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• Running a py script in the Cloud

  12 January 2018, by Anay Bose

  I’m new to Google’s cloud & Virtual Machine(VM) instances, and I need some clarifications on a couple of points. I have a python script; it imports a long range of functions. I need to run those functions in parallel. I’m using multiprocessing and Process, not threads. These functions are basically image and media processors, and they use many other tools like FFMPEG, imagemagick and Avisynth in addition to a wide range of python modules, including moviepy. Now, I would like to run some 50 functions in parallel assigning a CPU for each process. Images, media and avi files are stored in seperate folders. I’m on Windows7 Core-i7 machine. So, need cloud computing power.

  Now, my question can I run such a python script/app in the cloud that requires a very complicated file system and non-python tools i.e. ffmpeg, avisynth and avi files?

  Can Google VMs emulate my local machine and empower me with more cores and memory to run such a program? if not, then what are my options? Is their any tutorials that I can follow? I need your suggestions. I have given below an example script and some codes to help facilitate your understanding about my situation.

  from __future__ import unicode_literals
  
  import youtube_dl
  
  import os
  
  import time
  
  import sys
  
  reload(sys)  
  
  sys.setdefaultencoding('utf-8')
  
  from multiprocessing import Process
  
  from utils import *
  
  
  
  from clip31 import VIDEO31
  
  from clip32 import VIDEO32
  
  from clip189 import VIDEO189
  
  from clip16 import VIDEO16
  
  from clip39 import VIDEO39
  
  
  
  
  
  if __name__== '__main__':
  
  
  
      # 1. CALLING A FUNCTION
  
      folder = "bodyforce3\\16"
  
      serial = "16"
  
      images = get_filepaths("../16")
  
      videos = get_filepaths("12__media")
  
      pngs = get_filepaths("../pngs")
  
  
  
      Process(target=VIDEO192, args=(folder, serial, color1, color2, color3, images, videos)).start()
  
  
  
  
  
      # 2. CALLING A FUNCTION
  
      folder = "bodyforce3\\20"
  
      serial = "20"
  
      images = get_filepaths("../20")
  
      videos = get_filepaths("18__media")
  
  
  
      Process(target=VIDEO32, args=(folder, serial, color1, color2, color3, images, videos)).start()
  
  
  
  
  
      # 3. CALLING A FUNCTION
  
      folder = "bodyforce3\\14"
  
      serial = "14"
  
      images = get_filepaths("../14")
  
      videos = get_filepaths("16__media")
  
  
  
      Process(target=VIDEO91, args=(folder, serial, color1, color2, color3, images, videos)).start()

  I copy avi files in functions like this:

  src = "clip50_files"
  
  src_files = os.listdir(src)
  
  for file_name in src_files:
  
      full_file_name = os.path.join(src, file_name)
  
      if (os.path.isfile(full_file_name)):
  
          shutil.copy(full_file_name, folder)

  I call ffmpeg commands like this, and they are included within py functions.

  ###########################
  
  #### FFMPEG OPERATIONS ####
  
  ###########################
  
  
  
  print "Starting FFMPEG operations ..."
  
  
  
  if os.path.isfile(os.path.join(folder, "bounce-(3).avi")):
  
      os.remove(os.path.join(folder, "bounce-(3).avi"))
  
  
  
  
  
  infile = folder + "/bounce-(3).avs"
  
  outfile = folder + "/bounce-(3).avi"
  
  codec = "rawvideo"
  
  pix_fmt = "bgra"
  
  
  
  try:
  
      subprocess.call(["ffmpeg",
  
                       "-i" ,infile, 
  
                       "-c:v" ,codec, 
  
                       "-pix_fmt", pix_fmt, 
  
                       outfile],
  
                      stdout=open(os.devnull, 'w'), 
  
                      stderr=subprocess.STDOUT)
  
  except subprocess.CalledProcessError as e:   
  
      #except subprocess.CalledProcessError as e:
  
      sys.exit(e.output)
  
  except OSError as e:
  
      sys.exit(e.strerror)
  
  
  
  
  
  print "FFMPEG operations ended"

• avcodec_decode_video2 fails to decode after frame resolution change

  10 April 2021, by Krzysztof Kansy

  I'm using ffmpeg in Android project via JNI to decode real-time H264 video stream. On the Java side I'm only sending the the byte arrays into native module. Native code is running a loop and checking data buffers for new data to decode. Each data chunk is processed with:
  

  



  int bytesLeft = data->GetSize();
int paserLength = 0;
int decodeDataLength = 0;
int gotPicture = 0;
const uint8_t* buffer = data->GetData();
while (bytesLeft > 0) {
    AVPacket packet;
    av_init_packet(&packet);
    paserLength = av_parser_parse2(_codecPaser, _codecCtx, &packet.data, &packet.size, buffer, bytesLeft, AV_NOPTS_VALUE, AV_NOPTS_VALUE, AV_NOPTS_VALUE);
    bytesLeft -= paserLength;
    buffer += paserLength;

    if (packet.size > 0) {
        decodeDataLength = avcodec_decode_video2(_codecCtx, _frame, &gotPicture, &packet);
    }
    else {
        break;
    }
    av_free_packet(&packet);
}

if (gotPicture) {
// pass the frame to rendering
}


  



  The system works pretty well until incoming video's resolution changes. I need to handle transition between 4:3 and 16:9 aspect ratios. While having AVCodecContext configured as follows:

  



  _codecCtx->flags2|=CODEC_FLAG2_FAST;
_codecCtx->thread_count = 2;
_codecCtx->thread_type = FF_THREAD_FRAME;

if(_codec->capabilities&CODEC_FLAG_LOW_DELAY){
    _codecCtx->flags|=CODEC_FLAG_LOW_DELAY;
}


  



  I wasn't able to continue decoding new frames after video resolution change. The got_picture_ptr flag that avcodec_decode_video2 enables when whole frame is available was never true after that.
  
This ticket made me wonder if the issue isn't connected with multithreading. Only useful thing I've noticed is that when I change thread_type to FF_THREAD_SLICE the decoder is not always blocked after resolution change, about half of my attempts were successfull. Switching to single-threaded processing is not possible, I need more computing power. Setting up the context to one thread does not solve the problem and makes the decoder not keeping up with processing incoming data.
  
Everything work well after app restart.
  

  



  I can only think of one workoround (it doesn't really solve the problem): unloading and loading the whole library after stream resolution change (e.g as mentioned in here). I don't think it's good tho, it will propably introduce other bugs and take a lot of time (from user's viewpoint).

  



  Is it possible to fix this issue?

  



  EDIT:
  
I've dumped the stream data that is passed to decoding pipeline. I've changed the resolution few times while stream was being captured. Playing it with ffplay showed that in moment when resolution changed and preview in application froze, ffplay managed to continue, but preview is glitchy for a second or so. You can see full ffplay log here. In this case video preview stopped when I changed resolution to 960x720 for the second time. (Reinit context to 960x720, pix_fmt: yuv420p in log).

  


• OpenCV 4.5.2 takes a long time (>100ms) to retrieve a single frame from a webcam, C++ on Windows 10

  9 June 2021, by Mustard Tiger

  I've been having a tough time getting my webcam working quickly with opencv. Frames take a very long time to read, (a recorded average of 124ms across 500 frames) I've tried on three different computers (running Windows 10) with a logitech C922 webcam. The most recent machine I tested on has a Ryzen 9 3950X, with 32gbs of ram; no lack of power.

  


  Here is the code:

  


  cv::VideoCapture cap = cv::VideoCapture(m_cameraNum);&#xA;&#xA;// Check if camera opened successfully&#xA;if (!cap.isOpened())&#xA;{&#xA;    m_logger->critical("Error opening video stream or file\n\r");&#xA;    return -1;&#xA;}&#xA;&#xA;bool result = true;&#xA;result &amp;= cap.set(cv::CAP_PROP_FRAME_WIDTH, 1280);&#xA;result &amp;= cap.set(cv::CAP_PROP_FRAME_HEIGHT, 720);&#xA;&#xA;bool ready = false;&#xA;std::vector<string> timeLog;&#xA;timeLog.reserve(50000);&#xA;int i = 0;&#xA;&#xA;while (i &lt; 500)&#xA;{&#xA;    auto start = std::chrono::system_clock::now();&#xA;    &#xA;    cv::Mat img;&#xA;    ready = cap.read(img);&#xA;&#xA;    // If the frame is empty, break immediately&#xA;    if (!ready)&#xA;    {&#xA;        timeLog.push_back("continue");&#xA;        continue;&#xA;    }&#xA;&#xA;    i&#x2B;&#x2B;;&#xA;    auto end = std::chrono::system_clock::now();&#xA;    timeLog.push_back(std::to_string(std::chrono::duration_cast(end - start).count()));&#xA;}&#xA;&#xA;for (auto&amp; entry : timeLog)&#xA;    m_logger->info(entry);&#xA;&#xA;cap.release();&#xA;return 0;&#xA;</string>

  


  Notice that I write the elapsed time to a log file at the end of execution. The average time is 124ms for debug and release, and not one instance of "continue" after half a dozen runs.

  


  It doesn't matter if I use USB 2 or USB 3 ports (the camera is USB2) or if I run a debug build or a release build, the log file will show anywhere from 110ms to 130ms of time for each frame. The camera works fine in other app, OBS can get a smooth 1080@30fps or 720@60fps.

  


  Stepping through the debugger and doing a lot of Googling, I've learned the following about my system:

  


  

  • The backend chosen by default is DSHOW. GStreamer and FFMPEG are also available.

  


  • DSHOW uses FFMPEG somehow (it needs the FFMPEG dll) but I cannot use FFMPEG directly through opencv. Attempting to use cv::VideoCapture(m_cameraNum, cv::CAP_FFMPEG) always fails. It seems like Opencv's interface to FFMPEG is only capable of opening video files.

  


  • Microsoft really screwed up camera devices in Windows a few years back, not sure if this is related to my problem.

  


  


  Here's a short list of the fixes I have tried, most taken from older SO posts:

  


  

  • result &= cap.set(cv::CAP_PROP_FRAME_COUNT, 30); // Returns false, does nothing

  


  • result &= cap.set(cv::CAP_PROP_CONVERT_RGB, 0); // Returns true, does nothing

  


  • result &= cap.set(cv::CAP_PROP_MODE, cv::VideoWriter::fourcc('M', 'J', 'P', 'G')); // Returns false, does nothing

  


  • Set registry key from http://alax.info/blog/1693 that should disable the new Windows camera server.

  


  • Updated from 4.5.0 to 4.5.2, no change.

  


  • Asked device manager to find a newer driver, no newer driver found.

  


  


  I'm out of ideas. Any help?