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Rennes Emotion Map 2010-11
19 octobre 2011, par
Mis à jour : Juillet 2013
Langue : français
Type : Texte
Autres articles (50)
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La file d’attente de SPIPmotion
28 novembre 2010, parUne file d’attente stockée dans la base de donnée
Lors de son installation, SPIPmotion crée une nouvelle table dans la base de donnée intitulée spip_spipmotion_attentes.
Cette nouvelle table est constituée des champs suivants : id_spipmotion_attente, l’identifiant numérique unique de la tâche à traiter ; id_document, l’identifiant numérique du document original à encoder ; id_objet l’identifiant unique de l’objet auquel le document encodé devra être attaché automatiquement ; objet, le type d’objet auquel (...) -
Other interesting software
13 avril 2011, parWe don’t claim to be the only ones doing what we do ... and especially not to assert claims to be the best either ... What we do, we just try to do it well and getting better ...
The following list represents softwares that tend to be more or less as MediaSPIP or that MediaSPIP tries more or less to do the same, whatever ...
We don’t know them, we didn’t try them, but you can take a peek.
Videopress
Website : http://videopress.com/
License : GNU/GPL v2
Source code : (...) -
Personnaliser en ajoutant son logo, sa bannière ou son image de fond
5 septembre 2013, parCertains 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 ;
Sur d’autres sites (5455)
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swresample/resample : do not increase phase_count on exact_rational
17 juin 2016, par Muhammad Faizswresample/resample : do not increase phase_count on exact_rational
high phase_count is only useful when dst_incr_mod is non zero
in other word, it is only useful on soft compensationon init, it will build filter with low phase_count
but when soft compensation is enabled, rebuild filter
with high phase_countthis approach saves lots of memory
Reviewed-by : Michael Niedermayer <michael@niedermayer.cc>
Signed-off-by : Muhammad Faiz <mfcc64@gmail.com> -
Is there an efficient way to use ffmpeg to create a huge quantity of small video file, cut from a larger one ?
9 mars 2024, par Giuliano OliveriI'm trying to cut video files into smaller chunks. (each one being one word said in the video, so they're not all of equal size)


I've tried a lot of different approaches to try to be as efficient as possible, but I can't get the runtime to be under 2/3rd of the original video length. That's an issue because I'm trying to process 400+ hours of video.


Is there a more efficient way to do this ? Or am I doomed to run this for weeks ?


Here is the command for my best attempt so far


ffmpeg -hwaccel cuda -hwaccel_output_format cuda -ss start_timestamp -t to_timestamp -i file_name -vf "fps=30,scale_cuda=1280:720" -c:v h264_nvenc -y output_file



Note that the machine running the code has a 4090
This command is then executed via python, which gives it the right timestamps and file paths for each smaller clip in a for loop


I think it's wasting a lot of time calling a new process each time, however I haven't been able to get better results with a split filter ; but here's the ffmpeg-python code for that attempt :


Creation of the stream :


inp = (
 ffmpeg
 .input(file_name, hwaccel="cuda", hwaccel_output_format="cuda")
 .filter("fps",fps=30)
 .filter('scale_cuda', '1280','720')
 .filter_multi_output('split')
)



Which then gets called in a for loop


(
 ffmpeg
 .filter(inp, 'trim', start=row[1]['start'], end=row[1]['end'])
 .filter('setpts', 'PTS-STARTPTS')
 .output(output_file,vcodec='h264_nvenc')
 .run()
)



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Is there an efficient way to use ffmpeg to perform a large quantity of cuts from a single file ?
16 mars 2024, par Giuliano OliveriI'm trying to cut video files into smaller chunks. (each one being one word said in the video, so they're not all of equal size)


I've tried a lot of different approaches to try to be as efficient as possible, but I can't get the runtime to be under 2/3rd of the original video length. That's an issue because I'm trying to process 400+ hours of video.


Is there a more efficient way to do this ? Or am I doomed to run this for weeks ?


Here is the command for my best attempt so far


ffmpeg -hwaccel cuda -hwaccel_output_format cuda -ss start_timestamp -t to_timestamp -i file_name -vf "fps=30,scale_cuda=1280:720" -c:v h264_nvenc -y output_file



Note that the machine running the code has a 4090
This command is then executed via python, which gives it the right timestamps and file paths for each smaller clip in a for loop


I think it's wasting a lot of time calling a new process each time, however I haven't been able to get better results with a split filter ; but here's the ffmpeg-python code for that attempt :


Creation of the stream :


inp = (
 ffmpeg
 .input(file_name, hwaccel="cuda", hwaccel_output_format="cuda")
 .filter("fps",fps=30)
 .filter('scale_cuda', '1280','720')
 .filter_multi_output('split')
)



Which then gets called in a for loop


(
 ffmpeg
 .filter(inp, 'trim', start=row[1]['start'], end=row[1]['end'])
 .filter('setpts', 'PTS-STARTPTS')
 .output(output_file,vcodec='h264_nvenc')
 .run()
)