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• Anomalie #4114 (Fermé) : paramètre media:joindre_deballer_lister_zip ignoré

  27 septembre 2018, par cedric -

  Corrigé par https://zone.spip.org/trac/spip-zone/changeset/111718

• How to decode video using AMF, Intel Media SDK, and NVIDIA CUDA for hardware decoding all platforms ?

  23 novembre 2022, par Guy

  I want to make a multi-platform video streaming app but idk how to implement hardware decoding for AMD, NVIDIA and Intel.
For this project I also want to use FFmpeg.
Pls help.

  


  I tried d3d11va on windows but I want other rendering API's as well.

  


• How to save media files to Heroku local storage with Django ?

  25 juillet 2022, par Diyan Kalaydzhiev

  Im 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