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Autres articles (98)
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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 (...) -
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 ;
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Multilang : améliorer l’interface pour les blocs multilingues
18 février 2011, parMultilang est un plugin supplémentaire qui n’est pas activé par défaut lors de l’initialisation de MediaSPIP.
Après son activation, une préconfiguration est mise en place automatiquement par MediaSPIP init permettant à la nouvelle fonctionnalité d’être automatiquement opérationnelle. Il n’est donc pas obligatoire de passer par une étape de configuration pour cela.
Sur d’autres sites (12861)
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How can I save the RAW rtp output file by ffmpeg
13 septembre 2016, par JeromyI have a problem that to save Output RTP as a file.
(Is that a possible ? Am I Right ?)Trans-coding goal as below :
1. Save the RTP stream to file in local storage using FFMPEG.
2. Input is file.
3. Output is RTP stream file.I`m using that.
./ffmpeg -re -i ../Video_Sample/03.Fashion_DivX720p_ASP_87s_1000k_720p.mp4 -c:v libx264 -b:v 1000k -preset superfast -an -f rtp -y test.rtp
But I got a message like that :
Could not write header for output file #0 (incorrect codec parameters ?) : Invalid argument
How can I fix it ?
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Save screenshots taken with FFmpeg into Amazon S3 bucket
30 mars 2021, par HomeAloneIn my python app I take screenshots of videos. I save them locally and it works just fine but now I want to save them in an Amazon S3 bucket.


subprocess.run(["ffmpeg", "-ss", "00:00:30", "-i", src, "-map", "0:v", "-vframes", "1", "pipe:pic.jpeg | aws s3 cp - s3://mypublicbucket"])



I get an
Unable to find a suitable output format
when running this command. What I try to do is to upload the picture straight into my public amazon bucket.

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How to save media files to Heroku local storage with Django ?
25 juillet 2022, par Diyan KalaydzhievIm having a Django REST app with React for client. Im recording a file with React and sending in to Django. When i save it i modify it with ffmpeg and save it again in the same folder with a new name, the ffmpeg command looks like this :


os.system(f"ffmpeg -i {audio_path} -ac 1 -ar 16000 {target_path}")


Because i need a path for my audio both for opening and saving, i can't use cloud stores like "Bucket S3, Cloudinary etc.". And the fact that im using it only for a few seconds and then deleting it makes Heroku (the app is deployed there) the perfect place to save it non-persistent. The problem is that the file isn't getting saved in my library with media files. It saves in the postgre db but doesn't in my filesystem and when i try to access it my program returns that there isn't a file with that name. My question is How can i save media files in Heroku file system and how to access them ?


settings.py


MEDIA_ROOT = os.path.join(BASE_DIR,'EmotionTalk/AI_emotion_recognizer/recordings')
MEDIA_URL = '/'



urls.py


urlpatterns = [
path('admin/', admin.site.urls),
path('', include('EmotionTalk.emotion_talk_app.urls')),
path('auth/', include('EmotionTalk.auth_app.urls')),
path('api-token-auth/', views.obtain_auth_token),
] + static(settings.STATIC_URL, document_root=settings.STATIC_ROOT) \
+ static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)



views.py


def post(self, request):
 file_serializer = RecordingSerializer(data=request.data)

 if file_serializer.is_valid():
 file_serializer.save()

 file_name = file_serializer.data.get('recording')
 owner_id = file_serializer.data.get('owner_id')

 current_emotions_count = len(Profile.objects.get(user_id=owner_id).last_emotions)

 print(file_name)
 recognize_emotion.delay(file_name, owner_id)

 return Response({
 'data': file_serializer.data,
 'current_emotions_count': current_emotions_count
 }, status=status.HTTP_201_CREATED)

 return Response(file_serializer.errors, status=status.HTTP_400_BAD_REQUEST)



tasks.py


def parse_arguments(filename):
import argparse
parser = argparse.ArgumentParser()

new_filename = filename.lstrip('v')

parser.add_argument("audio_path")
parser.add_argument("target_path")

args = parser.parse_args([f'EmotionTalk/AI_emotion_recognizer/recordings/{filename}',
 f'EmotionTalk/AI_emotion_recognizer/recordings/{new_filename}'])
audio_path = args.audio_path
target_path = args.target_path

if os.path.isfile(audio_path) and audio_path.endswith(".wav"):
 if not target_path.endswith(".wav"):
 target_path += ".wav"
 convert_audio(audio_path, target_path)
 return target_path
else:
 raise TypeError("The audio_path file you specified isn't appropriate for this operation")



parse_arguments is called from recognize_emotion