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Autres articles (7)

  • Personnaliser les catégories

    21 juin 2013, par

    Formulaire de création d’une catégorie
    Pour ceux qui connaissent bien SPIP, une catégorie peut être assimilée à une rubrique.
    Dans le cas d’un document de type catégorie, les champs proposés par défaut sont : Texte
    On peut modifier ce formulaire dans la partie :
    Administration > Configuration des masques de formulaire.
    Dans le cas d’un document de type média, les champs non affichés par défaut sont : Descriptif rapide
    Par ailleurs, c’est dans cette partie configuration qu’on peut indiquer le (...)

  • 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 (...)

  • Contribute to a better visual interface

    13 avril 2011

    MediaSPIP is based on a system of themes and templates. Templates define the placement of information on the page, and can be adapted to a wide range of uses. Themes define the overall graphic appearance of the site.
    Anyone can submit a new graphic theme or template and make it available to the MediaSPIP community.

Sur d’autres sites (3467)

  • FFMPEG hardware acceleration in Windows Scheduled Task [closed]

    25 mars 2022, par cfairer

    I'm setting up an unattended Windows 10 machine that will stream video from an RTSP nest cam feed using FFMPEG and Apache.
As it will be unattended and will lose power for six hours a day, I have created a Scheduled Task to run at boot without a user logged to run ffmpeg.

    


    It all works fine with conventional encoders for task started automatically or manually by Windows Task Scheduler :
ffmpeg.exe -i rtsp ://user:pw@nestcam:554 -vf scale=1280:720 -vcodec libx264 -g 20 -r 10 -b:v 1120000 -crf 31 -map 0 -map -0:a -acodec aac -sc_threshold 0 -f hls -hls_time 2 -segment_time 2 -hls_flags delete_segments -hls_list_size 20 C :\webpages\video\stream.m3u8

    


    It works fine when I use hardware acceleration too, but only outside Task Scheduler (e.g. a command prompt) :
ffmpeg.exe -init_hw_device qsv=hw -filter_hw_device hw -i rtsp ://user:pw@nestcam:554 -vf hwupload=extra_hw_frames=64,format=qsv -c:v h264_qsv -g 20 -r 10 -b:v 1120000 -crf 31 -map 0 -map -0:a -acodec aac -sc_threshold 0 -f hls -hls_time 2 -segment_time 2 -hls_flags delete_segments -hls_list_size 20 C :\webpages\video\stream.m3u8

    


    The hardware accelerated version fails when executed by Windows Task Scheduler, whether started automatically or manually. The relevant output is as follows :
[AVHWDeviceContext @ 00000184ba5cc800] Failed to create Direct3D device
Device creation failed : -1313558101.
Failed to set value 'qsv=hw' for option 'init_hw_device' : Unknown error occurred
Error parsing global options : Unknown error occurred

    


    Why can't the ffmpeg task started by Task Scheduler see the hardware-accelerated hardware ? Any ideas on how to resolve this ?

    


    The hardware-accelerated version reduces the load on the CPU by about 75% (ie 50% down to 13%), so it's a significant benefit.

    


    Thanks

    


  • imdct15 : remove the AArch64 assembly

    4 janvier 2017, par Rostislav Pehlivanov
    imdct15 : remove the AArch64 assembly
    

    Prep work for the next commit, which will add a new FFT algorithm
    which makes the iMDCT over 3x faster than it is currently (standalone,
    the FFT is with some framesizes over 10x faster).

    The new FFT algorithm uses the already thouroughly SIMD’d power of two
    FFT which already has SIMD for AArch64, so users of that platform will
    still see an improvement.

    The previous FFT+SIMD was barely 2.5x faster than the C versions on these
    platforms.

    Signed-off-by : Rostislav Pehlivanov <atomnuker@gmail.com>

    • [DH] libavcodec/aarch64/Makefile
    • [DH] libavcodec/aarch64/imdct15_init.c
    • [DH] libavcodec/aarch64/imdct15_neon.S
    • [DH] libavcodec/imdct15.c
    • [DH] libavcodec/imdct15.h
  • How to 'convert' MP3 file to numpy array or list

    30 mai 2021, par Ajayi Olamide

    I'm working on an audio-related project that connects with Django backend via rest api. Part of the front-end requires to display waveforms of associated mp3 files and for this, it in turn requires optimized data of each mp3 file in form of an array, which the front-end (javascript) then processes and converts to a waveform. I can pick the associated mp3 file from backend storage, the problem is converting it into an array which I can serve to the front-end api. I have tried several methods but none seem to be working. I tried this How to read a MP3 audio file into a numpy array / save a numpy array to MP3 ? which leaves my computer hanging until I forced it to restart by holding the power button down. I have a working ffmpeg and so, I have also tried this Trying to convert an mp3 file to a Numpy Array, and ffmpeg just hangs which continues to raise TypeError on np.fromstring(data[data.find("data")&#x2B;4:], np.int16). I can't actually say what the problem is and I really hope someone can help. Thank you in advance !

    &#xA;

    EDIT&#xA;This is the django view for retrieving the waveform data :

    &#xA;

    NB : I've only included useful codes as I'm typing with my mobile phone.

    &#xA;

    def waveform(self, request, ptype, id):&#xA;    project = Project.objects.get(pk=id)&#xA;    audio = project.audio&#xA;&#xA;    mp3_path = os.path.join(cdn_dir, audio) &#xA;    cmd = [&#x27;ffmpeg&#x27;, &#x27;-i&#x27;, mp3_path, &#x27;-f&#x27;, &#x27;wav&#x27;, &#x27;-&#x27;]&#xA;    p = Popen(cmd, stdin=PIPE, stdout=PIPE, stderr=PIPE, creationflags=0x8000000)&#xA;    data = p.communicate()[0]&#xA;    array = np.fromstring(data[data.find("data")&#x2B;4:], np.int16)&#xA;&#xA;    return Response(array)&#xA;

    &#xA;

    The TypeError I get is this :&#xA;TypeError: argument should be integer or bytes-like object, not "str"

    &#xA;