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cameracv/libs/opencv/modules/photo/src/npr.hpp
Danyok 4e24d82c36 initial commit
2023-05-18 21:39:43 +03:00

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
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// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
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//M*/
#include "precomp.hpp"
#include "opencv2/photo.hpp"
#include <iostream>
#include <stdlib.h>
#include <limits>
#include "math.h"
using namespace std;
using namespace cv;
double myinf = std::numeric_limits<double>::infinity();
class Domain_Filter
{
public:
Mat ct_H, ct_V, horiz, vert, O, O_t, lower_idx, upper_idx;
void init(const Mat &img, int flags, float sigma_s, float sigma_r);
void getGradientx( const Mat &img, Mat &gx);
void getGradienty( const Mat &img, Mat &gy);
void diffx(const Mat &img, Mat &temp);
void diffy(const Mat &img, Mat &temp);
void find_magnitude(Mat &img, Mat &mag);
void compute_boxfilter(Mat &output, Mat &hz, Mat &psketch, float radius);
void compute_Rfilter(Mat &O, Mat &horiz, float sigma_h);
void compute_NCfilter(Mat &O, Mat &horiz, Mat &psketch, float radius);
void filter(const Mat &img, Mat &res, float sigma_s, float sigma_r, int flags);
void pencil_sketch(const Mat &img, Mat &sketch, Mat &color_res, float sigma_s, float sigma_r, float shade_factor);
void Depth_of_field(const Mat &img, Mat &img1, float sigma_s, float sigma_r);
};
void Domain_Filter::diffx(const Mat &img, Mat &temp)
{
int channel = img.channels();
for(int i = 0; i < img.size().height; i++)
for(int j = 0; j < img.size().width-1; j++)
{
for(int c =0; c < channel; c++)
{
temp.at<float>(i,j*channel+c) =
img.at<float>(i,(j+1)*channel+c) - img.at<float>(i,j*channel+c);
}
}
}
void Domain_Filter::diffy(const Mat &img, Mat &temp)
{
int channel = img.channels();
for(int i = 0; i < img.size().height-1; i++)
for(int j = 0; j < img.size().width; j++)
{
for(int c =0; c < channel; c++)
{
temp.at<float>(i,j*channel+c) =
img.at<float>((i+1),j*channel+c) - img.at<float>(i,j*channel+c);
}
}
}
void Domain_Filter::getGradientx( const Mat &img, Mat &gx)
{
int w = img.cols;
int h = img.rows;
int channel = img.channels();
for(int i=0;i<h;i++)
for(int j=0;j<w;j++)
for(int c=0;c<channel;++c)
{
gx.at<float>(i,j*channel+c) =
img.at<float>(i,(j+1)*channel+c) - img.at<float>(i,j*channel+c);
}
}
void Domain_Filter::getGradienty( const Mat &img, Mat &gy)
{
int w = img.cols;
int h = img.rows;
int channel = img.channels();
for(int i=0;i<h;i++)
for(int j=0;j<w;j++)
for(int c=0;c<channel;++c)
{
gy.at<float>(i,j*channel+c) =
img.at<float>(i+1,j*channel+c) - img.at<float>(i,j*channel+c);
}
}
void Domain_Filter::find_magnitude(Mat &img, Mat &mag)
{
int h = img.rows;
int w = img.cols;
vector <Mat> planes;
split(img, planes);
Mat magXR = Mat(h, w, CV_32FC1);
Mat magYR = Mat(h, w, CV_32FC1);
Mat magXG = Mat(h, w, CV_32FC1);
Mat magYG = Mat(h, w, CV_32FC1);
Mat magXB = Mat(h, w, CV_32FC1);
Mat magYB = Mat(h, w, CV_32FC1);
Sobel(planes[0], magXR, CV_32FC1, 1, 0, 3);
Sobel(planes[0], magYR, CV_32FC1, 0, 1, 3);
Sobel(planes[1], magXG, CV_32FC1, 1, 0, 3);
Sobel(planes[1], magYG, CV_32FC1, 0, 1, 3);
Sobel(planes[2], magXB, CV_32FC1, 1, 0, 3);
Sobel(planes[2], magYB, CV_32FC1, 0, 1, 3);
Mat mag1 = Mat(h,w,CV_32FC1);
Mat mag2 = Mat(h,w,CV_32FC1);
Mat mag3 = Mat(h,w,CV_32FC1);
magnitude(magXR,magYR,mag1);
magnitude(magXG,magYG,mag2);
magnitude(magXB,magYB,mag3);
mag = mag1 + mag2 + mag3;
mag = 1.0f - mag;
}
void Domain_Filter::compute_Rfilter(Mat &output, Mat &hz, float sigma_h)
{
int h = output.rows;
int w = output.cols;
int channel = output.channels();
float a = (float) exp((-1.0 * sqrt(2.0)) / sigma_h);
Mat temp = Mat(h,w,CV_32FC3);
output.copyTo(temp);
Mat V = Mat(h,w,CV_32FC1);
for(int i=0;i<h;i++)
for(int j=0;j<w;j++)
V.at<float>(i,j) = pow(a,hz.at<float>(i,j));
for(int i=0; i<h; i++)
{
for(int j =1; j < w; j++)
{
for(int c = 0; c<channel; c++)
{
temp.at<float>(i,j*channel+c) = temp.at<float>(i,j*channel+c) +
(temp.at<float>(i,(j-1)*channel+c) - temp.at<float>(i,j*channel+c)) * V.at<float>(i,j);
}
}
}
for(int i=0; i<h; i++)
{
for(int j =w-2; j >= 0; j--)
{
for(int c = 0; c<channel; c++)
{
temp.at<float>(i,j*channel+c) = temp.at<float>(i,j*channel+c) +
(temp.at<float>(i,(j+1)*channel+c) - temp.at<float>(i,j*channel+c))*V.at<float>(i,j+1);
}
}
}
temp.copyTo(output);
}
void Domain_Filter::compute_boxfilter(Mat &output, Mat &hz, Mat &psketch, float radius)
{
int h = output.rows;
int w = output.cols;
Mat lower_pos = Mat(h,w,CV_32FC1);
Mat upper_pos = Mat(h,w,CV_32FC1);
lower_pos = hz - radius;
upper_pos = hz + radius;
lower_idx = Mat::zeros(h,w,CV_32FC1);
upper_idx = Mat::zeros(h,w,CV_32FC1);
Mat domain_row = Mat::zeros(1,w+1,CV_32FC1);
for(int i=0;i<h;i++)
{
for(int j=0;j<w;j++)
domain_row.at<float>(0,j) = hz.at<float>(i,j);
domain_row.at<float>(0,w) = (float) myinf;
Mat lower_pos_row = Mat::zeros(1,w,CV_32FC1);
Mat upper_pos_row = Mat::zeros(1,w,CV_32FC1);
for(int j=0;j<w;j++)
{
lower_pos_row.at<float>(0,j) = lower_pos.at<float>(i,j);
upper_pos_row.at<float>(0,j) = upper_pos.at<float>(i,j);
}
Mat temp_lower_idx = Mat::zeros(1,w,CV_32FC1);
Mat temp_upper_idx = Mat::zeros(1,w,CV_32FC1);
for(int j=0;j<w;j++)
{
if(domain_row.at<float>(0,j) > lower_pos_row.at<float>(0,0))
{
temp_lower_idx.at<float>(0,0) = (float) j;
break;
}
}
for(int j=0;j<w;j++)
{
if(domain_row.at<float>(0,j) > upper_pos_row.at<float>(0,0))
{
temp_upper_idx.at<float>(0,0) = (float) j;
break;
}
}
int temp = 0;
for(int j=1;j<w;j++)
{
int count=0;
for(int k=(int) temp_lower_idx.at<float>(0,j-1);k<w+1;k++)
{
if(domain_row.at<float>(0,k) > lower_pos_row.at<float>(0,j))
{
temp = count;
break;
}
count++;
}
temp_lower_idx.at<float>(0,j) = temp_lower_idx.at<float>(0,j-1) + temp;
count = 0;
for(int k=(int) temp_upper_idx.at<float>(0,j-1);k<w+1;k++)
{
if(domain_row.at<float>(0,k) > upper_pos_row.at<float>(0,j))
{
temp = count;
break;
}
count++;
}
temp_upper_idx.at<float>(0,j) = temp_upper_idx.at<float>(0,j-1) + temp;
}
for(int j=0;j<w;j++)
{
lower_idx.at<float>(i,j) = temp_lower_idx.at<float>(0,j) + 1;
upper_idx.at<float>(i,j) = temp_upper_idx.at<float>(0,j) + 1;
}
}
psketch = upper_idx - lower_idx;
}
void Domain_Filter::compute_NCfilter(Mat &output, Mat &hz, Mat &psketch, float radius)
{
int h = output.rows;
int w = output.cols;
int channel = output.channels();
compute_boxfilter(output,hz,psketch,radius);
Mat box_filter = Mat::zeros(h,w+1,CV_32FC3);
for(int i = 0; i < h; i++)
{
box_filter.at<float>(i,1*channel+0) = output.at<float>(i,0*channel+0);
box_filter.at<float>(i,1*channel+1) = output.at<float>(i,0*channel+1);
box_filter.at<float>(i,1*channel+2) = output.at<float>(i,0*channel+2);
for(int j = 2; j < w+1; j++)
{
for(int c=0;c<channel;c++)
box_filter.at<float>(i,j*channel+c) = output.at<float>(i,(j-1)*channel+c) + box_filter.at<float>(i,(j-1)*channel+c);
}
}
Mat indices = Mat::zeros(h,w,CV_32FC1);
Mat final = Mat::zeros(h,w,CV_32FC3);
for(int i=0;i<h;i++)
for(int j=0;j<w;j++)
indices.at<float>(i,j) = (float) i+1;
Mat a = Mat::zeros(h,w,CV_32FC1);
Mat b = Mat::zeros(h,w,CV_32FC1);
// Compute the box filter using a summed area table.
for(int c=0;c<channel;c++)
{
Mat flag = Mat::ones(h,w,CV_32FC1);
multiply(flag,c+1,flag);
Mat temp1, temp2;
multiply(flag - 1,h*(w+1),temp1);
multiply(lower_idx - 1,h,temp2);
a = temp1 + temp2 + indices;
multiply(flag - 1,h*(w+1),temp1);
multiply(upper_idx - 1,h,temp2);
b = temp1 + temp2 + indices;
int p,q,r,rem;
int p1,q1,r1,rem1;
// Calculating indices
for(int i=0;i<h;i++)
{
for(int j=0;j<w;j++)
{
r = (int) b.at<float>(i,j)/(h*(w+1));
rem = (int) b.at<float>(i,j) - r*h*(w+1);
q = rem/h;
p = rem - q*h;
if(q==0)
{
p=h;
q=w;
r=r-1;
}
if(p==0)
{
p=h;
q=q-1;
}
r1 = (int) a.at<float>(i,j)/(h*(w+1));
rem1 = (int) a.at<float>(i,j) - r1*h*(w+1);
q1 = rem1/h;
p1 = rem1 - q1*h;
if(p1==0)
{
p1=h;
q1=q1-1;
}
final.at<float>(i,j*channel+2-c) = (box_filter.at<float>(p-1,q*channel+(2-r)) - box_filter.at<float>(p1-1,q1*channel+(2-r1)))
/(upper_idx.at<float>(i,j) - lower_idx.at<float>(i,j));
}
}
}
final.copyTo(output);
}
void Domain_Filter::init(const Mat &img, int flags, float sigma_s, float sigma_r)
{
int h = img.size().height;
int w = img.size().width;
int channel = img.channels();
//////////////////////////////////// horizontal and vertical partial derivatives /////////////////////////////////
Mat derivx = Mat::zeros(h,w-1,CV_32FC3);
Mat derivy = Mat::zeros(h-1,w,CV_32FC3);
diffx(img,derivx);
diffy(img,derivy);
Mat distx = Mat::zeros(h,w,CV_32FC1);
Mat disty = Mat::zeros(h,w,CV_32FC1);
//////////////////////// Compute the l1-norm distance of neighbor pixels ////////////////////////////////////////////////
for(int i = 0; i < h; i++)
for(int j = 0,k=1; j < w-1; j++,k++)
for(int c = 0; c < channel; c++)
{
distx.at<float>(i,k) =
distx.at<float>(i,k) + abs(derivx.at<float>(i,j*channel+c));
}
for(int i = 0,k=1; i < h-1; i++,k++)
for(int j = 0; j < w; j++)
for(int c = 0; c < channel; c++)
{
disty.at<float>(k,j) =
disty.at<float>(k,j) + abs(derivy.at<float>(i,j*channel+c));
}
////////////////////// Compute the derivatives of the horizontal and vertical domain transforms. /////////////////////////////
horiz = Mat(h,w,CV_32FC1);
vert = Mat(h,w,CV_32FC1);
Mat final = Mat(h,w,CV_32FC3);
Mat tempx,tempy;
multiply(distx,sigma_s/sigma_r,tempx);
multiply(disty,sigma_s/sigma_r,tempy);
horiz = 1.0f + tempx;
vert = 1.0f + tempy;
O = Mat(h,w,CV_32FC3);
img.copyTo(O);
O_t = Mat(w,h,CV_32FC3);
if(flags == 2)
{
ct_H = Mat(h,w,CV_32FC1);
ct_V = Mat(h,w,CV_32FC1);
for(int i = 0; i < h; i++)
{
ct_H.at<float>(i,0) = horiz.at<float>(i,0);
for(int j = 1; j < w; j++)
{
ct_H.at<float>(i,j) = horiz.at<float>(i,j) + ct_H.at<float>(i,j-1);
}
}
for(int j = 0; j < w; j++)
{
ct_V.at<float>(0,j) = vert.at<float>(0,j);
for(int i = 1; i < h; i++)
{
ct_V.at<float>(i,j) = vert.at<float>(i,j) + ct_V.at<float>(i-1,j);
}
}
}
}
void Domain_Filter::filter(const Mat &img, Mat &res, float sigma_s = 60, float sigma_r = 0.4, int flags = 1)
{
int no_of_iter = 3;
int h = img.size().height;
int w = img.size().width;
float sigma_h = sigma_s;
init(img,flags,sigma_s,sigma_r);
if(flags == 1)
{
Mat vert_t = vert.t();
for(int i=0;i<no_of_iter;i++)
{
sigma_h = (float) (sigma_s * sqrt(3.0) * pow(2.0,(no_of_iter - (i+1))) / sqrt(pow(4.0,no_of_iter) -1));
compute_Rfilter(O, horiz, sigma_h);
O_t = O.t();
compute_Rfilter(O_t, vert_t, sigma_h);
O = O_t.t();
}
}
else if(flags == 2)
{
Mat vert_t = ct_V.t();
Mat temp = Mat(h,w,CV_32FC1);
Mat temp1 = Mat(w,h,CV_32FC1);
float radius;
for(int i=0;i<no_of_iter;i++)
{
sigma_h = (float) (sigma_s * sqrt(3.0) * pow(2.0,(no_of_iter - (i+1))) / sqrt(pow(4.0,no_of_iter) -1));
radius = (float) sqrt(3.0) * sigma_h;
compute_NCfilter(O, ct_H, temp,radius);
O_t = O.t();
compute_NCfilter(O_t, vert_t, temp1, radius);
O = O_t.t();
}
}
res = O.clone();
}
void Domain_Filter::pencil_sketch(const Mat &img, Mat &sketch, Mat &color_res, float sigma_s, float sigma_r, float shade_factor)
{
int no_of_iter = 3;
init(img,2,sigma_s,sigma_r);
int h = img.size().height;
int w = img.size().width;
/////////////////////// convert to YCBCR model for color pencil drawing //////////////////////////////////////////////////////
Mat color_sketch = Mat(h,w,CV_32FC3);
cvtColor(img,color_sketch,COLOR_BGR2YCrCb);
vector <Mat> YUV_channel;
Mat vert_t = ct_V.t();
float sigma_h = sigma_s;
Mat penx = Mat(h,w,CV_32FC1);
Mat pen_res = Mat::zeros(h,w,CV_32FC1);
Mat peny = Mat(w,h,CV_32FC1);
Mat peny_t;
float radius;
for(int i=0;i<no_of_iter;i++)
{
sigma_h = (float) (sigma_s * sqrt(3.0) * pow(2.0,(no_of_iter - (i+1))) / sqrt(pow(4.0,no_of_iter) -1));
radius = (float) sqrt(3.0) * sigma_h;
compute_boxfilter(O, ct_H, penx, radius);
O_t = O.t();
compute_boxfilter(O_t, vert_t, peny, radius);
O = O_t.t();
peny_t = peny.t();
for(int k=0;k<h;k++)
for(int j=0;j<w;j++)
pen_res.at<float>(k,j) = (shade_factor * (penx.at<float>(k,j) + peny_t.at<float>(k,j)));
if(i==0)
{
sketch = pen_res.clone();
split(color_sketch,YUV_channel);
pen_res.copyTo(YUV_channel[0]);
merge(YUV_channel,color_sketch);
cvtColor(color_sketch,color_res,COLOR_YCrCb2BGR);
}
}
}
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