99 lines
3.4 KiB
C
99 lines
3.4 KiB
C
/*
|
|
** © 2011-2016 by Kornel Lesiński.
|
|
** See COPYRIGHT file for license.
|
|
*/
|
|
|
|
#include "libimagequant.h"
|
|
#include "pam.h"
|
|
#include "kmeans.h"
|
|
#include "nearest.h"
|
|
#include <stdlib.h>
|
|
#include <string.h>
|
|
|
|
#ifdef _OPENMP
|
|
#include <omp.h>
|
|
#else
|
|
#define omp_get_max_threads() 1
|
|
#define omp_get_thread_num() 0
|
|
#endif
|
|
|
|
/*
|
|
* K-Means iteration: new palette color is computed from weighted average of colors that map to that palette entry.
|
|
*/
|
|
LIQ_PRIVATE void kmeans_init(const colormap *map, const unsigned int max_threads, kmeans_state average_color[])
|
|
{
|
|
memset(average_color, 0, sizeof(average_color[0])*(KMEANS_CACHE_LINE_GAP+map->colors)*max_threads);
|
|
}
|
|
|
|
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[])
|
|
{
|
|
match += thread * (KMEANS_CACHE_LINE_GAP+map->colors);
|
|
average_color[match].a += acolor.a * value;
|
|
average_color[match].r += acolor.r * value;
|
|
average_color[match].g += acolor.g * value;
|
|
average_color[match].b += acolor.b * value;
|
|
average_color[match].total += value;
|
|
}
|
|
|
|
LIQ_PRIVATE void kmeans_finalize(colormap *map, const unsigned int max_threads, const kmeans_state average_color[])
|
|
{
|
|
for (unsigned int i=0; i < map->colors; i++) {
|
|
double a=0, r=0, g=0, b=0, total=0;
|
|
|
|
// Aggregate results from all threads
|
|
for(unsigned int t=0; t < max_threads; t++) {
|
|
const unsigned int offset = (KMEANS_CACHE_LINE_GAP+map->colors) * t + i;
|
|
|
|
a += average_color[offset].a;
|
|
r += average_color[offset].r;
|
|
g += average_color[offset].g;
|
|
b += average_color[offset].b;
|
|
total += average_color[offset].total;
|
|
}
|
|
|
|
if (total && !map->palette[i].fixed) {
|
|
map->palette[i].acolor = (f_pixel){
|
|
.a = a / total,
|
|
.r = r / total,
|
|
.g = g / total,
|
|
.b = b / total,
|
|
};
|
|
map->palette[i].popularity = total;
|
|
}
|
|
}
|
|
}
|
|
|
|
LIQ_PRIVATE double kmeans_do_iteration(histogram *hist, colormap *const map, kmeans_callback callback)
|
|
{
|
|
const unsigned int max_threads = omp_get_max_threads();
|
|
LIQ_ARRAY(kmeans_state, average_color, (KMEANS_CACHE_LINE_GAP+map->colors) * max_threads);
|
|
kmeans_init(map, max_threads, average_color);
|
|
struct nearest_map *const n = nearest_init(map);
|
|
hist_item *const achv = hist->achv;
|
|
const int hist_size = hist->size;
|
|
|
|
double total_diff=0;
|
|
#if __GNUC__ >= 9
|
|
#pragma omp parallel for if (hist_size > 2000) \
|
|
schedule(static) default(none) shared(achv,average_color,callback,hist_size,map,n) reduction(+:total_diff)
|
|
#else
|
|
#pragma omp parallel for if (hist_size > 2000) \
|
|
schedule(static) default(none) shared(average_color,callback) reduction(+:total_diff)
|
|
#endif
|
|
for(int j=0; j < hist_size; j++) {
|
|
float diff;
|
|
unsigned int match = nearest_search(n, &achv[j].acolor, achv[j].tmp.likely_colormap_index, &diff);
|
|
achv[j].tmp.likely_colormap_index = match;
|
|
total_diff += diff * achv[j].perceptual_weight;
|
|
|
|
kmeans_update_color(achv[j].acolor, achv[j].perceptual_weight, map, match, omp_get_thread_num(), average_color);
|
|
|
|
if (callback) callback(&achv[j], diff);
|
|
}
|
|
|
|
nearest_free(n);
|
|
kmeans_finalize(map, max_threads, average_color);
|
|
|
|
return total_diff / hist->total_perceptual_weight;
|
|
}
|