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Autres articles (14)

  • 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 (...)

  • Organiser par catégorie

    17 mai 2013, par

    Dans MédiaSPIP, une rubrique a 2 noms : catégorie et rubrique.
    Les différents documents stockés dans MédiaSPIP peuvent être rangés dans différentes catégories. On peut créer une catégorie en cliquant sur "publier une catégorie" dans le menu publier en haut à droite ( après authentification ). Une catégorie peut être rangée dans une autre catégorie aussi ce qui fait qu’on peut construire une arborescence de catégories.
    Lors de la publication prochaine d’un document, la nouvelle catégorie créée sera proposée (...)

  • Keeping control of your media in your hands

    13 avril 2011, par

    The vocabulary used on this site and around MediaSPIP in general, aims to avoid reference to Web 2.0 and the companies that profit from media-sharing.
    While using MediaSPIP, you are invited to avoid using words like "Brand", "Cloud" and "Market".
    MediaSPIP is designed to facilitate the sharing of creative media online, while allowing authors to retain complete control of their work.
    MediaSPIP aims to be accessible to as many people as possible and development is based on expanding the (...)

Sur d’autres sites (5490)

  • Only using 1 core when I converting video to tiff sequnce file

    20 août 2019, par gsk

    My workspace spec :

    • CPU : Ryzen 1950x
    • GPU : GTX 1080Ti
    • RAM : 128GB
    • SSD : 512GB samsung 960pro
    • OS : window10

    When I convert to tiff sequence file from my video(3min/mp4) CPU only used 1 core with 28 frame per sec.
    If I delete -pix_fmt rgb48le option can used more core and speed up(50 frame per sec).
    but, I need changing color space for making dcp...

    I already tried -threads option (0,1,2,16,32,64...) but still used 1 core.
    and found about GPU acceleration from other forum but I think tiff codec can’t use CUDA.

    ./ffmpeg -i test.mp4 -q:v 1 -aspect 1.85 -s 1988:1080 -an -pix_fmt rgb48le -src_range 1 -dst_range 1 -r 24 \test%010d.tiff

    tiff codec don’t support multi core ?
    if don’t support multi core how can I increase speed for encoding.
    thank you.

  • FFmpeg on android is crashing in ff_h2645_extract_rbsp function

    6 décembre 2019, par TheWindLaugh

    I have used ffmpeg decode in my decode2 function, it just like this :

    AVPacket pkt;
    
av_init_packet(&pkt);
    
pkt.data = (uint8*)vd+16;
    
pkt.size = vl-16;
    
m_is_decoding = true;
    
avcodec_send_packet(m_cctx, &pkt);
    
int ret = avcodec_receive_frame(m_cctx, m_cfrm);

    Everything works great up until the avcodec_decode_video2 call :

    Build fingerprint: 'HUAWEI/VTR-AL00/HWVTR:9/HUAWEIVTR-AL00/9.1.0.201C00:user/release-keys'
    
Revision: '0'
    
cpuAbi/cpuAbi2: 'arm64-v8a#armeabi-v7a#armeabi'
    
pid: 5829, tid: 6106, name: .myapp.online  >>> com.myapp.online <<<
    
signal 11 (SIGSEGV), code 2 (SEGV_ACCERR), fault addr 0xcc180000
    

    
backtrace:
    
     #00 pc 0064c098  /data/app/com.myapp.online-r3eLwyIHdUEbHPM-MUYw1g==/lib/arm/libapp.so (ff_h2645_extract_rbsp+52)
    
     #01 pc 0064c580  /data/app/com.myapp.online-r3eLwyIHdUEbHPM-MUYw1g==/lib/arm/libapp.so (ff_h2645_packet_split+592)
    
     #02 pc 0037c9e0  /data/app/com.myapp.online-r3eLwyIHdUEbHPM-MUYw1g==/lib/arm/libapp.so
    
     #03 pc 004e6d18  /data/app/com.myapp.online-r3eLwyIHdUEbHPM-MUYw1g==/lib/arm/libapp.so (avcodec_decode_video2+380)
    
     #04 pc 004e76a4  /data/app/com.myapp.online-r3eLwyIHdUEbHPM-MUYw1g==/lib/arm/libapp.so
    
     #05 pc 004eb344  /data/app/com.myapp.online-r3eLwyIHdUEbHPM-MUYw1g==/lib/arm/libapp.so (avcodec_send_packet+308)
    
     #06 pc 001df578  /data/app/com.myapp.online-r3eLwyIHdUEbHPM-MUYw1g==/lib/arm/libapp.so (_bio_binder_codec_video_::decode2(void*, yuv_r*, void const*, int)+1384)
    
     #07 pc 002e66b8  /data/app/com.myapp.online-r3eLwyIHdUEbHPM-MUYw1g==/lib/arm/libapp.so (hm_video_decode_yuv+244)
    
     #08 pc 0003f598  /data/app/com.myapp.online-r3eLwyIHdUEbHPM-MUYw1g==/lib/arm/libapp_yunguan.so (Device::DecodeVideo()+336)
    
     #09 pc 00037324  /data/app/com.myapp.online-r3eLwyIHdUEbHPM-MUYw1g==/lib/arm/libapp_yunguan.so (boost::detail::thread_data, boost::_bi::list1 > > >::run()+32)
    
     #10 pc 00046455  /data/app/com.myapp.online-r3eLwyIHdUEbHPM-MUYw1g==/lib/arm/libapp_yunguan.so
    
     #11 pc 00065ac7  /system/lib/libc.so (__pthread_start(void*)+22)
    
     #12 pc 0001e9ad  /system/lib/libc.so (__start_thread+32)

  • How do I avoid out of memory when using ffmpeg-python ?

    26 janvier 2020, par Takada Shigeomi

    When executing the following code, process ends up running out of memory.
    How do I avoid out of memory ?

    import ffmpeg
    

    
path_to_file = 'my_video.mp4'
    

    
source = ffmpeg.input(path_to_file)
    

    
# Memory usage goes up without reproducibility during processing.
    
out, _ = (
    
    source.video # Video file of about 100MB for 20 minutes
    
    .output('pipe:', format='rawvideo', pix_fmt='rgb24')
    
    .run(capture_stdout=True)
    
)
    

    
# The following error message is displayed.
    
MemoryError
    
av_interleaved_write_frame(): Broken pipe
    
Error writing trailer of pipe:: Broken pipe
    
frame= 5722 fps=367 q=-0.0 Lsize=15448652kB time=00:03:10.73 bitrate=663519.9kbits/s speed=12.2x
    
video:15449400kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: unknown
    
Conversion failed!

    My computer spec :

    • OS : Ubuntu 18.04
    • CPU : Core i3-9100F
    • Memory : 16GB
    • SSD : 256GB
    • ffmpeg version : 4.2.2
    • ffmpeg-python version : 0.2.0
    • Python version : 3.7.3

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