Sur d’autres sites (8767)

• Reading in pydub AudioSegment from url. BytesIO returning "OSError [Errno 2] No such file or directory" on heroku only ; fine on localhost

  24 octobre 2014, par Mark

  EDIT 1 for anyone with the same error : installing ffmpeg did indeed solve that BytesIO error

  EDIT 1 for anyone still willing to help : my problem is now that when I AudioSegment.export("filename.mp3", format="mp3"), the file is made, but has size 0 bytes — details below (as "EDIT 1")

  ---

  EDIT 2 : All problems now solved.

  • Files can be read in as AudioSegment using BytesIO
  • I found buildpacks to ensure ffmpeg was installed correctly on my app, with lame support for exporting proper mp3 files

  Answer below

  ---

  Original question

  I have pydub working nicely locally to crop a particular mp3 file based on parameters in the url.
  (?start_time=3.8&end_time=5.1)

  When I run foreman start it all looks good on localhost. The html renders nicely.
  The key lines from the views.py include reading in a file from a url using

  url = "https://s3.amazonaws.com/shareducate02/The_giving_tree__by_Alex_Blumberg__sponsored_by_mailchimp-short.mp3"
  
  mp3 = urllib.urlopen(url).read() # inspired by http://nbviewer.ipython.org/github/ipython-books/cookbook-code/blob/master/notebooks/chapter11_image/06_speech.ipynb
  
  original=AudioSegment.from_mp3(BytesIO(mp3))  # AudioSegment.from_mp3 is a pydub command, see http://pydub.com
  
  section = original[start_time_ms:end_time_ms]

  That all works great... until I push to heroku (django app) and run it online.
  then when I load the same page now on the herokuapp.com, I get this error

  OSError at /path/to/page
  
  [Errno 2] No such file or directory
  
  Request Method: GET
  
  Request URL:    http://my.website.com/path/to/page?start_time=3.8&end_time=5
  
  Django Version: 1.6.5
  
  Exception Type: OSError
  
  Exception Value:    
  
  [Errno 2] No such file or directory
  
  Exception Location: /app/.heroku/python/lib/python2.7/subprocess.py in _execute_child, line 1327
  
  Python Executable:  /app/.heroku/python/bin/python
  
  Python Version: 2.7.8
  
  Python Path:    
  
  ['/app',
  
   '/app/.heroku/python/bin',
  
   '/app/.heroku/python/lib/python2.7/site-packages/setuptools-5.4.1-py2.7.egg',
  
   '/app/.heroku/python/lib/python2.7/site-packages/distribute-0.6.36-py2.7.egg',
  
   '/app/.heroku/python/lib/python2.7/site-packages/pip-1.3.1-py2.7.egg',
  
   '/app',
  
   '/app/.heroku/python/lib/python27.zip',
  
   '/app/.heroku/python/lib/python2.7',
  
   '/app/.heroku/python/lib/python2.7/plat-linux2',
  
   '/app/.heroku/python/lib/python2.7/lib-tk',
  
   '/app/.heroku/python/lib/python2.7/lib-old',
  
   '/app/.heroku/python/lib/python2.7/lib-dynload',
  
   '/app/.heroku/python/lib/python2.7/site-packages',
  
   '/app/.heroku/python/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg-info']
  
  
  
  
  
  Traceback:
  
  File "/app/.heroku/python/lib/python2.7/site-packages/django/core/handlers/base.py" in get_response
  
    112.                     response = wrapped_callback(request, *callback_args, **callback_kwargs)
  
  File "/app/evernote/views.py" in finalize
  
    105.       original=AudioSegment.from_mp3(BytesIO(mp3))
  
  File "/app/.heroku/python/lib/python2.7/site-packages/pydub/audio_segment.py" in from_mp3
  
    318.         return cls.from_file(file, 'mp3')
  
  File "/app/.heroku/python/lib/python2.7/site-packages/pydub/audio_segment.py" in from_file
  
    302.         retcode = subprocess.call(convertion_command, stderr=open(os.devnull))
  
  File "/app/.heroku/python/lib/python2.7/subprocess.py" in call
  
    522.     return Popen(*popenargs, **kwargs).wait()
  
  File "/app/.heroku/python/lib/python2.7/subprocess.py" in __init__
  
    710.                                 errread, errwrite)
  
  File "/app/.heroku/python/lib/python2.7/subprocess.py" in _execute_child
  
    1327.                 raise child_exception

  I have commented out some of the original to convince myself that sure enough the single line original=AudioSegment.from_mp3(BytesIO(mp3)) is where the problem kicks in... but this is not a problem locally

  The full function in views.py starts like this :

  from django.shortcuts import render, get_object_or_404 
  
  from django.http import HttpResponseRedirect #, Http404, HttpResponse
  
  from django.core.urlresolvers import reverse
  
  from django.views import generic
  
  import pydub
  
  # Maybe only need: 
  
  from pydub import AudioSegment # == see below
  
  from time import gmtime, strftime
  
  
  
  import boto
  
  from boto.s3.connection import S3Connection
  
  from boto.s3.key import Key
  
  
  
  # http://nbviewer.ipython.org/github/ipython-books/cookbook-code/blob/master/notebooks/chapter11_image/06_speech.ipynb
  
  import urllib
  
  from io import BytesIO
  
  # import numpy as np
  
  # import scipy.signal as sg
  
  # import pydub # mentioned above already
  
  # import matplotlib.pyplot as plt
  
  # from IPython.display import Audio, display
  
  # import matplotlib as mpl
  
  # %matplotlib inline
  
  
  
  import os
  
  # from settings import AWS_ACCESS_KEY, AWS_SECRET_KEY, AWS_BUCKET_NAME
  
  AWS_ACCESS_KEY = os.environ.get('AWS_ACCESS_KEY') # there must be a better way?
  
  AWS_SECRET_KEY = os.environ.get('AWS_SECRET_KEY')
  
  AWS_BUCKET_NAME = os.environ.get('S3_BUCKET_NAME')
  
  
  
  # http://stackoverflow.com/questions/415511/how-to-get-current-time-in-python
  
  
  
  boto_conn = S3Connection(AWS_ACCESS_KEY, AWS_SECRET_KEY)
  
  bucket = boto_conn.get_bucket(AWS_BUCKET_NAME)
  
  s3_url_format = 'https://s3.amazonaws.com/shareducate02/{end_path}'

  and specifically the view in views.py that’s called when I visit the page :

  def finalize(request):
  
  
  
      start_time = request.GET.get('start_time')
  
  
  
      end_time = request.GET.get('end_time')
  
  
  
      original_file = "https://s3.amazonaws.com/shareducate02/The_giving_tree__by_Alex_Blumberg__sponsored_by_mailchimp-short.mp3"
  
  
  
  
  
      if start_time:
  
  
  
        # original=AudioSegment.from_mp3(original_file)  #...that didn't work 
  
        # but this works below:
  
  
  
        # next three uncommented lines from http://nbviewer.ipython.org/github/ipython-books/cookbook-code/blob/master/notebooks/chapter11_image/06_speech.ipynb
  
        # python 2.x
  
        url = original_file
  
        # req = urllib.Request(url, headers={'User-Agent': ''}) # Note: I commented out this because I got error that "Request" did not exist
  
        mp3 = urllib.urlopen(url).read()
  
        # That's for my 2.7
  
  
  
        # If I ever upgrade to python 3.x, would need to change it to:
  
        # req = urllib.request.Request(url, headers={'User-Agent': ''}) 
  
        # mp3 = urllib.request.urlopen(req).read()
  
        # as per instructions on http://nbviewer.ipython.org/github/ipython-books/cookbook-code/blob/master/notebooks/chapter11_image/06_speech.ipynb
  
  
  
        original=AudioSegment.from_mp3(BytesIO(mp3))
  
        # original=AudioSegment.from_mp3("static/givingtree.mp3") # alternative that works locally (on laptop) but no use for heroku
  
  
  
        start_time_ms = int(float(start_time) * 1000)
  
        if end_time:
  
          end_time_ms = int(float(end_time) * 1000)
  
        else:
  
          end_time_ms = int(float(original.duration_seconds) * 1000)
  
        duration_ms = end_time_ms - start_time_ms
  
        # duration = end_time - start_time
  
        duration = duration_ms/1000
  
  
  
     #   section = original[start_time_ms:end_time_ms]
  
     #   section_with_fading = section.fade_in(100).fade_out(100)
  
  
  
        clip = "demo-"
  
        number = strftime("%Y-%m-%d_%H-%M-%S", gmtime())
  
        clip += number
  
        clip += ".mp3" 
  
  
  
        # DON'T BOTHER writing locally:
  
        # clip_with_path = "evernote/static/"+clip
  
        # section_with_fading.export(clip_with_path, format = "mp3")
  
  
  
     #   tempclip = section_with_fading.export(format = "mp3")
  
  
  
        # commented out while de-bugging, but was working earlier if run on localhost
  
        # c = boto.connect_s3()
  
        # b = c.get_bucket(S3_BUCKET_NAME)  # as defined above
  
        # k = Key(b)
  
        # k.key=clip
  
        # # k.set_contents_from_filename(clip_with_path)
  
        # k.set_contents_from_file(tempclip)
  
        # k.set_acl('public-read')
  
        clip_made = True
  
      else: 
  
        duration = 0.0
  
        clip_made = False
  
        clip = ""
  
      context = {'original_file':original_file, 'new_file':clip, 'start_time': start_time, 'end_time':end_time, 'duration':duration, 'clip_made':clip_made} 
  
      return render(request, 'finalize.html' , context) 

  Any suggestions ?

  Potentially related :
  I have ffmpeg installed locally

  But have been unable to install it onto heroku, due to not understanding buildpacks. I tried just a moment ago (http://stackoverflow.com/questions/14407388/how-to-install-ffmpeg-for-a-django-app-on-heroku and https://github.com/shunjikonishi/heroku-buildpack-ffmpeg) but so far ffmpeg is not working on heroku (ffmpeg is not recognised when I do "heroku run ffmpeg —version")
  ...do you think this is the reason ?

  An answer like any of these would be much appreciated as I’m going round in circles here :

  1. "I think ffmpeg is indeed your problem. Try harder to sort that out, to get it installed on heroku"
  2. "Actually, I think this is why BytesIO is not working for you : ..."
  3. "Your approach is terrible anyway... if you want to read in an audio file to process using pydub, you should just do this instead : ..." (since I’m just hacking my way through pydub for my first time... my approach may be poor)

  ---

  EDIT 1

  ffmpeg is now installed (e.g., I can output wav files)

  However, I can’t create mp3 files, still... or more correctly, I can, but the filesize is zero

  (venv-app)moriartymacbookair13:getstartapp macuser$ heroku config:add BUILDPACK_URL=https://github.com/ddollar/heroku-buildpack-multi.git 
  
  Setting config vars and restarting awe01... done, v93
  
  BUILDPACK_URL: https://github.com/ddollar/heroku-buildpack-multi.git
  
  (venv-app)moriartymacbookair13:getstartapp macuser$ vim .buildpacks 
  
  (venv-app)moriartymacbookair13:getstartapp macuser$ cat .buildpacks 
  
  https://github.com/shunjikonishi/heroku-buildpack-ffmpeg.git
  
  https://github.com/heroku/heroku-buildpack-python.git
  
  (venv-app)moriartymacbookair13:getstartapp macuser$ git add --all
  
  (venv-app)moriartymacbookair13:getstartapp macuser$ git commit -m "need multi, not just ffmpeg, so adding back in multi + shun + heroku, with trailing .git in .buildpacks file"
  
  [master cd99fef] need multi, not just ffmpeg, so adding back in multi + shun + heroku, with trailing .git in .buildpacks file
  
   1 file changed, 2 insertions(+), 2 deletions(-)
  
  (venv-app)moriartymacbookair13:getstartapp macuser$ git push heroku master
  
  Fetching repository, done.
  
  Counting objects: 5, done.
  
  Delta compression using up to 4 threads.
  
  Compressing objects: 100% (3/3), done.
  
  Writing objects: 100% (3/3), 372 bytes | 0 bytes/s, done.
  
  Total 3 (delta 2), reused 0 (delta 0)
  
  
  
  -----> Fetching custom git buildpack... done
  
  -----> Multipack app detected
  
  =====> Downloading Buildpack: https://github.com/shunjikonishi/heroku-buildpack-ffmpeg.git
  
  =====> Detected Framework: ffmpeg
  
  -----> Install ffmpeg
  
         DOWNLOAD_URL =  http://flect.github.io/heroku-binaries/libs/ffmpeg.tar.gz
  
         exporting PATH and LIBRARY_PATH
  
  =====> Downloading Buildpack: https://github.com/heroku/heroku-buildpack-python.git
  
  =====> Detected Framework: Python
  
  -----> Installing dependencies with pip
  
         Cleaning up...
  
  
  
  -----> Preparing static assets
  
         Collectstatic configuration error. To debug, run:
  
         $ heroku run python ./example/manage.py collectstatic --noinput
  
  
  
  Using release configuration from last framework (Python).
  
  -----> Discovering process types
  
         Procfile declares types -> web
  
  
  
  -----> Compressing... done, 198.1MB
  
  -----> Launching... done, v94
  
         http://[redacted].herokuapp.com/ deployed to Heroku
  
  
  
  To git@heroku.com:awe01.git
  
     78d6b68..cd99fef  master -> master
  
  (venv-app)moriartymacbookair13:getstartapp macuser$ heroku run ffmpeg
  
  Running `ffmpeg` attached to terminal... up, run.6408
  
  ffmpeg version git-2013-06-02-5711e4f Copyright (c) 2000-2013 the FFmpeg developers
  
    built on Jun  2 2013 07:38:40 with gcc 4.4.3 (Ubuntu 4.4.3-4ubuntu5.1)
  
    configuration: --enable-shared --disable-asm --prefix=/app/vendor/ffmpeg
  
    libavutil      52. 34.100 / 52. 34.100
  
    libavcodec     55. 13.100 / 55. 13.100
  
    libavformat    55.  8.102 / 55.  8.102
  
    libavdevice    55.  2.100 / 55.  2.100
  
    libavfilter     3. 74.101 /  3. 74.101
  
    libswscale      2.  3.100 /  2.  3.100
  
    libswresample   0. 17.102 /  0. 17.102
  
  Hyper fast Audio and Video encoder
  
  usage: ffmpeg [options] [[infile options] -i infile]... {[outfile options] outfile}...
  
  
  
  Use -h to get full help or, even better, run 'man ffmpeg'
  
  (venv-app)moriartymacbookair13:getstartapp macuser$ heroku run bash
  
  Running `bash` attached to terminal... up, run.9660
  
  ~ $ python
  
  Python 2.7.8 (default, Jul  9 2014, 20:47:08) 
  
  [GCC 4.4.3] on linux2
  
  Type "help", "copyright", "credits" or "license" for more information.
  
  >>> import pydub
  
  >>> from pydub import AudioSegment
  
  >>> exit()
  
  ~ $ which ffmpeg
  
  /app/vendor/ffmpeg/bin/ffmpeg
  
  ~ $ python 
  
  
  
  Python 2.7.8 (default, Jul  9 2014, 20:47:08) 
  
  [GCC 4.4.3] on linux2
  
  Type "help", "copyright", "credits" or "license" for more information.
  
  >>> import pydub
  
  >>> from pydub import AudioSegment
  
  >>> AudioSegment.silent(5000).export("/tmp/asdf.mp3", "mp3")
  
  <open file="file"></open>tmp/asdf.mp3', mode 'wb+' at 0x7f9a37d44780>
  
  >>> exit ()
  
  ~ $ cd /tmp/
  
  /tmp $ ls
  
  asdf.mp3
  
  /tmp $ open asdf.mp3
  
  bash: open: command not found
  
  /tmp $ ls -lah
  
  total 8.0K
  
  drwx------  2 u36483 36483 4.0K 2014-10-22 04:14 .
  
  drwxr-xr-x 14 root   root  4.0K 2014-09-26 07:08 ..
  
  -rw-------  1 u36483 36483    0 2014-10-22 04:14 asdf.mp3

  Note the file size of 0 above for the mp3 file... when I do the same thing on my macbook, the file size is never zero

  Back to the heroku shell :

  /tmp $ python
  
  Python 2.7.8 (default, Jul  9 2014, 20:47:08) 
  
  [GCC 4.4.3] on linux2
  
  Type "help", "copyright", "credits" or "license" for more information.
  
  >>> import pydub
  
  >>> from pydub import AudioSegment
  
  >>> pydub.AudioSegment.ffmpeg = "/app/vendor/ffmpeg/bin/ffmpeg" 
  
  >>> AudioSegment.silence(1200).export("/tmp/herokuSilence.mp3", format="mp3")
  
  Traceback (most recent call last):
  
    File "<stdin>", line 1, in <module>
  
  AttributeError: type object 'AudioSegment' has no attribute 'silence'
  
  >>> AudioSegment.silent(1200).export("/tmp/herokuSilence.mp3", format="mp3")
  
  <open file="file"></open>tmp/herokuSilence.mp3', mode 'wb+' at 0x7fcc2017c780>
  
  >>> exit()
  
  /tmp $ ls
  
  asdf.mp3  herokuSilence.mp3
  
  /tmp $ ls -lah
  
  total 8.0K
  
  drwx------  2 u36483 36483 4.0K 2014-10-22 04:29 .
  
  drwxr-xr-x 14 root   root  4.0K 2014-09-26 07:08 ..
  
  -rw-------  1 u36483 36483    0 2014-10-22 04:14 asdf.mp3
  
  -rw-------  1 u36483 36483    0 2014-10-22 04:29 herokuSilence.mp3
  
  </module></stdin>

  I realised the first time that I had forgotten the pydub.AudioSegment.ffmpeg = "/app/vendor/ffmpeg/bin/ffmpeg" command, but as you can see above, the file is still zero size

  Out of desperation, I even tried adding the ".heroku" into the path to be as verbatim as your example, but that didn’t fix it :

  /tmp $ python
  
  Python 2.7.8 (default, Jul  9 2014, 20:47:08) 
  
  [GCC 4.4.3] on linux2
  
  Type "help", "copyright", "credits" or "license" for more information.
  
  >>> import pydub
  
  >>> from pydub import AudioSegment
  
  >>> pydub.AudioSegment.ffmpeg = "/app/.heroku/vendor/ffmpeg/bin/ffmpeg"
  
  >>> AudioSegment.silent(1200).export("/tmp/herokuSilence03.mp3", format="mp3")
  
  <open file="file"></open>tmp/herokuSilence03.mp3', mode 'wb+' at 0x7fc92aca7780>
  
  >>> exit()
  
  /tmp $ ls -lah
  
  total 8.0K
  
  drwx------  2 u36483 36483 4.0K 2014-10-22 04:31 .
  
  drwxr-xr-x 14 root   root  4.0K 2014-09-26 07:08 ..
  
  -rw-------  1 u36483 36483    0 2014-10-22 04:14 asdf.mp3
  
  -rw-------  1 u36483 36483    0 2014-10-22 04:31 herokuSilence03.mp3
  
  -rw-------  1 u36483 36483    0 2014-10-22 04:29 herokuSilence.mp3

  Finally, I tried exporting a .wav file to check pydub was at least working correctly

  /tmp $ python
  
  Python 2.7.8 (default, Jul  9 2014, 20:47:08) 
  
  [GCC 4.4.3] on linux2
  
  Type "help", "copyright", "credits" or "license" for more information.
  
  >>> import pydub
  
  >>> from pydub import AudioSegment
  
  >>> pydub.AudioSegment.ffmpeg = "/app/vendor/ffmpeg/bin/ffmpeg"
  
  >>> AudioSegment.silent(1300).export("/tmp/heroku_wav_silence01.wav", format="wav")
  
  <open file="file"></open>tmp/heroku_wav_silence01.wav', mode 'wb+' at 0x7fa33cbf3780>
  
  >>> exit()
  
  /tmp $ ls
  
  asdf.mp3  herokuSilence03.mp3  herokuSilence.mp3  heroku_wav_silence01.wav
  
  /tmp $ ls -lah
  
  total 40K
  
  drwx------  2 u36483 36483 4.0K 2014-10-22 04:42 .
  
  drwxr-xr-x 14 root   root  4.0K 2014-09-26 07:08 ..
  
  -rw-------  1 u36483 36483    0 2014-10-22 04:14 asdf.mp3
  
  -rw-------  1 u36483 36483    0 2014-10-22 04:31 herokuSilence03.mp3
  
  -rw-------  1 u36483 36483    0 2014-10-22 04:29 herokuSilence.mp3
  
  -rw-------  1 u36483 36483  29K 2014-10-22 04:42 heroku_wav_silence01.wav
  
  /tmp $ 

  At least that filesize for .wav is non-zero, so pydub is working

  My current theory is that either I’m still not using ffmpeg correctly, or it’s insufficient... maybe I need an mp3 additional install on top of basic ffmpeg.

  Several sites mention "libavcodec-extra-53" but I’m not sure how to install that on heroku, or to check if I have it ? https://github.com/jiaaro/pydub/issues/36
  Similarly tutorials on libmp3lame seem to be geared towards laptop installation rather than installation on heroku, so I’m at a loss http://superuser.com/questions/196857/how-to-install-libmp3lame-for-ffmpeg

  In case relevant, I also have youtube-dl in my requirements.txt... this also works locally on my macbook, but fails when I run it in the heroku shell :

  ~/ytdl $ youtube-dl --restrict-filenames -x --audio-format mp3 n2anDgdUHic
  
  [youtube] Setting language
  
  [youtube] Confirming age
  
  [youtube] n2anDgdUHic: Downloading webpage
  
  [youtube] n2anDgdUHic: Downloading video info webpage
  
  [youtube] n2anDgdUHic: Extracting video information
  
  [download] Destination: Boyce_Avenue_feat._Megan_Nicole_-_Skyscraper_Patrick_Ebert_Edit-n2anDgdUHic.m4a
  
  [download] 100% of 5.92MiB in 00:00
  
  [ffmpeg] Destination: Boyce_Avenue_feat._Megan_Nicole_-_Skyscraper_Patrick_Ebert_Edit-n2anDgdUHic.mp3
  
  ERROR: audio conversion failed: Unknown encoder 'libmp3lame'
  
  ~/ytdl $ 

  The informative link is that it too specificies an mp3 failure, so perhaps they two issues are related.

  ---

  EDIT 2

  See answer, all problems solved

• On-premise analytics demand grows as Google Analytics GDPR uncertainties continue

  7 janvier 2020, par Jake Thornton — Privacy

  The Google Analytics GDPR relationship is a complicated one. Website owners in states like Berlin in Germany are now required to ask users for consent to collect their data. This doesn’t make for the friendliest user-experience and often the website visitor will simply click “no.”

  The problem Google Analytics now presents website owners in the EU is with more visitors clicking “no”, the less accurate your data will become.

  Why do you need to ask your visitors for consent ?

  At this stage it’s simply because Google Analytics collects data for its own purposes. An example of this is using your visitor’s personal data for retargeting purposes across their advertising platforms like Google Ads and YouTube. 

  Google’s Privacy & Terms states : “when you visit a website that uses advertising services like AdSense, including analytics tools like Google Analytics, or embeds video content from YouTube, your web browser automatically sends certain information to Google. This includes the URL of the page you’re visiting and your IP address. We may also set cookies on your browser or read cookies that are already there. Apps that use Google advertising services also share information with Google, such as the name of the app and a unique identifier for advertising.”

  

  The rise of hosting web analytics on-premise

  Managing Google Analytics and GDPR can quickly become complicated, so there’s been an increase in website owners switching from cloud-hosted web analytics platforms, like Google Analytics, to more GDPR compliant alternatives, where you can host web analytics software on your own servers. This is called hosting web analytics on-premise.

  Hosting web analytics on your own servers means :

  No third-parties are involved

  The visitor data your website collects is stored on your own internal infrastructure. This means no third-parties are involved and there’s no risk of personal data being used in the way Google Analytics uses it e.g. sending personal data to its advertising platforms. 

  When you sign up with Google Analytics you sign away control of your user’s personal data. With on-premise website analytics, you own your data and are in full control.

  NOTE : Though Google Analytics uses personal data for its own purposes, not all cloud hosted web analytics platforms do this. As an example, Matomo Analytics Cloud hosted solution states that all personal data collected is not used for its own purposes and that Matomo has no rights in accessing or using this personal data. 

  

  You control where in the world your personal data is stored

  Google Analytics servers are based out of USA, Europe and Asia, so where your personal data will end up is uncertain and you don’t have the option to choose which location it goes to when using free Google Analytics.

  Different countries have different laws when it comes to accessing personal data. When you choose to host your web analytics on-premise, you can choose the location of your servers and where the personal data is stored.

  More flexibility

  With self-hosted web analytics platforms like Matomo On-Premise, you can extend the platform to do anything you want without the restrictions that cloud hosted platforms impose.

  You can :

  • Get full access to the source code of open-source solutions, like Matomo
  • Extend the platform however you want for your business
  • Get access to APIs
  • Have no data limitations or restrictions
  • Get RAW data access
  • Have control over security

  >> Read more about on-premise flexibility for web analytics here

  

  So what does the future look like for Google Analytics and GDPR ?

  It’s difficult to assess this right now. How exactly GDPR is enforced is still quite unclear. 

  What is clear however, is now website owners in Berlin using Google Analytics are lawfully required to ask their visitors for consent to collect personal data. It has been reported that Google Analytics has already received 200,000 complaints in Germany alone and it appears this trend is likely to continue across much of the EU.

  When using Google Analytics in the EU you must also ensure your privacy policy is updated so website visitors are aware that data is being collected through Google Analytics for its own purposes.

  Moving to a web analytics on-premise platform

  Matomo Analytics is the #1 open-source web analytics platform in the world and has been rated as an exceptional alternative to Google Analytics. Check the reviews on Capterra.

  Choosing Matomo On-Premise means you can control exactly where your data is stored, you have full flexibility to customise the platform to do what you want and it’s FREE.

  Matomo’s mission is to give control back to website owners and the team has designed the platform so that moving away from Google Analytics is seamless. Matomo offers most of your favourite Google Analytics features, a leaner interface to navigate, and the option to add free and paid premium features that Google Analytics can’t even offer you.

  And now you can import your historical Google Analytics data directly into your Matomo with the Google Analytics Importer plugin.

  DOWNLOAD MATOMO (FREE)

  And if you can’t host web analytics on your own servers ...

  Hosting web analytics on-premise is not an option for all businesses as you do need the internal infrastructure and technical knowledge to host your own platform.

  If you can’t self-host, then Matomo has a Cloud hosted solution you can easily install and operate like Google Analytics, which is hosted on Matomo’s servers in the EU. 

  The GDPR advantages of choosing Matomo Cloud over Google Analytics are :

  • Servers are secure and based in the EU (strict laws forbid outside access)
  • 100% data ownership – we never use data for our own purposes
  • You can export your data anytime and switch to Matomo On-Premise whenever you like
  • User-privacy protection
  • Advanced GDPR Manager and data anonymisation features which GA doesn’t offer

  

  Interested to learn more ?

  If you are wanting to learn more about why users are making the move from Google Analytics to Matomo, check out our Matomo Analytics vs Google Analytics comparison page.

  >> Matomo Analytics vs Google Analytics

• JavaCV Create Compatible MP4

  15 juin 2017, par Hamish258

  Trying to modify JavaCV 3.2.0 sample https://github.com/bytedeco/javacv/blob/master/samples/WebcamAndMicrophoneCapture.java, to produce an mp4 that quicktime on macOS 10.12.5 can use. Output mp4 works fine with VLC but for the software I’m producing I’d like to minimise users having to install additional products.

  The sample code produces the following output

  [libx264 @ 0x7f927794e200] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX
[libx264 @ 0x7f927794e200] profile Constrained Baseline, level 3.1
[libx264 @ 0x7f927794e200] 264 - core 148 - H.264/MPEG-4 AVC codec - Copyleft 2003-2016 - http://www.videolan.org/x264.html - options: cabac=0 ref=1 deblock=0:0:0 analyse=0:0 me=dia subme=0 psy=1 psy_rd=1.00:0.00 mixed_ref=0 me_range=16 chroma_me=1 trellis=0 8x8dct=0 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=0 threads=4 lookahead_threads=4 sliced_threads=1 slices=4 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=0 weightp=0 keyint=60 keyint_min=6 scenecut=0 intra_refresh=0 rc=crf mbtree=0 crf=28.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=0
Output #0, mp4, to 'alatest.mp4':
 Metadata:
   encoder         : Lavf57.56.100
   Stream #0:0: Video: h264 (Constrained Baseline) ([33][0][0][0] / 0x0021), yuv420p, 1280x720, q=2-31, 2000 kb/s, 15360 tbn
   Stream #0:1: Audio: aac (LC) ([64][0][0][0] / 0x0040), 44100 Hz, stereo fltp, 192 kb/s

  The constrained baseline to 3.1 should produce usable mp4 according to https://trac.ffmpeg.org/wiki/Encode/H.264

  If I use the command line ffmpeg -i alatest.mp4 -pix_fmt yuv420p alantest.mp4 it produces a usable mo4, even though as you can see above yuv420p is the pixel format in use so there’s something else I don’t understand, the code snippet from the sample link is :

     FFmpegFrameRecorder recorder = new FFmpegFrameRecorder("alatest.mp4",1280, 720, 2);
   recorder.setInterleaved(true);
   recorder.setVideoOption("tune", "zerolatency");
   recorder.setVideoOption("preset", "ultrafast");
   recorder.setVideoOption("crf", "28");
   recorder.setVideoBitrate(2000000);
   recorder.setVideoCodec(avcodec.AV_CODEC_ID_H264);
   recorder.setPixelFormat(avutil.AV_PIX_FMT_YUV420P);
   recorder.setFormat("flv");
   recorder.setFrameRate(30);
   recorder.setGopSize(60);

  The command line ffmpeg is displaying

  [libx264 @ 0x7ffca4019400] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX
[libx264 @ 0x7ffca4019400] profile High, level 3.1
[libx264 @ 0x7ffca4019400] 264 - core 148 - H.264/MPEG-4 AVC codec - Copyleft 2003-2016 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=6 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
Output #0, mp4, to 'alantest.mp4':
 Metadata:
   encoder         : Lavf57.71.100
   Stream #0:0: Video: h264 (libx264) ([33][0][0][0] / 0x0021), yuv420p, 1280x720, q=-1--1, 30 fps, 15360 tbn, 30 tbc
   Metadata:
     encoder         : Lavc57.89.100 libx264
   Side data:
     cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
   Stream #0:1: Audio: aac (LC) ([64][0][0][0] / 0x0040), 44100 Hz, stereo, fltp, 128 kb/s
   Metadata:
     encoder         : Lavc57.89.100 aac
frame=  179 fps= 54 q=-1.0 Lsize=     570kB time=00:00:05.94 bitrate= 786.2kbits/s dup=93 drop=0 speed= 1.8x
video:470kB audio:93kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 1.341890%

  This is using a High profile and I see q being set differently and tbc. I can’t figure out how to mimic this behaviour in JavaCV, all help greatly appreciated !