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  • Personnaliser en ajoutant son logo, sa bannière ou son image de fond

    5 septembre 2013, par

    Certains thèmes prennent en compte trois éléments de personnalisation : l’ajout d’un logo ; l’ajout d’une bannière l’ajout d’une image de fond ;

  • Ecrire une actualité

    21 juin 2013, par

    Présentez les changements dans votre MédiaSPIP ou les actualités de vos projets sur votre MédiaSPIP grâce à la rubrique actualités.
    Dans le thème par défaut spipeo de MédiaSPIP, les actualités sont affichées en bas de la page principale sous les éditoriaux.
    Vous pouvez personnaliser le formulaire de création d’une actualité.
    Formulaire de création d’une actualité Dans le cas d’un document de type actualité, les champs proposés par défaut sont : Date de publication ( personnaliser la date de publication ) (...)

  • Mise à jour de la version 0.1 vers 0.2

    24 juin 2013, par

    Explications des différents changements notables lors du passage de la version 0.1 de MediaSPIP à la version 0.3. Quelles sont les nouveautés
    Au niveau des dépendances logicielles Utilisation des dernières versions de FFMpeg (>= v1.2.1) ; Installation des dépendances pour Smush ; Installation de MediaInfo et FFprobe pour la récupération des métadonnées ; On n’utilise plus ffmpeg2theora ; On n’installe plus flvtool2 au profit de flvtool++ ; On n’installe plus ffmpeg-php qui n’est plus maintenu au (...)

Sur d’autres sites (6102)

  • Direct Show Video capture performance

    23 mai 2019, par Barry Andrews

    I originally started out looking for an example of how I can use FFMPEG in c++ builder to create an application to record from usb capture device and playback video because of apparrent poor performance

    I tried Mitov components, Datastead, FFMPEGVCL and winsoft camera which use directshow but their capture performance seemed poor.

    I need to capture 1920x1080 at up to 60fps into a compressed format and play this back later at both normal speed and slow speed.

    What I found was that DirectShow itself has a number of limitations which can be improved by adding things like FFMPEG, but ultimately PC hardware, in particular the HDD and processor limit capture capability.

    1920x1080 60fps is basically the upper end for DirectShow so you need to have best performing hardware in order to achieve this sort of performance @Spektre kindly gave me examples of DirectShow using the API direct which were good for comparison with the purchased components.

    Using this and comparing to the components I found that MITOV has a major issue with regards the larger video sizes and frame rates. Using this 1920x108 30fps and 60fps can be previewed but they have a massive delay between video feed and preview (5 or 6 seconds). The other components performed similar to the API direct method with only minor variations in performance. None were able to capture and record 1920x108 60fps with any sort of compression filter without large frame drops and very jerky preview.

  • libavdevice/gdigrab : fix ffmpeg -devices doesn't show gdigrab

    17 mai 2019, par Jun Zhao
    libavdevice/gdigrab : fix ffmpeg -devices doesn't show gdigrab
    

    missed the category AV_CLASS_CATEGORY_DEVICE_VIDEO_INPUT lead to
    ffmpeg -devices doesn't show gdigrab as a input device

    FIx #7848

    Found-by : dangibson
    Reviewed-by : Paul B Mahol <onemda@gmail.com>
    Signed-off-by : Jun Zhao <barryjzhao@tencent.com>

    • [DH] libavdevice/gdigrab.c
  • How can I get my saved mp4 to exactly match the output of plot.show() ?

    10 mai 2019, par Jimmy

    When I try to save the results of an animation to mp4 using ffmpeg, I am getting a jumbled mess.

    plt.show() shows exactly what I want it to show in the animation. However, when I save it using ffmpeg, the result is very different from what plt.show() returns. I have tried various arguments for fps etc. but nothing has helped.

    %matplotlib
    import pandas as pd
    import matplotlib as mpl ## uncomment this if you are running this on a Mac
    #mpl.use('TkAgg')         ## and want to use blit=True
    import matplotlib.pyplot as plt
    import matplotlib.animation as animation
    import numpy as np
    import csv

    people = ('','Jim', 'Dan')
    plt.rcdefaults()
    fig, ax = plt.subplots()
    y_pos = np.arange(len(people))

    ax.set_xlim(0,10)
    ax.set_yticks(y_pos)
    ax.set_yticklabels(people)
    ax.invert_yaxis()
    ax.set_xlabel('Skill')
    titleList=['Basketball','Hockey','Baseball']
    df=[[0,5,7],[0,4,9],[0,2,6]]
    def animate(i):
      # Example data
       while i&lt;3:
           ax.set_yticks(y_pos)
           ax.set_yticklabels(people)
           ax.set_xlabel(titleList[i])
           performance=df[i]

           title = ax.text(0.5,0.95,str(titleList[i]), bbox={'facecolor':'w', 'alpha':0.5, 'pad':5},transform=ax.transAxes, ha="center")

           rects = ax.barh(y_pos, performance, align='center',
                   color='blue', ecolor='None')
           return [rect for rect in rects] + [title]


    ani = animation.FuncAnimation(fig,animate, frames=3, blit=True
                               ,interval=2000,repeat=False)

    plt.rcParams['animation.ffmpeg_path'] = 'C:\\ffmpeg\\bin\\ffmpeg.exe'
    Writer = animation.writers['ffmpeg']
    ani.save('test.mp4')
    plt.show()

    The result is a very fast video where all the data gets written over (similar to the plt.show() results when blit=False).