Recherche avancée

Sur d’autres sites (4773)

• Accord.Video.FFMpeg : Problem of duration difference between recording time and video time

  5 mars 2020, par ckrby

  I want to save the footage I get from the webcam as a video in webM (Vp8) format. I use the Accord library. But when recording, there is almost 2-3 times the difference between the time spent and the video time. The code I use and some debug outputs are below.

  Accord.Video.FFMpeg 3.8.2-Alpha (double pts/dts bug fixed version)
  Video Save Format : VP8 (.WebM)

  Record Start Settings :

  videoCodec = VideoCodec.Vp8;    
  
  bitrate : 1250000   
  
  framerate :10   
  
  height :720 
  
  width: 1280 
  
  videoSource.VideoResolution: 1280x720, 30 fps (30 max fps), 24 bpp  
  
  FileWriter.BitRate = bitRate;   
  
  FileWriter.FrameRate = new Accord.Math.Rational((int)framerate );   
  
  FileWriter.Width = width;   
  
  FileWriter.Height = height; 
  
  FileWriter.VideoCodec = videoCodec; 
  
  FileWriter.Open(FileName);  
  
  _recording = true;  
  
  StartTimeStamp = DateTime.Now;  

  newFrame Event

  private void VideoSourcePlayer1_NewFrame(object sender, ref Bitmap image)
  
  {
  
      if (_recording)
  
      {
  
          try
  
          {
  
              Bitmap CurrentBitmap = image;
  
              DateTime CurrentTimeStamp = DateTime.Now;
  
              TimeSpan CurrentTimeSpan = StartTimeStamp - CurrentTimeStamp;
  
              Console.WriteLine("Video Write Timespan: " + CurrentTimeSpan.ToString());
  
              FileWriter.WriteVideoFrame(CurrentBitmap, CurrentTimeSpan);
  
              // FileWriter.WriteVideoFrame(image);  
  
          }
  
          catch (Exception ex)
  
          {
  
              Console.WriteLine("VideoSourcePlayer1_NewFrame catch: " + ex.Message);
  
          }
  
      }
  
  }

  Note : It is the same issue with timespan or without timespan writing.

  In the 122 second (02.02 min) period, 50 seconds of video recording is created. I couldn’t solve it.

  Little Part of the debug output :

  Video Write Timespan : -00:01:55.4107365
  pts:4,730000e+004 pts_time:47,3 dts:4,730000e+004 dts_time:47,3 duration:1,000000e+002 duration_time:0,1
  Video Write Timespan : -00:01:55.6136263
  pts:4,740000e+004 pts_time:47,4 dts:4,740000e+004 dts_time:47,4 duration:1,000000e+002 duration_time:0,1
  Video Write Timespan : -00:01:55.8354960
  pts:4,750000e+004 pts_time:47,5 dts:4,750000e+004 dts_time:47,5 duration:1,000000e+002 duration_time:0,1
  Video Write Timespan : -00:01:56.5161088
  pts:4,760000e+004 pts_time:47,6 dts:4,760000e+004 dts_time:47,6 duration:1,000000e+002 duration_time:0,1
  Video Write Timespan : -00:01:56.7309841
  pts:4,770000e+004 pts_time:47,7 dts:4,770000e+004 dts_time:47,7 duration:1,000000e+002 duration_time:0,1
  Video Write Timespan : -00:01:56.9758413
  pts:4,780000e+004 pts_time:47,8 dts:4,780000e+004 dts_time:47,8 duration:1,000000e+002 duration_time:0,1
  Video Write Timespan : -00:01:57.1947200
  pts:4,790000e+004 pts_time:47,9 dts:4,790000e+004 dts_time:47,9 duration:1,000000e+002 duration_time:0,1
  Video Write Timespan : -00:01:57.4375834
  pts:4,800000e+004 pts_time:48 dts:4,800000e+004 dts_time:48 duration:1,000000e+002 duration_time:0,1
  Video Write Timespan : -00:01:57.5804983

  The last two outputs :

  Video Write Timespan : -00:02:02.7505463
  pts:5,000000e+004 pts_time : 50 dts:5,000000e+004 dts_time : 50 duration:1,000000e+002 duration_time:0,1
  Video Write Timespan : -00:02:02.9884038
  pts:5,010000e+004 pts_time : 50,1 dts:5,010000e+004 dts_time : 50,1 duration:1,000000e+002 duration_time:0,1

  Why is there a difference between timespan and dts/pts time ? Could the problem be due to this ?

  Note : When I set the framerate to 30 ; Another process 95 seconds (1.35 min) recording time is 16 seconds in the video.

  As the frame rate increases, the length of the video gets shorter and
  shorter than the actual value it should be.

  Output :

  Video Write Timespan : -00:01:35.1086178
  pts:1,606700e+004 pts_time : 16,067 dts:1,606700e+004 dts_time : 16,067 duration:3,300000e+001 duration_time:0,033
  Video Write Timespan : -00:01:35.2565302
  pts:1,610000e+004 pts_time : 16,1 dts:1,610000e+004 dts_time : 16,1 duration:3,300000e+001 duration_time:0,033
  Video Write Timespan : -00:01:35.3984494
  pts:1,613300e+004 pts_time : 16,133 dts:1,613300e+004 dts_time : 16,133 duration:3,300000e+001 duration_time:0,033

  So the video duration is like dts_time. Why is the video duration not
  value of timespan time, I still can’t find it ??

  Soory for my bad english & expression,

• Stopping Referrer Spam

  13 mai 2015, par Piwik Core Team — Community

  In this blog post we explain what is Referrer spam, this new kind of spam that has recently appeared on the Internet. We also provide solutions to stop it and preserve the quality of your analytics data.

  What is Referrer Spam ?

  Referrer spam (also known as log spam or referrer bombing) is a kind of spamming aimed at web analytics tools. A spammer bot makes repeated web site requests using a fake referrer URL to the site the spammer wishes to advertise.

  Here is an example of referrer spam in action :

  

  Half of those referrers are spams, here are some well know spammers that you may have seen in your logs : buttons-for-you-website.com, best-seo-offer.com, semalt.com…

  The benefit for spammers is that their website will appear in analytics tools like Piwik or Google Analytics :

  • public analytics reports (or logs) will be indexed by search engines : links to the spammer’s website will improve its ranking
  • curious webmasters are likely to visit their referrers, thus bringing traffic to the spammer’s website

  How to deal with Referrer Spam ?

  Referrer spam is still new and analytics tools are all handling it differently.

  Referrer Spam in Piwik

  At Piwik we started working on mitigating Referrer spam more than a year ago. If you use Piwik and keep it up to date, you do not need to do anything.

  Referrer spammers are automatically excluded from your reports to keep your data clean and useful.

  New spammers are continuously detected and added to Piwik’s blacklist on each update. If you find a new spammer in your analytics data, you can even report it so that it is added to the Piwik’s open referrer blacklist and blocked for everyone.

  Referrer Spam in Google Analytics

  Google Analytics doesn’t offer any spam protection by default. It can however be configured manually using a custom Filter.

  To create a filter in Google Analytics go to the Admin section and click on All Filters. Create a new custom filter that excludes based on the Campaign Source field. In the Filter pattern enter the spammers domains you want to exclude (this is a regular expression) :

  

  If new spammers arise you will need to update this list. You can also use Piwik’s referrer blacklist to exclude all the spammers currently detected.

  Other Analytics Tools

  Many web analytics tools do not yet handle Referrer spam and when using these tools, you will often find a lot of spam data in your Referrer Websites analytics reports.

  If you use an analytics tool that does not exclude Referrer spam, we recommend to contact the vendor and ask them to implement a mechanism to remove these referrer spammers. As of today many analytics vendors still have not mitigated this issue.

  Public List of Referrer Spammers

  At Piwik with the help of our large community we have decided to tackle this growing spam issue. We have created a list of up to date referrer spammers that anyone can edit.

  The list is available in a simple text file on Github : github.com/piwik/referrer-spam-blacklist.

  The list is released under the Public Domain and anyone can use it within their applications to exclude referrer spammers.

  Many people have already contributed new spammers to the list. We invite you to use the list in your apps and websites and help us keep the list up to date !

  Let’s unite and fight the spammers together.

  Happy Analytics !

• Stopping Referrer Spam

  13 mai 2015, par Piwik Core Team — Community

  In this blog post we explain what is Referrer spam, this new kind of spam that has recently appeared on the Internet. We also provide solutions to stop it and preserve the quality of your analytics data.

  What is Referrer Spam ?

  Referrer spam (also known as log spam or referrer bombing) is a kind of spamming aimed at web analytics tools. A spammer bot makes repeated web site requests using a fake referrer URL to the site the spammer wishes to advertise.

  Here is an example of referrer spam in action :

  

  Half of those referrers are spams, here are some well know spammers that you may have seen in your logs : buttons-for-you-website.com, best-seo-offer.com, semalt.com…

  The benefit for spammers is that their website will appear in analytics tools like Piwik or Google Analytics :

  • public analytics reports (or logs) will be indexed by search engines : links to the spammer’s website will improve its ranking
  • curious webmasters are likely to visit their referrers, thus bringing traffic to the spammer’s website

  How to deal with Referrer Spam ?

  Referrer spam is still new and analytics tools are all handling it differently.

  Referrer Spam in Piwik

  At Piwik we started working on mitigating Referrer spam more than a year ago. If you use Piwik and keep it up to date, you do not need to do anything.

  Referrer spammers are automatically excluded from your reports to keep your data clean and useful.

  New spammers are continuously detected and added to Piwik’s blacklist on each update. If you find a new spammer in your analytics data, you can even report it so that it is added to the Piwik’s open referrer blacklist and blocked for everyone.

  Referrer Spam in Google Analytics

  Google Analytics doesn’t offer any spam protection by default. It can however be configured manually using a custom Filter.

  To create a filter in Google Analytics go to the Admin section and click on All Filters. Create a new custom filter that excludes based on the Campaign Source field. In the Filter pattern enter the spammers domains you want to exclude (this is a regular expression) :

  

  If new spammers arise you will need to update this list. You can also use Piwik’s referrer blacklist to exclude all the spammers currently detected.

  Other Analytics Tools

  Many web analytics tools do not yet handle Referrer spam and when using these tools, you will often find a lot of spam data in your Referrer Websites analytics reports.

  If you use an analytics tool that does not exclude Referrer spam, we recommend to contact the vendor and ask them to implement a mechanism to remove these referrer spammers. As of today many analytics vendors still have not mitigated this issue.

  Public List of Referrer Spammers

  At Piwik with the help of our large community we have decided to tackle this growing spam issue. We have created a list of up to date referrer spammers that anyone can edit.

  The list is available in a simple text file on Github : github.com/piwik/referrer-spam-blacklist.

  The list is released under the Public Domain and anyone can use it within their applications to exclude referrer spammers.

  Many people have already contributed new spammers to the list. We invite you to use the list in your apps and websites and help us keep the list up to date !

  Let’s unite and fight the spammers together.

  Happy Analytics !