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Autres articles (94)

  • HTML5 audio and video support

    13 avril 2011, par

    MediaSPIP uses HTML5 video and audio tags to play multimedia files, taking advantage of the latest W3C innovations supported by modern browsers.
    The MediaSPIP player used has been created specifically for MediaSPIP and can be easily adapted to fit in with a specific theme.
    For older browsers the Flowplayer flash fallback is used.
    MediaSPIP allows for media playback on major mobile platforms with the above (...)

  • De l’upload à la vidéo finale [version standalone]

    31 janvier 2010, par

    Le chemin d’un document audio ou vidéo dans SPIPMotion est divisé en trois étapes distinctes.
    Upload et récupération d’informations de la vidéo source
    Dans un premier temps, il est nécessaire de créer un article SPIP et de lui joindre le document vidéo "source".
    Au moment où ce document est joint à l’article, deux actions supplémentaires au comportement normal sont exécutées : La récupération des informations techniques des flux audio et video du fichier ; La génération d’une vignette : extraction d’une (...)

  • Librairies et binaires spécifiques au traitement vidéo et sonore

    31 janvier 2010, par

    Les logiciels et librairies suivantes sont utilisées par SPIPmotion d’une manière ou d’une autre.
    Binaires obligatoires FFMpeg : encodeur principal, permet de transcoder presque tous les types de fichiers vidéo et sonores dans les formats lisibles sur Internet. CF ce tutoriel pour son installation ; Oggz-tools : outils d’inspection de fichiers ogg ; Mediainfo : récupération d’informations depuis la plupart des formats vidéos et sonores ;
    Binaires complémentaires et facultatifs flvtool2 : (...)

Sur d’autres sites (4829)

  • ffmpeg with drawtext filenames of diffrent files within a -i concat filelist.txt

    10 juillet 2016, par halanson

    with the following script i am able to concatenate multiple video files within a textfile to a single video.

    now i want to have the individual names of each source video file displayed in the output video.

    here is a example of my source videoList.txt file with filename and filepath

    # videoList.txt
    file 'C:\video_0020.mp4'
    file 'C:\video_0040.mp4'
    file '..'

    and the windows batch file :

    @ECHO off
    SETLOCAL

    SET ffmpeg=C:\ffmpeg\bin
    SET inFile=-f concat -i C:\videoList.txt
    SET outFile=C:\output.mov

    SET codec=-r 24 -vcodec mjpeg -q:v 6
    REM videoFilter/filterComplex
    SET filterComplex=drawtext=fontfile='C\:\\Windows\\Fonts\\arial.ttf': text='%%{filenameOfEachVideo}'

    REM bring it all together
    SET commandline=%ffmpeg%\ffmpeg.exe %inFile% -filter_complex "%filterComplex%" %codec% %outFile%

    REM execute command
    %commandline%
  • Streaming MJPEG video over RTSP without re-encoding using ffmpeg in Ubuntu

    5 août 2023, par user8109

    I have a video file encoded in MJPEG format stored as .avi file. I want to stream this video without re-encoding using ffmpeg tool from an Ubuntu machine to a remote server over RTSP protocol. I could achieve this for videos encoded in H.264 format and H.265 format using the below command.

    


    ffmpeg -re -i "$input_file" -c copy -f rtsp "$output_url"


    


    But, I am getting errors when I am streaming MJPEG video. One alternative approach could be to extract individual JPEG frames and stream that over the network using the following command.

    


    ffmpeg -re -i "$input_file" -f image2pipe -vcodec mjpeg -pix_fmt yuvj420p - | ffmpeg -i - -c:v copy -an -f rtsp "$output_url"


    


    But I am getting errors here also. Any solution is fine for me.

    


  • Greed is Good ; Greed Works

    25 novembre 2010, par Multimedia Mike — VP8

    Greed, for lack of a better word, is good ; Greed works. Well, most of the time. Maybe.

    Picking Prediction Modes
    VP8 uses one of 4 prediction modes to predict a 16x16 luma block or 8x8 chroma block before processing it (for luma, a block can also be broken into 16 4x4 blocks for individual prediction using even more modes).

    So, how to pick the best predictor mode ? I had no idea when I started writing my VP8 encoder. I did not read any literature on the matter ; I just sat down and thought of a brute-force approach. According to the comments in my code :

    // naive, greedy algorithm :
    //   residual = source - predictor
    //   mean = mean(residual)
    //   residual -= mean
    //   find the max diff between the mean and the residual
    // the thinking is that, post-prediction, the best block will
    // be comprised of similar samples
    

    After removing the predictor from the macroblock, individual 4x4 subblocks are put through a forward DCT and quantized. Optimal compression in this scenario results when all samples are the same since only the DC coefficient will be non-zero. Failing that, when the input samples are at least similar to each other, few of the AC coefficients will be non-zero, which helps compression. When the samples are all over the scale, there aren’t a whole lot of non-zero coefficients unless you crank up the quantizer, which results in poor quality in the reconstructed subblocks.

    Thus, my goal was to pick a prediction mode that, when applied to the input block, resulted in a residual in which each element would feature the least deviation from the mean of the residual (relative to other prediction choices).

    Greedy Approach
    I realized that this algorithm falls into the broad general category of "greedy" algorithms— one that makes locally optimal decisions at each stage. There are most likely smarter algorithms. But this one was good enough for making an encoder that just barely works.

    Compression Results
    I checked the total file compression size on my usual 640x360 Big Buck Bunny logo image while forcing prediction modes vs. using my greedy prediction picking algorithm. In this very simple test, DC-only actually resulted in slightly better compression than the greedy algorithm (which says nothing about overall quality).

    prediction mode quantizer index = 0 (minimum) quantizer index = 10
    greedy 286260 98028
    DC 280593 95378
    vertical 297206 105316
    horizontal 295357 104185
    TrueMotion 311660 113480

    As another data point, in both quantizer cases, my greedy algorithm selected a healthy mix of prediction modes :

    • quantizer index 0 : DC = 521, VERT = 151, HORIZ = 183, TM = 65
    • quantizer index 10 : DC = 486, VERT = 167, HORIZ = 190, TM = 77

    Size vs. Quality
    Again, note that this ad-hoc test only measures one property (a highly objective one)— compression size. It did not account for quality which is a far more controversial topic that I have yet to wade into.