colors

extract colors from pictures
git clone git://git.2f30.org/colors.git
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commit 9037cdd3fae2eda25f838d06afd7cb37698438b8
parent 21e5f9472c2bfdb87f4e1f47e2d5d57ac7196827
Author: sin <sin@2f30.org>
Date:   Tue,  9 Jun 2015 16:29:36 +0100

Add support for k-medians clustering

Diffstat:
colors.1 | 10++++++----
colors.c | 71++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++---
2 files changed, 74 insertions(+), 7 deletions(-)

diff --git a/colors.1 b/colors.1 @@ -1,4 +1,4 @@ -.Dd June 6, 2015 +.Dd June 9, 2015 .Dt COLORS 1 .Os .Sh NAME @@ -6,19 +6,21 @@ .Nd extract colors from pictures .Sh SYNOPSIS .Nm colors -.Op Fl er +.Op Fl erm .Op Fl h | Fl p .Op Fl n Ar clusters .Ar file .Sh DESCRIPTION .Nm -is a simple tool that uses k-means clustering to extract dominant colors -from pictures. By default it selects initial clusters based on brightness +is a simple tool to extract dominant colors from pictures. By default it selects +initial clusters based on brightness steps. .Sh OPTIONS .Bl -tag -width Ds .It Fl e Print empty clusters as well. +.It Fl m +Use k-medians clustering instead of k-means. .It Fl r Randomize cluster selection. .It Fl h diff --git a/colors.c b/colors.c @@ -33,6 +33,7 @@ int eflag; int rflag; int hflag; int pflag; +int mflag; int distance(struct point *p1, struct point *p2) @@ -46,7 +47,7 @@ distance(struct point *p1, struct point *p2) } void -adjcluster(struct cluster *c) +adjmeans(struct cluster *c) { struct point *p; struct point newc = { 0 }; @@ -67,13 +68,72 @@ adjcluster(struct cluster *c) c->center = newc; } +struct cluster *curcluster; +int +pointcmp(const void *a, const void *b) +{ + struct point *p1 = *(struct point **)a; + struct point *p2 = *(struct point **)b; + int d1, d2; + + d1 = distance(&curcluster->center, p1); + d2 = distance(&curcluster->center, p2); + return d1 - d2; +} + +void +adjmedians(struct cluster *c) +{ + struct point *p, **tab; + struct point newc = { 0 }; + long x, y, z; + size_t i; + + if (!c->nmembers) + return; + + /* create a table out of the list to make sorting easy */ + tab = malloc(c->nmembers * sizeof(*tab)); + if (!tab) + err(1, "malloc"); + i = 0; + TAILQ_FOREACH(p, &c->members, e) + tab[i++] = p; + + qsort(tab, c->nmembers, sizeof(*tab), pointcmp); + + /* calculate median */ + x = tab[c->nmembers / 2]->x; + y = tab[c->nmembers / 2]->y; + z = tab[c->nmembers / 2]->z; + if (!(c->nmembers % 2)) { + x += tab[c->nmembers / 2 - 1]->x; + y += tab[c->nmembers / 2 - 1]->y; + z += tab[c->nmembers / 2 - 1]->z; + newc.x = x / 2; + newc.y = y / 2; + newc.z = z / 2; + } else { + newc.x = x; + newc.y = y; + newc.z = z; + } + + c->center = newc; + free(tab); +} + +void (*adjcluster)(struct cluster *c) = adjmeans; + void adjclusters(struct cluster *c, size_t n) { size_t i; - for (i = 0; i < n; i++) + for (i = 0; i < n; i++) { + curcluster = &c[i]; adjcluster(&c[i]); + } } void @@ -259,7 +319,7 @@ printclusters(void) void usage(void) { - fprintf(stderr, "usage: %s [-er] [-h | -p] [-n clusters] file\n", argv0); + fprintf(stderr, "usage: %s [-emr] [-h | -p] [-n clusters] file\n", argv0); exit(1); } @@ -272,6 +332,9 @@ main(int argc, char *argv[]) case 'e': eflag = 1; break; + case 'm': + mflag = 1; + break; case 'r': rflag = 1; break; @@ -299,6 +362,8 @@ main(int argc, char *argv[]) TAILQ_INIT(&points); parseimg(argv[0], fillpoints); + if (mflag) + adjcluster = adjmedians; if (rflag) srand(time(NULL)); if (pflag) {