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• FFMPEG : Need to mix dow multiple audio stream to single stereo

  17 avril 2018, par Serge Dumoulin

  I have an input file with 2 stereo stream of audio.
  I am trying to create an output wav file with the audio mixdown :
  first stereo stream mixdown to left channel of a single stereo stream
  Second stereo stream mixdown to right channel of the same stereo stream.
  So output file have only one stereo stream.
  I have tried different things but its not clear how to manage streams and channels inside them. Found no example on how to do this.

  I’ve tried playing with -filter_complex , amix, and amerge filters, as well as the -map parameter, but I can’t seem to find the right combination of values.

  Here was my input file looks like :

  Input #0,
  
    Metadata:
  
      major_brand     : qt  
  
      minor_version   : 537199360
  
      compatible_brands: qt  
  
      creation_time   : 2018-03-20T16:48:32.000000Z
  
      com.apple.finalcutstudio.media.uuid: 2BE95371-6901-42C7-AB84-6357F53A4592
  
    Duration: 00:05:40.38, start: 0.000000, bitrate: 32679 kb/s
  
      Stream #0:0(eng): Video: prores (apco / 0x6F637061), yuv422p10le(bt709, progressive), 1920x1080, 29590 kb/s, SAR 1:1 DAR 16:9, 23.98 fps, 23.98 tbr, 23976 tbn, 23976 tbc (default)
  
      Metadata:
  
        creation_time   : 2018-03-20T16:48:32.000000Z
  
        handler_name    : Apple Alias Data Handler
  
        encoder         : Apple ProRes 422 Proxy
  
        timecode        : 09:59:20:00
  
  
  
  Stream #0:1(eng): Audio: pcm_s16le (sowt / 0x74776F73), 48000 Hz, stereo, s16, 1536 kb/s (default)
  
      Metadata:
  
        creation_time   : 2018-03-20T16:48:32.000000Z
  
        handler_name    : Apple Alias Data Handler
  
  
  
  Stream #0:2(eng): Audio: pcm_s16le (sowt / 0x74776F73), 48000 Hz, stereo, s16, 1536 kb/s (default)
  
      Metadata:
  
        creation_time   : 2018-03-20T16:48:32.000000Z

• Handling high volume traffic and traffic peaks with Matomo just got easier

  16 avril 2018, par Matomo Core Team

  When you use the self-hosted version of Matomo on-premise instead of the Matomo cloud-hosted solution, you may experience some traffic peaks on your Matomo server when the traffic volume on your websites increases. For example, every day at a certain time you might receive two or three times the amount of traffic that usually visits your website. This can have many negative impacts, including :

  • Slow loading time for your JavaScript tracker (piwik.js) which in turn may slow down your website giving your users a poor experience. Also you may see less page views in Matomo because by the time the tracker is loaded on your website, the user has already moved on to another page.
  • Some tracking requests might be simply ignored at some point because your server might not be able to handle any tracking requests anymore which results in many untracked visits and page views.
  • You may need additional servers only to handle traffic peaks which results in increased server costs, maintenance work and maintenance costs.

  The solution

  Handling traffic peaks has been possible with Matomo for years using the Queued Tracking plugin. When this feature is enabled, tracking requests are put into a queue instead of being processed immediately. Then when a job is running separately it takes the requests out of the queue and processes them. This brings various benefits.

  Faster tracking

  It improves the tracking speed on your server by a factor of 5 to 15. So for example, instead of a tracking request taking 50ms, it takes only 5ms. This means your server will be able to handle a lot more concurrent requests compared to the traditional tracking and is likely to survive traffics peaks much more likely without any trouble at all.

  Faster processing

  When a request is queued, the request still needs to be processed eventually. Because the Queued Tracking solution can take multiple tracking requests out of the queue at once and process them in one go, the processing speed increases massively as well. This is because by default each tracking request has to bootstrap Matomo and do a lot of things again and again which takes quite a bit of time (you’d be surprised). Instead, many things can now be cached and don’t have to be done multiple times. As a result, your server can process tracking requests much faster and needs less resources overall which in turn reduces cost and trouble.

  Queued Tracking is now easier to set up

  In the background, Queued Tracking has been using Redis, an in-memory database. While Redis is very fast, it’s not simple to setup and maintain it. Especially when it comes to making Redis “highly available” and when you need to scale your Redis. Also, your servers will need a lot more memory for Redis as all queued tracking requests are stored in memory.

  One click setup

  We have now added support for a MySQL database so you can activate Queued Tracking with a simple click. What used to take hours or maybe even weeks to set up and a lot of maintenance, can now be cut down to seconds. Queued Tracking will then simply reuse the database that you have been using all along for storing all your visits. A side benefit is that your server won’t need more memory and all queued tracking requests even survive a server reboot.

  Both Redis and MySQL are now supported in Queued Tracking. If you do have experience with managing Redis, we still recommend using this solution as it’s likely a bit faster. However, in most cases the MySQL solution should work just as well.

  Further improvements

  We have made various other improvements for Queued Tracking that increases the performance and you can now be notified when the number of queued tracking requests reaches a certain threshold. View the changelog for a list of all changes.

  Learn more

  We have been setting up Queued Tracking multiple times when it comes to high volume traffic or dealing with peaks and are amazed by the results. Often, we can even reduce the overall amount of needed servers.

  If this sounds like something that could be beneficial to you, we recommend you have a look at the Queued Tracking page and also check out the FAQ. You might be also interested in learning how to configure Matomo for speed.

  Need help with setting up, maintaining, or scaling Matomo ? Get in touch now.

  The post Handling high volume traffic and traffic peaks with Matomo just got easier appeared first on Analytics Platform - Matomo.

• merge multiple videos and images dynamically using ffmpeg [duplicate]

  16 avril 2018, par robert tamunoemi

  This question already has an answer here :

  • FFmpeg : concat multiple videos, some with audio, some without
    
    1 answer
    
  • FFmpeg concatenation, no Audio in Final Output
    
    1 answer
    

  I am trying to merge several images and videos together. When there is more than one video, the audio of the next video is lost. Here is my command :

  $filter = "[0][1][2][3][4]concat=n=5:v=1:a=0,scale=320:240";
  
  
  
  $cmd = 'ffmpeg -y  -i videos/video__152344425320.mp4  -loop 1 -framerate 24 -t 10 -i images/4_152222487376001.png -i videos/video__152344425320.mp4 -loop 1 -framerate 24 -t 10 -i images/4_152222487376002.png -loop 1 -framerate 24 -t 10 -i images/4_152222487376003.png -filter_complex '.$filter.' out.mp4'; 
  
  shell_exec($cmd.' 2> log.txt');

  This works but when I set concat=n=5:v=2:a=1, I get this error :

  ffmpeg version N-89674-g57d0c24132 Copyright (c) 2000-2018 the FFmpeg developers
  
    built with gcc 7.2.0 (GCC)
  
    configuration: --enable-gpl --enable-version3 --enable-sdl2 --enable-bzlib --enable-fontconfig --enable-gnutls --enable-iconv --enable-libass --enable-libbluray --enable-libfreetype --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libopus --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libtheora --enable-libtwolame --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libzimg --enable-lzma --enable-zlib --enable-gmp --enable-libvidstab --enable-libvorbis --enable-libvo-amrwbenc --enable-libmysofa --enable-libspeex --enable-amf --enable-cuda --enable-cuvid --enable-d3d11va --enable-nvenc --enable-dxva2 --enable-avisynth --enable-libmfx
  
    libavutil      56.  7.100 / 56.  7.100
  
    libavcodec     58.  9.100 / 58.  9.100
  
    libavformat    58.  3.100 / 58.  3.100
  
    libavdevice    58.  0.100 / 58.  0.100
  
    libavfilter     7.  8.100 /  7.  8.100
  
    libswscale      5.  0.101 /  5.  0.101
  
    libswresample   3.  0.101 /  3.  0.101
  
    libpostproc    55.  0.100 / 55.  0.100
  
  Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'videos/video__152344425320.mp4':
  
    Metadata:
  
      major_brand     : mp42
  
      minor_version   : 0
  
      compatible_brands: isommp42
  
      creation_time   : 2017-12-10T04:51:23.000000Z
  
    Duration: 00:02:48.62, start: 0.000000, bitrate: 77 kb/s
  
      Stream #0:0(und): Video: mpeg4 (Simple Profile) (mp4v / 0x7634706D), yuv420p, 176x144 [SAR 1:1 DAR 11:9], 51 kb/s, 10.01 fps, 9.99 tbr, 15984 tbn, 999 tbc (default)
  
      Metadata:
  
        creation_time   : 2017-12-10T04:51:23.000000Z
  
        handler_name    : IsoMedia File Produced by Google, 5-11-2011
  
      Stream #0:1(und): Audio: aac (LC) (mp4a / 0x6134706D), 22050 Hz, mono, fltp, 24 kb/s (default)
  
      Metadata:
  
        creation_time   : 2017-12-10T04:51:24.000000Z
  
        handler_name    : IsoMedia File Produced by Google, 5-11-2011
  
  Input #1, png_pipe, from 'images/4_152222487376001.png':
  
    Duration: N/A, bitrate: N/A
  
      Stream #1:0: Video: png, rgba(pc), 176x144 [SAR 3780:3780 DAR 11:9], 24 fps, 24 tbr, 24 tbn, 24 tbc
  
  Input #2, mov,mp4,m4a,3gp,3g2,mj2, from 'videos/video__152344425320.mp4':
  
    Metadata:
  
      major_brand     : mp42
  
      minor_version   : 0
  
      compatible_brands: isommp42
  
      creation_time   : 2017-12-10T04:51:23.000000Z
  
    Duration: 00:02:48.62, start: 0.000000, bitrate: 77 kb/s
  
      Stream #2:0(und): Video: mpeg4 (Simple Profile) (mp4v / 0x7634706D), yuv420p, 176x144 [SAR 1:1 DAR 11:9], 51 kb/s, 10.01 fps, 9.99 tbr, 15984 tbn, 999 tbc (default)
  
      Metadata:
  
        creation_time   : 2017-12-10T04:51:23.000000Z
  
        handler_name    : IsoMedia File Produced by Google, 5-11-2011
  
      Stream #2:1(und): Audio: aac (LC) (mp4a / 0x6134706D), 22050 Hz, mono, fltp, 24 kb/s (default)
  
      Metadata:
  
        creation_time   : 2017-12-10T04:51:24.000000Z
  
        handler_name    : IsoMedia File Produced by Google, 5-11-2011
  
  Input #3, png_pipe, from 'images/4_152222487376002.png':
  
    Duration: N/A, bitrate: N/A
  
      Stream #3:0: Video: png, rgba(pc), 176x144 [SAR 3780:3780 DAR 11:9], 24 fps, 24 tbr, 24 tbn, 24 tbc
  
  Input #4, png_pipe, from 'images/4_152222487376003.png':
  
    Duration: N/A, bitrate: N/A
  
      Stream #4:0: Video: png, rgba(pc), 176x144 [SAR 3780:3780 DAR 11:9], 24 fps, 24 tbr, 24 tbn, 24 tbc
  
  [AVFilterGraph @ 00000000030fe580] Too many inputs specified for the "scale" filter.
  
  Error initializing complex filters.
  
  Invalid argument