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  • MediaSPIP version 0.1 Beta

    16 avril 2011, par

    MediaSPIP 0.1 beta est la première version de MediaSPIP décrétée comme "utilisable".
    Le fichier zip ici présent contient uniquement les sources de MediaSPIP en version standalone.
    Pour avoir une installation fonctionnelle, il est nécessaire d’installer manuellement l’ensemble des dépendances logicielles sur le serveur.
    Si vous souhaitez utiliser cette archive pour une installation en mode ferme, il vous faudra également procéder à d’autres modifications (...)

  • MediaSPIP 0.1 Beta version

    25 avril 2011, par

    MediaSPIP 0.1 beta is the first version of MediaSPIP proclaimed as "usable".
    The zip file provided here only contains the sources of MediaSPIP in its standalone version.
    To get a working installation, you must manually install all-software dependencies on the server.
    If you want to use this archive for an installation in "farm mode", you will also need to proceed to other manual (...)

  • Amélioration de la version de base

    13 septembre 2013

    Jolie sélection multiple
    Le plugin Chosen permet d’améliorer l’ergonomie des champs de sélection multiple. Voir les deux images suivantes pour comparer.
    Il suffit pour cela d’activer le plugin Chosen (Configuration générale du site > Gestion des plugins), puis de configurer le plugin (Les squelettes > Chosen) en activant l’utilisation de Chosen dans le site public et en spécifiant les éléments de formulaires à améliorer, par exemple select[multiple] pour les listes à sélection multiple (...)

Sur d’autres sites (8766)

  • Firebase Function using ffmpeg successful with emulator, out of memory when deployed

    25 septembre 2024, par flyingL123

    I need some help. I have a .mov file in Firebase Storage. The file is 25 seconds long and 106 MB. I wrote a callable Firebase function that uses ffmpeg to convert the file to a .mp4 file and save it to Firebase Storage. When I test the function using the Functions emulator, it works without issue. The function returns successfully and I see the converted file appear in storage. The converted video is about 6 MB and plays correctly when dowloaded.

    


    When I deploy this function and run it in production on the exact same video file, the function fails with :

    


    


    'Memory limit of 256 MiB exceeded with 407 MiB used. Consider
increasing the memory limit, see
https://cloud.google.com/functions/docs/configuring/memory'

    


    


    As a test, I edited the function and changed its allocated memory to 1 GiB. Then I test the function again in production. Now I receive the same error :

    


    


    'Memory limit of 1024 MiB exceeded with 1029 MiB used. Consider
increasing the memory limit, see
https://cloud.google.com/functions/docs/configuring/memory'

    


    


    This is my function code :

    


    const {initializeApp} = require("firebase-admin/app");
const {onCall} = require("firebase-functions/v2/https");
const { getStorage, getDownloadURL } = require('firebase-admin/storage');

initializeApp();

exports.convertVideo = onCall((request) => {
  const ffmpegPath = require('@ffmpeg-installer/ffmpeg').path;
  const ffmpeg = require('fluent-ffmpeg');
  ffmpeg.setFfmpegPath(ffmpegPath);
  const originalLocation = request.data.originalLocation;
  const convertedLocation = request.data.convertedLocation;
  const originalVideoFile = getStorage().bucket().file(originalLocation);
  const newVideoFile = getStorage().bucket().file(convertedLocation);

  return new Promise(async (resolve, reject) => {
    await originalVideoFile.download({destination: '/tmp/original'}).catch(console.error);
    
    ffmpeg('/tmp/original')
      .addOutputOptions('-movflags +frag_keyframe+separate_moof+omit_tfhd_offset+empty_moov')
      .format('mp4')
      .on('error', (err) => {
        console.log(err);
      })
      .pipe(newVideoFile.createWriteStream())
      .on('error', (err) => {
        console.log(err);
      })
      .on('close', async () => {
        fs.unlink('/tmp/original', (err) => {
          if (err) throw err;
        });
        const convertedUrl = await getDownloadURL(newVideoFile);
        resolve([convertedLocation, convertedUrl]);
      });
  });
});


    


    I am sending a test request to the Function emulator using curl :

    


    curl -d '{"data": {"originalLocation": "customer_videos/original_video.mov", "convertedLocation": "customer_videos/converted/original_video.mp4"}}' -H "Content-Type: application/json" http://127.0.0.1:5001/foo/bar/convertVideo


    


    This works correctly. I send the same request to the deployed function, and receive the out of memory error.

    


    curl -d '{"data": {"originalLocation": "customer_videos/original_video.mov", "convertedLocation": "customer_videos/converted/original_video.mp4"}}' -H "Content-Type: application/json" https://convertvideo-foobarbaz-uc.a.run.ap


    


    Can somebody please help me understand why this is happening ? I didn't think I was doing anything too memory intensive, especially since it works correctly using the emulator.

    


  • Revision 4831 : on ajoute ts et mts comme documents vidéos avec des infos supp donc ...

    28 janvier 2011, par kent1 — Log

    on ajoute ts et mts comme documents vidéos avec des infos supp donc Petits ajouts également pour mieux styler les blocs de docs

  • Convert ogg byte array to wav byte array Python

    2 février 2023, par Ramish Rasool

    I want to convert ogg byte array/bytes with Opus codec to wav byte array/bytes without saving to disk. I have downloaded audio from telegram api and it is in byte array format with .ogg extension. I do not want to save it to filesystem to eliminate filesystem io latencey.

    


    Currently what I am doing is after saving the audio file in .ogg format using code the below code using telegram api for reference https://docs.python-telegram-bot.org/en/stable/telegram.file.html#telegram.File.download_to_drive

    


    # listen for audio messages
async def audio(update, context):
    newFile = await context.bot.get_file(update.message.voice.file_id)
    await newFile.download_to_drive(output_path)


    


    I am using the code

    


    subprocess.call(["ffmpeg", "-i", output_path, output_path.replace(".ogg", ".wav"), '-y'], stderr=subprocess.DEVNULL, stdout=subprocess.DEVNULL)


    


    to convert ogg file to wav file. But this is not what I want.

    


    I want the code

    


    async def audio(update, context):
    newFile = await context.bot.get_file(update.message.voice.file_id)
    byte_array = await newFile.download_as_bytearray()


    


    to get byte_array and now I want this byte_array to be converted to wav without saving to disk and without using ffmpeg. Let me know in comments if something is unclear. Thanks !

    


    Note : I have setted up a telegram bot at the backend which listens for audios sent to private chat which I do manually for testing purposes.