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MediaSPIP 0.1 Beta version
25 avril 2011, parMediaSPIP 0.1 beta is the first version of MediaSPIP proclaimed as "usable".
The zip file provided here only contains the sources of MediaSPIP in its standalone version.
To get a working installation, you must manually install all-software dependencies on the server.
If you want to use this archive for an installation in "farm mode", you will also need to proceed to other manual (...) -
Amélioration de la version de base
13 septembre 2013Jolie sélection multiple
Le plugin Chosen permet d’améliorer l’ergonomie des champs de sélection multiple. Voir les deux images suivantes pour comparer.
Il suffit pour cela d’activer le plugin Chosen (Configuration générale du site > Gestion des plugins), puis de configurer le plugin (Les squelettes > Chosen) en activant l’utilisation de Chosen dans le site public et en spécifiant les éléments de formulaires à améliorer, par exemple select[multiple] pour les listes à sélection multiple (...) -
Mise à jour de la version 0.1 vers 0.2
24 juin 2013, parExplications des différents changements notables lors du passage de la version 0.1 de MediaSPIP à la version 0.3. Quelles sont les nouveautés
Au niveau des dépendances logicielles Utilisation des dernières versions de FFMpeg (>= v1.2.1) ; Installation des dépendances pour Smush ; Installation de MediaInfo et FFprobe pour la récupération des métadonnées ; On n’utilise plus ffmpeg2theora ; On n’installe plus flvtool2 au profit de flvtool++ ; On n’installe plus ffmpeg-php qui n’est plus maintenu au (...)
Sur d’autres sites (11128)
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Python Lambda function and ffmpeg command with stdout from jpg to ts file
28 juillet 2021, par SflaggI have a AWS Lambda Python function setup to process jpg and convert it to a ts file.


I followed these instructions https://aws.amazon.com/blogs/media/processing-user-generated-content-using-aws-lambda-and-ffmpeg/ but changed the command from vfr to cfr conversion to a jpg to ts conversion.


This is the command I am using


ffmpeg_cmd = "/opt/bin/ffmpeg -r 30000/1001 -loop 1 -i \"" + s3_source_signed_url + "\" -f lavfi -i anullsrc=channel_layout=stereo:sample_rate=48000 -t 30 -vcodec libx264 -crf 23 -s 1920x1080 -r 30000/1001 -g 150 -pix_fmt yuv420p -acodec aac -b:a 96k -ar 48000 -"


Everything else is basically the same from the AWS article besides having s3 triggers in my Lambda look for jpeg and jpg suffixes.


But this results in 0 byte ts file.


I have a hunch that I need to modify the command that has a seekable output format (e.g. mpegts) when writing to stdout ; currently my command is likely not working for stdout and that is why I get an empty ts file. But I am having trouble formatting the command correctly. Any help with this would be greatly appreciated !


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AWS EC2 and OpenCV with UDP consumer
22 juillet 2021, par NoobZikI have two EC2


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- A That grabs the video feed from Amazon Kinesis Video to send it into via UDP to B
- B the consumer which it will grab the UDP feed from the A






While debugging my opencv not grabbing the UDP feed, I suspect something is wrong with ffpmeg, so I am going to make sure that ffplay can read packets sent from A.


Now when I try to read udp packets with
ffplay {adress-ip-with-port}
I have the following error :

Could not initialize SDL - No available video device
(Did you set the DISPLAY variable?)



How do I fix this one since there is no display on EC2.


Also if it can help, this is my code for the consumer part


Create your views here.
from django.http import HttpResponse
from django.template import loader
from django.shortcuts import render
# from .models import Vehicule
import cv2
import threading
from django.views.decorators import gzip
from django.http import StreamingHttpResponse


@gzip.gzip_page
def webcam(request):
 try:
 cam = VideoCamera()
 return StreamingHttpResponse(gen(cam), content_type="multipart/x-mixed-replace;boundary=frame")
 except:
 pass
 return render(request, 'vebcam.html')

#capture video
class VideoCamera(object):
 def __init__(self):
 self.video = cv2.VideoCapture('udp://172.31.57.243:55055', cv2.CAP_FFMPEG)
 (self.grabbed, self.frame) = self.video.read()
 threading.Thread(target=self.update, args=()).start()

 def __del__(self):
 self.video.release()

 def get_frame(self):
 image = self.frame
 _, jpeg = cv2.imencode('.jpg', image)
 return jpeg.tobytes()

 def update(self):
 while True:
 (self.grabbed, self.frame) = self.video.read()

def gen(camera):
 while True:
 frame = camera.get_frame()
 yield (b'--frame\r\n'b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')



It runs fine on local but not on EC2


This is the log that led me to check ffplay


Traceback (most recent call last):
 File "/usr/lib/python3.8/wsgiref/handlers.py", line 138, in run
 self.finish_response()
 File "/usr/lib/python3.8/wsgiref/handlers.py", line 183, in finish_response
 for data in self.result:
 File "/home/ubuntu/.local/lib/python3.8/site-packages/django/utils/text.py", line 304, in compress_sequence
 for item in sequence:
 File "/home/ubuntu/site/mysite/mysite/views.py", line 42, in gen
 frame = camera.get_frame()
 File "/home/ubuntu/site/mysite/mysite/views.py", line 33, in get_frame
 _, jpeg = cv2.imencode('.jpg', image)
cv2.error: OpenCV(4.5.3) /tmp/pip-req-build-xw6jtoah/opencv/modules/imgcodecs/src/loadsave.cpp:978: error: (-215:Assertion failed) !image.empty() in function 'imencode'



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AWS Lambda and Fluent FFMPEG error "cannot read property "isStream" of undefined"
29 mai 2021, par Travis Leeso here's the goal : convert a .webm file hosted in an S3 into a gif and upload that to a new bucket. This all works fine when run locally, but when trying to translate it into a lambda, fluent-ffmpeg throws errors when it runs the command.


Here's the code snippet :


ffmpeg(new URL(vid))
 .outputOptions("-vf", "scale=320:-1:flags=lanczos,fps=14")
 .on('progress', () => {
 console.log('progress');
 })
 .on('end', () => {
 //Do stuff with the result when it is done
 })
 .output(newKey)
 .run(newKey);



in this snippet, "vid" is a presigned GET url for an S3 bucket containing the .webm video file, and "newKey" is the name of the new bucket (and a temporary writeStream/File that is created in the lambda to store the new .gif file until we upload it to S3 - not super relevant to this issue).


What should happen (and does locally) is that a new output is created containing the converted .gif file


What happens when it is deployed in a lambda is that it reaches the .outputOptions call and throws a type error saying that it cannot read property isStream of undefined.


At first glance, this seems like I simply don't have FFMPEG installed in the lambda, but I do. I have tried with the prebuilt layer using NodeJS 10 found here : https://serverlessrepo.aws.amazon.com/applications/us-east-1/145266761615/ffmpeg-lambda-layer ,
with a NodeJS 12 layer that was built by some engineers here previously, and tried building a NodeJS 14 FFMPEG layer myself and using that. I tried for all three using no configuration and letting it call the PATH ffmpeg, using the FFMPEG_PATH and FFPROBE_PATH environment variables set to either what was specified in the previous layers, or what I made it in the newly built one, and even manually setting the path to the executables using the setFfmpegPath and setFfprobePath functions found on the fluent-ffmpeg object.


Lastly, I even tried bundling the executables in with the actual lambda code itself and uploading it through an S3, trying all three above methods of getting it to point to the correct paths once again to no avail.


I'm seriously in need of help if anyone else has encountered something similar or just might know what is going on. I'm at wit's end here trying to figure this out.