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• Getting ffprobe or avprobe not found while using youtube_dl module

  26 décembre 2016, par Avinash

  import youtube_dl
  
  
  
  
  
  options = {
  
      'format':'bestaudio/best',
  
      'extractaudio':True,
  
      'audioformat': 'mp3',
  
      'outtmpl':'%(id)s.%(ext)s',
  
      'noplaylist':True,
  
      'nocheckcertificate':True,
  
      'postprocessors': [{
  
          'key': 'FFmpegExtractAudio',
  
          'preferredcodec': 'mp3',
  
          'preferredquality': '192',
  
      }],
  
  
  
  }
  
  
  
  with youtube_dl.YoutubeDL(options) as ydl:
  
      ydl.download(['http://www.youtube.com/watch?v=BaW_jenozKc'])

  I am Getting

  "youtube_dl.utils.DownloadError : ERROR : ffprobe or avprobe not found.
  Please install one."

  I downloaded ffmpeg and tried giving its bin folder location in path variable . I also tried copying that bin folder to my youtube_dl package folder. None of them worked.

  Thanks in advance.

• nginx-rtmp module with ffmpeg

  1er janvier 2017, par sara

  I am new in video live streaming.I searched and found nginx-rtmp module to create a my media server,
  when i saw that ,
  i understood that we can run ffmpeg command in ngnix to transcode my video , or create a hls-variants , and this commands apply on videos on the fly . am i true ?
  
  if it is true , so with large video it takes a long time to tarnscode on the fly .so i wanna to execute my ffmpeg command when i sotre my video in my hls file path. so i create a hls files(.ts) first with running ffmpeg commands.and then i serve my files with ngnix-rtmp module.
  
  now my question is this 2 approaches(run async and sync(on the fly) ffmpeg command ) are true ?
  i saw a lot of example that implement first approach.and i interested in using second approach .second approach is not a common approach ?why ?is this approach has a problem and issue that i am not aware of that ?
  tnx

• Could not read frame error when trying to decompress mp4 file with ffmpeg and Python's threading module

  23 janvier 2017, par mdornfe1

  I’m training constitutional neural networks with video data. So far the bottle neck of my application is decompressing the mp4 files before passing the images to the CNN for training. I had the idea to try to have multiple cpu threads decompress the images concurrently and having one thread pass images to the CNN for training. I made a class VideoStream which makes connection to the mp4 file using the ImageIO module which is built on top of ffmpeg. The structure of my program is a follows :

  1) Generate random ints which represent the frame numbers of the mp4 file that will be used in training. Store these ints in list frame_idxs.

  2) Pass this list of ints and an empty list called frame_queue to the worker function decompress_video_data.

  3) Each worker function makes a connection to the mp4 file using VideoStream.

  4) Each worker function then pops of elements of frame_idxs, decompresses that frame, and then stores that frame as numpy array in list frame_queue.

  Here is the code

  import numpy as np
  
  import os, threading, multiprocessing
  
  
  
  
  
  def decompress_video_data(frame_queue, frame_idxs, full_path):
  
      vs = VideoStream(full_path)
  
      while len(frame_idxs) >1 0:
  
          i = frame_idxs.pop()
  
          frame = vs[i]
  
          frame_queue.append(frame)
  
  
  
  video_folder = '/mnt/data_drive/frame_viewer_client'
  
  video_files = os.listdir(video_folder)
  
  video_file = video_files[0]
  
  full_path = os.path.join(video_folder, video_file)
  
  vs = VideoStream(full_path)
  
  
  
  num_samples = 1000
  
  batch_size = 1
  
  frame_queue = []
  
  decompress_threads = []
  
  frame_idxs = list(np.random.randint(0, len(vs), 
  
      size = batch_size * num_samples))
  
  num_cores = multiprocessing.cpu_count()
  
  
  
  for n in range(num_cores - 1):
  
      decompress_thread = threading.Thread(target=decompress_video_data, 
  
          args=(frame_queue, frame_idxs, full_path))
  
      decompress_threads.append(decompress_thread)
  
      decompress_thread.start()

  The program will sucessfuly decompress approximately 200 frames, and then ImageIO will throw an RuntimeError : Could not read frame. The full error is here. Does anyone know why this is happening ? Is it possible to do what I’m trying to do ? Does ffmpeg just not work with multi threading ?