          stream = ffmpeg.input(url)
  
          stream = ffmpeg.output(stream, temp_file,
  
                                 **{"codec:v": "copy",
  
                                    "rtsp_transport": "tcp",
  
                                    "y": None
  
                                    }
  
                                 )
  
          ffmpeg.run(stream)
  
  
  
          print(f"\n\nMP4 file created: {temp_file}")
  
  
  
          number_of_files_to_collect -= 1
  
          start = end + 1
  
          end = start + seconds_per_clip

• Easily track Events within Matomo Analytics thanks to Matomo Tag Manager

  7 juin 2019, par Matomo Core Team — Analytics Tips

  Easily track Events within Matomo Analytics thanks to Matomo Tag Manager

  Introduction

  In this article we’ll cover what events in Matomo Analytics are ; and how you can easily set them up thanks to Matomo Tag Manager.

  Key concepts within this article

  • Events
  • Quick definition of the Tag Management System
  • Matomo config
  • Creating triggers
  • Variables

  What are events in Matomo Analytics and why are they useful ?

  Events allow you to measure interactions on your website which are not defined by default. With them you can measure clicks on some elements of a page, such as, how visitors are interacting with dropdown menus, media players, scrolling behaviours etc. You can also use them to define goals which make them a key feature in Matomo Analytics. Learn more about tracking events in Matomo.

  You can easily access the Events report in Matomo Analytics by clicking on the Behaviour category :

  

  And you may read the following message and feel a bit frustrated :

  

  “There is no data for this report” is a nice way to say, “Hey, you are tracking just a tiny part of what Matomo Analytics can do for you.”

  Matomo is a great software, but it can’t guess what you want to track.

  In order for Matomo to register those event tracking interactions, you’ll need to explain it by adding a line of code similar to this one when the interaction happens :

   

  _paq.push(['trackEvent', 'Here you enter whatever you want', 'Here too', 'and here also']);

   

  Let’s imagine you want to track a click on an HTML button, your code will look something similar to this at the moment of the interaction :

  Click Me !

  As you can imagine, two main challenges will arise for non developers :

  1. How to access the source code ?
  2. How to define the interaction ?

  Luckily, Matomo Tag Manager makes those steps easy for you. Let’s see how the same tracking is implemented with Matomo Tag Manager.

  A quick definition of what Matomo Tag Manager is

  Matomo Tag Manager lets you manage all your tracking and marketing tags in one easy-to-access place. Please visit this page to learn more about Matomo Tag Manager. In order to start using it, you’ll need to copy/paste a tracking code, named a “container”, within the section of your pages.

  Once the container is on your website, all you need to do is to follow these simple steps :

  1. Add a Matomo Tag.
  2. Assign the condition to fire the tag (what we call the trigger).
  3. Publish your work.
  4. And enjoy

  1 – Add a Matomo Event tracking code

  All you have to do here is click on “CREATE NEW TAG”

  

  Once selected, just mention how you’d like this tag to be named (it is for your internal purpose here so always use an explicit tag name) and the Matomo configuration (the default configuration setting will be fine in most of the cases) :

  

  Then Matomo Tag Manager will ask you the type of tracking you’d like to deploy, in this case, this is an event so select “Event” :

  

  Then all you need is to indicate the values you’d like to push through your event :

  

  To put it in perspective, all we did here through Matomo Tag Manager was implement the equivalent of the following line of code :

  _paq.push(['trackEvent', 'Element interactions', 'Click button', 'Click Me']);

  Let’s now see how can we do this on click code part which we call a trigger.

  2 – Assign the condition to fire the tag

  In order to execute the event we’ll need to define when it will happen. You do this by clicking on Create a new trigger now :

  

  As the interaction we’d like to track is happening when a click occurs, it will be a click trigger, and as our button is not a link, we’ll select All Elements Click :

  

  Once selected you’ll need to be precise on the condition in which the event will be triggered. In this case we do not want to have events pushed every time someone is clicking on something on our website. We only want to track when they click on this specific button. That’s the reason why our trigger is set to fire only when the click occurs on an element which has an id and has the value “cta” :

  Once you click on the green button named CREATE NEW TRIGGER, you validate the tag by clicking on CREATE NEW TAG :

  

  

  Then you can move to the last part.

  3 – Publish your work

  Tag Managers are very powerful as they allow you to easily execute any JavaScript code, CSS or even text content on your websites.

  That’s why when you create your tag it doesn’t go live straight away on your website. In order to do this you need to publish your tag and this is what the “Publish” category is designed for :

  

  After that, click on the second button if you’re confident your tag and trigger are both ready to go live :

  

  4 – Enjoy

  Well done. As your tag is now live, every click made on this button will now be pushed to your Matomo Analytics account within :
  

  1. The visitor log report :

  

  2. The events report :

  

  You may now be asking, “That’s great, but can I collect something more exciting than clicks ?” 

  Of course you can ! This is what the Matomo Tag Manager is all about.

  As long as you can express it through a trigger you can really push whatever you want to Matomo Analytics. You can track scrolling patterns, an element visible on the page like an image, an ad or the time spent on the page. The options are now open to you with Tag Manager.

  Give them a try ! Change the triggers, start playing around with variables and discover that the possibilities are endless.

  Happy analytics,
  Matomo team

• libx265 : Update ROI behaviour to match documentation

  4 juin 2019, par Mark Thompson

  libx265 : Update ROI behaviour to match documentation
  Equivalent to the previous patch for libx264.
  

  • [DH] libavcodec/libx265.c