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Autres articles (104)

  • Les vidéos

    21 avril 2011, par

    Comme les documents de type "audio", Mediaspip affiche dans la mesure du possible les vidéos grâce à la balise html5 .
    Un des inconvénients de cette balise est qu’elle n’est pas reconnue correctement par certains navigateurs (Internet Explorer pour ne pas le nommer) et que chaque navigateur ne gère en natif que certains formats de vidéos.
    Son avantage principal quant à lui est de bénéficier de la prise en charge native de vidéos dans les navigateur et donc de se passer de l’utilisation de Flash et (...)

  • Submit bugs and patches

    13 avril 2011

    Unfortunately a software is never perfect.
    If you think you have found a bug, report it using our ticket system. Please to help us to fix it by providing the following information : the browser you are using, including the exact version as precise an explanation as possible of the problem if possible, the steps taken resulting in the problem a link to the site / page in question
    If you think you have solved the bug, fill in a ticket and attach to it a corrective patch.
    You may also (...)

  • Encoding and processing into web-friendly formats

    13 avril 2011, par

    MediaSPIP automatically converts uploaded files to internet-compatible formats.
    Video files are encoded in MP4, Ogv and WebM (supported by HTML5) and MP4 (supported by Flash).
    Audio files are encoded in MP3 and Ogg (supported by HTML5) and MP3 (supported by Flash).
    Where possible, text is analyzed in order to retrieve the data needed for search engine detection, and then exported as a series of image files.
    All uploaded files are stored online in their original format, so you can (...)

Sur d’autres sites (7423)

  • FFmpeg java.lang.UnsatisfiedLinkError dlopen failed : library "libavutil.so" not found in Vivo model device

    9 février 2024, par sejn

    Facing a lot of crashes in the Android Vivo devices with the above error. Can I restrict this to the Vivo models in Android.

    


    I'm using the implementation 'com.arthenica:mobile-ffmpeg-full:4.4'

    


    Fatal Exception: java.lang.UnsatisfiedLinkError dlopen failed: library "libavutil.so" not found

init {
    try{
        System.loadLibrary("avutil")
        System.loadLibrary("avcodec")
        System.loadLibrary("avformat")
        System.loadLibrary("swscale")
        System.loadLibrary("avfilter")
    }
    catch (e:Exception){
        Log.i("error","${e.message}")
    }
}


    


    In app/build.gradle

    


    


    ndk 
abiFilters 'armeabi-v7a','arm64-v8a','x86','x86_64'

    


    


    Note : If I migrate to the latest version ffmpeg-kit-full:6.0-2

    


    Clarifications :

    


      

    1. Shall I need to add this below in the code as well if I use the FFmpeg-kit

      2. 


    2. If I did not need to use means, does it make any issues in the app ?.(i.e) if I removed

      3. 


    3. Shall I need to add any additional loadlibrary in the init ?

      4. 


    4. Is there any simple fix for the above error for Oppo alone without migrating ?

      5. 


    5. Shall I need to add these architectures in ndk of my app ?

      6. 


    


    


    arm-v7a, arm-v7a-neon, arm64-v8a, x86 and x86_64 architectures

    


    


     init {
        try{
            System.loadLibrary("avutil")
            System.loadLibrary("avcodec")
            System.loadLibrary("avformat")
            System.loadLibrary("swscale")
            System.loadLibrary("avfilter")
        }
        catch (e:Exception){
            Log.i("error","${e.message}")
        }
    }


    


  • Model the loss of video codec

    10 janvier 2024, par Monaco

    I want to use a neural network to model the error loss after video encoding. The modeling process is as follows :
enter image description here
I use ffmpeg to encode and decode video frames. Since this process is not implemented using tensors in PyTorch and cannot compute gradients, I have to separately implement a neural network in PyTorch to enable gradient backpropagation. However, it turns out that the neural network cannot effectively learn the video encoding.

    


    I want to know if there are currently any implementations of video encoders or decoders that support backpropagation of gradients. I don't necessarily need to update the parameters of the encoder/decoder, but I want it to support gradient backpropagation so that I can use it for various tasks related to deep learning.

    


  • avutil : introduce an Immersive Audio Model and Formats API

    25 novembre 2023, par James Almer
    avutil : introduce an Immersive Audio Model and Formats API

    Signed-off-by : James Almer <jamrial@gmail.com>
    • [DH] doc/APIchanges
    • [DH] libavutil/Makefile
    • [DH] libavutil/iamf.c
    • [DH] libavutil/iamf.h
    • [DH] libavutil/version.h

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