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Autres articles (50)
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Personnaliser les catégories
21 juin 2013, parFormulaire de création d’une catégorie
Pour ceux qui connaissent bien SPIP, une catégorie peut être assimilée à une rubrique.
Dans le cas d’un document de type catégorie, les champs proposés par défaut sont : Texte
On peut modifier ce formulaire dans la partie :
Administration > Configuration des masques de formulaire.
Dans le cas d’un document de type média, les champs non affichés par défaut sont : Descriptif rapide
Par ailleurs, c’est dans cette partie configuration qu’on peut indiquer le (...) -
Publier sur MédiaSpip
13 juin 2013Puis-je poster des contenus à partir d’une tablette Ipad ?
Oui, si votre Médiaspip installé est à la version 0.2 ou supérieure. Contacter au besoin l’administrateur de votre MédiaSpip pour le savoir -
Ajouter notes et légendes aux images
7 février 2011, parPour pouvoir ajouter notes et légendes aux images, la première étape est d’installer le plugin "Légendes".
Une fois le plugin activé, vous pouvez le configurer dans l’espace de configuration afin de modifier les droits de création / modification et de suppression des notes. Par défaut seuls les administrateurs du site peuvent ajouter des notes aux images.
Modification lors de l’ajout d’un média
Lors de l’ajout d’un média de type "image" un nouveau bouton apparait au dessus de la prévisualisation (...)
Sur d’autres sites (5405)
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How to build a daemon to encode video files on S3 ?
4 avril 2013, par Yuval CohenI am interested in running a daemon to go over user uploaded video files and encode them in an optimal format (and add some watermarks).
I was considering services such as Zencoder, Encoding.com, Amazon's encoding service but some lack overlaying capabilities and some are just too expensive for our (big) volumes.
I want to build a daemon that encodes videos that are located on S3 once users upload them.
The solution I thought of would be Python Heroku servers using Celery for a task queue to keep track of the encoded files and ffmpeg to do the actual work. However, I ran into troubles compiling ffmpeg for Heroku (with libass support, so the basic ffmpeg bins aren't enough).
What approach/technology stack would you consider for this mini-project ?
Thanks !
Yuval -
In my django app, celery task converts uploaded video w/ ffmpeg, but converted video won't save to s3 ?
29 janvier 2013, par GetItDoneI use Heroku to host my website, and Amazon s3 to store my static and media files. I have a celery task that converts the video file to flv, but the flv doesn't store anywhere. There isn't any error, just there is no file uploaded to my s3 bucket. How can I force the file to save to my s3 bucket after the conversion ? I'm still pretty new web development in general, and I have been stuck trying to get my video conversion working properly for weeks. To be honest, I'm not even sure that I'm doing the right thing with my task. Here is the code in my celery task :
@task(name='celeryfiles.tasks.convert_flv')
def convert_flv(video_id):
video = VideoUpload.objects.get(pk=video_id)
filename = video.video_upload
sourcefile = "%s%s" % (settings.MEDIA_URL, filename)
vidfilename = "%s.flv" % video.id
targetfile = "%svideos/flv/%s" % (settings.MEDIA_URL, vidfilename)
ffmpeg = "ffmpeg -i %s -ar 22050 -f flv -s 320x240 %s" % (sourcefile, targetfile)
#The next lines are code that I couldn't get to work in place of the line above, and are left commented out.
#I am open to suggestions or alternatives for this also.
#ffmpeg = "ffmpeg -i %s -acodec libmp3lame -ar 22050 -f flv -s 320x240 %s" % (sourcefile, targetfile)
#ffmpeg = "ffmpeg -i %s -acodec mp3 -ar 22050 -f flv -s 320x240 %s" % (sourcefile, targetfile)
try:
ffmpegresult = commands.getoutput(ffmpeg)
print "---------------FFMPEG---------------"
print "FFMPEGRESULT: %s" % ffmpegresult
except Exception as e:
ffmpegresult = None
print("Failed to convert video file %s to %s" % (sourcefile, targetfile))
print(traceback.format_exc())
video.flvfilename = vidfilename
video.save()My view :
def upload_video(request):
if request.method == 'POST':
form = VideoUploadForm(request.POST, request.FILES)
if form.is_valid():
video_upload=form.save()
video_id=video_upload.id
video_conversion = convert_flv.delay(video_id)
return HttpResponseRedirect('/current_classes/')
else:
...Any advice, insight, or ideas in general would be greatly appreciated. Obviously I am missing something, but I can't figure out what. I have been stuck with different aspects of getting my video conversion to work with ffmpeg using a celery task for weeks. Thanks in advance.
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What are the gotchas of using statically linked libraries in serverless platforms such as Google Cloud Functions ?
5 septembre 2017, par DzhLibraries such as ffmpeg-static upload statically linked binaries onto container.
I wonder what are the drawbacks of using this approach ?
Does the library size counts against your memory use (it’s billed by GCloud) ?
Does it slow down the container ? Perhaps some future-proofing issues ?
Edit : Found something of a related (I wanted to setup OpenCV) on AWS blog. It doesn’t explain drawbacks, just shows how to do it exactly.