Recherche avancée

Sur d’autres sites (6800)

• avformat/movenc : add support for Immersive Audio Model and Formats in ISOBMFF

  15 février 2024, par James Almer

  avformat/movenc : add support for Immersive Audio Model and Formats in ISOBMFF
  Signed-off-by : James Almer <jamrial@gmail.com>
  

  • [DH] libavformat/movenc.c
  • [DH] libavformat/movenc.h

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

  


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

  


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

  


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

  


  


  


  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 :

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.