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• carrierwave-ffmpeg .weba audio convert to .mp3 or .mp4

  14 mai 2018, par nmadoug

  I use react-mic on the front-end of my React/Rails application to capture audio from the user. react-mic formats the audio blob as .weba. I’m trying to convert the .weba to .mp4 or .mp3 using carrierwave-ffmpeg . I can isolate the issue to my Rails uploader, which is as follows :

  require 'fog/aws'
  
  
  
  class UserResponseUploader < CarrierWave::Uploader::Base
  
    include CarrierWave::FFmpeg
  
  
  
    if Rails.env.test?
  
      storage :file
  
    else
  
      storage :fog
  
    end
  
  
  
    version :mp3 do
  
      puts `which ffmpeg`
  
      # binding.pry
  
      process encode: [:mp3, audio_codec: "a libmp3lame -qscale:a 2"]
  
      # process :encode_audio=> [:mp4, audio_codec: "aac",:custom => "-strict experimental -qscale:a 2"]
  
  
  
      def full_filename(for_file)
  
        super.chomp(File.extname(super)) + '.mp3'
  
      end
  
    end
  
  
  
    # Directory where uploaded files will be stored on file system or AWS
  
    def store_dir
  
      "uploads/#{model.class.to_s.underscore}/#{mounted_as}/#{model.id}"
  
    end
  
  end

  ffmpeg is installed on my local PC and I can run the command on the terminal to get an audio file created

  ffmpeg -i audio.weba -codec:a libmp3lame -qscale:a 2 willwork.mp3

  My problem is when I try and run everything in my code, I get the following error message :

  NameError (undefined local variable or method `e' for #):

  I don’t know where it’s complaining. I have a feeling the encoding line is causing the problem and I don’t have it set up properly.

  Any ideas ?

• Failed to hard-ware accelerate video decoding via Tesla P40

  20 mai 2018, par Potemkin

  While I am writing a surveillance video recognition demo, I find it is much slower to simply play a video in the server(Xeon E5-2680 2.4GHz, Tesla P40) than in my laptop(i7-8550 1.8GHz, Intel UHD Graphics 620).

  I use DXVA-Checker to see the video decoder device, and notice that my laptop use the GPU for decoding, but the server use no GPU for the job. Then I check ’nvidia-smi’, and it shows all of GPUs are running in TCC driver model, not WDDM driver model. And I cannot turn it to WDDM because nvidia-smi says it is not supported.

  The video play demo is written via OPENCV, in which the video decoding part is from ffmpeg. The server runs in Windows-server-2012, and my laptop is on Windows 10.

  The question is how can I get the server decoding videos with GPUs, and is this the reason for the slowness or there is something else ?

• Using ffmpeg, the function av_find_input_format("avfoundation") return null

  28 avril 2019, par guojing

  I run this code in iPad mini 4 (Model A1538), iOS 11.2.6

  Try to record audio by FFmpeg.

  av_register_all();
  
  avcodec_register_all();
  
  avdevice_register_all();
  
  
  
  AVFormatContext *pFormatCtx = avformat_alloc_context();
  
  AVDictionary* options = NULL;
  
  av_dict_set(&options,"list_devices","true",0);
  
  AVInputFormat *iformat = av_find_input_format("avfoundation");
  
  printf("==AVFoundation Device Info===\n");
  
  avformat_open_input(&pFormatCtx,"",iformat,&options);
  
  printf("=============================\n");
  
  
  
  if(avformat_open_input(&pFormatCtx,"0",iformat,NULL)!=0){
  
      printf("Couldn't open input stream.\n");
  
      return;
  
  }

  pFormatCtx = NULL, and iformat = NULL.

  Why should this happen, did I missed anything to set ?