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Autres articles (26)
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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 (...) -
Contribute to documentation
13 avril 2011Documentation is vital to the development of improved technical capabilities.
MediaSPIP welcomes documentation by users as well as developers - including : critique of existing features and functions articles contributed by developers, administrators, content producers and editors screenshots to illustrate the above translations of existing documentation into other languages
To contribute, register to the project users’ mailing (...) -
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 (...)
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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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PipedInputStream / PipedOutputStream, ImageIO and ffmpeg
19 avril 2015, par jdevelopI have the following code in Scala :
val pos = new PipedOutputStream()
val pis = new PipedInputStream(pos)
Future {
LOG.trace("Start rendering")
generateFrames(videoRenderParams.length) {
img ⇒ ImageIO.write(img, "PNG", pos)
}
pos.flush()
IOUtils.closeQuietly(pos)
LOG.trace("Finished rendering")
} onComplete {
case Success(_) ⇒
LOG.trace("Complete successfully")
case Failure(err) ⇒
LOG.error("Can't render stuff", err)
IOUtils.closeQuietly(pis)
IOUtils.closeQuietly(pos)
}
val prc = (ffmpegCli #< pis).!(logger)the Future simply writes the generated images one by one to the OutputStream. Now the ffmpeg process reads the input images from stdin and converts them to MP4 file.
That works pretty well, but for some reason sometimes I’m getting the following stacktraces :
I/O error Pipe closed for process: <input stream="stream" />
java.io.IOException: Pipe closed
at java.io.PipedInputStream.checkStateForReceive(PipedInputStream.java:260)
at java.io.PipedInputStream.receive(PipedInputStream.java:226)
at java.io.PipedOutputStream.write(PipedOutputStream.java:149)
at scala.sys.process.BasicIO$.loop$1(BasicIO.scala:236)
at scala.sys.process.BasicIO$.transferFullyImpl(BasicIO.scala:242)
at scala.sys.process.BasicIO$.transferFully(BasicIO.scala:223)
at scala.sys.process.ProcessImpl$PipeThread.runloop(ProcessImpl.scala:159)
at scala.sys.process.ProcessImpl$PipeSource.run(ProcessImpl.scala:179)At the same time I’m getting the following error from another stream :
javax.imageio.IIOException: I/O error writing PNG file!
at com.sun.imageio.plugins.png.PNGImageWriter.write(PNGImageWriter.java:1168)
at javax.imageio.ImageWriter.write(ImageWriter.java:615)
at javax.imageio.ImageIO.doWrite(ImageIO.java:1612)
at javax.imageio.ImageIO.write(ImageIO.java:1578)
atSo it seems that the streams were broken somewhere in between, so ffmpeg can not read the data, and ImageIO can not write the data.
What is even more interesting - the problem is reproducible only on certain Linux server (Amazon). It works flawlessly on other Linux boxes. So I wonder if somebody could point me out to the possible causes of this error.
What I’ve tried so far :
- use Oracle JDK 8 and OpenJDK
- use different versions of FFMPEG
Nothing worked by the moment.
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AWS : Best way to generate a thumbnail for every frame of a s3 uploaded video
4 janvier 2018, par danielfrancaI need to process a video file, transcode it and generate a thumbnail for every frame.
It should happen every time there’s a new video on a specific AWS bucket.
I found out that AWS Lambda should be the best service for that
However, it is not working as expected and I’ll explain why
I’ve created a simple Python2.7 file using FFVideo
It seems that this library doesn’t support Python3.It is a nice abstraction on top of ffmpeg
To deploy the package I had run
lld
on the FFVideo shared object, and then copied everything to my project directory, as described in their documentation.
Zipped it and upload to AWS LambdaYet it doesn’t work, I keep getting errors as if the /usr/lib64/libstdc++ is missing, even after copied it to the projecct dir, also tried /usr/lib64 and /lib64
Then as a second thought I wonder if just running
ffmpeg
wouldn’t be easier...
So I just copied ffmpeg to the project dir and did a simple Python script to call it.Missing shared objects, ok,
lld
again and copied everything to the directory.Then AWS Lambda seems to be completely broken, I can’t save it anymore and it just says "Fix errors before saving"
But no error message, nothingI even have attempted to write inline a simple code, but now AWS Lambda don’t even open the online editor.
I also tried to remove all the shared objects I have added, returning to the original state, but still same generic error.
Same thing if I just create a new lambda function with same old code.Doesn’t matter what I do it never even enable the Save button anymore.
I thought it might be just some AWS unstability, but it been a while.I’ve looked to a similar project using Node
and it doesn’t seem to include anything except ffmpegMy other idea is to use SQS to trigger a python script somewhere else to create the thumbnails
Any idea how is the best approach for that ?