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• FFMPEG Determine average color of an area of a video

  12 novembre 2019, par Naved Khan

  I have a use case where I’d want to insert one of two watermarks - one designed for a dark-ish background, the other for a light background into a video. Let’s say that I’d want to do this on the top right corner of the video.

  How do I determine the average color of the top right section of the video ? Post this, how do I determine which watermark to use by looking at the average color ?

  I have a solution right now where I am taking equally spaced screenshots and then measuring the average color, but it’s excruciatingly slow, especially for longer videos.

  # Calculate average color
  
      black_distances = []
  
      white_distances = []
  
  
  
      movie = FFMPEG::Movie.new(video_file)
  
      (0..movie.duration / 10).each do |second|
  
  
  
        # extract a frame
  
        filename = "tmp/watermark/#{SecureRandom.uuid}.jpg"
  
        movie.screenshot filename.to_s, seek_time: second
  
  
  
        # analyse frame for color distance
  
        frame = MiniMagick::Image.open(filename)
  
        frame.crop('20%x20%+80%+0')
  
        frame.resize('1x1')
  
        pixel = frame.get_pixels.flatten
  
  
  
        distance_from_black = Math.sqrt(((black[0] - pixel[0])**2 + (black[1] - pixel[1])**2 + (black[2] - pixel[2])**2))
  
        distance_from_white = Math.sqrt(((white[0] - pixel[0])**2 + (white[1] - pixel[1])**2 + (white[2] - pixel[2])**2))
  
  
  
        black_distances.push distance_from_black
  
        white_distances.push distance_from_white
  
  
  
        File.delete(filename) if File.exist?(filename)
  
      end
  
  
  
      average_black_distance = black_distances.reduce(:+).to_f / black_distances.size
  
      average_white_distance = white_distances.reduce(:+).to_f / white_distances.size

  I am also confused about how to use the resulting average_black_distance and average_white_distance to determine which watermark to use.

• Is it possible to determine if a subtitle track is imaged based or text based with ffprobe

  21 février 2021, par Shex

  I'm writing a script that burns subtitles into video files to prepare them for a personal stream I'm hosting. I'm having a hard time finding which type of subtitle is used in the file. I use ffprobe to get the files' information, and I can get stuff like the codec type, but I was wondering if there is a way to determine if a subtitle track is image based or text based. I can only think of getting a list of all possible codecs and match the codec type with this list but it would be very useful to have an info somewhere that can tell me "OK this is an image-based subtitle track", as when I burn I cannot use the same filters with ffmpeg to burn image vs. text subtitles.

  


• Google Speech API - Is there a way to determine if the audio has human voice or not ?

  20 décembre 2019, par stupid_sma

  I am making an audio filtering application at work that reads over hundreds of audio files and filters them. So, if the audio has human voice in it, it will accept it and if it does not- it will delete the audio file.

  I am using ffmpeg to get the details of the audio and add other filters like size and duration and silence (though it is not very accurate in detecting silence for all audio files.)

  My company asked me to try the Google Cloud Speech API to detect if the audio has any human voice in it.

  So with this code, some audio files return a Transcript of spoken words in the audio file, but what I need is to determine if a human is speaking or not.

  I have considered using hark.js for it but there does not seem to be enough documentation and I am short on time !

  Ps. I am an intern and I’m just starting out with programming. I apologize if my question does not make sense or sounds dumb.

     # Includes the autoloader for libraries installed with composer
  
     require __DIR__ . '/vendor/autoload.php';
  
  
  
     # Imports the Google Cloud client library
  
     use Google\Cloud\Speech\V1\SpeechClient;
  
     use Google\Cloud\Speech\V1\RecognitionAudio;
  
     use Google\Cloud\Speech\V1\RecognitionConfig;
  
     use Google\Cloud\Speech\V1\RecognitionConfig\AudioEncoding;
  
  
  
     putenv('GOOGLE_APPLICATION_CREDENTIALS=../../credentials.json');
  
  
  
  
  
  
  
     echo getcwd() . "<br />";
  
     chdir('test-sounds');
  
     echo getcwd() . "<br />";
  
     echo shell_exec('ls -lr');
  
  
  
     $fileList = glob('*');
  
     foreach($fileList as $filename){
  
     //echo $filename, '<br />';
  
  
  
     # The name of the audio file to transcribe
  
     $audioFile = __DIR__ . '/' . $filename;
  
  
  
     # get contents of a file into a string
  
     $content = file_get_contents($audioFile);
  
  
  
     # set string as audio content
  
     $audio = (new RecognitionAudio())
  
         ->setContent($content);
  
  
  
     # The audio file's encoding, sample rate and language
  
     $config = new RecognitionConfig([
  
         'encoding' => AudioEncoding::LINEAR16,
  
         'language_code' => 'ja-JP'
  
     ]);
  
  
  
     # Instantiates a client
  
     $client = new SpeechClient();
  
  
  
     # Detects speech in the audio file
  
     $response = $client->recognize($config, $audio);
  
  
  
     # Print most likely transcription
  
     foreach ($response->getResults() as $result) {
  
         $alternatives = $result->getAlternatives();
  
         $mostLikely = $alternatives[0];
  
         $transcript = $mostLikely->getTranscript();
  
         printf('<br />Transcript: %s' . PHP_EOL, $transcript . '<br />');
  
  
  
     }
  
  
  
     $client->close();
  
  
  
     }
  
  
  
     ?> ```