
Recherche avancée
Autres articles (47)
-
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 -
Supporting all media types
13 avril 2011, parUnlike most software and media-sharing platforms, MediaSPIP aims to manage as many different media types as possible. The following are just a few examples from an ever-expanding list of supported formats : images : png, gif, jpg, bmp and more audio : MP3, Ogg, Wav and more video : AVI, MP4, OGV, mpg, mov, wmv and more text, code and other data : OpenOffice, Microsoft Office (Word, PowerPoint, Excel), web (html, CSS), LaTeX, Google Earth and (...)
-
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 (8413)
-
Celery to process task and modify the model fields
15 juillet 2015, par RobinI would like to convert video into mp4 using
ffmpeg
andcelery
for the asynchronous task. When user uploads a video, it will be for theoriginal_video
and save it. After that I want celery to convert it into a different version for themp4_720
field. However I am confused on how to apply that logic using celery.app.models.py :
class Video(models.Model):
title = models.CharField(max_length=75)
pubdate = models.DateTimeField(default=timezone.now)
original_video = models.FileField(upload_to=get_upload_file_name)
mp4_720 = models.FileField(upload_to=get_upload_file_name, blank=True, null=True)
converted = models.BooleanField(default=False)app.views.py :
def upload_video(request):
if request.POST:
form = VideoForm(request.POST, request.FILES)
if form.is_valid():
video = form.save(commit=False)
video.save()
// Celery to convert the video
convert_video.delay(video)
return HttpResponseRedirect('/')
else:
form = VideoForm()
return render(request, 'upload_video.html', {
'form':form
})app.tasks.py :
@app.task
def convert_video(video):
// Convert the original video into required format and save it in the mp4_720 field using the following command:
//subprocess.call('ffmpeg -i (path of the original_video) (video for mp4_720)')
// Change the converted boolean field to True
// SaveBasically my question is how to save the converted video in mp4_720. Your help and guidance will be very much appreciated. Thank you.
** update **
What I want that method to do is first convert the video.original_video and then save the converted video in the video.mp4_720 field. If all has been done correctly, change the video.converted to True. How do I define the method to do so ?
-
Revision ac50b75e50 : Use balanced model for intra prediction mode coding This commit replaces the pr
20 juin 2015, par Jingning HanChanged Paths :
Modify /vp9/common/vp9_entropymode.c
Modify /vp9/common/vp9_entropymode.h
Modify /vp9/decoder/vp9_decodeframe.c
Modify /vp9/decoder/vp9_decodemv.c
Modify /vp9/encoder/vp9_bitstream.c
Modify /vp9/encoder/vp9_encodeframe.c
Modify /vp9/encoder/vp9_pickmode.c
Modify /vp9/encoder/vp9_rd.c
Modify /vp9/encoder/vp9_rdopt.c
Use balanced model for intra prediction mode codingThis commit replaces the previous table based intra mode model
coding with a more balanced entropy coding system. It reduces the
decoder lookup table size by 1K bytes. The key frame compression
performance is about even on average. There are a few points where
the compression performance is improved by over 5%. Most test
points are fairly close to the lookup table approach.Change-Id : I47154276c0a6a22ae87de8845bc2d494681b95f6
-
Revision 948c6d882e : Enable transform block partition entropy coding Select the probability model fo
27 avril 2015, par Jingning HanChanged Paths :
Modify /vp9/common/vp9_alloccommon.c
Modify /vp9/common/vp9_blockd.h
Modify /vp9/common/vp9_entropymode.c
Modify /vp9/common/vp9_entropymode.h
Modify /vp9/common/vp9_onyxc_int.h
Modify /vp9/common/vp9_thread_common.c
Modify /vp9/decoder/vp9_decodeframe.c
Modify /vp9/decoder/vp9_decodemv.c
Modify /vp9/encoder/vp9_bitstream.c
Modify /vp9/encoder/vp9_encodeframe.c
Modify /vp9/encoder/vp9_rdopt.c
Modify /vp9/encoder/vp9_tokenize.c
Enable transform block partition entropy codingSelect the probability model for transform block partition coding
conditioned on the neighbor transform block sizes.Change-Id : Ib701296e59009bad97dbd21d8dcd58bc5e552f39