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  • 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 (...)

  • 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 (...)

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  • ffmpeg GPU use cuvid with hwdownload will never finished, Appeared only recently

    28 mai 2020, par tags bt

    ffmpeg :

    



    ffmpeg version N-97331-g10a68cc Copyright (c) 2000-2020 the FFmpeg developers
  built with gcc 7 (Ubuntu 7.3.0-16ubuntu3)
  configuration: --pkg-config-flags=--static --prefix=/usr/local/ffmpeg --bindir=/usr/local/ffmpeg/bin --extra-cflags='-I /usr/local/ffmpeg/include -I /usr/local/cuda/include/' --extra-ldflags='-L /usr/local/ffmpeg/lib -L /usr/local/cuda/lib64/' --extra-libs=-lpthread --enable-cuda --enable-cuda-nvcc --enable-cuvid --enable-libnpp --enable-gpl --enable-libass --enable-libfdk-aac --enable-vaapi --enable-libfreetype --enable-libmp3lame --enable-libopus --enable-libtheora --enable-libvorbis --enable-libvpx --enable-libx264 --enable-libx265 --enable-nonfree --enable-libaom --enable-nvenc


    



    nvidia-msi

    



    +-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.82       Driver Version: 440.82       CUDA Version: 10.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GTX 1080    Off  | 00000000:02:00.0 Off |                  N/A |
|  0%   51C    P8    13W / 200W |     18MiB /  8119MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|    0     23224      C   ffmpeg                                         8MiB |
+-----------------------------------------------------------------------------+



    



    if i use this command :

    



    ffmpeg -re -threads 0 -loglevel debug -hwaccel cuvid -hwaccel_output_format cuda -i 1.mp4 -c:v h264_nvenc -c:a aac -ac 2 -b:a 128k -strict -2 -filter_complex "[0:v]scale_npp=1280:-2" ouzz2t.mp4


    



    it will very fast.

    



    but if i use this command :

    



    ffmpeg -re -threads 0 -loglevel debug -vsync 0 -hwaccel cuvid -hwaccel_output_format cuda -hwaccel_device intel -i 1.mp4 -c:v h264_nvenc -c:a aac -ac 2 -b:a 128k -strict -2 -filter_complex "[0:v]scale_npp=1280:-2:format=yuv420p[tmp],[tmp]hwdownload,format=yuv420" ouzz2t.mp4


    



    it will never finished, one 40MB mp4 will transcode 44 minutes and not finished.

    



    as you see

    



    +-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|    0     23224      C   ffmpeg                                         8MiB |
+-----------------------------------------------------------------------------+


    



    it will only use GPU memory 8mib.

    



    and top will show :
enter image description here

    



    delug log :

    



    [AVHWDeviceContext @ 0x561cfaef92c0] Loaded lib: libcuda.so.1
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuInit
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuDeviceGetCount
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuDeviceGet
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuDeviceGetAttribute
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuDeviceGetName
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuDeviceComputeCapability
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuCtxCreate_v2
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuCtxSetLimit
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuCtxPushCurrent_v2
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuCtxPopCurrent_v2
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuCtxDestroy_v2
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuMemAlloc_v2
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuMemAllocPitch_v2
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuMemsetD8Async
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuMemFree_v2
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuMemcpy2D_v2
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuMemcpy2DAsync_v2
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuGetErrorName
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuGetErrorString
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuCtxGetDevice
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuDevicePrimaryCtxRetain
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuDevicePrimaryCtxRelease
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuDevicePrimaryCtxSetFlags
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuDevicePrimaryCtxGetState
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuDevicePrimaryCtxReset
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuStreamCreate
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuStreamQuery
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuStreamSynchronize
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuStreamDestroy_v2
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuStreamAddCallback
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuEventCreate
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuEventDestroy_v2
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuEventSynchronize
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuEventQuery
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuEventRecord
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuLaunchKernel
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuModuleLoadData
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuModuleUnload
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuModuleGetFunction
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuTexObjectCreate
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuTexObjectDestroy
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuGLGetDevices_v2
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuGraphicsGLRegisterImage
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuGraphicsUnregisterResource
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuGraphicsMapResources
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuGraphicsUnmapResources
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuGraphicsSubResourceGetMappedArray
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuDeviceGetUuid
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuImportExternalMemory
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuDestroyExternalMemory
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuExternalMemoryGetMappedBuffer
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuExternalMemoryGetMappedMipmappedArray
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuMipmappedArrayGetLevel
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuMipmappedArrayDestroy
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuImportExternalSemaphore
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuDestroyExternalSemaphore
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuSignalExternalSemaphoresAsync
[AVHWDeviceContext @ 0x561cfaef92c0] Loaded sym: cuWaitExternalSemaphoresAsync



    



    Stop at Loaded sym : cuWaitExternalSemaphoresAsync, and ffmpeg will always 100% cpu and never finished.

    



    Appeared only recently, last week it work fine, but today it work worse.

    



    somebody know what happen to me ?

    


  • avcodec/encode : restructure the core encoding code

    9 juin 2020, par James Almer
    avcodec/encode : restructure the core encoding code

    This commit follows the same logic as 061a0c14bb, but for the encode API : The
    
new public encoding API will no longer be a wrapper around the old deprecated
    
one, and the internal API used by the encoders now consists of a single
    
receive_packet() callback that pulls frames as required.
    

    amf encoders adapted by James Almer
    
librav1e encoder adapted by James Almer
    
nvidia encoders adapted by James Almer
    
MediaFoundation encoders adapted by James Almer
    
vaapi encoders adapted by Linjie Fu
    
v4l2_m2m encoders adapted by Andriy Gelman
    

    Signed-off-by : James Almer <jamrial@gmail.com>
    • [DH] libavcodec/amfenc.c
    • [DH] libavcodec/amfenc.h
    • [DH] libavcodec/amfenc_h264.c
    • [DH] libavcodec/amfenc_hevc.c
    • [DH] libavcodec/codec.h
    • [DH] libavcodec/encode.c
    • [DH] libavcodec/encode.h
    • [DH] libavcodec/internal.h
    • [DH] libavcodec/librav1e.c
    • [DH] libavcodec/mfenc.c
    • [DH] libavcodec/nvenc.c
    • [DH] libavcodec/nvenc.h
    • [DH] libavcodec/nvenc_h264.c
    • [DH] libavcodec/nvenc_hevc.c
    • [DH] libavcodec/utils.c
    • [DH] libavcodec/v4l2_m2m.c
    • [DH] libavcodec/v4l2_m2m.h
    • [DH] libavcodec/v4l2_m2m_enc.c
    • [DH] libavcodec/vaapi_encode.c
    • [DH] libavcodec/vaapi_encode.h
    • [DH] libavcodec/vaapi_encode_h264.c
    • [DH] libavcodec/vaapi_encode_h265.c
    • [DH] libavcodec/vaapi_encode_mjpeg.c
    • [DH] libavcodec/vaapi_encode_mpeg2.c
    • [DH] libavcodec/vaapi_encode_vp8.c
    • [DH] libavcodec/vaapi_encode_vp9.c
    • [DH] libavcodec/version.h

  • What is the best gpu in the market for video encoding (H.264 and H.265) [closed]

    12 août 2020, par Hamza Ghizaoui

    So, I m using FFMPEG for video encoding.&#xA;I get a stream of BMP images, each with 4000x3000 resoltuion. 20 Image per second (image size circa 35 mbyte).&#xA;I must encode that and stream it in real time. a maximum of 100 ms is allowed between ghe moment of receiving the photo and the moment of displaying that on the browser.

    &#xA;

    I m using FFMPEG with nvidia nvenc hardware accelration .

    &#xA;

    maximum budget is 2000$ for the GPU.

    &#xA;

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