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• ffpmeg vs ffprobe performance

  13 décembre 2016, par Thomas

  I wanted to try extracting frames at scene changes with ffmpeg, vs. getting the frame numbers with ffprobe and extracting them later.

  But I had a surprise : ffprobe seems to be much slower than ffmpeg, while ffmpeg is taking the frames, resizing and saving them as well.

  ffmpeg command line :

  ffmpeg -hide_banner -y -i d:/test/m/long.mkv -vf "select=gt(scene\,0.4), showinfo, scale=320:-1, tile=12x200" -vsync 0 thumbnails%03d.png

  this takes : 488 seconds

  ffprobe command line :

  ffprobe -show_frames -of compact=p=0 -f lavfi "movie=/test/m/long.mkv,select=gt(scene\,.4)"

  this takes : 899 seconds

  I am missing something ?

• ARM compiler shoot-out, round 2

       
  20 août 2009, par Mans — ARM, Compilers

  In my recent test of ARM compilers, I had to leave out Texas Instrument’s compiler since it failed to build FFmpeg. Since then, the TI compiler team has been busy fixing bugs, and a snapshot I was given to test was able to build enough of a somewhat patched FFmpeg that I can now present round two in this shoot-out.

  The contenders this time were the fastest GCC variant from round one, ARM RVCT, and newcomer TI TMS470. With the same rules as last time, the exact versions and optimisation options were like this :

  • CodeSourcery GCC 2009q1 (based on 4.3.3), -mfpu=neon -mfloat-abi=softfp -mcpu=cortex-a8 -std=c99 -fomit-frame-pointer -O3 -fno-math-errno -fno-signed-zeros -fno-tree-vectorize
  • ARM RVCT 4.0 Build 591, -mfpu=neon -mfloat-abi=softfp -mcpu=cortex-a8 -std=c99 -fomit-frame-pointer -O3 -fno-math-errno -fno-signed-zeros
  • TI TMS470 4.7.0-a9229, --float_support=vfpv3 -mv=7a8 -O3 -mf=5

  
  To keep things fair, I left the vectoriser off also with the TI compiler. The table below lists the decoding times for the sample files, this time normalised against the participating GCC compiler. Remember, smaller numbers are better. Also keep in mind that this test was done with a development snapshot of TMS470, not an approved release.

  Sample name	Codec	Code type	GCC	RVCT	TI
  cathedral	H.264 CABAC	integer	1.00	0.95	1.02
  NeroAVC	H.264 CABAC	integer	1.00	0.96	1.05
  indiana_jones_4	H.264 CAVLC	integer	1.00	0.92	1.02
  NeroRecodeSample	MPEG-4 ASP	integer	1.00	1.01	1.08
  Silent_Light	MP3	64-bit integer	1.00	0.48	0.72
  When_I_Grow_Up	FLAC	integer	1.00	0.87	0.93
  Lumme-Badloop	Vorbis	float	1.00	0.94	1.05
  Canyon	AC-3	float	1.00	0.88	1.01
  lotr	DTS	float	1.00	1.00	1.08

  Overall, the TI TMS470 compiler comes off slightly worse than GCC. In two cases, however, it was significantly better than GCC, but not as good as RVCT. Incidentally, those were also the ones where RVCT scored the biggest win over GCC.

  My conclusions from this test are twofold :

  • ARM’s own compiler is very hard to beat. They do seem to know how their chips work.
  • GCC is incredibly bad at 64-bit arithmetic on 32-bit machines.

  The logical next step is to test these compilers with vectorisation enabled. FFmpeg should offer plenty of opportunities for this feature to shine. Unfortunately, that test will have to wait until the RVCT vectoriser is fixed. The current release does not compile FFmpeg with vectorisation enabled.

• Stop doing this in your encoder comparisons

  14 juin 2010, par Dark Shikari — Uncategorized

  I’ll do a more detailed post later on how to properly compare encoders, but lately I’ve seen a lot of people doing something in particular that demonstrates they have no idea what they’re doing.

  PSNR is not a very good metric. But it’s useful for one thing : if every encoder optimizes for it, you can effectively measure how good those encoders are at optimizing for PSNR. Certainly this doesn’t tell you everything you want to know, but it can give you a good approximation of “how good the encoder is at optimizing for SOMETHING“. The hope is that this is decently close to the visual results. This of course can fail to be the case if one encoder has psy optimizations and the other does not.

  But it only works to begin with if both encoders are optimized for PSNR. If one optimizes for, say, SSIM, and one optimizes for PSNR, comparing PSNR numbers is completely meaningless. If anything, it’s worse than meaningless — it will bias enormously towards the encoder that is tuned towards PSNR, for obvious reasons.

  And yet people keep doing this.

  They keep comparing x264 against other encoders which are tuned against PSNR. But they don’t tell x264 to also tune for PSNR (–tune psnr, it’s not hard !), and surprise surprise, x264 loses. Of course, these people never bother to actually look at the output ; if they did, they’d notice that x264 usually looks quite a bit better despite having lower PSNR.

  This happens so often that I suspect this is largely being done intentionally in order to cheat in encoder comparisons. Or perhaps it’s because tons of people who know absolutely nothing about video coding insist on doing comparisons without checking their methodology. Whatever it is, it clearly demonstrates that the person doing the test doesn’t understand what PSNR is or why it is used.

  Another victim of this is Theora Ptalarbvorm, which optimizes for SSIM at the expense of PSNR — an absolutely great decision for visual quality. And of course if you just blindly compare Ptalarbvorm (1.2) and Thusnelda (1.1), you’ll notice Ptalarbvorm has much lower PSNR ! Clearly, it must be a worse encoder, right ?

  Stop doing this. And call out the people who insist on cheating.