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Rennes Emotion Map 2010-11
19 octobre 2011, par
Mis à jour : Juillet 2013
Langue : français
Type : Texte
Autres articles (67)
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Participer à sa traduction
10 avril 2011Vous pouvez nous aider à améliorer les locutions utilisées dans le logiciel ou à traduire celui-ci dans n’importe qu’elle nouvelle langue permettant sa diffusion à de nouvelles communautés linguistiques.
Pour ce faire, on utilise l’interface de traduction de SPIP où l’ensemble des modules de langue de MediaSPIP sont à disposition. ll vous suffit de vous inscrire sur la liste de discussion des traducteurs pour demander plus d’informations.
Actuellement MediaSPIP n’est disponible qu’en français et (...) -
Websites made with MediaSPIP
2 mai 2011, parThis page lists some websites based on MediaSPIP.
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Possibilité de déploiement en ferme
12 avril 2011, parMediaSPIP peut être installé comme une ferme, avec un seul "noyau" hébergé sur un serveur dédié et utilisé par une multitude de sites différents.
Cela permet, par exemple : de pouvoir partager les frais de mise en œuvre entre plusieurs projets / individus ; de pouvoir déployer rapidement une multitude de sites uniques ; d’éviter d’avoir à mettre l’ensemble des créations dans un fourre-tout numérique comme c’est le cas pour les grandes plate-formes tout public disséminées sur le (...)
Sur d’autres sites (10742)
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AWS Lambda execution time for FFMPEG transcoding
4 janvier 2023, par FlamingMoeI'm using AWS Lambda for converting files from WEBM to MP4


I'm using ffmpeg version 4.3.1-static https://johnvansickle.com/ffmpeg/ (I have done the following tests also with the ffmpeg in serverless AWS ffmpeg layer (that includes de 4.1.3), but results are even worse (about 25% slower)


I'm using Node 10x as container.


WEBM size Time to convert. Memory Lambda. Memory used (as shown in log)

80Mb ~44s 3008 410
40Mb ~44s 3008 375

80Mb ~70s 1024 321
40Mb ~70s 1024 279



All videos are 80s length. So as far as I can see, it does not matter the size of the WEBM, if the length of the video is the same, it takes the same to convert. So ffmpeg takes more time if the video length is higher, not if the file size is higher ... curious ;-)


But in the other hand, I'm confused with Lambda memory. I know memory and CPU comes together in Lambda ... the more memory you choose, the more CPU is assigned.


But...


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- Why ffmpeg just take about 300/400Mb if it has more to run ?
- How can I tell ffmpeg to use more memory ?
- Is there any option to accelerate the process in Lambda ?








Btw, In all tests, all ffmpeg are the same, and


cpu-used paramenter)


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- I added to ffmpeg parameters cpu-used=100, and it does not matter at all if I put cpu-used=5 ... times are the same, so I guess that parameter is useless (i don't know why)




threads parameter)


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- Also I did some tests with "threads" parameters, but it's useless also.




I know it's not a good comparison, but same files takes about 5 seconds to be converted in a simple dedicated server (8 vCores and 8GB RAM in OVH Centos VPS).


Btw, Amazon Elastic Transcoder is not an option :
a) it's extremely more expensive
b) it has just his profiles to convert, and my ffmpeg commands are very complex (watermarks, effects, etc ...)


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How to create a DASH VOD for Chromecast with ffmpeg ?
19 novembre 2020, par Oleg YablokovI need to serve long videos ( 2 hours) from a web server to mobile clients and the clients should be able to play the videos via
Chromecast
. I have chosenmpeg-dash
for this purpose : video encoder ish.264
(level 4.1), audio isaac
(although I've tried diffrent ones).

I've tried
ffmpeg
,MP4Box
and some other tools to generate videos ; most of the time I succeeded playing them on VLC or on a mobile client (locally), but not with Chromecast.

I've tried Amazon's
Elastic Transcoder
and it worked, but it gave me one big file whereas I need many small segments.

CORS are set.


Chromecast remote debugging didn't help much.


Do you know how to do this ?


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why ffmpeg starts many processes
29 octobre 2020, par jamesI have a doubt about the functioning of the ffmpeg program, I noticed that after starting the program on a 4gb memory raspberry pi4 many processes are started, is it normal or is there something wrong with my program ? I remember that on an amazon ec2 instance by controlling with htop only one process was created


Code I used


from subprocess import Popen

ffmpeg_process = Popen(["ffmpeg", "-hide_banner", "-loglevel", "panic", "-y", "-i", "./video/video1.mp4",
 "-vcodec", "h264", "-acodec", "mp3", "./video/video2.mp4"],
 start_new_session=True)

ffmpeg_process.wait()