506ea20d36
Added Gürkan Sengün to the bugfinders as he found the problem. Thanks ! git-svn-id: svn://pulkomandy.tk/GrafX2/trunk@759 416bcca6-2ee7-4201-b75f-2eb2f807beb1
1233 lines
32 KiB
C
1233 lines
32 KiB
C
/* Grafx2 - The Ultimate 256-color bitmap paint program
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||
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Copyright 2007 Adrien Destugues
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Copyright 1996-2001 Sunset Design (Guillaume Dorme & Karl Maritaud)
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Grafx2 is free software; you can redistribute it and/or
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modify it under the terms of the GNU General Public License
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||
as published by the Free Software Foundation; version 2
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of the License.
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||
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Grafx2 is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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||
You should have received a copy of the GNU General Public License
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along with Grafx2; if not, see <http://www.gnu.org/licenses/> or
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write to the Free Software Foundation, Inc.,
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59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
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*/
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#include <unistd.h>
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#include <stdlib.h>
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#include <string.h>
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#include <stdio.h>
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#include <fcntl.h>
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#include <sys/stat.h>
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#include <math.h>
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#include "op_c.h"
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#include "errors.h"
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void RGB_to_HSL(int r,int g,int b,byte * hr,byte * sr,byte* lr)
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{
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double rd,gd,bd,h,s,l,max,min;
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// convert RGB to HSV
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rd = r / 255.0; // rd,gd,bd range 0-1 instead of 0-255
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gd = g / 255.0;
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bd = b / 255.0;
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// compute L
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// l=(rd*0.30)+(gd*0.59)+(bd*0.11);
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// compute maximum of rd,gd,bd
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if (rd>=gd)
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{
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||
if (rd>=bd)
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max = rd;
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else
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max = bd;
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}
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else
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{
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if (gd>=bd)
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max = gd;
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else
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max = bd;
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||
}
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||
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// compute minimum of rd,gd,bd
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if (rd<=gd)
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{
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if (rd<=bd)
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min = rd;
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else
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min = bd;
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}
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else
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{
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if (gd<=bd)
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min = gd;
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else
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min = bd;
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}
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l = (max + min) / 2.0;
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if(max==min)
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s = h = 0;
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else
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{
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if (l<=0.5)
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s = (max - min) / (max + min);
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else
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s = (max - min) / (2 - (max + min));
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if (max == rd)
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h = 42.5 * (gd-bd)/(max-min);
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else if (max == gd)
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h = 42.5 * (bd-rd)/(max-min)+85;
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else
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h = 42.5 * (rd-gd)/(max-min)+170;
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if (h<0) h+=255;
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}
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*hr = h;
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*lr = (l*255.0);
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*sr = (s*255.0);
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}
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void HSL_to_RGB(byte h,byte s,byte l, byte* r, byte* g, byte* b)
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{
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float rf =0 ,gf = 0,bf = 0;
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float hf,lf,sf;
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float p,q;
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if(s==0)
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{
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*r=*g=*b=l;
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return;
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}
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hf = h / 255.0;
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lf = l / 255.0;
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sf = s / 255.0;
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if (lf<=0.5)
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q = lf*(1+sf);
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else
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q = lf+sf-lf*sf;
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p = 2*lf-q;
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rf = hf + (1 / 3.0);
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gf = hf;
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bf = hf - (1 / 3.0);
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if (rf < 0) rf+=1;
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if (rf > 1) rf-=1;
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if (gf < 0) gf+=1;
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if (gf > 1) gf-=1;
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if (bf < 0) bf+=1;
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if (bf > 1) bf-=1;
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if (rf < 1/6.0)
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rf = p + ((q-p)*6*rf);
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else if(rf < 0.5)
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rf = q;
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else if(rf < 2/3.0)
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rf = p + ((q-p)*6*(2/3.0-rf));
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else
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rf = p;
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if (gf < 1/6.0)
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gf = p + ((q-p)*6*gf);
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else if(gf < 0.5)
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gf = q;
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else if(gf < 2/3.0)
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gf = p + ((q-p)*6*(2/3.0-gf));
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else
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gf = p;
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if (bf < 1/6.0)
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bf = p + ((q-p)*6*bf);
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else if(bf < 0.5)
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bf = q;
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else if(bf < 2/3.0)
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bf = p + ((q-p)*6*(2/3.0-bf));
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else
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bf = p;
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*r = rf * (255);
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*g = gf * (255);
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*b = bf * (255);
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}
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||
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/////////////////////////////////////////////////////////////////////////////
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///////////////////////////// M<>thodes de gestion des tables de conversion //
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/////////////////////////////////////////////////////////////////////////////
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T_Conversion_table * CT_new(int nbb_r,int nbb_g,int nbb_b)
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{
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||
T_Conversion_table * n;
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int size;
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||
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n=(T_Conversion_table *)malloc(sizeof(T_Conversion_table));
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if (n!=NULL)
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{
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// On recopie les param<61>tres demand<6E>s
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n->nbb_r=nbb_r;
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n->nbb_g=nbb_g;
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n->nbb_b=nbb_b;
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// On calcule les autres
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n->rng_r=(1<<nbb_r);
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n->rng_g=(1<<nbb_g);
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n->rng_b=(1<<nbb_b);
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n->dec_r=nbb_g+nbb_b;
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n->dec_g=nbb_b;
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n->dec_b=0;
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n->red_r=8-nbb_r;
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n->red_g=8-nbb_g;
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||
n->red_b=8-nbb_b;
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||
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// On tente d'allouer la table
|
||
size=(n->rng_r)*(n->rng_g)*(n->rng_b);
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n->table=(byte *)malloc(size);
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||
if (n->table!=NULL)
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// C'est bon!
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memset(n->table,0,size); // Inutile, mais plus propre
|
||
else
|
||
{
|
||
// Table impossible <20> allouer
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||
free(n);
|
||
n=NULL;
|
||
}
|
||
}
|
||
|
||
return n;
|
||
}
|
||
|
||
void CT_delete(T_Conversion_table * t)
|
||
{
|
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free(t->table);
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||
free(t);
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}
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||
|
||
byte CT_get(T_Conversion_table * t,int r,int g,int b)
|
||
{
|
||
int index;
|
||
|
||
// On r<>duit le nombre de bits par couleur
|
||
r=(r>>t->red_r);
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||
g=(g>>t->red_g);
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||
b=(b>>t->red_b);
|
||
|
||
// On recherche la couleur la plus proche dans la table de conversion
|
||
index=(r<<t->dec_r) | (g<<t->dec_g) | (b<<t->dec_b);
|
||
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||
return t->table[index];
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||
}
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||
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void CT_set(T_Conversion_table * t,int r,int g,int b,byte i)
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{
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||
int index;
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||
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index=(r<<t->dec_r) | (g<<t->dec_g) | (b<<t->dec_b);
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||
t->table[index]=i;
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}
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||
|
||
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||
|
||
/////////////////////////////////////////////////////////////////////////////
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||
/////////////////////////////// M<>thodes de gestion des tables d'occurence //
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||
/////////////////////////////////////////////////////////////////////////////
|
||
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||
void OT_init(T_Occurrence_table * t)
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{
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||
int size;
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size=(t->rng_r)*(t->rng_g)*(t->rng_b)*sizeof(int);
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memset(t->table,0,size); // On initialise <20> 0
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}
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T_Occurrence_table * OT_new(int nbb_r,int nbb_g,int nbb_b)
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{
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T_Occurrence_table * n;
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||
int size;
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n=(T_Occurrence_table *)malloc(sizeof(T_Occurrence_table));
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||
if (n!=0)
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{
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||
// On recopie les param<61>tres demand<6E>s
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n->nbb_r=nbb_r;
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n->nbb_g=nbb_g;
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n->nbb_b=nbb_b;
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// On calcule les autres
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n->rng_r=(1<<nbb_r);
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n->rng_g=(1<<nbb_g);
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n->rng_b=(1<<nbb_b);
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n->dec_r=nbb_g+nbb_b;
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n->dec_g=nbb_b;
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n->dec_b=0;
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n->red_r=8-nbb_r;
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n->red_g=8-nbb_g;
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n->red_b=8-nbb_b;
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// On tente d'allouer la table
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||
size=(n->rng_r)*(n->rng_g)*(n->rng_b)*sizeof(int);
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n->table=(int *)malloc(size);
|
||
if (n->table!=0)
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||
// C'est bon! On initialise <20> 0
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OT_init(n);
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||
else
|
||
{
|
||
// Table impossible <20> allouer
|
||
free(n);
|
||
n=0;
|
||
}
|
||
}
|
||
|
||
return n;
|
||
}
|
||
|
||
void OT_delete(T_Occurrence_table * t)
|
||
{
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free(t->table);
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free(t);
|
||
}
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||
|
||
int OT_get(T_Occurrence_table * t,int r,int g,int b)
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||
{
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||
int index;
|
||
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||
index=(r<<t->dec_r) | (g<<t->dec_g) | (b<<t->dec_b);
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return t->table[index];
|
||
}
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||
|
||
void OT_set(T_Occurrence_table * t,int r,int g,int b,int i)
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{
|
||
int index;
|
||
|
||
r=(r>>t->red_r);
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||
g=(g>>t->red_g);
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||
b=(b>>t->red_b);
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||
index=(r<<t->dec_r) | (g<<t->dec_g) | (b<<t->dec_b);
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t->table[index]=i;
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||
}
|
||
|
||
void OT_inc(T_Occurrence_table * t,int r,int g,int b)
|
||
{
|
||
int index;
|
||
|
||
r=(r>>t->red_r);
|
||
g=(g>>t->red_g);
|
||
b=(b>>t->red_b);
|
||
index=(r<<t->dec_r) | (g<<t->dec_g) | (b<<t->dec_b);
|
||
t->table[index]++;
|
||
}
|
||
|
||
void OT_count_occurrences(T_Occurrence_table * t,T_Bitmap24B image,int size)
|
||
{
|
||
T_Bitmap24B ptr;
|
||
int index;
|
||
|
||
for (index=size,ptr=image;index>0;index--,ptr++)
|
||
OT_inc(t,ptr->R,ptr->G,ptr->B);
|
||
}
|
||
|
||
int OT_count_colors(T_Occurrence_table * t)
|
||
{
|
||
int val; // Valeur de retour
|
||
int nb; // Nombre de couleurs <20> tester
|
||
int i; // Compteur de couleurs test<73>es
|
||
|
||
val=0;
|
||
nb=(t->rng_r)*(t->rng_g)*(t->rng_b);
|
||
for (i=0;i<nb;i++)
|
||
if (t->table[i]>0)
|
||
val++;
|
||
|
||
return val;
|
||
}
|
||
|
||
|
||
|
||
/////////////////////////////////////////////////////////////////////////////
|
||
///////////////////////////////////////// M<>thodes de gestion des clusters //
|
||
/////////////////////////////////////////////////////////////////////////////
|
||
|
||
void Cluster_analyser(T_Cluster * c,T_Occurrence_table * to)
|
||
{
|
||
int rmin,rmax,vmin,vmax,bmin,bmax;
|
||
int r,g,b;
|
||
|
||
// On cherche les mins et les maxs de chaque composante sur la couverture
|
||
|
||
// int nbocc;
|
||
|
||
// On pr<70>d<EFBFBD>cale tout pour <20>viter de faire trop de bazar en se for<6F>ant <20> utiliser OT_get, plus rapide
|
||
rmin=c->rmax <<16; rmax=c->rmin << 16;
|
||
vmin=c->vmax << 8; vmax=c->vmin << 8;
|
||
bmin=c->bmax; bmax=c->bmin;
|
||
c->occurences=0;
|
||
/*
|
||
for (r=c->rmin<<16;r<=c->rmax<<16;r+=1<<16)
|
||
for (g=c->vmin<<8;g<=c->vmax<<8;g+=1<<8)
|
||
for (b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
nbocc=to->table[r + g + b]; // OT_get
|
||
if (nbocc)
|
||
{
|
||
if (r<rmin) rmin=r;
|
||
else if (r>rmax) rmax=r;
|
||
if (g<vmin) vmin=g;
|
||
else if (g>vmax) vmax=g;
|
||
if (b<bmin) bmin=b;
|
||
else if (b>bmax) bmax=b;
|
||
c->occurences+=nbocc;
|
||
}
|
||
}
|
||
*/
|
||
|
||
// On recherche le minimum et le maximum en parcourant le cluster selon chaque composante,
|
||
// <20>a <20>vite des acc<63>s m<>moires inutiles, de plus chaque boucle est plus petite que la
|
||
// pr<70>c<EFBFBD>dente puisqu'on connait une borne suppl<70>mentaire
|
||
|
||
for(r=c->rmin<<16;r<=c->rmax<<16;r+=1<<16)
|
||
for(g=c->vmin<<8;g<=c->vmax<<8;g+=1<<8)
|
||
for(b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
if(to->table[r + g + b]) // OT_get
|
||
{
|
||
rmin=r;
|
||
goto RMAX;
|
||
}
|
||
}
|
||
RMAX:
|
||
for(r=c->rmax<<16;r>=rmin;r-=1<<16)
|
||
for(g=c->vmin<<8;g<=c->vmax<<8;g+=1<<8)
|
||
for(b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
if(to->table[r + g + b]) // OT_get
|
||
{
|
||
rmax=r;
|
||
goto VMIN;
|
||
}
|
||
}
|
||
VMIN:
|
||
for(g=c->vmin<<8;g<=c->vmax<<8;g+=1<<8)
|
||
for(r=rmin;r<=rmax;r+=1<<16)
|
||
for(b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
if(to->table[r + g + b]) // OT_get
|
||
{
|
||
vmin=g;
|
||
goto VMAX;
|
||
}
|
||
}
|
||
VMAX:
|
||
for(g=c->vmax<<8;g>=vmin;g-=1<<8)
|
||
for(r=rmin;r<=rmax;r+=1<<16)
|
||
for(b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
if(to->table[r + g + b]) // OT_get
|
||
{
|
||
vmax=g;
|
||
goto BMIN;
|
||
}
|
||
}
|
||
BMIN:
|
||
for(b=c->bmin;b<=c->bmax;b++)
|
||
for(r=rmin;r<=rmax;r+=1<<16)
|
||
for(g=vmin;g<=vmax;g+=1<<8)
|
||
{
|
||
if(to->table[r + g + b]) // OT_get
|
||
{
|
||
bmin=b;
|
||
goto BMAX;
|
||
}
|
||
}
|
||
BMAX:
|
||
for(b=c->bmax;b>=bmin;b--)
|
||
for(r=rmin;r<=rmax;r+=1<<16)
|
||
for(g=vmin;g<=vmax;g+=1<<8)
|
||
{
|
||
if(to->table[r + g + b]) // OT_get
|
||
{
|
||
bmax=b;
|
||
goto ENDCRUSH;
|
||
}
|
||
}
|
||
ENDCRUSH:
|
||
// Il faut quand m<>me parcourir la partie utile du cluster, pour savoir combien il y a d'occurences
|
||
for(r=rmin;r<=rmax;r+=1<<16)
|
||
for(g=vmin;g<=vmax;g+=1<<8)
|
||
for(b=bmin;b<=bmax;b++)
|
||
{
|
||
c->occurences+=to->table[r + g + b]; // OT_get
|
||
}
|
||
|
||
c->rmin=rmin>>16; c->rmax=rmax>>16;
|
||
c->vmin=vmin>>8; c->vmax=vmax>>8;
|
||
c->bmin=bmin; c->bmax=bmax;
|
||
|
||
// On regarde la composante qui a la variation la plus grande
|
||
r=(c->rmax-c->rmin)*299;
|
||
g=(c->vmax-c->vmin)*587;
|
||
b=(c->bmax-c->bmin)*114;
|
||
|
||
if (g>=r)
|
||
{
|
||
// G>=R
|
||
if (g>=b)
|
||
{
|
||
// G>=R et G>=B
|
||
c->plus_large=1;
|
||
}
|
||
else
|
||
{
|
||
// G>=R et G<B
|
||
c->plus_large=2;
|
||
}
|
||
}
|
||
else
|
||
{
|
||
// R>G
|
||
if (r>=b)
|
||
{
|
||
// R>G et R>=B
|
||
c->plus_large=0;
|
||
}
|
||
else
|
||
{
|
||
// R>G et R<B
|
||
c->plus_large=2;
|
||
}
|
||
}
|
||
}
|
||
|
||
void Cluster_split(T_Cluster * c,T_Cluster * c1,T_Cluster * c2,int hue,T_Occurrence_table * to)
|
||
{
|
||
int limit;
|
||
int cumul;
|
||
int r,g,b;
|
||
|
||
limit=(c->occurences)/2;
|
||
cumul=0;
|
||
if (hue==0)
|
||
{
|
||
for (r=c->rmin<<16;r<=c->rmax<<16;r+=1<<16)
|
||
{
|
||
for (g=c->vmin<<8;g<=c->vmax<<8;g+=1<<8)
|
||
{
|
||
for (b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
cumul+=to->table[r + g + b];
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
|
||
r>>=16;
|
||
g>>=8;
|
||
|
||
if (r==c->rmin)
|
||
r++;
|
||
// R est la valeur de d<>but du 2nd cluster
|
||
|
||
c1->Rmin=c->Rmin; c1->Rmax=r-1;
|
||
c1->rmin=c->rmin; c1->rmax=r-1;
|
||
c1->Gmin=c->Gmin; c1->Vmax=c->Vmax;
|
||
c1->vmin=c->vmin; c1->vmax=c->vmax;
|
||
c1->Bmin=c->Bmin; c1->Bmax=c->Bmax;
|
||
c1->bmin=c->bmin; c1->bmax=c->bmax;
|
||
c2->Rmin=r; c2->Rmax=c->Rmax;
|
||
c2->rmin=r; c2->rmax=c->rmax;
|
||
c2->Gmin=c->Gmin; c2->Vmax=c->Vmax;
|
||
c2->vmin=c->vmin; c2->vmax=c->vmax;
|
||
c2->Bmin=c->Bmin; c2->Bmax=c->Bmax;
|
||
c2->bmin=c->bmin; c2->bmax=c->bmax;
|
||
}
|
||
else
|
||
if (hue==1)
|
||
{
|
||
|
||
for (g=c->vmin<<8;g<=c->vmax<<8;g+=1<<8)
|
||
{
|
||
for (r=c->rmin<<16;r<=c->rmax<<16;r+=1<<16)
|
||
{
|
||
for (b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
cumul+=to->table[r + g + b];
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
|
||
r>>=16; g>>=8;
|
||
|
||
if (g==c->vmin)
|
||
g++;
|
||
// G est la valeur de d<>but du 2nd cluster
|
||
|
||
c1->Rmin=c->Rmin; c1->Rmax=c->Rmax;
|
||
c1->rmin=c->rmin; c1->rmax=c->rmax;
|
||
c1->Gmin=c->Gmin; c1->Vmax=g-1;
|
||
c1->vmin=c->vmin; c1->vmax=g-1;
|
||
c1->Bmin=c->Bmin; c1->Bmax=c->Bmax;
|
||
c1->bmin=c->bmin; c1->bmax=c->bmax;
|
||
c2->Rmin=c->Rmin; c2->Rmax=c->Rmax;
|
||
c2->rmin=c->rmin; c2->rmax=c->rmax;
|
||
c2->Gmin=g; c2->Vmax=c->Vmax;
|
||
c2->vmin=g; c2->vmax=c->vmax;
|
||
c2->Bmin=c->Bmin; c2->Bmax=c->Bmax;
|
||
c2->bmin=c->bmin; c2->bmax=c->bmax;
|
||
}
|
||
else
|
||
{
|
||
|
||
for (b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
for (g=c->vmin<<8;g<=c->vmax<<8;g+=1<<8)
|
||
{
|
||
for (r=c->rmin<<16;r<=c->rmax<<16;r+=1<<16)
|
||
{
|
||
cumul+=to->table[r + g + b];
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
|
||
r>>=16; g>>=8;
|
||
|
||
if (b==c->bmin)
|
||
b++;
|
||
// B est la valeur de d<>but du 2nd cluster
|
||
|
||
c1->Rmin=c->Rmin; c1->Rmax=c->Rmax;
|
||
c1->rmin=c->rmin; c1->rmax=c->rmax;
|
||
c1->Gmin=c->Gmin; c1->Vmax=c->Vmax;
|
||
c1->vmin=c->vmin; c1->vmax=c->vmax;
|
||
c1->Bmin=c->Bmin; c1->Bmax=b-1;
|
||
c1->bmin=c->bmin; c1->bmax=b-1;
|
||
c2->Rmin=c->Rmin; c2->Rmax=c->Rmax;
|
||
c2->rmin=c->rmin; c2->rmax=c->rmax;
|
||
c2->Gmin=c->Gmin; c2->Vmax=c->Vmax;
|
||
c2->vmin=c->vmin; c2->vmax=c->vmax;
|
||
c2->Bmin=b; c2->Bmax=c->Bmax;
|
||
c2->bmin=b; c2->bmax=c->bmax;
|
||
}
|
||
}
|
||
|
||
void Cluster_compute_hue(T_Cluster * c,T_Occurrence_table * to)
|
||
{
|
||
int cumul_r,cumul_g,cumul_b;
|
||
int r,g,b;
|
||
int nbocc;
|
||
|
||
byte s=0;
|
||
|
||
cumul_r=cumul_g=cumul_b=0;
|
||
for (r=c->rmin;r<=c->rmax;r++)
|
||
for (g=c->vmin;g<=c->vmax;g++)
|
||
for (b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
nbocc=OT_get(to,r,g,b);
|
||
if (nbocc)
|
||
{
|
||
cumul_r+=r*nbocc;
|
||
cumul_g+=g*nbocc;
|
||
cumul_b+=b*nbocc;
|
||
}
|
||
}
|
||
|
||
c->r=(cumul_r<<to->red_r)/c->occurences;
|
||
c->g=(cumul_g<<to->red_g)/c->occurences;
|
||
c->b=(cumul_b<<to->red_b)/c->occurences;
|
||
RGB_to_HSL(c->r,c->g,c->b,&c->h,&s,&c->l);
|
||
}
|
||
|
||
|
||
|
||
/////////////////////////////////////////////////////////////////////////////
|
||
//////////////////////////// M<>thodes de gestion des ensembles de clusters //
|
||
/////////////////////////////////////////////////////////////////////////////
|
||
|
||
void CS_Init(T_Cluster_set * cs,T_Occurrence_table * to)
|
||
{
|
||
cs->clusters[0].Rmin=cs->clusters[0].rmin=0;
|
||
cs->clusters[0].Gmin=cs->clusters[0].vmin=0;
|
||
cs->clusters[0].Bmin=cs->clusters[0].bmin=0;
|
||
cs->clusters[0].Rmax=cs->clusters[0].rmax=to->rng_r-1;
|
||
cs->clusters[0].Vmax=cs->clusters[0].vmax=to->rng_g-1;
|
||
cs->clusters[0].Bmax=cs->clusters[0].bmax=to->rng_b-1;
|
||
Cluster_analyser(cs->clusters+0,to);
|
||
// Et hop : le 1er ensemble de couleurs est initialis<69>
|
||
cs->nb=1;
|
||
}
|
||
|
||
T_Cluster_set * CS_New(int nbmax,T_Occurrence_table * to)
|
||
{
|
||
T_Cluster_set * n;
|
||
|
||
n=(T_Cluster_set *)malloc(sizeof(T_Cluster_set));
|
||
if (n!=0)
|
||
{
|
||
// On recopie les param<61>tres demand<6E>s
|
||
n->nb_max=OT_count_colors(to);
|
||
|
||
// On vient de compter le nombre de couleurs existantes, s'il est plus grand que 256 on limit <20> 256 (nombre de couleurs voulu au final)
|
||
if (n->nb_max>nbmax)
|
||
{
|
||
n->nb_max=nbmax;
|
||
}
|
||
|
||
// On tente d'allouer la table
|
||
n->clusters=(T_Cluster *)malloc(nbmax*sizeof(T_Cluster));
|
||
if (n->clusters!=NULL)
|
||
// C'est bon! On initialise
|
||
CS_Init(n,to);
|
||
else
|
||
{
|
||
// Table impossible <20> allouer
|
||
free(n);
|
||
n=0;
|
||
}
|
||
}
|
||
|
||
return n;
|
||
}
|
||
|
||
void CS_Delete(T_Cluster_set * cs)
|
||
{
|
||
free(cs->clusters);
|
||
free(cs);
|
||
}
|
||
|
||
void CS_Get(T_Cluster_set * cs,T_Cluster * c)
|
||
{
|
||
int index;
|
||
|
||
// On cherche un cluster que l'on peut couper en deux, donc avec au moins deux valeurs
|
||
// diff<66>rentes sur l'une des composantes
|
||
for (index=0;index<cs->nb;index++)
|
||
if ( (cs->clusters[index].rmin<cs->clusters[index].rmax) ||
|
||
(cs->clusters[index].vmin<cs->clusters[index].vmax) ||
|
||
(cs->clusters[index].bmin<cs->clusters[index].bmax) )
|
||
break;
|
||
|
||
// On le recopie dans c
|
||
*c=cs->clusters[index];
|
||
|
||
// On d<>cr<63>mente le nombre et on d<>cale tous les clusters suivants
|
||
// Sachant qu'on va r<>ins<6E>rer juste apr<70>s, il me semble que <20>a serait une bonne id<69>e de g<>rer les clusters
|
||
// comme une liste chain<69>e... on n'a aucun acc<63>s direct dedans, que des parcours ...
|
||
cs->nb--;
|
||
memcpy((cs->clusters+index),(cs->clusters+index+1),(cs->nb-index)*sizeof(T_Cluster));
|
||
}
|
||
|
||
void CS_Set(T_Cluster_set * cs,T_Cluster * c)
|
||
{
|
||
int index;
|
||
// int decalage;
|
||
|
||
// Le tableau des clusters est tri<72> par nombre d'occurences. Donc on cherche la position du premier cluster
|
||
// qui est plus grand que le notre
|
||
for (index=0;index<cs->nb;index++)
|
||
if (cs->clusters[index].occurences<c->occurences)
|
||
/*
|
||
if (((OPTPAL_Cluster[index].rmax-OPTPAL_Cluster[index].rmin+1)*
|
||
(OPTPAL_Cluster[index].gmax-OPTPAL_Cluster[index].gmin+1)*
|
||
(OPTPAL_Cluster[index].bmax-OPTPAL_Cluster[index].bmin+1))
|
||
<
|
||
((Set->rmax-Set->rmin+1)*
|
||
(Set->gmax-Set->gmin+1)*
|
||
(Set->bmax-Set->bmin+1))
|
||
)
|
||
*/
|
||
break;
|
||
|
||
if (index<cs->nb)
|
||
{
|
||
// On distingue ici une insertion plutot qu'un placement en fin de liste.
|
||
// On doit donc d<>caler les ensembles suivants vers la fin pour se faire
|
||
// une place dans la liste.
|
||
|
||
//for (decalage=cs->nb;decalage>index;decalage--)
|
||
// memcpy((cs->clusters+decalage),(cs->clusters+decalage-1),sizeof(T_Cluster));
|
||
memmove(cs->clusters+index+1,cs->clusters+index,(cs->nb-index)*sizeof(T_Cluster));
|
||
}
|
||
|
||
cs->clusters[index]=*c;
|
||
cs->nb++;
|
||
}
|
||
|
||
// D<>termination de la meilleure palette en utilisant l'algo Median Cut :
|
||
// 1) On consid<69>re l'espace (R,G,B) comme 1 bo<62>te
|
||
// 2) On cherche les extr<74>mes de la bo<62>te en (R,G,B)
|
||
// 3) On trie les pixels de l'image selon l'axe le plus long parmi (R,G,B)
|
||
// 4) On coupe la bo<62>te en deux au milieu, et on compacte pour que chaque bord corresponde bien <20> un pixel extreme
|
||
// 5) On recommence <20> couper selon le plus grand axe toutes bo<62>tes confondues
|
||
// 6) On s'arr<72>te quand on a le nombre de couleurs voulu
|
||
void CS_Generate(T_Cluster_set * cs,T_Occurrence_table * to)
|
||
{
|
||
T_Cluster current;
|
||
T_Cluster Nouveau1;
|
||
T_Cluster Nouveau2;
|
||
|
||
// Tant qu'on a moins de 256 clusters
|
||
while (cs->nb<cs->nb_max)
|
||
{
|
||
// On r<>cup<75>re le plus grand cluster
|
||
CS_Get(cs,¤t);
|
||
|
||
// On le coupe en deux
|
||
Cluster_split(¤t,&Nouveau1,&Nouveau2,current.plus_large,to);
|
||
|
||
// On compacte ces deux nouveaux (il peut y avoir un espace entre l'endroit de la coupure et les premiers pixels du cluster)
|
||
Cluster_analyser(&Nouveau1,to);
|
||
Cluster_analyser(&Nouveau2,to);
|
||
|
||
// On met ces deux nouveaux clusters dans le clusterSet... sauf s'ils sont vides
|
||
if(Nouveau1.occurences>0)
|
||
CS_Set(cs,&Nouveau1);
|
||
if(Nouveau2.occurences>0)
|
||
CS_Set(cs,&Nouveau2);
|
||
}
|
||
}
|
||
|
||
void CS_Compute_colors(T_Cluster_set * cs,T_Occurrence_table * to)
|
||
{
|
||
int index;
|
||
T_Cluster * c;
|
||
|
||
for (index=0,c=cs->clusters;index<cs->nb;index++,c++)
|
||
Cluster_compute_hue(c,to);
|
||
}
|
||
|
||
void CS_Sort_by_chrominance(T_Cluster_set * cs)
|
||
{
|
||
int byte_used[256];
|
||
int decalages[256];
|
||
int index;
|
||
T_Cluster * nc;
|
||
|
||
nc=(T_Cluster *)malloc(cs->nb_max*sizeof(T_Cluster));
|
||
|
||
// Initialisation de la table d'occurence de chaque octet
|
||
for (index=0;index<256;index++)
|
||
byte_used[index]=0;
|
||
|
||
// Comptage du nombre d'occurences de chaque octet
|
||
for (index=0;index<cs->nb;index++)
|
||
byte_used[cs->clusters[index].h]++;
|
||
|
||
// Calcul de la table des d<>calages
|
||
decalages[0]=0;
|
||
for (index=1;index<256;index++)
|
||
decalages[index]=decalages[index-1]+byte_used[index-1];
|
||
|
||
// Copie r<>ordonn<6E>e dans la nouvelle liste
|
||
for (index=0;index<cs->nb;index++)
|
||
{
|
||
nc[decalages[cs->clusters[index].h]]=cs->clusters[index];
|
||
decalages[cs->clusters[index].h]++;
|
||
}
|
||
|
||
// Remplacement de la liste d<>sordonn<6E>e par celle tri<72>e
|
||
free(cs->clusters);
|
||
cs->clusters=nc;
|
||
}
|
||
|
||
void CS_Sort_by_luminance(T_Cluster_set * cs)
|
||
{
|
||
int byte_used[256];
|
||
int decalages[256];
|
||
int index;
|
||
T_Cluster * nc;
|
||
|
||
nc=(T_Cluster *)malloc(cs->nb_max*sizeof(T_Cluster));
|
||
|
||
// Initialisation de la table d'occurence de chaque octet
|
||
for (index=0;index<256;index++)
|
||
byte_used[index]=0;
|
||
|
||
// Comptage du nombre d'occurences de chaque octet
|
||
for (index=0;index<cs->nb;index++)
|
||
byte_used[cs->clusters[index].l]++;
|
||
|
||
// Calcul de la table des d<>calages
|
||
decalages[0]=0;
|
||
for (index=1;index<256;index++)
|
||
decalages[index]=decalages[index-1]+byte_used[index-1];
|
||
|
||
// Copie r<>ordonn<6E>e dans la nouvelle liste
|
||
for (index=0;index<cs->nb;index++)
|
||
{
|
||
nc[decalages[cs->clusters[index].l]]=cs->clusters[index];
|
||
decalages[cs->clusters[index].l]++;
|
||
}
|
||
|
||
// Remplacement de la liste d<>sordonn<6E>e par celle tri<72>e
|
||
free(cs->clusters);
|
||
cs->clusters=nc;
|
||
}
|
||
|
||
void CS_Generate_color_table_and_palette(T_Cluster_set * cs,T_Conversion_table * tc,T_Components * palette)
|
||
{
|
||
int index;
|
||
int r,g,b;
|
||
|
||
for (index=0;index<cs->nb;index++)
|
||
{
|
||
palette[index].R=cs->clusters[index].r;
|
||
palette[index].G=cs->clusters[index].g;
|
||
palette[index].B=cs->clusters[index].b;
|
||
|
||
for (r=cs->clusters[index].Rmin;r<=cs->clusters[index].Rmax;r++)
|
||
for (g=cs->clusters[index].Gmin;g<=cs->clusters[index].Vmax;g++)
|
||
for (b=cs->clusters[index].Bmin;b<=cs->clusters[index].Bmax;b++)
|
||
CT_set(tc,r,g,b,index);
|
||
}
|
||
}
|
||
|
||
/////////////////////////////////////////////////////////////////////////////
|
||
///////////////////////////////////////// M<>thodes de gestion des d<>grad<61>s //
|
||
/////////////////////////////////////////////////////////////////////////////
|
||
|
||
void GS_Init(T_Gradient_set * ds,T_Cluster_set * cs)
|
||
{
|
||
ds->gradients[0].nb_colors=1;
|
||
ds->gradients[0].min=cs->clusters[0].h;
|
||
ds->gradients[0].max=cs->clusters[0].h;
|
||
ds->gradients[0].hue=cs->clusters[0].h;
|
||
// Et hop : le 1er ensemble de d<>grad<61>s est initialis<69>
|
||
ds->nb=1;
|
||
}
|
||
|
||
T_Gradient_set * GS_New(T_Cluster_set * cs)
|
||
{
|
||
T_Gradient_set * n;
|
||
|
||
n=(T_Gradient_set *)malloc(sizeof(T_Gradient_set));
|
||
if (n!=NULL)
|
||
{
|
||
// On recopie les param<61>tres demand<6E>s
|
||
n->nb_max=cs->nb_max;
|
||
|
||
// On tente d'allouer la table
|
||
n->gradients=(T_Gradient *)malloc((n->nb_max)*sizeof(T_Gradient));
|
||
if (n->gradients!=0)
|
||
// C'est bon! On initialise
|
||
GS_Init(n,cs);
|
||
else
|
||
{
|
||
// Table impossible <20> allouer
|
||
free(n);
|
||
n=0;
|
||
}
|
||
}
|
||
|
||
return n;
|
||
}
|
||
|
||
void GS_Delete(T_Gradient_set * ds)
|
||
{
|
||
free(ds->gradients);
|
||
free(ds);
|
||
}
|
||
|
||
void GS_Generate(T_Gradient_set * ds,T_Cluster_set * cs)
|
||
{
|
||
int ic,id; // Les indexs de parcours des ensembles
|
||
int best_gradient; // Meilleur d<>grad<61>
|
||
int best_diff; // Meilleure diff<66>rence de chrominance
|
||
int diff; // difference de chrominance courante
|
||
|
||
// Pour chacun des clusters <20> traiter
|
||
for (ic=0;ic<cs->nb;ic++)
|
||
{
|
||
// On recherche le d<>grad<61> le plus proche de la chrominance du cluster
|
||
best_gradient=-1;
|
||
best_diff=99999999;
|
||
for (id=0;id<ds->nb;id++)
|
||
{
|
||
diff=abs(cs->clusters[ic].h - ds->gradients[id].hue);
|
||
if ((best_diff>diff) && (diff<16))
|
||
{
|
||
best_gradient=id;
|
||
best_diff=diff;
|
||
}
|
||
}
|
||
|
||
// Si on a trouv<75> un d<>grad<61> dans lequel inclure le cluster
|
||
if (best_gradient!=-1)
|
||
{
|
||
// On met <20> jour le d<>grad<61>
|
||
if (cs->clusters[ic].h < ds->gradients[best_gradient].min)
|
||
ds->gradients[best_gradient].min=cs->clusters[ic].h;
|
||
if (cs->clusters[ic].h > ds->gradients[best_gradient].max)
|
||
ds->gradients[best_gradient].max=cs->clusters[ic].h;
|
||
ds->gradients[best_gradient].hue=((ds->gradients[best_gradient].hue*
|
||
ds->gradients[best_gradient].nb_colors)
|
||
+cs->clusters[ic].h)
|
||
/(ds->gradients[best_gradient].nb_colors+1);
|
||
ds->gradients[best_gradient].nb_colors++;
|
||
}
|
||
else
|
||
{
|
||
// On cr<63>e un nouveau d<>grad<61>
|
||
best_gradient=ds->nb;
|
||
ds->gradients[best_gradient].nb_colors=1;
|
||
ds->gradients[best_gradient].min=cs->clusters[ic].h;
|
||
ds->gradients[best_gradient].max=cs->clusters[ic].h;
|
||
ds->gradients[best_gradient].hue=cs->clusters[ic].h;
|
||
ds->nb++;
|
||
}
|
||
cs->clusters[ic].h=best_gradient;
|
||
}
|
||
|
||
// On redistribue les valeurs dans les clusters
|
||
for (ic=0;ic<cs->nb;ic++)
|
||
cs->clusters[ic].h=ds->gradients[cs->clusters[ic].h].hue;
|
||
}
|
||
|
||
|
||
|
||
|
||
T_Conversion_table * Optimize_palette(T_Bitmap24B image,int size,T_Components * palette,int r,int g,int b)
|
||
{
|
||
T_Occurrence_table * to;
|
||
T_Conversion_table * tc;
|
||
T_Cluster_set * cs;
|
||
T_Gradient_set * ds;
|
||
|
||
// Cr<43>ation des <20>l<EFBFBD>ments n<>cessaires au calcul de palette optimis<69>e:
|
||
to=0; tc=0; cs=0; ds=0;
|
||
|
||
to=OT_new(r,g,b);
|
||
if (to!=0)
|
||
{
|
||
tc=CT_new(r,g,b);
|
||
if (tc!=0)
|
||
{
|
||
|
||
// Premi<6D>re <20>tape : on compte les pixels de chaque couleur pour pouvoir trier l<> dessus
|
||
OT_count_occurrences(to,image,size);
|
||
|
||
cs=CS_New(256,to);
|
||
if (cs!=0)
|
||
{
|
||
// C'est bon, on a pu tout allouer
|
||
|
||
// On g<>n<EFBFBD>re les clusters (avec l'algo du median cut)
|
||
CS_Generate(cs,to);
|
||
|
||
// On calcule la teinte de chaque pixel (Luminance et chrominance)
|
||
CS_Compute_colors(cs,to);
|
||
|
||
ds=GS_New(cs);
|
||
if (ds!=0)
|
||
{
|
||
GS_Generate(ds,cs);
|
||
GS_Delete(ds);
|
||
}
|
||
|
||
// Enfin on trie les clusters (donc les couleurs de la palette) dans un ordre sympa : par couleur, et par luminosit<69> pour chaque couleur
|
||
CS_Sort_by_luminance(cs);
|
||
CS_Sort_by_chrominance(cs);
|
||
|
||
// Enfin on g<>n<EFBFBD>re la palette et la table de correspondance entre chaque couleur 24b et sa couleur palette associ<63>e.
|
||
CS_Generate_color_table_and_palette(cs,tc,palette);
|
||
|
||
CS_Delete(cs);
|
||
OT_delete(to);
|
||
return tc;
|
||
}
|
||
CT_delete(tc);
|
||
}
|
||
OT_delete(to);
|
||
}
|
||
// Si on arrive ici c'est que l'allocation n'a pas r<>ussi,
|
||
// l'appelant devra recommencer avec une pr<70>cision plus faible (3 derniers param<61>tres)
|
||
return 0;
|
||
}
|
||
|
||
int Modified_value(int value,int modif)
|
||
{
|
||
value+=modif;
|
||
if (value<0)
|
||
{
|
||
value=0;
|
||
}
|
||
else if (value>255)
|
||
{
|
||
value=255;
|
||
}
|
||
return value;
|
||
}
|
||
|
||
void Convert_24b_bitmap_to_256_Floyd_Steinberg(T_Bitmap256 dest,T_Bitmap24B source,int width,int height,T_Components * palette,T_Conversion_table * tc)
|
||
// Cette fonction d<>grade au fur et <20> mesure le bitmap source, donc soit on ne
|
||
// s'en ressert pas, soit on passe <20> la fonction une copie de travail du
|
||
// bitmap original.
|
||
{
|
||
T_Bitmap24B current;
|
||
T_Bitmap24B c_plus1;
|
||
T_Bitmap24B u_minus1;
|
||
T_Bitmap24B next;
|
||
T_Bitmap24B u_plus1;
|
||
T_Bitmap256 d;
|
||
int x_pos,y_pos;
|
||
int red,green,blue;
|
||
float e_red,e_green,e_blue;
|
||
|
||
// On initialise les variables de parcours:
|
||
current =source; // Le pixel dont on s'occupe
|
||
next =current+width; // Le pixel en dessous
|
||
c_plus1 =current+1; // Le pixel <20> droite
|
||
u_minus1=next-1; // Le pixel en bas <20> gauche
|
||
u_plus1 =next+1; // Le pixel en bas <20> droite
|
||
d =dest;
|
||
|
||
// On parcours chaque pixel:
|
||
for (y_pos=0;y_pos<height;y_pos++)
|
||
{
|
||
for (x_pos=0;x_pos<width;x_pos++)
|
||
{
|
||
// On prends la meilleure couleur de la palette qui traduit la couleur
|
||
// 24 bits de la source:
|
||
red=current->R;
|
||
green =current->G;
|
||
blue =current->B;
|
||
// Cherche la couleur correspondant dans la palette et la range dans l'image de destination
|
||
*d=CT_get(tc,red,green,blue);
|
||
|
||
// Puis on calcule pour chaque composante l'erreur d<>e <20> l'approximation
|
||
red-=palette[*d].R;
|
||
green -=palette[*d].G;
|
||
blue -=palette[*d].B;
|
||
|
||
// Et dans chaque pixel voisin on propage l'erreur
|
||
// A droite:
|
||
e_red=(red*7)/16.0;
|
||
e_green =(green *7)/16.0;
|
||
e_blue =(blue *7)/16.0;
|
||
if (x_pos+1<width)
|
||
{
|
||
// Modified_value fait la somme des 2 params en bornant sur [0,255]
|
||
c_plus1->R=Modified_value(c_plus1->R,e_red);
|
||
c_plus1->G=Modified_value(c_plus1->G,e_green );
|
||
c_plus1->B=Modified_value(c_plus1->B,e_blue );
|
||
}
|
||
// En bas <20> gauche:
|
||
if (y_pos+1<height)
|
||
{
|
||
e_red=(red*3)/16.0;
|
||
e_green =(green *3)/16.0;
|
||
e_blue =(blue *3)/16.0;
|
||
if (x_pos>0)
|
||
{
|
||
u_minus1->R=Modified_value(u_minus1->R,e_red);
|
||
u_minus1->G=Modified_value(u_minus1->G,e_green );
|
||
u_minus1->B=Modified_value(u_minus1->B,e_blue );
|
||
}
|
||
// En bas:
|
||
e_red=(red*5/16.0);
|
||
e_green =(green*5 /16.0);
|
||
e_blue =(blue*5 /16.0);
|
||
next->R=Modified_value(next->R,e_red);
|
||
next->G=Modified_value(next->G,e_green );
|
||
next->B=Modified_value(next->B,e_blue );
|
||
// En bas <20> droite:
|
||
if (x_pos+1<width)
|
||
{
|
||
e_red=(red/16.0);
|
||
e_green =(green /16.0);
|
||
e_blue =(blue /16.0);
|
||
u_plus1->R=Modified_value(u_plus1->R,e_red);
|
||
u_plus1->G=Modified_value(u_plus1->G,e_green );
|
||
u_plus1->B=Modified_value(u_plus1->B,e_blue );
|
||
}
|
||
}
|
||
|
||
// On passe au pixel suivant :
|
||
current++;
|
||
c_plus1++;
|
||
u_minus1++;
|
||
next++;
|
||
u_plus1++;
|
||
d++;
|
||
}
|
||
}
|
||
|
||
}
|
||
|
||
|
||
|
||
static const byte precision_24b[]=
|
||
{
|
||
8,8,8,
|
||
6,6,6,
|
||
6,6,5,
|
||
5,6,5,
|
||
5,5,5,
|
||
5,5,4,
|
||
4,5,4,
|
||
4,4,4,
|
||
4,4,3,
|
||
3,4,3,
|
||
3,3,3,
|
||
3,3,2};
|
||
|
||
|
||
// Convertie avec le plus de pr<70>cision possible une image 24b en 256c
|
||
// Renvoie s'il y a eu une erreur ou pas..
|
||
|
||
// Cette fonction utilise l'algorithme "median cut" (Optimize_palette) pour trouver la palette, et diffuse les erreurs avec floyd-steinberg.
|
||
|
||
int Convert_24b_bitmap_to_256(T_Bitmap256 dest,T_Bitmap24B source,int width,int height,T_Components * palette)
|
||
{
|
||
T_Conversion_table * table; // table de conversion
|
||
int ip; // index de pr<70>cision pour la conversion
|
||
|
||
// On essaye d'obtenir une table de conversion qui loge en m<>moire, avec la
|
||
// meilleure pr<70>cision possible
|
||
for (ip=0;ip<(10*3);ip+=3)
|
||
{
|
||
table=Optimize_palette(source,width*height,palette,precision_24b[ip+0],
|
||
precision_24b[ip+1],precision_24b[ip+2]);
|
||
if (table!=0)
|
||
break;
|
||
}
|
||
|
||
if (table!=0)
|
||
{
|
||
Convert_24b_bitmap_to_256_Floyd_Steinberg(dest,source,width,height,palette,table);
|
||
CT_delete(table);
|
||
return 0;
|
||
}
|
||
else
|
||
return 1;
|
||
}
|
||
|
||
|
||
|