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Médias (17)
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Matmos - Action at a Distance
15 septembre 2011, par
Mis à jour : Septembre 2011
Langue : English
Type : Audio
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DJ Dolores - Oslodum 2004 (includes (cc) sample of “Oslodum” by Gilberto Gil)
15 septembre 2011, par
Mis à jour : Septembre 2011
Langue : English
Type : Audio
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Danger Mouse & Jemini - What U Sittin’ On ? (starring Cee Lo and Tha Alkaholiks)
15 septembre 2011, par
Mis à jour : Septembre 2011
Langue : English
Type : Audio
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Cornelius - Wataridori 2
15 septembre 2011, par
Mis à jour : Septembre 2011
Langue : English
Type : Audio
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The Rapture - Sister Saviour (Blackstrobe Remix)
15 septembre 2011, par
Mis à jour : Septembre 2011
Langue : English
Type : Audio
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Chuck D with Fine Arts Militia - No Meaning No
15 septembre 2011, par
Mis à jour : Septembre 2011
Langue : English
Type : Audio
Autres articles (96)
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MediaSPIP 0.1 Beta version
25 avril 2011, parMediaSPIP 0.1 beta is the first version of MediaSPIP proclaimed as "usable".
The zip file provided here only contains the sources of MediaSPIP in its standalone version.
To get a working installation, you must manually install all-software dependencies on the server.
If you want to use this archive for an installation in "farm mode", you will also need to proceed to other manual (...) -
Multilang : améliorer l’interface pour les blocs multilingues
18 février 2011, parMultilang est un plugin supplémentaire qui n’est pas activé par défaut lors de l’initialisation de MediaSPIP.
Après son activation, une préconfiguration est mise en place automatiquement par MediaSPIP init permettant à la nouvelle fonctionnalité d’être automatiquement opérationnelle. Il n’est donc pas obligatoire de passer par une étape de configuration pour cela. -
Les tâches Cron régulières de la ferme
1er décembre 2010, parLa gestion de la ferme passe par l’exécution à intervalle régulier de plusieurs tâches répétitives dites Cron.
Le super Cron (gestion_mutu_super_cron)
Cette tâche, planifiée chaque minute, a pour simple effet d’appeler le Cron de l’ensemble des instances de la mutualisation régulièrement. Couplée avec un Cron système sur le site central de la mutualisation, cela permet de simplement générer des visites régulières sur les différents sites et éviter que les tâches des sites peu visités soient trop (...)
Sur d’autres sites (11419)
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Live streaming HLS via ffmpeg, How to force client to start playing from the beginning ? From 1st segment
27 janvier 2021, par vedeojunkyIs there a way, maybe via an ffmpeg option or flag, to force the client player to always start the playlist from the beginning when live streaming rather than the real time mid-stream ?



Say the user comes in 1mn after the stream has started, rather than starting to watch at 1mn the player would start at the beginning of the video so minute zero.



Here is my ffmpeg command :



ffmpeg -f "screen capture" -s 1280x720 -r 30 -i :0.0+nomouse -f alsa -ac 2 -i pulse -async 30 -vcodec libx264 -pix_fmt yuv420p -acodec libfdk_aac -ar 44100 -b:a 64k -threads 0 -s 640x360 -f hls -g 1 -hls_time 1 -hls_list_size 1 -hls_allow_cache 0 /hls/#{@stream_name}/index.m3u8




Thanks !


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Python-FFMPEG Corruption Problems
11 juillet 2023, par Gabriel Ruben GuzmanI'm repurposing some python code to generate gifs/mp4s showcasing nba player movements dot form. (With the 'frames' used in the gifs being generated by matplotlib).


The repo comes with two different functions for generating the gifs, watch_play and animate_play. Both of which use python command line functionalities to run ffmpeg and generate the mp4s.
I've been able to use the watch_play succesfully, bot every time I try using animate_play, which according to the documention is meant to be significantly faster than watch play, I run into the error showcased here.(I printed the cmd string being passed into the pipe, in the hopes it would make debugging easier)


I've tried generating gifs/mp4s of various size and added a decent bit of code to lessen the volume of data being processed. (I'm essentially repurposing the code just to generate clips, so I've been able to remove a lot of the pbp/tracking data logs to speed up the run time) But no matter what I've done, gotten some variation of the screenshotted error.


pipe: : corrupt input packet in stream 0
[rawvideo @ 0x55ccc0e2bb80] Invalid buffer size, packet size 691200 < expected frame_size 921600
Error while decoding stream #0:0 : Invalid argument


The code for animate_play


def animate_play(self, game_time=None, length=None, highlight_player=None,
 commentary=True, show_spacing=None):
 """
 Method for animating plays in game.
 Outputs video file of play in {cwd}/temp.
 Individual frames are streamed directly to ffmpeg without writing them
 to the disk, which is a great speed improvement over watch_play

 Args:
 game_time (int): time in game to start video
 (seconds into the game).
 Currently game_time can also be an tuple of length two
 with (starting_frame, ending_frame)if you want to
 watch a play using frames instead of game time.
 length (int): length of play to watch (seconds)
 highlight_player (str): If not None, video will highlight
 the circle of the inputed player for easy tracking.
 commentary (bool): Whether to include play-by-play commentary in
 the animation
 show_spacing (str) in ['home', 'away']: show convex hull
 spacing of home or away team.
 If None, does not show spacing.

 Returns: an instance of self, and outputs video file of play
 """
 if type(game_time) == tuple:
 starting_frame = game_time[0]
 ending_frame = game_time[1]
 else:
 game_time= self.start +(self.quarter*720)
 end_time= self.end +(self.quarter*720)
 length = end_time-game_time
 # Get starting and ending frame from requested 
 # game_time and length
 print('hit')
 print(len(self.moments))
 print(game_time)
 print(end_time)
 print(length)
 print(game_time+length)
 
 print(self.moments.game_time.min())
 print(self.moments.game_time.max())

 sys.exit()
 starting_frame = self.moments[self.moments.game_time.round() ==
 game_time].index.values[0]
 ending_frame = self.moments[self.moments.game_time.round() ==
 game_time + length].index.values[0]

 # Make video of each frame
 filename = "./temp/{game_time}.mp4".format(game_time=game_time)
 if commentary:
 size = (960, 960)
 else:
 size = (480, 480)
 cmdstring = ('ffmpeg',
 '-y', '-r', '20', # fps
 '-s', '%dx%d' % size, # size of image string
 '-pix_fmt', 'argb', # Stream argb data from matplotlib
 '-f', 'rawvideo','-i', '-',
 '-vcodec', 'libx264', filename)
 #print(pipe)
 #print(cmdstring)
 
 

 # Stream plots to pipe
 pipe = Popen(cmdstring, stdin=PIPE)
 print(cmdstring)
 for frame in range(starting_frame, ending_frame):
 print(frame)
 self.plot_frame(frame, highlight_player=highlight_player,
 commentary=commentary, show_spacing=show_spacing,
 pipe=pipe)
 print(cmdstring)
 pipe.stdin.close()
 pipe.wait()
 return self



The code for watch play


def watch_play(self, game_time=None, length=None, highlight_player=None,
 commentary=True, show_spacing=None):

 """
 DEPRECIATED. See animate_play() for similar (fastere) method

 Method for viewing plays in game.
 Outputs video file of play in {cwd}/temp

 Args:
 game_time (int): time in game to start video
 (seconds into the game).
 Currently game_time can also be an tuple of length
 two with (starting_frame, ending_frame) if you want
 to watch a play using frames instead of game time.
 length (int): length of play to watch (seconds)
 highlight_player (str): If not None, video will highlight
 the circle of the inputed player for easy tracking.
 commentary (bool): Whether to include play-by-play
 commentary underneath video
 show_spacing (str in ['home', 'away']): show convex hull
 of home or away team.
 if None, does not display any convex hull

 Returns: an instance of self, and outputs video file of play
 """
 print('hit this point ')
 warnings.warn(("watch_play is extremely slow. "
 "Use animate_play for similar functionality, "
 "but greater efficiency"))

 if type(game_time) == tuple:
 starting_frame = game_time[0]
 ending_frame = game_time[1]
 else:
 # Get starting and ending frame from requested game_time and length
 game_time= self.start +(self.quarter*720)
 end_time= self.end +(self.quarter*720)
 length = end_time-game_time


 starting_frame = self.moments[self.moments.game_time.round() ==
 game_time].index.values[0]
 ending_frame = self.moments[self.moments.game_time.round() ==
 game_time + length].index.values[0]
 #print(self.moments.head(2))
 #print(starting_frame)
 #print(ending_frame)
 print(len(self.moments))
 # Make video of each frame
 title = str(starting_frame)+'-'+str(ending_frame)
 for frame in range(starting_frame, ending_frame):
 print(frame)
 self.plot_frame(frame, highlight_player=highlight_player,
 commentary=commentary, show_spacing=show_spacing)
 command = ('ffmpeg -framerate 20 -start_number {starting_frame} '
 '-i %d.png -c:v libx264 -r 30 -pix_fmt yuv420p -vf '
 '"scale=trunc(iw/2)*2:trunc(ih/2)*2" {title}'
 '.mp4').format(starting_frame=starting_frame,title=title)
 os.chdir('temp')
 os.system(command)
 os.chdir('..')

 # Delete images
 for file in os.listdir('./temp'):
 if os.path.splitext(file)[1] == '.png':
 os.remove('./temp/{file}'.format(file=file))

 return self'



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For converting video to frames, should I do client or server side processing ?
23 mars 2024, par Tomas MarsonHere is the thing, I have a Nodejs API that serves one video at a time when client request it.


The client (made in react) receives the video, which has no more than 15 seconds, watch it and decide if he wants to approve or deny it.
If he approves the video, it must be displayed in a sort of frames carousel, with one frame per second, so there is no more than 15 images/frames.


So the question is, should I do the conversion video-to-frames on client once he approves the video or should I do it on server-side and then request each frame (or streaming all frames with one request if possible) ?


Now, I'm doing the conversion on server with ffmpeg, but it seems tricky to send all the frames when the client already have them inside the video.