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• SDL2 won't play with more than 6 audio channels

  13 juin 2020, par Hiko Haieto

  I am trying to stream (raw) video and audio from a capture device as part of my home media setup (with my pc acting similarly to a receiver in a typical home theatre setup), but the biggest problem I haven't been able to get past is that I haven't been able to get ffplay (using SDL2 as its audio backend) to work with all 8 channels in 7.1 streams - two simply get dropped, despite it recognising 8 channel input or me specifying a 7.1 layout.

  



  I have been able to confirm that all 8 channels are present in the source by first using ffmpeg to save the output of a speaker test to a file and playing that back with both mplayer (which works) and ffplay (which doesn't). I also wrote some minimal code to play the audio directly through SDL's API with the same result, so it's not the fault of ffplay. I might simply use mplayer if it weren't for the fact that piping output from ffmpeg adds too much latency for real-time use. I am using libSDL version 2.0.12 and ffplay 4.2.3, both of which are the latest at the time of writing and are ostensibly supposed to support 7.1 audio.

  



  Using output recorded from speaker-test -c 8, I am using the following to play it back in mplayer :

  



  mplayer -channels 8 -rawaudio channels=8 -format s16le -demuxer rawaudio speaker-test.pcm


  



  and the following to play it back in ffplay :

  



  ffplay -f s16le -ac 8 -af 'channelmap=channel_layout=7.1' speaker-test.pcm


  



  No matter what I try, the two side channels get dropped. I couldn't figure out how to play raw pcm in SDL, so I repeated the same tests with wav output and used the following code to play it back :

  



  #include <sdl2></sdl2>SDL.h>&#xA;&#xA;int main(int argc, char **argv) {&#xA;    SDL_Init(SDL_INIT_AUDIO);&#xA;    SDL_AudioSpec wavSpec;&#xA;    Uint32 wavLength;&#xA;    Uint8 *wavBuffer;&#xA;    SDL_LoadWAV("speaker-test.wav", &amp;wavSpec, &amp;wavBuffer, &amp;wavLength);&#xA;    SDL_AudioDeviceID deviceID = SDL_OpenAudioDevice(NULL, 0, &amp;wavSpec, NULL, 0);&#xA;    SDL_QueueAudio(deviceID, wavBuffer, wavLength);&#xA;    SDL_PauseAudioDevice(deviceID, 0);&#xA;    SDL_Delay(30000);&#xA;    SDL_CloseAudioDevice(deviceID);&#xA;    SDL_FreeWAV(wavBuffer);&#xA;    SDL_Quit();&#xA;    return 0;&#xA;}&#xA;

  



  The above code exhibits the same behaviour of dropping the two additional side channels, despite it being the latest version of SDL that should have supported 7.1 for many releases now. Why might this be happening, and how might I fix it ?

  


• Transcoding WAV audio to AAC in an MP4 container using FFmpeg C API

  7 novembre 2022, par vstrom coder

  I'm trying to compose source video and audio into a final MP4 video.
I have a problem with the WAV audio. After decoding and filtering, I'm getting an error from the output encoder : [aac @ 0x145e04c40] more samples than frame size

  


  I initially used the following filter graph (minimal reproducible example) :

  


      abuffer -> aformat -> abuffersink


  


  At this point I was getting the error mentioned above.

  


  Then, I tried to insert a aresample filter to the graph :

  


      abuffer -> aresample -> aformat -> abuffersink


  


  But still getting the same error.
This was based on the fact that the ffmpeg CLI uses this filter when converting WAV to MP4 :

  


  Command :

  


      ffmpeg -i source.wav output.mp4 -loglevel debug


  


  Output contains :

  


      [graph_0_in_0_0 @ 0x138f06200] Setting 'time_base' to value '1/44100'
    [graph_0_in_0_0 @ 0x138f06200] Setting 'sample_rate' to value '44100'
    [graph_0_in_0_0 @ 0x138f06200] Setting 'sample_fmt' to value 's16'
    [graph_0_in_0_0 @ 0x138f06200] Setting 'channel_layout' to value 'mono'
    [graph_0_in_0_0 @ 0x138f06200] tb:1/44100 samplefmt:s16 samplerate:44100 chlayout:mono
    [format_out_0_0 @ 0x138f06620] Setting 'sample_fmts' to value 'fltp'
    [format_out_0_0 @ 0x138f06620] Setting 'sample_rates' to value '96000|88200|64000|48000|44100|32000|24000|22050|16000|12000|11025|8000|7350'
    [format_out_0_0 @ 0x138f06620] auto-inserting filter 'auto_aresample_0' between the filter 'Parsed_anull_0' and the filter 'format_out_0_0'
    [AVFilterGraph @ 0x138f060f0] query_formats: 4 queried, 6 merged, 3 already done, 0 delayed
    [auto_aresample_0 @ 0x138f06c30] [SWR @ 0x120098000] Using s16p internally between filters
    [auto_aresample_0 @ 0x138f06c30] ch:1 chl:mono fmt:s16 r:44100Hz -> ch:1 chl:mono fmt:fltp r:44100Hz
    Output #0, mp4, to 'output.mp4':
      Metadata:
        encoder         : Lavf59.27.100
      Stream #0:0, 0, 1/44100: Audio: aac (LC) (mp4a / 0x6134706D), 44100 Hz, mono, fltp, delay 1024, 69 kb/s
        Metadata:
          encoder         : Lavc59.37.100 aac


  


  I'm trying to figure out whether I should use the SWR library directly as exemplified in the transcode_aac example.

  


• Efficient real-time video stream processing and forwarding with RTMP servers

  19 mai 2023, par dumbQuestions

  I have a scenario where I need to retrieve a video stream from an RTMP server, apply image processing (specifically, adding blur to frames), and then forward the processed stream to another RTMP server (in this case, Twitch).

  


  Currently, I'm using ffmpeg in conjunction with cv2 to retrieve and process the stream. However, this approach introduces significant lag when applying the blur. I'm seeking an alternative method that can achieve the desired result more efficiently. I did attempt to solely rely on ffmpeg for the entire process, but I couldn't find a way to selectively process frames based on a given condition and subsequently transmit only those processed frames.

  


  Is there a more efficient approach or alternative solution that can address this issue and enable real-time video stream processing with minimal lag ?

  


  Thanks in advance !

  


  def forward_stream(server_url, stream_key, twitch_stream_key):
    get_ffmpeg_command = [...]

    send_ffmpeg_command [...]

    # Start get FFmpeg process
    read_process = subprocess.Popen(get_ffmpeg_command, stdout=subprocess.PIPE, stderr=subprocess.DEVNULL)

    # Start send FFmpeg process
    send_process = send_process = subprocess.Popen(send_ffmpeg_command, stdin=subprocess.PIPE, stderr=subprocess.DEVNULL)

    # Open video capture
    cap = cv2.VideoCapture(f'{server_url}')

    while True:
        # Read the frame
        ret, frame = cap.read()
        if ret:
            # Apply machine learning algorithm
            should_blur = machine_learning_algorithm(frame)

            # Apply blur if necessary
            if machine_learning_algorithm(frame):
                frame = cv2.blur(frame, (25, 25))

            # Write the frame to FFmpeg process
            send_process.stdin.write(frame.tobytes())
        else:
            break

    # Release resources
    cap.release()
    read_process.stdin.close()
    read_process.wait()