94 lines
3.2 KiB
C
94 lines
3.2 KiB
C
/*
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** © 2011-2016 by Kornel Lesiński.
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** See COPYRIGHT file for license.
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*/
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#include "libimagequant.h"
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#include "pam.h"
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#include "kmeans.h"
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#include "nearest.h"
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#include <stdlib.h>
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#include <string.h>
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#ifdef _OPENMP
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#include <omp.h>
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#else
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#define omp_get_max_threads() 1
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#define omp_get_thread_num() 0
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#endif
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/*
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* K-Means iteration: new palette color is computed from weighted average of colors that map to that palette entry.
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*/
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LIQ_PRIVATE void kmeans_init(const colormap *map, const unsigned int max_threads, kmeans_state average_color[])
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{
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memset(average_color, 0, sizeof(average_color[0])*(KMEANS_CACHE_LINE_GAP+map->colors)*max_threads);
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}
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LIQ_PRIVATE void kmeans_update_color(const f_pixel acolor, const float value, const colormap *map, unsigned int match, const unsigned int thread, kmeans_state average_color[])
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{
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match += thread * (KMEANS_CACHE_LINE_GAP+map->colors);
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average_color[match].a += acolor.a * value;
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average_color[match].r += acolor.r * value;
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average_color[match].g += acolor.g * value;
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average_color[match].b += acolor.b * value;
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average_color[match].total += value;
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}
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LIQ_PRIVATE void kmeans_finalize(colormap *map, const unsigned int max_threads, const kmeans_state average_color[])
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{
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for (unsigned int i=0; i < map->colors; i++) {
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double a=0, r=0, g=0, b=0, total=0;
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// Aggregate results from all threads
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for(unsigned int t=0; t < max_threads; t++) {
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const unsigned int offset = (KMEANS_CACHE_LINE_GAP+map->colors) * t + i;
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a += average_color[offset].a;
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r += average_color[offset].r;
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g += average_color[offset].g;
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b += average_color[offset].b;
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total += average_color[offset].total;
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}
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if (total && !map->palette[i].fixed) {
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map->palette[i].acolor = (f_pixel){
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.a = a / total,
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.r = r / total,
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.g = g / total,
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.b = b / total,
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};
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map->palette[i].popularity = total;
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}
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}
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}
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LIQ_PRIVATE double kmeans_do_iteration(histogram *hist, colormap *const map, kmeans_callback callback)
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{
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const unsigned int max_threads = omp_get_max_threads();
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LIQ_ARRAY(kmeans_state, average_color, (KMEANS_CACHE_LINE_GAP+map->colors) * max_threads);
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kmeans_init(map, max_threads, average_color);
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struct nearest_map *const n = nearest_init(map);
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hist_item *const achv = hist->achv;
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const int hist_size = hist->size;
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double total_diff=0;
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#pragma omp parallel for if (hist_size > 2000) \
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schedule(static) default(none) shared(average_color,callback) reduction(+:total_diff)
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for(int j=0; j < hist_size; j++) {
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float diff;
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unsigned int match = nearest_search(n, &achv[j].acolor, achv[j].tmp.likely_colormap_index, &diff);
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achv[j].tmp.likely_colormap_index = match;
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total_diff += diff * achv[j].perceptual_weight;
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kmeans_update_color(achv[j].acolor, achv[j].perceptual_weight, map, match, omp_get_thread_num(), average_color);
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if (callback) callback(&achv[j], diff);
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}
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nearest_free(n);
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kmeans_finalize(map, max_threads, average_color);
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return total_diff / hist->total_perceptual_weight;
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}
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