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• avdevice/dshow : list_devices : show media type(s) per device

  21 décembre 2021, par Diederick Niehorster

  avdevice/dshow : list_devices : show media type(s) per device
  the list_devices option of dshow didn't indicate whether a specific
  
  device provides audio or video output. This patch iterates through all
  
  media formats of all pins exposed by the device to see what types it
  
  provides for capture, and prints this to the console for each device.
  
  Importantly, this now allows to find devices that provide both audio and
  
  video, and devices that provide neither.
  Signed-off-by : Diederick Niehorster <dcnieho@gmail.com>
  
  Reviewed-by : Roger Pack <rogerdpack2@gmail.com>
  

  • [DH] libavdevice/dshow.c

• How correctly show video with transparency in Qt with OpenCV + FFMpeg

  11 avril 2022, par TheEnigmist

  I'm trying to show a video with transparency in a Qt6 application using OpenCV + FFMPEG.
Actually those are tool versions :

  


  

  • Win 11

  


  • Qt 6.3.0

  


  • OpenCV 4.5.5 (built with CMake)

  


  • FFMPEG 2022-04-03-git-1291568c98-full_build-www.gyan.dev

  


  


  I've used a base .mov video with transparency as test (link provided below).
First of all I've converted .mov video to .webm video (VP9) and I see in output text that alpha channel remains

  


  


  ffmpeg -i '.\Retro Bars.mov' -c:v libvpx-vp9 -crf 30 -b:v 0 output.webm

  


  


  Input #0, mov,mp4,m4a,3gp,3g2,mj2,
    ...
    Stream #0:0[0x1](eng): Video: qtrle (rle  / 0x20656C72), argb(progressive),
    ...

Output #0, webm, 
   ...
   Stream #0:0(eng): Video: vp9, yuva420p(tv, progressive),
   ...


  


  But when I show info of output file with ffmpeg it loses alpha channel :

  


  


  ffmpeg -i .\output.webm

  


  


  Input #0, matroska,webm,
    ...
    Stream #0:0(eng): Video: vp9 (Profile 0), yuv420p(tv, progressive),
    ...


  


  If I open output.webm with OBS it is shown correctly without a background, as shown in picture :


  


  If I try to open it with OpenCV + FFMPEG it shows a black background under bars, as shown in picture :


  


  This is how I load video in Qt :

  


  cv::VideoCapture capture;
capture.open(filename, cv::CAP_FFMPEG);
capture.set(cv::CAP_PROP_CONVERT_RGB, false); // try forcing load alpha channel
... //in a thread
while (capture.read(frame)) {
    qDebug() << "c" << frame.channels() << "t" <<  frame.type() << "d" <<  frame.depth(); // output: c 3 t 16 d 0
    cv::cvtColor(frame, frame, cv::COLOR_BGR2RGBA); //useless since no alpha channel is detected
    img = QImage(frame.data, frame.cols, frame.rows, QImage::Format_RGBA8888);
    emit processedImage(img); // to show image in a QLabel with QPixmap::fromImage(img)
}


  


  I think the problem is when I load the video with OpenCV, it doens't detect alpha channel, since I can load correctly in other player (obs, html5, etc.)

  


  What I'm wrong with all process to show this video in Qt with transparency ?

  


  EDIT : Added dropbox link with test video + ffmpeg outputs :
sample items

  


• I tried to play the audio on Alexa skill from my S3 Bucket, from the test tab, **it show but in fact, I can't hear any sound

  19 avril 2022, par Siti Mayna

  So I tried to play the audio on Alexa skill from my S3 Bucket, from the test tab, it show but in fact, I can't hear any sound. Another fact is, that I tried to use the sample audio from https://developer.amazon.com/en-US/docs/alexa/custom-skills/ask-soundlibrary.html and it is worked, but why it won't work when it comes from my own S3 Bucket ?

  


  Notes :

  


  I've tried to test the skill using my mobile phone also.

  


  I've tried to encode the audio using FFmpeg.

  


  I've tried to use Jovo to convert the audio. https://v3.jovo.tech/audio-converter

  


  I don't know how to fix this error.

  


  There is no error message on cloud watch.

  


  Assumptions :
There is some problem related to the audio resources or there is more set to play audio from S3 Bucket since the sample audio is working.

  


  Steps to reproduce :

  


  


  Build the interaction model

  


  


  


  Encode the audio to make it Alexa skill friendly (fulfill the requirements, like sample rate, etc), I used and tried all of these :

  


  


  A :

  


  ffmpeg -i  -ac 2 -codec:a libmp3lame -b:a 48k -ar 16000 -write_xing 0 


  


  B :

  


  ffmpeg -i  -ac 2 -codec:a libmp3lame -b:a 48k -ar 24000 -write_xing 0 


  


  C :

  


  ffmpeg -y -i input.mp3 -ar 16000 -ab 48k -codec:a libmp3lame -ac 1 output.mp3


  


  


  Upload the audio resources on S3Bucket
Audio sample on s3 storage but none of them are produce any sounds

  


  


  


  Use the link and insert it to APLA.json

  


  


  
    {
      "type": "APLA",
      "version": "0.91",
      "description": "Simple document that generates speech",
      "mainTemplate": {
        "parameters": [
          "payload"
        ],
        "type": "Sequencer",
        "items": [
          {
            "type": "Audio",
            "source": "https://72578561-d9d8-47b4-811c-cafbcbc5ddb9-us-east-1.s3.amazonaws.com/Media/one-small-step-alexa-24.mp3"
          }
        ]
      }
    }



  


  notes : I change the link sources based on audio that I tried.

  


  


  the intent on lambda_function.py :

  


  


  def _load_apl_document(file_path):
    # type: (str) -> Dict[str, Any]
    """Load the apl json document at the path into a dict object."""
    with open(file_path) as f:
        return json.load(f)

class LaunchRequestHandler(AbstractRequestHandler):
    """Handler for Skill Launch."""
    def can_handle(self, handler_input):
        # type: (HandlerInput) -> bool

        return ask_utils.is_request_type("LaunchRequest")(handler_input)

    def handle(self, handler_input):
        # type: (HandlerInput) -> Response
        logger.info("In LaunchRequestHandler")

        # type: (HandlerInput) -> Response
        speak_output = "Hello World!"
        # .ask("add a reprompt if you want to keep the session open for the user to respond")

        return (
            handler_input.response_builder
                #.speak(speak_output)
                .add_directive(
                        RenderDocumentDirective(
                            token="pagerToken",
                            document=_load_apl_document("APLA.json"),
                            datasources={}
                        )
                    )
                .response
        )


  


  


  Deploy

  


  


  


  Test it

  


  


  


  The result of the test on my end :

The response for testing

  


  


  the JSON response :

  


  {
    "body": {
        "version": "1.0",
        "response": {
            "directives": [
                {
                    "type": "Alexa.Presentation.APLA.RenderDocument",
                    "token": "pagerToken",
                    "document": {
                        "type": "APLA",
                        "version": "0.91",
                        "description": "Simple document that generates speech",
                        "mainTemplate": {
                            "parameters": [
                                "payload"
                            ],
                            "type": "Sequencer",
                            "items": [
                                {
                                    "type": "Audio",
                                    "source": "https://72578561-d9d8-47b4-811c-cafbcbc5ddb9-us-east-1.s3.amazonaws.com/Media/one-small-step-alexa-24.mp3"
                                }
                            ]
                        }
                    },
                    "datasources": {}
                }
            ],
            "type": "_DEFAULT_RESPONSE"
        },
        "sessionAttributes": {},
        "userAgent": "ask-python/1.16.1 Python/3.7.12"
    }
}


  


  


  On my cloud Watch :
Cloud Watch