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  • Support audio et vidéo HTML5

    10 avril 2011

    MediaSPIP utilise les balises HTML5 video et audio pour la lecture de documents multimedia en profitant des dernières innovations du W3C supportées par les navigateurs modernes.
    Pour les navigateurs plus anciens, le lecteur flash Flowplayer est utilisé.
    Le lecteur HTML5 utilisé a été spécifiquement créé pour MediaSPIP : il est complètement modifiable graphiquement pour correspondre à un thème choisi.
    Ces technologies permettent de distribuer vidéo et son à la fois sur des ordinateurs conventionnels (...)

  • 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 (...)

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  • Animated line chart with pandas, matplotlib and ffmpeg

    10 avril 2020, par Mark K

    In producing an animated line chart, I have below data and codes.

    



    But when the chart produced, it shows no line. What did I do wrong ?

    



    Thank you.

    



    import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.animation as animation

title = 'Heroin Overdoses'

data = {'Year' : ["1999","2000","2001","2002","2003","2004","2005","2006","2007","2008","2009","2010","2011","2012","2013","2014","2015","2016"], 
'Heroin Overdoses' : [280,443,413,486,475,148,197,170,448,103,137,160,483,356,352,300,466,278]}
overdose = pd.DataFrame(data)

Writer = animation.writers['ffmpeg']
writer = Writer(fps=20, metadata=dict(artist='Me'), bitrate=1800)

fig = plt.figure(figsize=(10,6))
plt.xlim(1999, 2016)
plt.ylim(np.min(overdose)[0], np.max(overdose)[0])
plt.xlabel('Year',fontsize=20)
plt.ylabel(title,fontsize=20)
plt.title('Heroin Overdoses per Year',fontsize=20)

def animate(i):
    data = overdose.iloc[:int(i+1)] #select data range
    p = sns.lineplot(x=data.index, y=data[title], data=data, color="r")
    p.tick_params(labelsize=17)
    plt.setp(p.lines,linewidth=7)

ani = matplotlib.animation.FuncAnimation(fig, animate, frames=17, repeat=True)

ani.save('C:\\folder\\line chart.mp4', writer=writer)


    


  • Revision 876c72a093 : AVX2 Convolve Optimization Two convolve functions were optimized for AVX2 : 1. v

    17 janvier 2014, par levytamar82

    Changed Paths :
     Modify /vp9/common/vp9_rtcd_defs.sh


     Modify /vp9/common/x86/vp9_asm_stubs.c


     Add /vp9/common/x86/vp9_subpixel_8t_intrin_avx2.c


     Modify /vp9/vp9_common.mk



    AVX2 Convolve Optimization

    Two convolve functions were optimized for AVX2 :
    1. vp9_filter_block1d16_h8
    2. vp9_filter_block1d16_v8
    vp9_filter_block1d16_v8 was optimized for AVX2 by reducing the number of
    loop strides by half, two strides were processed in parallel.
    vp9_filter_block1d16_v8 was also optimized in the same way also some of the
    loads were being done outside of the loop and by that preventing redundant
    loads.
    This Optimization gives 43% function level gain and 1.3% user level gain.
    Now can be compiled in Windows

    Change-Id : I2714124cfb0c14a77d7a0ce126a20db92ffbf92c

  • Creating personalized video from user submitted pictures and data

    18 décembre 2016, par Rajat Singhal

    Can someone guide me towards what technology to use to create personalized video from user submitted pictures and data.. The process has to be automated, as in server must be able to create a downloadable video from photos and text submitted by user..

    So the process will probably be like one video will be created by a hired artist, with placeholders where the user submitted pictures and text will fit in. Now with user submitted data video can be created and downloaded from the website..

    An example can be the videos created by facebook now-a-days on your birthday or year end. They consist some of your photos, some text and have a common video theme.. You can view one here http://newsroom.fb.com/news/2016/12/facebook-2016-year-in-review/

    One way I’ve found is to write the video code in html5 and then record it with phantomjs and ffmpeg.. http://mindthecode.com/recording-a-website-with-phantomjs-and-ffmpeg/

    But it seems a bit unnatural way of doing it.. And also I think not a lot of good artists are out there who can create the video theme in html5..