2020-04-12 17:42:36 +00:00
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/* NeuQuant Neural-Net Quantization Algorithm Interface
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* ----------------------------------------------------
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*
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* Copyright (c) 1994 Anthony Dekker
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*
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* NEUQUANT Neural-Net quantization algorithm by Anthony Dekker, 1994.
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* See "Kohonen neural networks for optimal colour quantization"
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* in "Network: Computation in Neural Systems" Vol. 5 (1994) pp 351-367.
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* for a discussion of the algorithm.
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* See also http://www.acm.org/~dekker/NEUQUANT.HTML
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*
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* Any party obtaining a copy of these files from the author, directly or
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* indirectly, is granted, free of charge, a full and unrestricted irrevocable,
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* world-wide, paid up, royalty-free, nonexclusive right and license to deal
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* in this software and documentation files (the "Software"), including without
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* limitation the rights to use, copy, modify, merge, publish, distribute, sublicense,
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* and/or sell copies of the Software, and to permit persons who receive
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* copies from any such party to do so, with the only requirement being
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* that this copyright notice remain intact.
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*/
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#include <stdio.h>
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#define netsize 256 /* number of colours used */
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/* For 256 colours, fixed arrays need 8kb, plus space for the image
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---------------------------------------------------------------- */
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/* four primes near 500 - assume no image has a length so large */
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/* that it is divisible by all four primes */
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#define prime1 499
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#define prime2 491
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#define prime3 487
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#define prime4 503
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#define minpicturebytes (3*prime4) /* minimum size for input image */
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/* Initialise network in range (0,0,0) to (255,255,255) and set parameters
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----------------------------------------------------------------------- */
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void initnet(unsigned char *thepic, int len, int sample);
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/* Unbias network to give byte values 0..255 and record position i to prepare for sort
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----------------------------------------------------------------------------------- */
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void unbiasnet(); /* can edit this function to do output of colour map */
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/* Output colour map
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----------------- */
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void writecolourmap(FILE *f);
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/* Insertion sort of network and building of netindex[0..255] (to do after unbias)
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------------------------------------------------------------------------------- */
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void inxbuild();
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/* Search for BGR values 0..255 (after net is unbiased) and return colour index
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---------------------------------------------------------------------------- */
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2020-04-12 17:43:09 +00:00
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char inxsearch(register int b, register int g, register int r);
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2020-04-12 17:42:36 +00:00
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/* Main Learning Loop
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------------------ */
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void learn();
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/* Program Skeleton
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----------------
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[select samplefac in range 1..30]
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pic = (unsigned char*) malloc(3*width*height);
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[read image from input file into pic]
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initnet(pic,3*width*height,samplefac);
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learn();
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unbiasnet();
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[write output image header, using writecolourmap(f),
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possibly editing the loops in that function]
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inxbuild();
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[write output image using inxsearch(b,g,r)] */
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