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Médias (91)

Autres articles (38)

  • Support de tous types de médias

    10 avril 2011

    Contrairement à beaucoup de logiciels et autres plate-formes modernes de partage de documents, MediaSPIP a l’ambition de gérer un maximum de formats de documents différents qu’ils soient de type : images (png, gif, jpg, bmp et autres...) ; audio (MP3, Ogg, Wav et autres...) ; vidéo (Avi, MP4, Ogv, mpg, mov, wmv et autres...) ; contenu textuel, code ou autres (open office, microsoft office (tableur, présentation), web (html, css), LaTeX, Google Earth) (...)

  • Supporting all media types

    13 avril 2011, par

    Unlike most software and media-sharing platforms, MediaSPIP aims to manage as many different media types as possible. The following are just a few examples from an ever-expanding list of supported formats : images : png, gif, jpg, bmp and more audio : MP3, Ogg, Wav and more video : AVI, MP4, OGV, mpg, mov, wmv and more text, code and other data : OpenOffice, Microsoft Office (Word, PowerPoint, Excel), web (html, CSS), LaTeX, Google Earth and (...)

  • List of compatible distributions

    26 avril 2011, par

    The table below is the list of Linux distributions compatible with the automated installation script of MediaSPIP. Distribution nameVersion nameVersion number Debian Squeeze 6.x.x Debian Weezy 7.x.x Debian Jessie 8.x.x Ubuntu The Precise Pangolin 12.04 LTS Ubuntu The Trusty Tahr 14.04
    If you want to help us improve this list, you can provide us access to a machine whose distribution is not mentioned above or send the necessary fixes to add (...)

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  • Using ffmpeg to assemble images from S3 into a video

    10 juillet 2020, par Mass Dot Net

    I can easily assemble images from local disk into a video using ffmpeg and passing a %06d filespec. Here's what a typical (pseudocode) command would look like :

    


    ffmpeg.exe -hide_banner -y -r 60 -t 12 -i /JpgsToCombine/%06d.JPG <..etc..>


    


    However, I'm struggling to do the same with images stored in AWS S3, without using some third party software to mount a virtual drive (e.g. TNTDrive). The S3 folder containing our images is too large to download to the 20GB ephemeral storage provided for AWS containers, and we're trying to avoid EFS because we'd have to provision expensive bandwidth.

    


    Here's what the HTTP and S3 URLs to each of our JPGs looks like :

    


    # HTTP URL
https://massdotnet.s3.amazonaws.com/jpgs-to-combine/000000.JPG # frame 0
https://massdotnet.s3.amazonaws.com/jpgs-to-combine/000012.JPG # frame 12
https://massdotnet.s3.amazonaws.com/jpgs-to-combine/000123.JPG # frame 123
https://massdotnet.s3.amazonaws.com/jpgs-to-combine/456789.JPG # frame 456789

# S3 URL
s3://massdotnet/jpgs-to-combine/000000.JPG # frame 0
s3://massdotnet/jpgs-to-combine/000012.JPG # frame 12
s3://massdotnet/jpgs-to-combine/000123.JPG # frame 123
s3://massdotnet/jpgs-to-combine/456789.JPG # frame 456789


    


    Is there any way to get ffmpeg to assemble these ? We could generate a signed URL for each S3 file, and put several thousand of those URLs onto a command line with an FFMPEG concat filter. However, we'd run up into the command line input limit in Linux at some point using this approach. I'm hoping there's a better way...

    


  • Error : ffmpeg exited with code 1 on AWS Lambda

    16 juin 2022, par Hassnain Alvi

    I am using fluent-ffmpeg nodejs package to run ffmpeg for audio conversion on AWS Lambda. I am using this FFmpeg layer for lambda.
Here is my code

    


      const bitrate64 = ffmpeg("file.mp3").audioBitrate('64k');
    bitrate64.outputOptions([
        '-preset slow',
    '-g 48',
    "-map", "0:0",
        '-hls_time 6',
        '-master_pl_name master.m3u8',
        '-hls_segment_filename 64k/fileSequence%d.ts'
    ])
    .output('./64k/prog_index.m3u8')
    .on('progress', function(progress) {
        console.log('Processing 64k bitrate: ' + progress.percent + '% done')
    })  
    .on('end', function(err, stdout, stderr) {
        console.log('Finished processing 64k bitrate!')
    })
    .run() 


    


    after running it via AWS lambda I get following error message

    


    ERROR   Uncaught Exception  &#xA;{&#xA;    "errorType": "Error",&#xA;    "errorMessage": "ffmpeg exited with code 1: Conversion failed!\n",&#xA;    "stack": [&#xA;        "Error: ffmpeg exited with code 1: Conversion failed!",&#xA;        "",&#xA;        "    at ChildProcess.<anonymous> (/var/task/node_modules/fluent-ffmpeg/lib/processor.js:182:22)",&#xA;        "    at ChildProcess.emit (events.js:198:13)",&#xA;        "    at ChildProcess.EventEmitter.emit (domain.js:448:20)",&#xA;        "    at Process.ChildProcess._handle.onexit (internal/child_process.js:248:12)"&#xA;    ]&#xA;}&#xA;</anonymous>

    &#xA;

    I don't get any more info so I am not sure what's going on. Can anyone tell me what's wrong here and how can I enable more detailed logs ?

    &#xA;

  • What's the best FFMPEG method for frequent, automated compilation of timelapse videos ?

    5 août 2020, par GoOutside

    I have a web application running on a not-particularly beefy Ubuntu Amazon Lightsail instance that uses FFMPEG to build a timelapse video generated from downloaded .jpg webcam photos taken every 2 minutes throughout the day (720 total images each day, which grows throughout the day as new images are downloaded).

    &#xA;

    The code I'm running every 20 minutes is this :

    &#xA;

    ffmpeg -y -r 24 -pattern_type glob -I &#x27;picturefolder/*.jpg&#x27; -s 1024x576 -vcodec libx264 picturefolder/timelapse.mp4

    &#xA;

    This mostly works, but it is often quite slow, taking 30-60 seconds to run and getting slower as the day goes on, of course.

    &#xA;

    Recently, I tried to use concat instead of globbing the entire folder over and over. I did not see a noticeable performance improvement, ass it appears the concat processes the entire video in order to add even just a few frames to the end of it.

    &#xA;

    My question for any FFMPEG experts out there : what is the most efficient way to handle this kind of automated timelapse creation, given my setup ? Is there a flag I'm missing ? Perhaps a different, more efficient method ? Or maybe a way to have the FFMPEG process just crawl through this at a more 'slow and steady' pace instead of big bursts of CPU usage.

    &#xA;

    Or am I stuck with this and should just deal with it ? My ultimate goal would be to continue using my current tier (2 GB RAM, 1 vCPU) without the expense of upgrading. Thank you very kindly for your help !

    &#xA;