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Les autorisations surchargées par les plugins
27 avril 2010, parMediaspip core
autoriser_auteur_modifier() afin que les visiteurs soient capables de modifier leurs informations sur la page d’auteurs -
HTML5 audio and video support
13 avril 2011, parMediaSPIP 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 (...) -
Support audio et vidéo HTML5
10 avril 2011MediaSPIP 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 (...)
Sur d’autres sites (9937)
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Speedup matplotlib animation to video file
20 mai 2022, par gaggioOn Raspbian (Raspberry Pi 2), the following minimal example stripped from my script correctly produces an mp4 file :



import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation

def anim_lift(x, y):

 #set up the figure
 fig = plt.figure(figsize=(15, 9))

 def animate(i):
 # update plot
 pointplot.set_data(x[i], y[i])

 return pointplot

 # First frame
 ax0 = plt.plot(x,y)
 pointplot, = ax0.plot(x[0], y[0], 'or')

 anim = animation.FuncAnimation(fig, animate, repeat = False,
 frames=range(1,len(x)), 
 interval=200,
 blit=True, repeat_delay=1000)

 anim.save('out.mp4')
 plt.close(fig)

# Number of frames
nframes = 200

# Generate data
x = np.linspace(0, 100, num=nframes)
y = np.random.random_sample(np.size(x))

anim_lift(x, y)




Now, the file is produced with good quality and pretty small file size, but it takes 15 minutes to produce a 170 frames movie, which is not acceptable for my application. i'm looking for a significant speedup, video file size increase is not a problem.



I believe the bottleneck in the video production is in the temporary saving of the frames in png format. During processing I can see the png files apprearing in my working directory, with the CPU load at 25% only.



Please suggest a solution, that might also be based on a different package rather than simply
matplotlib.animation
, likeOpenCV
(which is anyway already imported in my project) ormoviepy
.


Versions in use :



- 

- python 2.7.3
- matplotlib 1.1.1rc2
- ffmpeg 0.8.17-6:0.8.17-1+rpi1








-
Speedup matplotlib animation to video file
9 juillet 2015, par gaggioOn Raspbian (Raspberry Pi 2), the following minimal example stripped from my script correctly produces an mp4 file :
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation
def anim_lift(x, y):
#set up the figure
fig = plt.figure(figsize=(15, 9))
def animate(i):
# update plot
pointplot.set_data(x[i], y[i])
return pointplot
# First frame
ax0 = plt.plot(x,y)
pointplot, = ax0.plot(x[0], y[0], 'or')
anim = animation.FuncAnimation(fig, animate, repeat = False,
frames=range(1,len(x)),
interval=200,
blit=True, repeat_delay=1000)
anim.save('out.mp4')
plt.close(fig)
# Number of frames
nframes = 200
# Generate data
x = np.linspace(0, 100, num=nframes)
y = np.random.random_sample(np.size(x))
anim_lift(x, y)Now, the file is produced with good quality and pretty small file size, but it takes 15 minutes to produce a 170 frames movie, which is not acceptable for my application. i’m looking for a significant speedup, video file size increase is not a problem.
I believe the bottleneck in the video production is in the temporary saving of the frames in png format. During processing I can see the png files apprearing in my working directory, with the CPU load at 25% only.
Please suggest a solution, that might also be based on a different package rather than simply
matplotlib.animation
, likeOpenCV
(which is anyway already imported in my project) ormoviepy
.Versions in use :
- python 2.7.3
- matplotlib 1.1.1rc2
- ffmpeg 0.8.17-6:0.8.17-1+rpi1
-
Stream real-time (video+audio) via WebRTC (TCP) with chromakey && webm, best practices - how ? [on hold]
18 octobre 2018, par Kirill KPlease tell us about the best practics in your opinion for the case described below.
Are there any hardware solutions for this case ?I want to get the real-time stream from the ip camera, overlay a chromakey, transcode into the necessary codecs (VP8 + opus), and distribute stream via webrtc over tcp to many users with some kind of authentication, for example, via a dynamic token.
The delay from real time should be minimal.
The solution should be stable (do not fall after 1 hour or 24 hours).Now I have decided on such a solution, but the time costs are too high (delay from real-time strem), maybe there you will offer be a more elegant solution :
- IP Camera (h264 + aac)
- FFmpeg (transcoding to VP8\OPUS + chromakey)
- FFserver (pack to rtp (for webcallserver))
- WebCallServer (WebRTC)
I tried the following solutions :
- Flussonic - missing WebRTC via TCP
- Wowza (written in java) - crashes, support could not say the exact reasons, talked for more than 2 months, tested on different servers in different Data Centres