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• Simply beyond ridiculous

  7 mai 2010, par Dark Shikari — H.265, speed

  For the past few years, various improvements on H.264 have been periodically proposed, ranging from larger transforms to better intra prediction. These finally came together in the JCT-VC meeting this past April, where over two dozen proposals were made for a next-generation video coding standard. Of course, all of these were in very rough-draft form ; it will likely take years to filter it down into a usable standard. In the process, they’ll pick the most useful features (hopefully) from each proposal and combine them into something a bit more sane. But, of course, it all has to start somewhere.

  A number of features were common : larger block sizes, larger transform sizes, fancier interpolation filters, improved intra prediction schemes, improved motion vector prediction, increased internal bit depth, new entropy coding schemes, and so forth. A lot of these are potentially quite promising and resolve a lot of complaints I’ve had about H.264, so I decided to try out the proposal that appeared the most interesting : the Samsung+BBC proposal (A124), which claims compression improvements of around 40%.

  The proposal combines a bouillabaisse of new features, ranging from a 12-tap interpolation filter to 12thpel motion compensation and transforms as large as 64×64. Overall, I would say it’s a good proposal and I don’t doubt their results given the sheer volume of useful features they’ve dumped into it. I was a bit worried about complexity, however, as 12-tap interpolation filters don’t exactly scream “fast”.

  I prepared myself for the slowness of an unoptimized encoder implementation, compiled their tool, and started a test encode with their recommended settings.

  I waited. The first frame, an I-frame, completed.

  I took a nap.

  I waited. The second frame, a P-frame, was done.

  I played a game of Settlers.

  I waited. The third frame, a B-frame, was done.

  I worked on a term paper.

  I waited. The fourth frame, a B-frame, was done.

  After a full 6 hours, 8 frames had encoded. Yes, at this rate, it would take a full two weeks to encode 10 seconds of HD video. On a Core i7. This is not merely slow ; this is over 1000 times slower than x264 on “placebo” mode. This is so slow that it is not merely impractical ; it is impossible to even test. This encoder is apparently designed for some sort of hypothetical future computer from space. And word from other developers is that the Intel proposal is even slower.

  This has led me to suspect that there is a great deal of cheating going on in the H.265 proposals. The goal of the proposals, of course, is to pick the best feature set for the next generation video compression standard. But there is an extra motivation : organizations whose features get accepted get patents on the resulting standard, and thus income. With such large sums of money in the picture, dishonesty becomes all the more profitable.

  There is a set of rules, of course, to limit how the proposals can optimize their encoders. If different encoders use different optimization techniques, the results will no longer be comparable — remember, they are trying to compare compression features, not methods of optimizing encoder-side decisions. Thus all encoders are required to use a constant quantizer, specified frame types, and so forth. But there are no limits on how slow an encoder can be or what algorithms it can use.

  It would be one thing if the proposed encoder was a mere 10 times slower than the current reference ; that would be reasonable, given the low level of optimization and higher complexity of the new standard. But this is beyond ridiculous. With the prize given to whoever can eke out the most PSNR at a given quantizer at the lowest bitrate (with no limits on speed), we’re just going to get an arms race of slow encoders, with every company trying to use the most ridiculous optimizations possible, even if they involve encoding the frame 100,000 times over to choose the optimal parameters. And the end result will be as I encountered here : encoders so slow that they are simply impossible to even test.

  Such an arms race certainly does little good in optimizing for reality where we don’t have 30 years to encode an HD movie : a feature that gives great compression improvements is useless if it’s impossible to optimize for in a reasonable amount of time. Certainly once the standard is finalized practical encoders will be written — but it makes no sense to optimize the standard for a use-case that doesn’t exist. And even attempting to “optimize” anything is difficult when encoding a few seconds of video takes weeks.

  Update : The people involved have contacted me and insist that there was in fact no cheating going on. This is probably correct ; the problem appears to be that the rules that were set out were simply not strict enough, making many changes that I would intuitively consider “cheating” to be perfectly allowed, and thus everyone can do it.

  I would like to apologize if I implied that the results weren’t valid ; they are — the Samsung-BBC proposal is definitely one of the best, which is why I picked it to test with. It’s just that I think any situation in which it’s impossible to test your own software is unreasonable, and thus the entire situation is an inherently broken one, given the lax rules, slow baseline encoder, and no restrictions on compute time.

• VP8 And FFmpeg

  18 juin 2010, par Multimedia Mike — VP8

  UPDATE, 2010-06-17 : You don’t need to struggle through these instructions anymore. libvpx 0.9.1 and FFmpeg 0.6 work together much better. Please see this post for simple instructions on getting up and running quickly.

  Let’s take the VP8 source code (in Google’s new libvpx library) for a spin ; get it to compile and hook it up to FFmpeg. I am hesitant to publish specific instructions for building in the somewhat hackish manner available on day 1 (download FFmpeg at a certain revision and apply a patch) since that kind of post has a tendency to rise in Google rankings. I will just need to remember to update this post after the library patches are applied to the official FFmpeg tree.

  Statement of libvpx’s Relationship to FFmpeg
  I don’t necessarily speak officially for FFmpeg. But I’ve been with the project long enough to explain how certain things work.

  Certainly, some may wonder if FFmpeg will incorporate Google’s newly open sourced libvpx library into FFmpeg. In the near term, FFmpeg will support encoding and decoding VP8 via external library as it does with a number of other libraries (most popularly, libx264). FFmpeg will not adopt the code for its own codebase, even if the license may allow it. That just isn’t how the FFmpeg crew rolls.

  In the longer term, expect the FFmpeg project to develop an independent, interoperable implementation of the VP8 decoder. Sometime after that, there may also be an independent VP8 encoder as well.

  Building libvpx
  Download and build libvpx. This is a basic ’configure && make’ process. The build process creates a static library, a bunch of header files, and 14 utilities. A bunch of these utilities operate on a file format called IVF which is apparently a simple transport method for VP8. I have recorded the file format on the wiki.

  We could use a decoder for this in the FFmpeg code base for testing VP8 in the future. Who’s game ? Just as I was proofreading this post, I saw that David Conrad has sent an IVF demuxer to the ffmpeg-devel list.

  There doesn’t seem to be a ’make install’ step for the library. Instead, go into the overly long directory (on my system, this is generated as vpx-vp8-nopost-nodocs-generic-gnu-v0.9.0), copy the contents of include/ to /usr/local/include and the static library in lib/ to /usr/local/lib .

  Building FFmpeg with libvpx
  Download FFmpeg source code at the revision specified or take your chances with the latest version (as I did). Download and apply provided patches. This part hurts since there is one diff per file. Most of them applied for me.

  Configure FFmpeg with 'configure --enable-libvpx_vp8 --enable-pthreads'. Ideally, this should yield no complaints and ’libvpx_vp8’ should show up in the enabled decoders and encoders sections. The library apparently relies on threading which is why '--enable-pthreads' is necessary. After I did this, I was able to create a new webm/VP8/Vorbis file simply with :

   ffmpeg -i input_file output_file.webm
  

  Unfortunately, I can’t complete the round trip as decoding doesn’t seem to work. Passing the generated .webm file back into FFmpeg results in a bunch of errors of this format :

  [libvpx_vp8 @ 0x8c4ab20]v0.9.0
  [libvpx_vp8 @ 0x8c4ab20]Failed to initialize decoder : Codec does not implement requested capability
  

  Maybe this is the FFmpeg revision mismatch biting me.

  FFmpeg Presets
  FFmpeg features support for preset files which contain collections of tuning options to be loaded into the program. Google provided some presets along with their FFmpeg patches :

  • 1080p50
  • 1080p
  • 360p
  • 720p50
  • 720p

  To invoke one of these (assuming the program has been installed via ’make install’ so that the presets are in the right place) :

   ffmpeg -i input_file -vcodec libvpx_vp8 -vpre 720p output_file.webm
  

  This will use a set of parameters that are known to do well when encoding a 720p video.

  Code Paths
  One of goals with this post was to visualize a call graph after I got the decoder hooked up to FFmpeg. Fortunately, this recon is greatly simplified by libvpx’s simple_decoder utility. Steps :

  • Build libvpx with --enable-gprof
  • Run simple_decoder on an IVF file
  • Get the pl_from_gprof.pl and dot_from_pl.pl scripts frome Graphviz’s gprof filters
  • gprof simple_decoder | ./pl_from_gprof.pl | ./dot_from_pl.pl > 001.dot
  • Remove the 2 [graph] and 1 [node] modifiers from the dot file (they only make the resulting graph very hard to read)
  • dot -Tpng 001.dot > 001.png

  Here are call graphs generated from decoding test vectors 001 and 017.

  
  

  

  Like this, only much larger and scarier (click for full graph)

  
  

  It’s funny to see several functions calling an empty bubble. Probably nothing to worry about. More interesting is the fact that a lot of function_c() functions are called. The ’_c’ at the end is important— that generally indicates that there are (or could be) SIMD-optimized versions. I know this codebase has plenty of assembly. All of the x86 ASM files appear to be written such that they could be compiled with NASM.

  Leftovers
  One interesting item in the code was vpx_scale/leapster. Is this in reference to the Leapster handheld educational gaming unit ? Based on this item from 2005 (archive.org copy), some Leapster titles probably used VP6. This reminds me of finding references to the PlayStation in Duck/On2’s original VpVision source release. I don’t know of any PlayStation games that used Duck’s original codecs but with thousands to choose from, it’s possible that we may find a few some day.

• Creating A Lossless SMC Encoder

  26 avril 2011, par Multimedia Mike — General

  Look, I can’t explain how or why I come up with this stuff. For some reason, I thought it would be interesting to write a new encoder for the Apple SMC video codec. I can’t even remember why. I just sat down the other day, started writing, and now I have a lossless SMC encoder that I’m not sure what to do with. Maybe this is to be my new thing— writing encoders for marginal multimedia formats.

  Introduction
  SMC is a vector quantizer (a lossy method) but I decided to attack it from the angle of lossless encoding. A.k.a. Apple Graphics Codec, SMC operates on 4x4 blocks in an 8-bit paletted colorspace. Each 4x4 block can be encoded with 1, 2, 4, 8, or 16 colors. Blocks can also be skipped (copied from previous frame) or copied from blocks rendered immediately prior within the same frame.

  Step 1 : Validating Infrastructure
  The goal of this step is to encode the most braindead SMC frame possible and see if FFmpeg/libav’s QuickTime muxer can create a valid file. I think the simplest frame would be one in which each vector is encoded with the single-color mode, starting with color 0 and incrementing through the palette.

  Status : Successful. The only ’trick’ was to set avctx->bits_per_coded_sample to 8. (For fun, this can also be set to 40 (8 | 0x20) to specify a grayscale palette.)
  

  
  
  

  Step 2 : Preprocessing
  The video frames will arrive at the encoder as 32-bit RGB. These will need to be converted to a paletted colorspace before encoding. I don’t want to use FFmpeg’s default dithering approach as this will result in a substantial loss of quality as described in this post. I would rather maintain a palette built from observed colors throughout successive frames. If the total number of unique observed colors ever exceeds 256, error out.

  That’s what I would like to do. However, I noticed that FFmpeg/libav’s QuickTime muxer has never taken into account the possibility of encoding palettes. The path of least resistance in this case is to dither the input to match QuickTime’s default 8-bit palette (if a paletted QuickTime file does not specify a palette, a default 1-, 2-, 4-, or 8-bit palette is selected).

  Status : Successful, if slow. I definitely need to optimize this step later.

  Step 3 : Most Naive Encoding
  The most basic encoding is to "encode" each block as a 16-color block. This will actually result in a slightly larger frame size than a raw encoding since each 4x4 block will be prepended by a byte opcode (0xE0 in this case) to indicate encoding mode. This should demonstrate that the encoder is functioning at the most basic level.

  Status : Successful. Try not to laugh too hard at the Big Buck Bunny dithered to an 8-bit palette :

  
  
  

  Step 4 : Better Representation
  It seems to me that encoding this format (losslessly) will entail performing vector operations on lots of 16-element (4x4-pixel) vectors. These could be done on the frame as-is, but it strikes me as more efficient and perhaps less error prone to rearrange the input images into a vector of vectors (or array of arrays if you prefer) :

    0  1  2  3  w ...
    4  5  6  7  x ...
    8  9  A  B  y ...
    C  D  E  F  z ...
  

    0 : [0 1 2 3 4 5 6 7 8 9 A B C D E F]
    1 : [...]
  

  Status : Successful.

  Step 5 : Add Interframe Skip Codes
  Time to add a bit of brainpower to the proceedings : On non-keyframes, compare the current vector to the vector at the same position from the previous frame.

  Test this by encoding a pair of identical frames. Ideally, all codes should be skip codes.

  Status : Successful, though my vector matching function could probably be improved.

  Step 6 : Analyze Blocks For Optimal Color Coding
  This is where things get potentially interesting, algorithmically. At least, I need to figure out (or look up) an algorithm to count the unique elements in a vector.

  Naive algorithm (i.e., first thing I can think of) :

  • initialize a count variable to 0
  • initialize an array of 256 flags to false
  • for each 8-bit element in vector :
    • if flag array[element] is 0, set array[element] to true and increment count

  Status : Successful. Here is the distribution for the 640x360 Big Buck Bunny title :

  1194 4636 4113 2140 1138 568 325 154 80 36 9 5 2 0 0 0

  Or, in pretty graph form, demonstrating that vectors with few distinct elements dominate :
  

  
  
  

  Step 7 : Encode Monochrome Blocks
  At this point, the structure is starting to come together pretty well. This phase involves encoding a 0x60 opcode and a palette index when the count_distinct() function returns 1.

  Status : Absolutely no problem.

  Step 8 : Encode 2-, 4-, and 8-color Modes
  This step is a little more involved. This is where SMC’s 2-, 4-, and 8-color circular palette caches come into play. E.g., when the first 2-color block is encoded, the pair of colors it uses will be inserted into entry 0 of the 2-color cache. During the next 2-color block encoding, if the block uses a pair of colors that already occurs in the cache, the encoding can reference that cache entry. Otherwise, it adds the pair to the next available cache entry, looping back around to 0 as necessary.

  I think I should modify the count_distinct() function to also return a 16-byte array that contains a sorted list of the palette indicies used in the vector. The color pair cache will contain 256 16-bit, 32-bit ints for the quads and 64-bit ints for the octets. This will allow a slightly faster linear cache search.

  Status : The 2-color encoding wasn’t too much trouble and I was able to adapt it to the 4-color mode pretty quickly afterward. I’m still having trouble with the insane 8-color coding mode, though. So that’s commented out for the time being.

  Step 9 : Run Encoding and Putting It All Together
  For each frame, convert the input pixels to a paletted format via one method or another (match to default QuickTime palette for first pass). Then, preprocess each vector to determine the minimum number of elements that can be used to represent it, storing the sorted list of distinct colors in a separate array. The number of elements can either be 0 (only for interframes and indicates a skip block), 1, 2, 4, 8, or 16. Also during this phase, for each vector after the first, test if the vector is the same as the previous vector. If it is, denote this fact in the preprocessed encoding (set the high bit of the element count number).

  Finally, pack it into the bytestream. Iterate through the element count array and search for the longest runs of elements that are encoded with the same mode (up to 256 for skip modes, up to 16 for other modes). If the high bit of an element count is set, that indicates that a copy mode can be encoded. Look for the longest run of element counts with the high bit set and encode a copy mode.

  Status : In-process. Will finish this as motivation strikes.