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• VP8 : a retrospective

  13 juillet 2010, par Dark Shikari — DCT, speed, VP8

  I’ve been working the past few weeks to help finish up the ffmpeg VP8 decoder, the first community implementation of On2′s VP8 video format. Now that I’ve written a thousand or two lines of assembly code and optimized a good bit of the C code, I’d like to look back at VP8 and comment on a variety of things — both good and bad — that slipped the net the first time, along with things that have changed since the time of that blog post.

  These are less-so issues related to compression — that issue has been beaten to death, particularly in MSU’s recent comparison, where x264 beat the crap out of VP8 and the VP8 developers pulled a Pinocchio in the developer comments. But that was expected and isn’t particularly interesting, so I won’t go into that. VP8 doesn’t have to be the best in the world in order to be useful.

  When the ffmpeg VP8 decoder is complete (just a few more asm functions to go), we’ll hopefully be able to post some benchmarks comparing it to libvpx.

  1. The spec, er, I mean, bitstream guide.

  Google has reneged on their claim that a spec existed at all and renamed it a “bitstream guide”. This is probably after it was found that — not merely was it incomplete — but at least a dozen places in the spec differed wildly from what was actually in their own encoder and decoder software ! The deblocking filter, motion vector clamping, probability tables, and many more parts simply disagreed flat-out with the spec. Fortunately, Ronald Bultje, one of the main authors of the ffmpeg VP8 decoder, is rather skilled at reverse-engineering, so we were able to put together a matching implementation regardless.

  Most of the differences aren’t particularly important — they don’t have a huge effect on compression or anything — but make it vastly more difficult to implement a “working” VP8 decoder, or for that matter, decide what “working” really is. For example, Google’s decoder will, if told to “swap the ALT and GOLDEN reference frames”, overwrite both with GOLDEN, because it first sets GOLDEN = ALT, and then sets ALT = GOLDEN. Is this a bug ? Or is this how it’s supposed to work ? It’s hard to tell — there isn’t a spec to say so. Google says that whatever libvpx does is right, but I doubt they intended this.

  I expect a spec will eventually be written, but it was a bit obnoxious of Google — both to the community and to their own developers — to release so early that they didn’t even have their own documentation ready.

  2. The TM intra prediction mode.

  One thing I glossed over in the original piece was that On2 had added an extra intra prediction mode to the standard batch that H.264 came with — they replaced Planar with “TM pred”. For i4x4, which didn’t have a Planar mode, they just added it without replacing an old one, resulting in a total of 10 modes to H.264′s 9. After understanding and writing assembly code for TM pred, I have to say that it is quite a cool idea. Here’s how it works :

  1. Let us take a block of size 4×4, 8×8, or 16×16.

  2. Define the pixels bordering the top of this block (starting from the left) as T[0], T[1], T[2]…

  3. Define the pixels bordering the left of this block (starting from the top) as L[0], L[1], L[2]…

  4. Define the pixel above the top-left of the block as TL.

  5. Predict every pixel <X,Y> in the block to be equal to clip3( T[X] + L[Y] – TL, 0, 255).

  It’s effectively a generalization of gradient prediction to the block level — predict each pixel based on the gradient between its top and left pixels, and the topleft. According to the VP8 devs, it’s chosen by the encoder quite a lot of the time, which isn’t surprising ; it seems like a pretty good idea. As just one more intra pred mode, it’s not going to do magic for compression, but it’s a cool idea and elegantly simple.

  3. Performance and the deblocking filter.
  

  On2 advertised for quite some that VP8′s goal was to be significantly faster to decode than H.264. When I saw the spec, I waited for the punchline, but apparently they were serious. There’s nothing wrong with being of similar speed or a bit slower — but I was rather confused as to the fact that their design didn’t match their stated goal at all. What apparently happened is they had multiple profiles of VP8 — high and low complexity profiles. They marketed the performance of the low complexity ones while touting the quality of the high complexity ones, a tad dishonest. More importantly though, practically nobody is using the low complexity modes, so anyone writing a decoder has to be prepared to handle the high complexity ones, which are the default.

  The primary time-eater here is the deblocking filter. VP8, being an H.264 derivative, has much the same problem as H.264 does in terms of deblocking — it spends an absurd amount of time there. As I write this post, we’re about to finish some of the deblocking filter asm code, but before it’s committed, up to 70% or more of total decoding time is spent in the deblocking filter ! Like H.264, it suffers from the 4×4 transform problem : a 4×4 transform requires a total of 8 length-16 and 8 length-8 loopfilter calls per macroblock, while Theora, with only an 8×8 transform, requires half that.

  This problem is aggravated in VP8 by the fact that the deblocking filter isn’t strength-adaptive ; if even one 4×4 block in a macroblock contains coefficients, every single edge has to be deblocked. Furthermore, the deblocking filter itself is quite complicated ; the “inner edge” filter is a bit more complex than H.264′s and the “macroblock edge” filter is vastly more complicated, having two entirely different codepaths chosen on a per-pixel basis. Of course, in SIMD, this means you have to do both and mask them together at the end.

  There’s nothing wrong with a good-but-slow deblocking filter. But given the amount of deblocking one needs to do in a 4×4-transform-based format, it might have been a better choice to make the filter simpler. It’s pretty difficult to beat H.264 on compression, but it’s certainly not hard to beat it on speed — and yet it seems VP8 missed a perfectly good chance to do so. Another option would have been to pick an 8×8 transform instead of 4×4, reducing the amount of deblocking by a factor of 2.

  And yes, there’s a simple filter available in the low complexity profile, but it doesn’t help if nobody uses it.

  4. Tree-based arithmetic coding.

  Binary arithmetic coding has become the standard entropy coding method for a wide variety of compressed formats, ranging from LZMA to VP6, H.264 and VP8. It’s simple, relatively fast compared to other arithmetic coding schemes, and easy to make adaptive. The problem with this is that you have to come up with a method for converting non-binary symbols into a list of binary symbols, and then choosing what probabilities to use to code each one. Here’s an example from H.264, the sub-partition mode symbol, which is either 8×8, 8×4, 4×8, or 4×4. encode_decision( context, bit ) writes a binary decision (bit) into a numbered context (context).

  8×8 : encode_decision( 21, 0 ) ;

  8×4 : encode_decision( 21, 1 ) ; encode_decision( 22, 0 ) ;

  4×8 : encode_decision( 21, 1 ) ; encode_decision( 22, 1 ) ; encode_decision( 23, 1 ) ;

  4×4 : encode_decision( 21, 1 ) ; encode_decision( 22, 1 ) ; encode_decision( 23, 0 ) ;

  As can be seen, this is clearly like a Huffman tree. Wouldn’t it be nice if we could represent this in the form of an actual tree data structure instead of code ? On2 thought so — they designed a simple system in VP8 that allowed all binarization schemes in the entire format to be represented as simple tree data structures. This greatly reduces the complexity — not speed-wise, but implementation-wise — of the entropy coder. Personally, I quite like it.

  5. The inverse transform ordering.

  I should at some point write a post about common mistakes made in video formats that everyone keeps making. These are not issues that are patent worries or huge issues for compression — just stupid mistakes that are repeatedly made in new video formats, probably because someone just never asked the guy next to him “does this look stupid ?” before sticking it in the spec.

  One common mistake is the problem of transform ordering. Every sane 2D transform is “separable” — that is, it can be done by doing a 1D transform vertically and doing the 1D transform again horizontally (or vice versa). The original iDCT as used in JPEG, H.263, and MPEG-1/2/4 was an “idealized” iDCT — nobody had to use the exact same iDCT, theirs just had to give very close results to a reference implementation. This ended up resulting in a lot of practical problems. It was also slow ; the only way to get an accurate enough iDCT was to do all the intermediate math in 32-bit.

  Practically every modern format, accordingly, has specified an exact iDCT. This includes H.264, VC-1, RV40, Theora, VP8, and many more. Of course, with an exact iDCT comes an exact ordering — while the “real” iDCT can be done in any order, an exact iDCT usually requires an exact order. That is, it specifies horizontal and then vertical, or vertical and then horizontal.

  All of these transforms end up being implemented in SIMD. In SIMD, a vertical transform is generally the only option, so a transpose is added to the process instead of doing a horizontal transform. Accordingly, there are two ways to do it :

  1. Transpose, vertical transform, transpose, vertical transform.

  2. Vertical transform, transpose, vertical transform, transpose.

  These may seem to be equally good, but there’s one catch — if the transpose is done first, it can be completely eliminated by merging it into the coefficient decoding process. On many modern CPUs, particularly x86, transposes are very expensive, so eliminating one of the two gives a pretty significant speed benefit.

  H.264 did it way 1).

  VC-1 did it way 1).

  Theora (inherited from VP3) did it way 1).

  But no. VP8 has to do it way 2), where you can’t eliminate the transpose. Bah. It’s not a huge deal ; probably only 1-2% overall at most speed-wise, but it’s just a needless waste. What really bugs me is that VP3 got it right — why in the world did they screw it up this time around if they got it right beforehand ?

  RV40 is the other modern format I know that made this mistake.

  (NB : You can do transforms without a transpose, but it’s generally not worth it unless the intermediate needs 32-bit math, as in the case of the “real” iDCT.)

  6. Not supporting interlacing.

  THANK YOU THANK YOU THANK YOU THANK YOU THANK YOU THANK YOU THANK YOU.

  Interlacing was the scourge of H.264. It weaseled its way into every nook and cranny of the spec, making every decoder a thousand lines longer. H.264 even included a highly complicated — and effective — dedicated interlaced coding scheme, MBAFF. The mere existence of MBAFF, despite its usefulness for broadcasters and others still stuck in the analog age with their 1080i, 576i , and 480i content, was a blight upon the video format.

  VP8 has once and for all avoided it.

  And if anyone suggests adding interlaced support to the experimental VP8 branch, find a straightjacket and padded cell for them before they cause any real damage.

• i am getting when i am trying to run Ffmpegrabberframe on alpine image [closed]

  18 mars 2020, par avinash tiwari

  # # A fatal error has been detected by the Java Runtime Environment :

  # SIGSEGV (0xb) at pc=0x000000000000dc56, pid=446, tid=0x00007fd3c478db20 # # JRE version : OpenJDK Runtime Environment

  (8.0_242-b08) (build 1.8.0_242-b08) # Java VM : OpenJDK 64-Bit Server
  VM (25.242-b08 mixed mode linux-amd64 compressed oops) # Derivative :
  IcedTea 3.15.0 # Distribution : Custom build (Wed Jan 29 10:43:50 UTC
  2020) # Problematic frame : # C 0x000000000000dc56 # # Failed to
  write core dump. Core dumps have been disabled. To enable core
  dumping, try "ulimit -c unlimited" before starting Java again # # An
  error report file with more information is saved as : #
  /builds/had/tip/asset-delivery/firstgen-ingestion---backend/hs_err_pid446.log

  # If you would like to submit a bug report, please include # instructions on how to reproduce the bug and visit : #

  https://icedtea.classpath.org/bugzilla # Exception in thread
  "Thread-8" java.io.EOFException at
  java.io.ObjectInputStream$BlockDataInputStream.peekByte(ObjectInputStream.java:3015)
  at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1576)
  at java.io.ObjectInputStream.readObject(ObjectInputStream.java:465)
  at java.io.ObjectInputStream.readObject(ObjectInputStream.java:423)
  at
  org.scalatest.tools.Framework$ScalaTestRunner$Skeleton$1$React.react(Framework.scala:818)
  at
  org.scalatest.tools.Framework$ScalaTestRunner$Skeleton$1.run(Framework.scala:807)

  def extractAVI(rawDrivePath: String): List[String] = {
  
      var errorList: List[String] = List.empty
  
      FileUtils.listFiles(new File(rawDrivePath), new SuffixFileFilter(".avi"), TrueFileFilter.INSTANCE)
  
        .asScala.toList.foreach(aviFile => {
  
        var grabber: FFmpegFrameGrabber = null
  
        var aviStream: InputStream = null
  
        var isFailedExtraction: Boolean = false
  
        try {
  
          LOGGER.info(s"--------inside try----------${aviFile.getAbsolutePath}")
  
          aviStream = new FileInputStream(aviFile.getAbsolutePath)
  
          LOGGER.info("--------create grabber----------")
  
          grabber = new FFmpegFrameGrabber(aviStream)
  
          LOGGER.info("--------created grabber extraction of drives----------")
  
          grabber.start()
  
          LOGGER.info("--------start grabber of drives----------")
  
          var count: Int = 1
  
          for (frame <- Iterator.continually(grabber.grabImage()).takeWhile(_ != null)) {
  
            ImageIO.write(converter.convert(frame), "jpg", new File(aviFile.getParent, "capture-" + count + ".jpg"))
  
            count += 1
  
          }
  
          grabber.stop()
  
        } catch {
  
          case ex: Exception => {
  
            LOGGER.info(s"Error while extracting images for ${aviFile.getAbsolutePath} {}", ex)
  
            errorList :+= s"${aviFile.getAbsolutePath.replace(rawDrivePath, "")} -> ${ex.getMessage}"
  
            isFailedExtraction = true
  
            LOGGER.info("last inside catch")
  
          }
  
        } finally {
  
          // Close the video file
  
          LOGGER.info(s"inside finally ")
  
          if (grabber != null)
  
            grabber.release()
  
          if (aviStream != null)
  
            aviStream.close()
  
          if (aviFile.exists() && !isFailedExtraction) {
  
            LOGGER.debug(s"Deleting ${aviFile.getAbsolutePath}")
  
            FileUtils.deleteQuietly(aviFile)
  
          }
  
        }
  
      })

• 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 !