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• How do I properly enable ffmpeg for matplotlib.animation ?

  7 mars 2017, par spanishgum

  I have covered a lot of ground on stack so far trying to get ffmpeg going so I can make a timelapse video.

  I am on a CentOS 7 machine, running python3.7.0a0.

  python3
  
  >>> import numpy as np
  
  >>> np.__version__
  
  '1.12.0'
  
  >>> import matplotlib as mpl
  
  >>> mpl.__version__
  
  '2.0.0'
  
  >>> import mpl_toolkits.basemap as base
  
  >>> base.__version__
  
  '1.0.7'

  I found this github gist on installing ffmpeg. I used the chromium source, and installed without a prefix option (using the default).

  I have confirmed that ffmpeg is installed, although I don’t know anything about testing whether it works.

  which ffmpeg
  
  /usr/local/bin/ffmpeg
  
  
  
  ffmpeg -version
  
  ffmpeg version N-83533-gada281d Copyright (c) 2000-2017 the FFmpeg dev elopers
  
  built with gcc 4.8.5 (GCC) 20150623 (Red Hat 4.8.5-11
  
  configuration:
  
  libavutil      55. 47.100 / 55. 47.100
  
  libavcodec     57. 80.100 / 57. 80.100
  
  libavformat    57. 66.102 / 57. 66.102
  
  libavdevice    57.  2.100 / 57.  2.100
  
  libavfilter     6. 73.100 /  6. 73.100
  
  libswscale      4.  3.101 /  4.  3.101
  
  libswresample   2.  4.100 /  2.  4.100

  I tried to run a few sample examples I found online :

  [1] http://matplotlib.org/examples/animation/basic_example_writer.html

  [2] http://stackoverflow.com/a/23098090/3454650

  Everything works fine up until I try to save the animation file.

  [1]

   anim.save('basic_animation.mp4', writer = FFwriter, fps=30, extra_args=['-vcodec', 'libx264'])

  [2]

  im_ani.save('im.mp4', writer=writer)

  I found here that explictly setting the path to ffmpeg might be necessary so I added this to the top of the test scripts :

  plt.rcParams['animation.ffmpeg_path'] = '/usr/local/bin/ffmpeg'

  I tried a few more tweaks in the code but always get the same response, which I do not know how to begin deciphering :

  Traceback (most recent call last):
  
    File "testanim.py", line 27, in <module>
  
      writer.grab_frame()
  
    File "/usr/local/lib/python3.7/contextlib.py", line 100, in __exit__
  
      self.gen.throw(type, value, traceback)
  
    File "/usr/local/lib/python3.7/site-packages/matplotlib/animation.py", line 256, in saving
  
      self.finish()
  
    File "/usr/local/lib/python3.7/site-packages/matplotlib/animation.py", line 276, in finish
  
      self.cleanup()
  
    File "/usr/local/lib/python3.7/site-packages/matplotlib/animation.py", line 311, in cleanup
  
      out, err = self._proc.communicate()
  
    File "/usr/local/lib/python3.7/subprocess.py", line 836, in communicate
  
      stdout, stderr = self._communicate(input, endtime, timeout)
  
    File "/usr/local/lib/python3.7/subprocess.py", line 1474, in _communicate
  
      selector.register(self.stdout, selectors.EVENT_READ)
  
    File "/usr/local/lib/python3.7/selectors.py", line 351, in register
  
      key = super().register(fileobj, events, data)
  
    File "/usr/local/lib/python3.7/selectors.py", line 237, in register
  
      key = SelectorKey(fileobj, self._fileobj_lookup(fileobj), events, data)
  
    File "/usr/local/lib/python3.7/selectors.py", line 224, in _fileobj_lookup
  
      return _fileobj_to_fd(fileobj)
  
    File "/usr/local/lib/python3.7/selectors.py", line 39, in _fileobj_to_fd
  
      "{!r}".format(fileobj)) from None
  
  ValueError: Invalid file object: &lt;_io.BufferedReader name=6>
  
  </module>

  Is there something with my configuration that is malformed ? I searched google for this error for some time but never found anything relevant to animations / ffmpeg. Any help would be greatly appreciated.

  ---

  UPDATE :

  @LordNeckBeard pointed me here : https://trac.ffmpeg.org/wiki/CompilationGuide/Centos

  I ran into problems with installing the x264 encoding dependency. Some files in libavcodec/*.c (in the make output) were reporting undefined references to several functions. After a wild goose chase found this : https://mailman.videolan.org/pipermail/x264-devel/2015-February/010971.html

  To fix the x264 installation, I simply added some configure flags :

  ./configure --enable-static --enable-shared --extra-ldflags="-lswresample -llzma"

  ---

  UPDATE :

  So everything installed fine after fixing the libx264 problems. I went ahead and copied the ffmpeg binary from the ffmpeg_build folder into /usr/local/bin/ffmpeg.

  After running the script I was getting problems where ffmpeg could not find the libx264 shared object. I think I will have to recompile everything using different prefixes. My intuition tells me there are old files laying around after I have messed with everything, using some configuration that is broken.

  So I decided maybe I should just try to use NUX : http://linoxide.com/linux-how-to/install-ffmpeg-centos-7/
  I installed ffmpeg using the new rpm, but to no avail. I still was not able to run ffmpeg because of a missing shared object.

  Finally, instead of usiong files copied into my /usr/local/bin folder, I ran ffmpeg directly from the build bin directory. Turns out that this does work properly !

  So in essence, if I want to install ffmpeg system wide, I need to manually compile from sources again but using a nonlocal prefix.

• What is the reason for getting libavcodec AVpacket presentation time as 0 ?

  13 août 2019, par Chamara Manoj

  Recently I am using FFmpeg library with VS 2017 decode and encode some video data. I used the example codes given with FFmpeg lib packages, transcoding.c.

  After encoding the video I was trying to extract the frames of the encoded and muxed video.mp4. However, when I read the frames using av_read_frame (AVFormatContext *s, AVPacket *pkt), in the last received frame, pts and dts times are both 0.

  What could be the reason for this ? My Video is playing smoothly and I have used H265 codec.

• What is Google Analytics data sampling and what’s so bad about it ?

  16 août 2019, par Joselyn Khor — Analytics Tips, Development
  What is Google Analytics data sampling, and what’s so bad about it ?

  Google (2019) explains what data sampling is :

  “In data analysis, sampling is the practice of analysing a subset of all data in order to uncover the meaningful information in the larger data set.”[1]

  This is basically saying instead of analysing all of the data, there’s a threshold on how much data is analysed and any data after that will be an assumption based on patterns.

  Google’s (2019) data sampling thresholds :

  Ad-hoc queries of your data are subject to the following general thresholds for sampling :
  [Google] Analytics Standard : 500k sessions at the property level for the date range you are using
  [Google] Analytics 360 : 100M sessions at the view level for the date range you are using (para. 3) [2]

  This threshold is limiting because your data in GA may become more inaccurate as the traffic to your website increases.

  Say you’re looking through all your traffic data from the last year and find you have 5 million page views. Only 500K of that 5 million is accurate ! The data for the remaining 4.5 million (90%) is an assumption based on the 500K sample size.

  This is a key weapon Google uses to sell to large businesses. In order to increase that threshold for more accurate reporting, upgrading to premium Google Analytics 360 for approximately US$150,000 per year seems to be the only choice.

  What’s so bad about data sampling ?

  It’s unfair to say sampled data is to be disregarded completely. There is a calculation ensuring it is representative and can allow you to get good enough insights. However, we don’t encourage it as we don’t just want “good enough” data. We want the actual facts.

  In a recent survey sent to Matomo customers, we found a large proportion of users switched from GA to Matomo due to the data sampling issue.

  The two reasons why data sampling isn’t preferable : 

  1. If the selected sample size is too small, you won’t get a good representative of all the data. 
  2. The bigger your website grows, the more inaccurate your reports will become.

  An example of why we don’t fully trust sampled data is, say you have an ecommerce store and see your GA revenue reports aren’t matching the actual sales data, due to data sampling. In GA you may be seeing revenue for the month as $1 million, instead of actual sales of $800K.

  The sampling here has caused an inaccuracy that could have negative financial implications. What you get in the GA report is an estimated dollar figure rather than the actual sales. Making decisions based on inaccurate data can be costly in this case. 

  Another disadvantage to sampled data is that you might be missing out on opportunities you would’ve noticed if you were given a view of the whole. E.g. not being able to see real patterns occurring due to the data already being predicted. 

  By not getting a chance to see things as they are and only being able to jump to the conclusions and assumptions made by GA is risky. The bigger your business grows, the less you can risk making business decisions based on assumptions that could be inaccurate. 

  If you feel you could be missing out on opportunities because your GA data is sampled data, get 100% accurately reported data. 

  The benefits of 100% accurate data

  Matomo doesn’t use data sampling on any of our products or plans. You get to see all of your data and not a sampled data set.

  Data quality is necessary for high impact decision-making. It’s hard to make strategic changes if you don’t have confidence that your data is reliable and accurate.

  Learn about how Matomo is a serious contender to Google Analytics 360. 

  Now you can import your Google Analytics data directly into your Matomo

  If you’re wanting to make the switch to Matomo but worried about losing all your historic Google Analytics data, you can now import this directly into your Matomo with the Google Analytics Importer tool.

  
  Take the challenge !

  Compare your Google Analytics data (sampled data) against your Matomo data, or if you don’t have Matomo data yet, sign up to our 30-day free trial and start tracking !

  References :

  [1 & 2] About data sampling. (2019). In Analytics Help About data sampling. Retrieved August 14, 2019, from https://support.google.com/analytics/answer/2637192