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• 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 ?

• Evolution #3819 : Pouvoir demander un module PHP dans paquet.xml

  7 février 2017

  Hum ça ça n’ennuie plus de backporter par contre.

  Par ailleurs ce n’est pas compliqué à intégrer. Ci-joint un patch rapide.

  J’ai testé en mettant dans z-core :
  - <necessite nom="php:curl"></necessite> OK
  - <necessite nom="php:CURL"></necessite> OK
  - <necessite nom="php:curly"></necessite> Pas OK (normal)

  Dans ce dernier cas, l’erreur affichée est :

  • Impossible d’activer le plugin ../plugins/zone/z-core
    • Nécessite le plugin PHP:CURLY

  Par contre, si on met juste ’php’ il indique bien :

  • Le plugin Z-core dépend de PHP [8.0 ;]

  Donc il faudrait ajouter une chaine de langue pour les extensions PHP aussi je suppose.

• Fail to restream with nginx-rtmp-module

  19 mai 2017, par Victor Ponomarenko

  I’m unable to start restream using command exec. Also I tried exec_pull.
  It didn’t help. My target is to restream rtmp://ktv.s4c.link/live/livestream url to my local nginx, to rtmp://localhost:1935/hls.
  /tmp/logs/ffmpeg.log is empty.
  I guess that exec not even called, but why ?

      rtmp {
  
  
  
      server {
  
      listen 1935;
  
      chunk_size 4096;
  
  
  
      application live {
  
          allow play all;
  
          live on;
  
          record off;
  
          #pull rtmp://ktv.s4c.link/live/livestream;
  
          exec ffmpeg -i rtmp://localhost:1935/live -f flv rtmp://localhost:1935/hls 2>>/tmp/logs/ffmpeg.log;
  
      }
  
  
  
          application hls {
  
          allow play all;
  
          live on;
  
          record off;
  
      }
  
  
  
      }

  I’m using nginx-1.12.0.
  I followed by this tutorial, watched this