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• ffmpeg on google app engine or other alternatives

  6 décembre 2022, par Jon Luc

  This isn’t really a problem with any specific bit of code more just a general question about how I would host a ffmpeg function within a severless function like google app engine. Basically I have a block of code that takes every n frame a video and uploads it to google cloud storage. I have tried implementing such a solution with Firebase functions but to no avail. I think the primary problem is really to do with file storage, from my undetnsdjng data should be written to the tmp folder.

  


  So if anyone can outline exactly how I could host this on app engine that would be great, please be very specific and don’t assumeI know anything because I’ve only really worked with functions :)

  


  Thanks so much

  


  
//Essentially this but on app engine or any other severless environment

try {
        const process = new ffmpeg('star_wars_film_scene.mp4');
        process.then(function(video) {
            // Callback mode
            video.fnExtractFrameToJPG('helpers/frames/', {
                every_n_frames: 500
                
            }, function(error, files) {
                if (error) {
                    console.log(error);
                    return;
                }
                ProcessFrames(files);
            });
        }, function(err) {
            console.log(err);
        });
    } catch (e) {
        console.log('Houston, we have a problem')
        console.log(e.code);
        console.log(e.msg);
    }



  


• Improving accuracy of Google Cloud Speech API

  17 août 2018, par Shaikat Haque

  I am currently recording audio from a web page on my Mac OS computer and running it through the cloud speech api to produce a transcript. However, the results aren’t that accurate and there are chunks of missing words in the results.

  Are there any steps that would help me yield more accurate results ?

  Here are the steps I am taking to convert audio to text :

  1. Use Soundflower to channel audio output from my soundcard to mic in.
  2. Play audio from website
  3. Use quickTime player to record audio which is saved as a .m4a file.
  4. Use the command line tool ffmpeg to convert the .m4a file to a
     .flac, and also combine 2 audio channels (stereo) to 1 audio channel (mono).
  5. Upload the .flac file to Google Cloud Storage. The file has a sample rate of 44100Hz and has 24 bits per sample.
  6. Use the longRunningRecognize api via the node.js client library,
     pointing to the file in Google cloud storage.

• doc/filters : add missed framesync part in filter docs

  1er mars 2020, par Jun Zhao

  doc/filters : add missed framesync part in filter docs
  Add missed framesync part in filter docs.
  Reviewed-by : Gyan Doshi <ffmpeg@gyani.pro>
  
  Signed-off-by : Jun Zhao <barryjzhao@tencent.com>
  

  • [DH] doc/filters.texi