Recherche avancée

Médias (0)

Mot : - Tags -/masques

Aucun média correspondant à vos critères n’est disponible sur le site.

Autres articles (18)

  • 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 (...)

  • Ajouter notes et légendes aux images

    7 février 2011, par

    Pour pouvoir ajouter notes et légendes aux images, la première étape est d’installer le plugin "Légendes".
    Une fois le plugin activé, vous pouvez le configurer dans l’espace de configuration afin de modifier les droits de création / modification et de suppression des notes. Par défaut seuls les administrateurs du site peuvent ajouter des notes aux images.
    Modification lors de l’ajout d’un média
    Lors de l’ajout d’un média de type "image" un nouveau bouton apparait au dessus de la prévisualisation (...)

  • Gestion générale des documents

    13 mai 2011, par

    MédiaSPIP ne modifie jamais le document original mis en ligne.
    Pour chaque document mis en ligne il effectue deux opérations successives : la création d’une version supplémentaire qui peut être facilement consultée en ligne tout en laissant l’original téléchargeable dans le cas où le document original ne peut être lu dans un navigateur Internet ; la récupération des métadonnées du document original pour illustrer textuellement le fichier ;
    Les tableaux ci-dessous expliquent ce que peut faire MédiaSPIP (...)

Sur d’autres sites (4071)

  • 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;