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  • L’agrémenter visuellement

    10 avril 2011

    MediaSPIP est basé sur un système de thèmes et de squelettes. Les squelettes définissent le placement des informations dans la page, définissant un usage spécifique de la plateforme, et les thèmes l’habillage graphique général.
    Chacun peut proposer un nouveau thème graphique ou un squelette et le mettre à disposition de la communauté.

  • Ajouter des informations spécifiques aux utilisateurs et autres modifications de comportement liées aux auteurs

    12 avril 2011, par

    La manière la plus simple d’ajouter des informations aux auteurs est d’installer le plugin Inscription3. Il permet également de modifier certains comportements liés aux utilisateurs (référez-vous à sa documentation pour plus d’informations).
    Il est également possible d’ajouter des champs aux auteurs en installant les plugins champs extras 2 et Interface pour champs extras.

  • 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 (...)

Sur d’autres sites (11917)

  • How to detect silence in a pyAV AudioFrame ?

    29 janvier 2024, par Sachin Dole

    I want to process streaming audio (coming in from a person speaking on the peer of a webRTC peer connection) to detect when the person is done talking. I have got the audio track and access to individual frames. I see that each frame can be converted to an nd_array using Frame.to_ndarray. I can also see values in the ndarray changing depending on what the person is speaking, what pitch, what volume etc. Now, I want to detect silence on the stream. My question is what is in the ndarray and how can I make sense of the data ?

    


            while True:
            try:
                frame:AudioFrame = await track.recv()
                frame_nd_array = frame.to_ndarray() 


    


    Where can I learn what is in the frame_nd_array ?

    


  • How to batch auto-generate videos according to audio length

    16 septembre 2020, par yociba

    I have hundreds of folders of Spanish short stories, with each folder having dozens of individual .MP3 files for each dialogue spoken. Along with the .MP3 files, lies in the folder, a JSON file of the format ["folder1-dialogue-1", "folder1-dialogue-2",...].

    


    I want to generate images, each containing the text values of the JSON file, like folder1-dialogue-1 and generate videos combining that image with its corresponding audio (folder1-dialogue-1.mp3), and then merge all the videos in the folder into one - folder1.mp4

    


    How do I go about doing this ?

    


    P.S I'm not straight up asking for code, but just advice as to how I go about doing this.

    


  • vulkan : fix sw_frame_deps counter

    20 novembre 2024, par Lynne
    vulkan : fix sw_frame_deps counter

    The code used as a basis was the buffer dependency code, where the
    
counter was incremented after each buffer, but for the sw_frame dep
    
API, we only support adding individual frames at a time.
    • [DH] libavutil/vulkan.c

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