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  • Participer à sa traduction

    10 avril 2011

    Vous pouvez nous aider à améliorer les locutions utilisées dans le logiciel ou à traduire celui-ci dans n’importe qu’elle nouvelle langue permettant sa diffusion à de nouvelles communautés linguistiques.
    Pour ce faire, on utilise l’interface de traduction de SPIP où l’ensemble des modules de langue de MediaSPIP sont à disposition. ll vous suffit de vous inscrire sur la liste de discussion des traducteurs pour demander plus d’informations.
    Actuellement MediaSPIP n’est disponible qu’en français et (...)

  • Websites made ​​with MediaSPIP

    2 mai 2011, par

    This page lists some websites based on MediaSPIP.

  • Possibilité de déploiement en ferme

    12 avril 2011, par

    MediaSPIP peut être installé comme une ferme, avec un seul "noyau" hébergé sur un serveur dédié et utilisé par une multitude de sites différents.
    Cela permet, par exemple : de pouvoir partager les frais de mise en œuvre entre plusieurs projets / individus ; de pouvoir déployer rapidement une multitude de sites uniques ; d’éviter d’avoir à mettre l’ensemble des créations dans un fourre-tout numérique comme c’est le cas pour les grandes plate-formes tout public disséminées sur le (...)

Sur d’autres sites (9331)

  • Converting png images series to webm with transparent white background from Daz3d

    25 août 2015, par James

    I’m trying to make a webm video with a transparent background from a Daz3D model.
    My process is export png image series with transparent background from Daz3D, use ffmpeg to convert png series to webm video.
    This was working well in Daz3D 4.6.

    But in Daz3D 4.8 the exported background is black instead of white, so when converted to webm is ok on Chrome as has the transparency, but on Firefox is black and has a halo (as Firefox does not support transparency so displays background).

    So I’m looking for a solution with Daz3D, or tools like ImageMagik.
    I almost got it with ImageMagik,

    convert -alpha extract *.png mask.png
    mogrify -flatten talk*.png
    for /f %x in ('dir /s /b blink*.png') do @composite -compose CopyOpacity mask-0.png %x %x

    But for some reason the final webm has a white background not transparent ...
    Some more info here,

    http://www.daz3d.com/forums/discussion/61237/daz3d-4-8-png-background-is-black

    and here,

    http://www.imagemagick.org/discourse-server/viewtopic.php?f=1&t=28214

    >
    Doh, okay I figured it out. My images were good, but I somehow have two different versions of ffmpeg on my computer and was using the wrong one that doesn’t seem to support transparency.

    Now it is working.

    My only issue is the last shell line,

    for /f %x in (’dir /s /b blink*.png’) do @composite -compose CopyOpacity mask-0.png %x %x

    This only uses mask-0.png, instead of mask-1 for blink01.png, mask-2 for blink02.png etc.

  • Android NDK - ffmpeg header files not found by compiler

    7 septembre 2015, par markt

    I am trying to use the ffmpeg libraries with Android NDK in the experimental plugin.

    I am attempting to compile this example :
    https://github.com/roman10/android-ffmpeg-tutorial/blob/master/android-ffmpeg-tutorial01/jni/tutorial01.c

    My problem is that the header files are not being found by the compiler :

    Error:(13, 32) libavcodec/avcodec.h: No such file or directory

    I added flags to build.grade :

    cppFlags += "-ilibavcodec -ilibavutil -ilibavformat -ilibswscale"
    ldFlags += "-llibavcodec -llibavutil -llibavformat -llibswscale"

    Which seems to keep lint happy, but not the compiler. (Not sure if I have done this right ?)

    I Have added the header files to the /jni folder :
    Project folder structure

    And build.grade looks like this :

    apply plugin: 'com.android.model.application'
    model {
       android {
           compileSdkVersion = 23
           buildToolsVersion = "23.0.1"

           defaultConfig.with {
               applicationId = "roman10.tutorial.android_ffmpeg_tutorial01"
               minSdkVersion.apiLevel = 10
               targetSdkVersion.apiLevel = 23

           }
       }

       compileOptions.with {
           sourceCompatibility = JavaVersion.VERSION_1_7
           targetCompatibility = JavaVersion.VERSION_1_7
       }

       android.buildTypes {
           release {
               minifyEnabled = false
               proguardFiles += file('proguard-rules.pro')
           }
       }


       android.ndk {
           moduleName = "tutorial01"
           ldLibs += ["android","log","jnigraphics","z"]
           cppFlags += "-ilibavcodec -ilibavutil -ilibavformat -ilibswscale"
           ldFlags += "-llibavcodec -llibavutil -llibavformat -llibswscale"
       }
    }

    dependencies {
       compile fileTree(dir: 'libs', include: ['*.jar'])
       compile 'com.android.support:support-v4:23.0.1'
    }

    Thanks.

  • Latency issue with CMU Sphinx 4

    22 septembre 2015, par vijaym

    I have written the speech recognition application using CMU sphinx 4 and followed the details from this link. I have defined the Acoustic,Dictionary and Language Model as below

    configuration.setAcousticModelPath("resource:/edu/cmu/sphinx/models/en-us/en-us");

    configuration.setDictionaryPath("resource:/edu/cmu/sphinx/models/en-us/cmudict-en-us.dict");

    configuration.setLanguageModelPath("resource:/edu/cmu/sphinx/models/en-us/en-us.lm.bin");

    With the above configuration the 20 minutes of wav file takes almost close to 20 minutes to do the transcription.Hence than I tried to pass the user defined config.xml. I did n’t find the configuration manager option to pass the user defined config.xml with the current version of Sphinx4.Then I had written own recognizer by extending the AbstractSpeechRecognizer.java class(It may be useless) and changed few parameters of config.xml and I tried it but still no improvement.

    I have downloaded video and audio across multiple source and converted into WAV file using FFMPEG

    The command is as below

    ffmpeg -i input.mp3 -acodec pcm_s16le -ac 1 -ar 16000 output.wav

    Environment Details :

    Java 8

    Ubuntu 14.04

    RAM 4GB

    I5 Processor

    What I would like to know is, what I am missing here and how to improve the performance ?