Porting Colorization using Optimization algorithm to C code and iPhone
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Hello,
Severall days I am struggling to port colorization using optimization algorithm (source and paper can be found here: http://www.cs.huji.ac.il/~yweiss/Colorization/) into C/C++ code and to run under iOS (iPhone/iPad).
Not to mention that automatically generated code by MATLAB Coder does not work correcly and scrables image, which lead me to manually rewrite most of generated C code procedures in order to match MATLAB .m runnable code results.
Let me explain in detail step by step what I am doing (with images output results included) after which I pose my question:
First of all we have input images in RGB24 bit format in form of (m x n x 3):int8 matrices. Lets define one image which b/w and need to be colorised as gI variable.
gI=double(g0)/255; % we take function input and make matrix double and divide matrix by 255, so now we have float values in matrix.
Below is the output to screen -> gI :
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/162448/image.png)
Second lets define second image with color RGB markers applied as cI variable.
cI=double(c0)/255; % we take function input and make matrix double and divide matrix by 255, so now we have float values in matrix.
Below is the output to screen -> cI :
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/162451/image.png)
gI-cI %Now according to patented algorithm we subtract gI-cI.
Below is the output to screen -> gI-cI :
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/162453/image.png)
abs(gI-cI) %Next we take absolute value of the subtraction results.
Below is the output to screen -> abs(gI-cI) :
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/162455/image.png)
sum(abs(gI-cI),3) %Next we make sum of matrix cell by 3-rd dimension, which is R,G,B color map in this case.
Below is the output to screen -> sum(abs(gI-cI),3) :
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/162456/image.png)
colorIm=(sum(abs(gI-cI),3)>0.01); %Now we take from result only values that are greater than 0.01 float.
colorIm2=double(colorIm); % and convert matrix with booleans to double
Below is the output to screen -> colorIm2 :
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/162457/image.png)
sgI=rgb2ntsc(gI); %In next step we convert RGB map *gI* input image to YIQ map NTSC image.
Below is the output to screen -> sgI :
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/162458/image.png)
scI=rgb2ntsc(cI); %In next step we convert RGB map *cI* input image to YIQ map NTSC image.
Below is the output to screen -> scI :
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/162461/image.png)
ntscIm(:,:,1)=sgI(:,:,1); %In this step we apply Y of YIQ map from *sgI* image to *ntscIm* var.
ntscIm(:,:,2)=scI(:,:,2); %In this step we apply I of YIQ map from *scI* image to *ntscIm* var.
ntscIm(:,:,3)=scI(:,:,3); %In this step we apply Q of YIQ map from *scI* image to *ntscIm* var.
Below is the output to screen -> ntscIm :
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/162463/image.png)
max_d=floor(log(min(size(ntscIm,1),size(ntscIm,2)))/log(2)-2);
iu=floor(size(ntscIm,1)/(2^(max_d-1)))*(2^(max_d-1));
ju=floor(size(ntscIm,2)/(2^(max_d-1)))*(2^(max_d-1));
colorIm3(1:iu,1:ju,1)=colorIm2(1:iu,1:ju,1); %Images are reshaped in order to fit in solver rules
ntscIm2=ntscIm(1:iu,1:ju,1:3); %Images are reshaped in order to fit in solver rules
I ended up that all these steps are running correctly on iPhone, while I had severely modify automated code.
Problem goes here, when one of the Solver methods gets executed:
n0=getVolColor(colorIm3,ntscIm2,[],[],[],[],5,1); % This method is provided as C++ MEX functions, and I was able to port it into iOS. I give my altered source below.
%n0=getColorExact(colorIm3,ntscIm2); % this is not supported by MATLAB coder as it uses Sparse Matrices.
So I have problems with getVolColor method ported as C++ function into iOS project.
It builds, executes, but provides totally messed picture...
My C++ Code for GetVolColor function:
#include "getvolcolor.h"
#include "string.h"
#include <cmath>
#include "mg.h"
#include <iostream>
#include "fmg.h"
#include "colorize_emxutil.h"
emxArray_real_T * getvolcolor(emxArray_real_T *pvar0, emxArray_real_T *pvar1, emxArray_real_T *pvar2, emxArray_real_T *pvar3, emxArray_real_T *pvar4, emxArray_real_T *pvar5, double pvar6, double pvar7, emxArray_real_T *n0) {
int size0 = pvar1->size[0];
int size1 = pvar1->size[1];
int sizel;
sizel=3;
const int n=size1;
const int m=size0;
const int k = 1;
int max_d, max_d1,max_d2, in_itr_num, out_itr_num, itr;
int x,y,z;
// if (sizel>3){
// k=sizes[3];
// } else {
// k=1;
// }
max_d1=int(floor(log(n)/log(2)-2)+0.1);
max_d2=int(floor(log(m)/log(2)-2)+0.1);
if (max_d1>max_d2){
max_d=max_d2;
}else{
max_d=max_d1;
}
double *lblImg_pr, *img_pr;
double *res_pr;
double **res_prv;
double *dx_pr,*dy_pr,*idx_pr,*idy_pr;
lblImg_pr=pvar0->data;
img_pr=pvar1->data;
Tensor3d D,G,I;
Tensor3d Dx,Dy,iDx,iDy;
MG smk;
G.set(m,n,k);
D.set(m,n,k);
I.set(m,n,k);
dy_pr=0;
dx_pr=0;
idy_pr=0;
idx_pr=0;
// if (nrhs>6){
in_itr_num=int(pvar6+0.5);
// }else{
// in_itr_num=5;
// }
// if (nrhs>7){
out_itr_num=int(pvar7+0.5);
// }else{
// out_itr_num=2;
// }
Dx.set(m,n,k-1);
Dy.set(m,n,k-1);
iDx.set(m,n,k-1);
iDy.set(m,n,k-1);
for ( z=0; z<(k-1); z++){
for ( y=0; y<n; y++){
for ( x=0; x<m; x++){
Dx(x,y,z)=*dx_pr; dx_pr++;
Dy(x,y,z)=*dy_pr; dy_pr++;
iDx(x,y,z)=*idx_pr; idx_pr++;
iDy(x,y,z)=*idy_pr; idy_pr++;
}
}
}
// int dims[4];
// dims[0]=m; dims[1]=n; dims[2]=3; dims[3]=k;
//double lvar0[m][n][3][k];//=mxCreateNumericArray(4, dims, mxDOUBLE_CLASS, mxREAL);
res_pr=&n0->data[0];
res_prv=new double*[k];
for (z=0; z<k; z++){
res_prv[z]=res_pr+n*m*3*z;
}
for ( z=0; z<k; z++){
for ( y=0; y<n; y++){
for ( x=0; x<m; x++){
I(x,y,z)=lblImg_pr[x+m*y+z*n*m];
G(x,y,z)=img_pr[x+y*m+z*m*n*3];
I(x,y,z)=!I(x,y,z);
}
}
}
for ( z=0; z<k; z++){
for ( y=0; y<n; y++){
for ( x=0; x<m; x++){
(*res_prv[z])=G(x,y,z);
res_prv[z]++;
}
}
}
smk.set(m,n,k,max_d);
smk.setI(I) ;
smk.setG(G);
smk.setFlow(Dx,Dy,iDx,iDy);
for (int t=1; t<3; t++){
for ( z=0; z<k; z++){
for ( y=0; y<n; y++){
for ( x=0; x<m; x++){
D(x,y,z)=img_pr[x+y*m+n*m*t+z*m*n*3];
smk.P()(x,y,z)=img_pr[x+y*m+n*m*t+z*m*n*3];
D(x,y,z)*=(!I(x,y,z));
}
}
}
smk.Div() = D ;
Tensor3d tP2;
if (k==1){
for (itr=0; itr<out_itr_num; itr++){
smk.setDepth(max_d);
Field_MGN(&smk, in_itr_num, 2) ;
smk.setDepth(ceil(max_d/2));
Field_MGN(&smk, in_itr_num, 2) ;
smk.setDepth(2);
Field_MGN(&smk, in_itr_num, 2) ;
smk.setDepth(1);
Field_MGN(&smk, in_itr_num, 4) ;
}
} else{
for (itr=0; itr<out_itr_num; itr++){
smk.setDepth(2);
Field_MGN(&smk, in_itr_num, 2) ;
smk.setDepth(1);
Field_MGN(&smk, in_itr_num, 4) ;
}
}
tP2=smk.P();
for ( z=0; z<k; z++){
for ( y=0; y<n; y++){
for ( x=0; x<m; x++){
(*res_prv[z])=tP2(x,y,z);
res_prv[z]++;
}
}
}
}
return n0;
}
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