| nnedi3 for Avisynth v2.5.x | v0.9.4 (10 June 2011) | by tritical | | HELP FILE | ----------------------------------------------------------------------------------------------------- ----------------------------------------------------------------------------------------------------- INFO: nnedi3 is an intra-field only deinterlacer. It takes in a frame, throws away one field, and then interpolates the missing pixels using only information from the kept field. It has same rate and double rate modes, and works with YV12, YUY2, and RGB24 input. nnedi3 is also very good for enlarging images by powers of 2, and includes a function 'nnedi3_rpow2' for that purpose. Syntax => nnedi3(int field, bool dh, bool Y, bool U, bool V, int nsize, int nns, int qual, int etype, int pscrn, int threads, int opt, int fapprox) nnedi3_rpow2(int rfactor, int nsize, int nns, int qual, int etype, int pscrn, string cshift, int fwidth, int fheight, float ep0, float ep1, int threads, int opt, int fapprox) PARAMETERS (nnedi3): field - Controls the mode of operation (double vs same rate) and which field is kept. Possible settings: -2 = double rate (alternates each frame), uses avisynth's internal parity value to start -1 = same rate, uses avisynth's internal parity value 0 = same rate, keep bottom field 1 = same rate, keep top field 2 = double rate (alternates each frame), starts with bottom 3 = double rate (alternates each frame), starts with top If field is set to -1, then nnedi3 calls child->GetParity(0) during initialization. If it returns true, then field is set to 1. If it returns false, then field is set to 0. If field is set to -2, then the same thing happens, but instead of setting field to 1 or 0 it is set to 3 or 2. Default: -1 (int) dh - Doubles the height of the input. Each line of the input is copied to every other line of the output and the missing lines are interpolated. If field=0, the input is copied to the odd lines of the output. If field=1, the input is copied to the even lines of the output. field must be set to either -1, 0, or 1 when using dh=true. Default: false (int) Y, U, V - These control whether or not the specified plane is processed. Set to true to process or false to ignore. Ignored planes are not copied, zero'd, or even considered. So what the ignored planes happen to contain on output is unpredictable. For RGB24 input Y=B, U=G, V=R. Default: Y = true (bool) U = true (bool) V = true (bool) nsize - Sets the size of the local neighborhood around each pixel that is used by the predictor neural network. Possible settings (x_diameter x y_diameter): 0 - 8x6 1 - 16x6 2 - 32x6 3 - 48x6 4 - 8x4 5 - 16x4 6 - 32x4 For image enlargement it is recommended to use 0 or 4. Larger y_diameter settings will result in sharper output. For deinterlacing larger x_diameter settings will allow connecting lines of smaller slope. However, what setting to use really depends on the amount of aliasing (lost information) in the source. If the source was heavily low-pass filtered before interlacing then aliasing will be low and a large x_diameter setting wont be needed, and vice versa. Default: 6 (int) nns - Sets the number of neurons in the predictor neural network. Possible settings are 0, 1, 2, 3, and 4. 0 is fastest. 4 is slowest, but should give the best quality. This is a quality vs speed option; however, differences are usually small. The difference in speed will become larger as 'qual' is increased. 0 - 16 1 - 32 2 - 64 3 - 128 4 - 256 Default: 1 (int) qual - Controls the number of different neural network predictions that are blended together to compute the final output value. Each neural network was trained on a different set of training data. Blending the results of these different networks improves generalization to unseen data. Possible values are 1 or 2. Essentially this is a quality vs speed option. Larger values will result in more processing time, but should give better results. However, the difference is usually pretty small. I would recommend using qual>1 for things like single image enlargement. Default: 1 (int) etype - Controls which set of weights to use in the predictor nn. Possible settings: 0 - weights trained to minimize absolute error 1 - weights trained to minimize squared error Default: 0 (int) pscrn - Controls whether or not the prescreener neural network is used to decide which pixels should be processed by the predictor neural network and which can be handled by simple cubic interpolation. The prescreener is trained to know whether cubic interpolation will be sufficient for a pixel or whether it should be predicted by the predictor nn. The computational complexity of the prescreener nn is much less than that of the predictor nn. Since most pixels can be handled by cubic interpolation, using the prescreener generally results in much faster processing. The prescreener is pretty accurate, so the difference between using it and not using it is almost always unnoticeable. Version 0.9.3 adds a new, faster prescreener with three selectable 'levels', which trade off the number of pixels detected as only requiring cubic interpolation versus incurred error. Therefore, pscrn is now an integer with possible values of 0, 1, 2, 3, and 4. 0 - no prescreening (same as false in prior versions) 1 - original prescreener (same as true in prior versions) 2 - new prescreener level 0 3 - new prescreener level 1 4 - new prescreener level 2 ** Higher levels for the new prescreener result in cubic interpolation being used on fewer pixels (so are slower, but incur less error). However, the difference is pretty much unnoticable. Level 2 is closest to the original prescreener in terms of incurred error, but is much faster. Default: 2 (int) threads - Controls how many threads will be used for processing. If set to 0, threads will be set equal to the number of detected processors. Default: 0 (int) opt - Sets which cpu optimizations to use. Possible settings: 0 = auto detect 1 = use c 2 = use sse2 ** for an older version supporting sse use v0.9.1 available at: ** http://bengal.missouri.edu/~kes25c/old_stuff/ Default: 0 (int) fapprox - Bitmask which enables or disables certain speed-ups. Value range is [0,15]. Mainly for debugging. 0 = nothing &1 = use int16 dot products in first layer of prescreener nn &2 = use int16 dot products in predictor nn &12 = 4 = use exp function approximation in predictor nn &12 = 8|12 = use faster (and more inaccurate) exp function approximation in predictor nn Default: 15 (int) PARAMETERS (nnedi3_rpow2): rfactor - Image enlargement factor. Must be a power of 2 in the range [2,1024]. Default: not set (int) cshift - Sets the resizer used for correcting the image center shift that nnedi3_rpow2 introduces. This can be any of Avisynth's internal resizers, such as "spline36resize", "lanczosresize", etc... If not specified the shift is not corrected. The correction is accomplished by using the subpixel cropping capability of Avisynth's internal resizers. Default: not set (string) fwidth/fheight - If correcting the image center shift by using the 'cshift' parameter, fwidth/fheight allow you to set a new output resolution. First, the image is enlarged by 'rfactor' using nnedi3. Once that is completed the image center shift is corrected, and the image is resampled to fwidth x fheight resolution. The shifting and resampling happen in one call using the internal Avisynth resizer you specify via the 'cshift' string. If fwidth/fheight are not specified, then they are set equal to rfactor*width and rfactor*height respectively (in other words they do nothing). Default: not set (int) not set (int) ep0/ep1 - Some Avisynth resizers take optional arguments, such as 'taps' for lanczosresize or 'p' for gaussresize. ep0/ep1 allow you to pass values for these optional arguments when using the 'cshift' parameter. If the resizer only takes one optional argument then ep0 is used. If the argument that the resizer takes is not a float value, then ep0 gets rounded to an integer. If the resizer takes two optional arguments, then ep0 corresponds to the first one, and ep1 corresponds to the second. The only resizer that takes more than one optional argument is bicubicresize(), which takes 'b' and 'c'. So ep0 = b, and ep1 = c. If ep0/ep1 are not set then the default value for the optional argument(s) of the resizer is used. Default: not set (float) not set (float) nsize/nns/qual/etype/pscrn/threads/opt/fapprox - Same as corresponding parameters in nnedi3. However, nnedi3_rpow2 uses nsize=0 and nns=3 by default (versus nsize=6 and nns=1 in nnedi3()). nnedi3_rpow2 EXAMPLES: a.) enlarge image by 4x, don't correct for center shift. nnedi3_rpow2(rfactor=4) b.) enlarge image by 2x, correct for center shift using spline36resize. nnedi3_rpow2(rfactor=2,cshift="spline36resize") c.) enlarge image by 8x, correct for center shift and downsample from 8x to 7x using lanczosresize with 5 taps. nnedi3_rpow2(rfactor=8,cshift="lanczosresize",fwidth=width*7,fheight=height*7,ep0=5) CHANGE LIST: 06/10/2011 v0.9.4 + some more optimizations + more aggressive new prescreener levels 06/06/2011 v0.9.3 + added new prescreener. Changed 'pscrn' parameter from bool to integer. + added 'etype' parameter and merged abs/squared weights into one binary 09/22/2010 v0.9.2 + clean up and release source code + speed improvements - (thanks Loren Merritt - akupenguin - for many ideas and code) int16 dot products in prescreener/predictor neural networks faster exp function approximation mean removal factored into weights lots of smaller changes + new prediction nn weights for certain nsize/nns combinations + added fapprox parameter - fixed bug with border mirroring - dropped support for sse/mmx - all asm code requires sse2. changed opt parameter accordingly. 07/15/2010 v0.9.1 + add nsize=5/6 (16x4,32x4) + add nns=0 (16 neurons). nns 0/1/2/3 from v0.9 are now 1/2/3/4. - new defaults. nnedi3: nsize=6,nns=1. nnedi3_rpow2: nns=3. - fix field=0/1 flipped with rgb24 input 06/10/2009 v0.9 + First official release - adds nns=0 (32 neurons). nns 0/1/2 from previous beta are now 1/2/3. - adds nsize=4 (8x4). - different nns/nsize defaults for nnedi3_rpow2() vs nnedi3() - change setcachehints call contact: doom9.org forum (nick = tritical)