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1,000,000
27 septembre 2011, par
Mis à jour : Septembre 2011
Langue : English
Type : Audio
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Demon Seed
26 septembre 2011, par
Mis à jour : Septembre 2011
Langue : English
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Mis à jour : Septembre 2011
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Mis à jour : Septembre 2011
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Mis à jour : Septembre 2011
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Head Down
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Mis à jour : Septembre 2011
Langue : English
Type : Audio
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Sur d’autres sites (11257)
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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