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  • 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 (...)

  • 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 (...)

  • Des sites réalisés avec MediaSPIP

    2 mai 2011, par

    Cette page présente quelques-uns des sites fonctionnant sous MediaSPIP.
    Vous pouvez bien entendu ajouter le votre grâce au formulaire en bas de page.

Sur d’autres sites (7352)

  • dnn : add layer pad which is equivalent to tf.pad

    29 juillet 2019, par Guo, Yejun
    dnn : add layer pad which is equivalent to tf.pad

    the reason to add this layer first is that vf_sr uses it in its
    
tensorflow model, and the next plan is to update the python script
    
to convert tf.pad into native model.
    

    Signed-off-by : Guo, Yejun <yejun.guo@intel.com>
    
Signed-off-by : Pedro Arthur <bygrandao@gmail.com>
    • [DH] libavfilter/dnn/Makefile
    • [DH] libavfilter/dnn/dnn_backend_native_layer_pad.c
    • [DH] libavfilter/dnn/dnn_backend_native_layer_pad.h

  • Python OpenCV real-time blurring with saving to output

    10 janvier 2024, par Oleg Novosad

    I have a live video stream via RTSP from my IP camera. I want to blur faces on that stream and output for mobile usage (HLS, H.264, etc). All this should ideally happen in real-time — with the minimum of resources consumed. I plan to deploy this later to some cloud, so the less money I spend on resources the better.

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    Currently I have a working solution like so :

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    • I capture video using OpenCV

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    • I update every frame with Gaussian Blur and save it to some folder

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    • After some amount of frames I create MP4 / AVI / whatever video and make it accessible via HTTP URL

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    • All of it is running on Django for now

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    I know I am doing something wrong, can someone suggest a better solution ?

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  • How to make video loop properly ?

    28 mai 2019, par woopwoop399

    I want to play this video in a loop https://www.nicovideo.jp/watch/sm16617386 . I want to play an mp4 file in such a way, that whenever it gets to some point in the video (let’s say, 30.3 seconds), it will loop back (to for example 5.85 seconds).

    I tried to add this code in ffplay.c , it didn’t work well enough, I can hear the transition. I guess seeking isn’t fast enough, or audio needs to be looped in an independant way somehow.

    static void video_refresh(void *opaque, double *remaining_time)
    
{
    
   (original code here...)
    
    time = get_master_clock(is);
    
    if (isnan(time))
    
        time = (double)is->seek_pos / AV_TIME_BASE;
    
    if (time > jump_when) {
    
        stream_seek(is, (int64_t)(6.0 * AV_TIME_BASE), (int64_t)(0.0 * AV_TIME_BASE), 0);
    
    }
    
}

    My current plan is to just dig into ffmpeg, understand how video and audio decoders work, and savestate/loadstate the decoders.

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