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• fluent-ffmpeg from an array of input files

  15 décembre 2016, par leonard vertighel

  I want to use fluent-ffmpeg to create a video of last n images of a directory, or database entries.

  Which is the correct syntax ?

  These are my tries :

  Mimic shell command

  ffmpeg()
  
    .addInput('ls *png | tail -n 17')
  
    .inputOptions("-pattern_type glob")
  
    .output("output.mp4").run()

  but it does not accept shell commands ;

  space - separated paths

  ffmpeg()
  
    .addInput('a*.png b*.png ')
  
    .inputOptions("-pattern_type glob")
  
    .output("output.mp4").run()

  but it does not accept list of files separated by spaces ;

  Array of image paths

  ffmpeg()
  
    .addInput(array) // ['aa.png', 'a1.png',,,'bbb.png']
  
    .inputOptions("-pattern_type glob")
  
    .output("output.mp4").run()

  but it does not accept arrays.

  EDIT :

  Also, from Merge Multiple Videos using node fluent ffmpeg, I am able to add multiple inputs using an array of files as

  var ffmpeg= require('fluent-ffmpeg');
  
  var f=ffmpeg() 
  
  pngarr.forEach(p => f.input(p)) /// pngarr is my array of png paths

  But running

  f.output("./output.mp4").run()

  I obtain just a video of 0 seconds containing the first png of the list.

• fluent-ffmpeg from an array of input files

  30 juillet 2017, par leonard vertighel

  I want to use fluent-ffmpeg to create a video of last n images of a directory, or database entries.

  Which is the correct syntax ?

  These are my tries :

  Mimic shell command

  ffmpeg()
  
    .addInput('ls *png | tail -n 17')
  
    .inputOptions("-pattern_type glob")
  
    .output("output.mp4").run()

  but it does not accept shell commands ;

  space - separated paths

  ffmpeg()
  
    .addInput('a*.png b*.png ')
  
    .inputOptions("-pattern_type glob")
  
    .output("output.mp4").run()

  but it does not accept list of files separated by spaces ;

  Array of image paths

  ffmpeg()
  
    .addInput(array) // ['aa.png', 'a1.png',,,'bbb.png']
  
    .inputOptions("-pattern_type glob")
  
    .output("output.mp4").run()

  but it does not accept arrays.

  EDIT :

  Also, from Merge Multiple Videos using node fluent ffmpeg, I am able to add multiple inputs using an array of files as

  var ffmpeg= require('fluent-ffmpeg');
  
  var f=ffmpeg() 
  
  pngarr.forEach(p => f.input(p)) /// pngarr is my array of png paths

  But running

  f.output("./output.mp4").run()

  I obtain just a video of 0 seconds containing the first png of the list.

• Run python ffmpeg audio convertion code file from subprocess.call() within a flask server

  11 novembre 2019, par Kasun

  I have build a small flask server to handle the request. I have 3 parameters in the api function that i want to get. those are type, user_id, audio_file, One is a file. Since it’s used for the audio file conversion. I have to get a file.. I have tested with this in Postman audio file get saved but the subprocess.call(command) in the api function doesn’t work..

  this is the flask server code

  @app.route('/voice', methods=['GET','POST'])
  
  def process_audio():
  
   try:
  
      if request.method == 'POST':
  
          input_type = request.form['type']
  
          user_id = request.form['user_id']
  
          static_file = request.files['audio_file']
  
          audio_name = secure_filename(static_file.filename)
  
          path = 't/'
  
          status = static_file.save(path + audio_name)
  
          full_file = path + audio_name
  
          if input_type == 1:
  
              cmd = "python t/convert_english.py --audio " + full_file
  
              res = subprocess.call([cmd],shell=True)
  
              f = open('t/ress.txt', 'w')
  
              f.write(str(res))
  
              f.close()
  
              return "true"
  
          else:
  
              cmd = "python t/convert_sinhala.py --audio " + full_file
  
              os.system(cmd)
  
              return "true"
  
      else:
  
          return "false"
  
  
  
  except Exception as e:
  
      print(e)
  
      logger.error(e)
  
      return e

  The audio file get saved in the directory as expected..

  this is the convert_english.py

  import subprocess
  
  import argparse
  
  import os
  
  import logging
  
  import speech_recognition as sr
  
  from tqdm import tqdm
  
  from multiprocessing.dummy import Pool
  
  
  
  #subprocess.call('pip install pydub',shell=True)
  
  
  
  from os import path
  
  from pydub import AudioSegment
  
  
  
  logging.basicConfig(filename='/var/www/img-p/t/ee.log', level=logging.DEBUG, 
  
                      format='%(asctime)s %(levelname)s %(name)s %(message)s')
  
  logger=logging.getLogger(__name__)
  
  
  
  ap = argparse.ArgumentParser()
  
  ap.add_argument("-a", "--audio", required=True,
  
      help="path to input audio file")
  
  args = vars(ap.parse_args())
  
  
  
  src = args["audio"]
  
  dst = "audio.wav"
  
  
  
  sound = AudioSegment.from_mp3(src)
  
  sound.export(dst, format="wav")
  
  
  
  #subprocess.call('pip install ffmpeg-python',shell=True)
  
  
  
  subprocess.call('mkdir parts',shell=True)
  
  
  
  subprocess.call('ffmpeg -i audio.wav -f segment -segment_time 30 -c copy parts/out%09d.wav',shell=True)
  
  
  
  #subprocess.call('pip install SpeechRecognition',shell=True)
  
  
  
  
  
  pool = Pool(8) # Number of concurrent threads
  
  
  
  with open("api-key.json") as f:
  
      GOOGLE_CLOUD_SPEECH_CREDENTIALS = f.read()
  
  
  
  r = sr.Recognizer()
  
  files = sorted(os.listdir('parts/'))
  
  
  
  def transcribe(data):
  
      idx, file = data
  
      name = "parts/" + file
  
      print(name + " started")
  
      # Load audio file
  
      with sr.AudioFile(name) as source:
  
          audio = r.record(source)
  
      # Transcribe audio file
  
      text = r.recognize_google_cloud(audio, credentials_json=GOOGLE_CLOUD_SPEECH_CREDENTIALS)
  
      print(name + " done")
  
      return {
  
          "idx": idx,
  
          "text": text
  
      }
  
  
  
  all_text = pool.map(transcribe, enumerate(files))
  
  pool.close()
  
  pool.join()
  
  
  
  transcript = ""
  
  for t in sorted(all_text, key=lambda x: x['idx']):
  
      total_seconds = t['idx'] * 30
  
      # Cool shortcut from:
  
      # https://stackoverflow.com/questions/775049/python-time-seconds-to-hms
  
      # to get hours, minutes and seconds
  
      m, s = divmod(total_seconds, 60)
  
      h, m = divmod(m, 60)
  
  
  
      # Format time as h:m:s - 30 seconds of text
  
      transcript = transcript + "{:0>2d}:{:0>2d}:{:0>2d} {}\n".format(h, m, s, t['text'])
  
  
  
  print(transcript)
  
  
  
  with open("transcript.txt", "w") as f:
  
      f.write(transcript)
  
  
  
  f = open("transcript.txt")
  
  lines = f.readlines()
  
  f.close()
  
  f = open("transcript.txt", "w", encoding="utf-8")
  
  for line in lines:
  
      f.write(line[8:])
  
  f.close()

  The thing is above code works when i manually run the command -> python t/convert_english.py —audio t/tttttttttt.mp3 like this in the terminal..

  But when i try to run from the flask server itself it doesn’t works.. And I’m not getting an error either.