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• Announcing our latest open source project : DeviceDetector

  30 juillet 2014, par Stefan Giehl — Community, Development, Meta, DeviceDetector

  This blog post is an announcement for our latest open source project release : DeviceDetector ! The Universal Device Detection library will parse any User Agent and detect the browser, operating system, device used (desktop, tablet, mobile, tv, cars, console, etc.), brand and model.

  Read on to learn more about this exciting release.

  Why did we create DeviceDetector ?

  Our previous library UserAgentParser only had the possibility to detect operating systems and browsers. But as more and more traffic is coming from mobile devices like smartphones and tablets it is getting more and more important to know which devices are used by the websites visitors.

  To ensure that the device detection within Piwik will gain the required attention, so it will be as accurate as possible, we decided to move that part of Piwik into a separate project, that we will maintain separately. As an own project we hope the DeviceDetector will gain a better visibility as well as a better support by and for the community !

  DeviceDetector is hosted on GitHub at piwik/device-detector. It is also available as composer package through Packagist.

  How DeviceDetector works

  Every client requesting data from a webserver identifies itself by sending a so-called User-Agent within the request to the server. Those User Agents might contain several information such as :

  • client name and version (clients can be browsers or other software like feed readers, media players, apps,…)
  • operating system name and version
  • device identifier, which can be used to detect the brand and model.

  For Example :

  Mozilla/5.0 (Linux; Android 4.4.2; Nexus 5 Build/KOT49H) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/32.0.1700.99 Mobile Safari/537.36

  This User Agent contains following information :

  Operating system is Android 4.4.2, client uses the browser Chrome Mobile 32.0.1700.99 and the device is a Google Nexus 5 smartphone.

  What DeviceDetector currently detects

  DeviceDetector is able to detect bots, like search engines, feed fetchers, site monitors and so on, five different client types, including around 100 browsers, 15 feed readers, some media players, personal information managers (like mail clients) and mobile apps using the AFNetworking framework, around 80 operating systems and nine different device types (smartphones, tablets, feature phones, consoles, tvs, car browsers, cameras, smart displays and desktop devices) from over 180 brands.

  Note : Piwik itself currently does not use the full feature set of DeviceDetector. Client detection is currently not implemented in Piwik (only detected browsers are reported, other clients are marked as Unknown). Client detection will be implemented into Piwik in the future, follow #5413 to stay updated.

  Performance of DeviceDetector

  Our detections are currently handled by an enormous number of regexes, that are defined in several .YML Files. As parsing these .YML files is a bit slow, DeviceDetector is able to cache the parsed .YML Files. By default DeviceDetector uses a static cache, which means that everything is cached in static variables. As that only improves speed for many detections within one process, there are also adapters to cache in files or memcache for speeding up detections across requests.

  How can users help contribute to DeviceDetector ?

  Submit your devices that are not detected yet

  If you own a device, that is currently not correctly detected by the DeviceDetector, please create a issue on GitHub
  In order to check if your device is detected correctly by the DeviceDetector go to your Piwik server, click on ‘Settings’ link, then click on ‘Device Detection’ under the Diagnostic menu. If the data does not match, please copy the displayed User Agent and use that and your device data to create a ticket.

  Submit a list of your User Agents

  In order to create new detections or improve the existing ones, it is necessary for us to have lists of User Agents. If you have a website used by mostly non desktop devices it would be useful if you send a list of the User Agents that visited your website. To do so you need access to your access logs. The following command will extract the User Agents :

  zcat ~/path/to/access/logs* | awk -F'"' '{print $6}' | sort | uniq -c | sort -rn | head -n20000 > /home/piwik/top-user-agents.txt

  If you want to help us with those data, please get in touch at devicedetector@piwik.org

  Submit improvements on GitHub

  As DeviceDetector is free/libre library, we invite you to help us improving the detections as well as the code. Please feel free to create tickets and pull requests on Github.

  What’s the next big thing for DeviceDetector ?

  Please check out the list of issues in device-detector issue tracker.

  We hope the community will answer our call for help. Together, we can build DeviceDetector as the most powerful device detection library !

  Happy Device Detection,

• Ruby on Rails 4 Heroku App Crash while uploading large size video

  22 juillet 2016, par Krishna Vyas

  large video file isn’t uploading on heroku and throwing Application Crash error
  Here is my Model Code :

  has_attached_file :video, :styles => {
  
    :medium => {
  
      :geometry => "640x480",
  
      :format => 'mp4',
  
      :convert_options => {
  
      :output => {
  
        :vcodec => 'libx264',
  
        :acodec => 'copy'
  
      }
  
    }
  
    },
  
    :thumb => {
  
      :geometry => "300x300#",
  
      :format => 'jpg',
  
      :time => 2,
  
      :auto_rotate => true
  
    }
  
  }, :processors => [:transcoder]
  
  
  
  validates_attachment_content_type :video, content_type: /\Avideo\/.*\Z/

  Here is my log from heroku

  2016-07-22T13:15:13.616340+00:00 app[web.1]: Command :: file -b --mime '/tmp/33028ec79c8028f75908c90d9f018aeb20160722-3-1e90wvf.mp4'
  
  2016-07-22T13:15:13.771935+00:00 app[web.1]: [AV] Running command: if command -v avprobe 2>/dev/null; then echo "true"; else echo "false"; fi
  
  2016-07-22T13:15:13.773078+00:00 app[web.1]: [AV] Running command: if command -v ffmpeg 2>/dev/null; then echo "true"; else echo "false"; fi
  
  2016-07-22T13:15:13.774121+00:00 app[web.1]: [AV] Found ["ffmpeg"], using: Ffmpeg
  
  2016-07-22T13:15:13.774159+00:00 app[web.1]: [AV] Running command: if command -v avprobe 2>/dev/null; then echo "true"; else echo "false"; fi
  
  2016-07-22T13:15:13.775225+00:00 app[web.1]: [AV] Running command: if command -v ffmpeg 2>/dev/null; then echo "true"; else echo "false"; fi
  
  2016-07-22T13:15:13.776771+00:00 app[web.1]: [AV] Found ["ffmpeg"], using: Ffmpeg
  
  2016-07-22T13:15:13.776807+00:00 app[web.1]: [AV] Running command: ffmpeg -i "/tmp/33028ec79c8028f75908c90d9f018aeb20160722-3-xbemwt.mp4" 2>&1
  
  2016-07-22T13:15:13.814982+00:00 app[web.1]: [paperclip] [transcoder] Transocding supported file /tmp/33028ec79c8028f75908c90d9f018aeb20160722-3-xbemwt.mp4
  
  2016-07-22T13:15:13.815056+00:00 app[web.1]: [AV] Adding output parameter ["acodec", "aac"]
  
  2016-07-22T13:15:13.815103+00:00 app[web.1]: [AV] Adding output parameter ["strict", "experimental"]
  
  2016-07-22T13:15:13.815289+00:00 app[web.1]: [AV] Adding output parameter [:s, "640x480"]
  
  2016-07-22T13:15:13.815379+00:00 app[web.1]: [AV] Running command: ffmpeg -i "/tmp/33028ec79c8028f75908c90d9f018aeb20160722-3-xbemwt.mp4" -acodec aac -strict experimental -s 640x480 -y "/tmp/33028ec79c8028f75908c90d9f018aeb20160722-3-xbemwt20160722-3-1pwdg2k.mp4"
  
  2016-07-22T13:15:43.237749+00:00 heroku[router]: at=error code=H12 desc="Request timeout" method=POST path="/courses/5/sections/7/lessons/11" host=xxxxx.herokuapp.com request_id=a1408ac7-c7c3-40f4-8365-86156d2d2314 fwd="43.255.56.1" dyno=web.1 connect=0ms service=188655ms status=503 bytes=0

• dnn/native : unify error return to DNN_ERROR

  25 août 2020, par Ting Fu

  dnn/native : unify error return to DNN_ERROR
  Unify all error return as DNN_ERROR, in order to cease model executing
  
  when return error in ff_dnn_execute_model_native layer_func.pf_exec
  Signed-off-by : Ting Fu <ting.fu@intel.com>
  

  • [DH] libavfilter/dnn/dnn_backend_native.c
  • [DH] libavfilter/dnn/dnn_backend_native_layer_avgpool.c
  • [DH] libavfilter/dnn/dnn_backend_native_layer_conv2d.c
  • [DH] libavfilter/dnn/dnn_backend_native_layer_depth2space.c
  • [DH] libavfilter/dnn/dnn_backend_native_layer_mathbinary.c
  • [DH] libavfilter/dnn/dnn_backend_native_layer_mathunary.c
  • [DH] libavfilter/dnn/dnn_backend_native_layer_pad.c