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• Video streaming with FFMPEG, how can I draw text on video from an updating text file ? [duplicate]

  22 mai 2020, par akouris

  Followed @matiaspl instructions to install ffmpeg-dl in order to live stream using Blackmagic's UltraStudio Mini Recorder on MacOS/OSX, with the following script :

  



  /usr/local/opt/ffmpegdecklink/bin/ffmpeg-dl -f decklink -i "UltraStudio Mini Recorder" -video_input sdi -format_code Hp25 -audio_input embedded -channels 2 -vf yadif=1 -c:v h264_videotoolbox -profile:v main -b:v 3M -pix_fmt yuv420p -color_range 1 -coder cabac -c:a aac_at -b:a 128k -threads 15 -f flv rtmp://a.rtmp.youtube.com/live2/your-streamkey


  



  My question is how can I draw text on that stream, from a text file which is being updated once every 3-4 minutes ?

  


• Computer crashing when using python tools in same script

  5 février 2023, par SL1997

  I am attempting to use the speech recognition toolkit VOSK and the speech diarization package Resemblyzer to transcibe audio and then identify the speakers in the audio.

  


  Tools :

  


  https://github.com/alphacep/vosk-api
  
https://github.com/resemble-ai/Resemblyzer

  


  I can do both things individually but run into issues when trying to do them when running the one python script.

  


  I used the following guide when setting up the diarization system :

  


  https://medium.com/saarthi-ai/who-spoke-when-build-your-own-speaker-diarization-module-from-scratch-e7d725ee279

  


  Computer specs are as follows :

  


  Intel(R) Core(TM) i3-7100 CPU @ 3.90GHz, 3912 Mhz, 2 Core(s), 4 Logical Processor(s)
  
32GB RAM

  


  The following is my code, I am not to sure if using threading is appropriate or if I even implemented it correctly, how can I best optimize this code as to achieve the results I am looking for and not crash.

  


  from vosk import Model, KaldiRecognizer
from pydub import AudioSegment
import json
import sys
import os
import subprocess
import datetime
from resemblyzer import preprocess_wav, VoiceEncoder
from pathlib import Path
from resemblyzer.hparams import sampling_rate
from spectralcluster import SpectralClusterer
import threading
import queue
import gc



def recognition(queue, audio, FRAME_RATE):

    model = Model("Vosk_Models/vosk-model-small-en-us-0.15")

    rec = KaldiRecognizer(model, FRAME_RATE)
    rec.SetWords(True)

    rec.AcceptWaveform(audio.raw_data)
    result = rec.Result()

    transcript = json.loads(result)#["text"]

    #return transcript
    queue.put(transcript)



def diarization(queue, audio):

    wav = preprocess_wav(audio)
    encoder = VoiceEncoder("cpu")
    _, cont_embeds, wav_splits = encoder.embed_utterance(wav, return_partials=True, rate=16)
    print(cont_embeds.shape)

    clusterer = SpectralClusterer(
        min_clusters=2,
        max_clusters=100,
        p_percentile=0.90,
        gaussian_blur_sigma=1)

    labels = clusterer.predict(cont_embeds)

    def create_labelling(labels, wav_splits):

        times = [((s.start + s.stop) / 2) / sampling_rate for s in wav_splits]
        labelling = []
        start_time = 0

        for i, time in enumerate(times):
            if i > 0 and labels[i] != labels[i - 1]:
                temp = [str(labels[i - 1]), start_time, time]
                labelling.append(tuple(temp))
                start_time = time
            if i == len(times) - 1:
                temp = [str(labels[i]), start_time, time]
                labelling.append(tuple(temp))

        return labelling

    #return
    labelling = create_labelling(labels, wav_splits)
    queue.put(labelling)



def identify_speaker(queue1, queue2):

    transcript = queue1.get()
    labelling = queue2.get()

    for speaker in labelling:

        speakerID = speaker[0]
        speakerStart = speaker[1]
        speakerEnd = speaker[2]

        result = transcript['result']
        words = [r['word'] for r in result if speakerStart < r['start'] < speakerEnd]
        #return
        print("Speaker",speakerID,":",' '.join(words), "\n")





def main():

    queue1 = queue.Queue()
    queue2 = queue.Queue()

    FRAME_RATE = 16000
    CHANNELS = 1

    podcast = AudioSegment.from_mp3("Podcast_Audio/Film-Release-Clip.mp3")
    podcast = podcast.set_channels(CHANNELS)
    podcast = podcast.set_frame_rate(FRAME_RATE)

    first_thread = threading.Thread(target=recognition, args=(queue1, podcast, FRAME_RATE))
    second_thread = threading.Thread(target=diarization, args=(queue2, podcast))
    third_thread = threading.Thread(target=identify_speaker, args=(queue1, queue2))

    first_thread.start()
    first_thread.join()
    gc.collect()

    second_thread.start()
    second_thread.join()
    gc.collect()

    third_thread.start()
    third_thread.join()
    gc.collect()

    # transcript = recognition(podcast,FRAME_RATE)
    #
    # labelling = diarization(podcast)
    #
    # print(identify_speaker(transcript, labelling))


if __name__ == '__main__':
    main()


  


  When I say crash I mean everything freezes, I have to hold down the power button on the desktop and turn it back on again. No blue/blank screen, just frozen in my IDE looking at my code. Any help in resolving this issue would be greatly appreciated.

  


• How to make your plugin multilingual – Introducing the Piwik Platform

  29 octobre 2014, par Thomas Steur — Development

  This is the next post of our blog series where we introduce the capabilities of the Piwik platform (our previous post was Generating test data – Introducing the Piwik Platform). This time you’ll learn how to equip your plugin with translations. Users of your plugin will be very thankful that they can use and translate the plugin in their language !

  Getting started

  In this post, we assume that you have already set up your development environment and created a plugin. If not, visit the Piwik Developer Zone where you’ll find the tutorial Setting up Piwik and other Guides that help you to develop a plugin.

  Managing translations

  Piwik is available in over 50 languages and comes with many translations. The core itself provides some basic translations for words like “Visitor” and “Help”. They are stored in the directory /lang. In addition, each plugin can provide its own translations for wordings that are used in this plugin. They are located in /plugins/*/lang. In those directories you’ll find one JSON file for each language. Each language file consists in turn of tokens that belong to a group.

  {
  
      "MyPlugin":{
  
          "BlogPost": "Blog post",
  
          "MyToken": "My translation",
  
          "InteractionRate": "Interaction Rate"
  
      }
  
  }

  A group usually represents the name of a plugin, in this case “MyPlugin”. Within this group, all the tokens are listed on the left side and the related translations on the right side.

  Building a translation key

  As you will later see to actually translate a word or a sentence you’ll need to know the corresponding translation key. This key is built by combining a group and a token separated by an underscore. You can for instance use the key MyPlugin_BlogPost to get a translation of “Blog post”. Defining a new key is as easy as adding a new entry to the “MyPlugin” group.

  Providing default translations

  If a translation cannot be found then the English translation will be used as a default. Therefore, you should always provide a default translation in English for all keys in the file en.json (ie, /plugins/MyPlugin/lang/en.json).

  Adding translations for other languages

  This is as easy as creating new files in the lang subdirectory of your plugin. The filename consists of a 2 letter ISO 639-1 language code completed by the extension .json. This means German translations go into a file named de.json, French ones into a file named fr.json. To see a list of languages you can use have a look at the /lang directory.

  Reusing translations

  As mentioned Piwik comes with quite a lot of translations. You can and should reuse them but you are supposed to be aware that a translation key might be removed or renamed in the future. It is also possible that a translation key was added in a recent version and therefore is not available in older versions of Piwik. We do not currently announce any of such changes. Still, 99% of the translation keys do not change and it is therefore usually a good idea to reuse existing translations. Especially when you or your company would otherwise not be able to provide them. To find any existing translation keys go to Settings => Translation search in your Piwik installation. The menu item will only appear if the development mode is enabled.

  Translations in PHP

  Use the Piwik::translate() function to translate any text in PHP. Simply pass any existing translation key and you will get the translated text in the language of the current user in return. The English translation will be returned in case none for the current language exists.

  $translatedText = Piwik::translate('MyPlugin_BlogPost');

  Translations in Twig Templates

  To translate text in Twig templates, use the translate filter.

  {{ 'MyPlugin_BlogPost'|translate }}

  Contributing translations to Piwik

  Did you know you can contribute translations to Piwik ? In case you want to improve an existing translation, translate a missing one or add a new language go to Piwik Translations and sign up for an account. You won’t need any knowledge in development to do this.

  Advanced features

  Of course there are more useful things you can do with translations. For instance you can use placeholders like %s in your translations and you can use translations in JavaScript as well. In case you want to know more about those topics check out our Internationalization guide. Currently, this guide only covers translations but we will cover more topics like formatting numbers and handling currencies in the future.

  Congratulations, you have learnt how to make your plugin multilingual !

  If you have any feedback regarding our APIs or our guides in the Developer Zone feel free to send it to us.