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xin-xinhanggaoxin-xinhanggao
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complete the first version
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‎clone.cpp

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#include "clone.h"
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#include "poisson_solver.h"
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#include <opencv2/opencv.hpp>
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#include <iostream>
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#include <Eigen/Sparse>
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#include <Eigen/Dense>
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bool findOverlap(cv::InputArray background,
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cv::InputArray foreground,
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int offsetX, int offsetY,
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cv::Rect &rBackground,
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cv::Rect &rForeground)
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{
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cv::Mat bg = background.getMat();
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cv::Mat fg = foreground.getMat();
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rBackground = cv::Rect(0, 0, bg.cols, bg.rows) &
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cv::Rect(offsetX, offsetY, fg.cols, fg.rows);
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// Compensate for negative offsets. If offset < 0, offset in foreground is positive.
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rForeground = cv::Rect(std::max<int>(-offsetX, 0),
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std::max<int>(-offsetY, 0),
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rBackground.width,
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rBackground.height);
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return rForeground.area() > 0;
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}
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void computeMixedGradientVectorField(cv::InputArray background,
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cv::InputArray foreground,
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cv::OutputArray vx_,
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cv::OutputArray vy_)
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{
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cv::Mat bg = background.getMat();
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cv::Mat fg = foreground.getMat();
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const int channels = bg.channels();
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vx_.create(bg.size(), CV_MAKETYPE(CV_32F, channels));
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vy_.create(bg.size(), CV_MAKETYPE(CV_32F, channels));
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cv::Mat vx = vx_.getMat();
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cv::Mat vy = vy_.getMat();
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cv::Mat kernelx = (cv::Mat_<float>(1, 3) << -0.5, 0, 0.5);
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cv::Mat kernely = (cv::Mat_<float>(3, 1) << -0.5, 0, 0.5);
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cv::Mat vxf, vyf, vxb, vyb;
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cv::filter2D(fg, vxf, CV_32F, kernelx, cv::Point(-1,-1), 0, cv::BORDER_REPLICATE);
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cv::filter2D(fg, vyf, CV_32F, kernely, cv::Point(-1,-1), 0, cv::BORDER_REPLICATE);
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cv::filter2D(bg, vxb, CV_32F, kernelx, cv::Point(-1,-1), 0, cv::BORDER_REPLICATE);
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cv::filter2D(bg, vyb, CV_32F, kernely, cv::Point(-1,-1), 0, cv::BORDER_REPLICATE);
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for(int id = 0; id <= (vx.rows * vx.cols * channels - channels); ++id)
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{
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const cv::Vec2f g[2] = {
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cv::Vec2f(vxf.ptr<float>()[id], vyf.ptr<float>()[id]),
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cv::Vec2f(vxb.ptr<float>()[id], vyb.ptr<float>()[id])
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};
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int which = (g[0].dot(g[0]) > g[1].dot(g[1])) ? 0 : 1;
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vx.ptr<float>()[id] = g[which][0];
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vy.ptr<float>()[id] = g[which][1];
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}
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}
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void computeWeightedGradientVectorField(cv::InputArray background,
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cv::InputArray foreground,
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cv::OutputArray vx,
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cv::OutputArray vy,
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float weightForeground)
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{
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cv::Mat bg = background.getMat();
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cv::Mat fg = foreground.getMat();
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cv::Mat kernelx = (cv::Mat_<float>(1, 3) << -0.5, 0, 0.5);
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cv::Mat kernely = (cv::Mat_<float>(3, 1) << -0.5, 0, 0.5);
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cv::Mat vxf, vyf, vxb, vyb;
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cv::filter2D(fg, vxf, CV_32F, kernelx, cv::Point(-1,-1), 0, cv::BORDER_REPLICATE);
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cv::filter2D(fg, vyf, CV_32F, kernely, cv::Point(-1,-1), 0, cv::BORDER_REPLICATE);
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cv::filter2D(bg, vxb, CV_32F, kernelx, cv::Point(-1,-1), 0, cv::BORDER_REPLICATE);
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cv::filter2D(bg, vyb, CV_32F, kernely, cv::Point(-1,-1), 0, cv::BORDER_REPLICATE);
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cv::addWeighted(vxf, weightForeground, vxb, 1.f - weightForeground, 0, vx);
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cv::addWeighted(vyf, weightForeground, vyb, 1.f - weightForeground, 0, vy);
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}
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void seamlessClone(cv::InputArray background,
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cv::InputArray foreground,
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cv::InputArray foregroundMask,
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int offsetX,
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int offsetY,
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cv::OutputArray destination,
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CloneType type)
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{
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// Copy original background as we only solve for the overlapping area of the translated foreground mask.
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background.getMat().copyTo(destination);
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// Find overlapping region. We will only perform on this region
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cv::Rect rbg, rfg;
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if (!findOverlap(background, foreground, offsetX, offsetY, rbg, rfg))
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return;
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cv::Mat fore, back;
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cv::Mat lap = (cv::Mat_<float>(3, 3) << 0.0, -1, 0.0, -1, 4, -1, 0.0, -1, 0.0);
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cv::filter2D(foreground.getMat()(rfg), fore, CV_32F, lap, cv::Point(-1,-1), 0, cv::BORDER_REPLICATE);
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cv::filter2D(background.getMat()(rbg), back, CV_32F, lap, cv::Point(-1,-1), 0, cv::BORDER_REPLICATE);
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cv::Mat f = fore;
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cv::Mat boundaryMask(rfg.size(), CV_8UC1);
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cv::threshold(foregroundMask.getMat()(rfg), boundaryMask, UNKNOWN, DIRICHLET_BD, cv::THRESH_BINARY_INV);
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cv::rectangle(boundaryMask, cv::Rect(0, 0, boundaryMask.cols, boundaryMask.rows), DIRICHLET_BD, 1);
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cv::Mat boundaryValues(rfg.size(), CV_MAKETYPE(CV_32F, background.channels()));
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background.getMat()(rbg).convertTo(boundaryValues, CV_32F);
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cv::Mat foreValues(rfg.size(), CV_MAKETYPE(CV_32F, foreground.channels()));
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foreground.getMat()(rfg).convertTo(foreValues, CV_32F);
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/*
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cv::Mat image = boundaryMask;
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int nr=image.rows;
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int nc=image.cols;
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if(image.isContinuous())
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{
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nr=1;
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nc=nc*image.rows*image.channels();
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}
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for(int i=0;i<nr;i++)
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{
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const uchar* inData=image.ptr<uchar>(i);
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for(int j=0;j<nc;j++)
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{
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std::cout<<int(*inData++)<<std::endl;
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}
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}
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*/
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// Solve Poisson equation
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cv::Mat result;
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/*
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solvePoissonEquations(f,
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boundaryMask,
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boundaryValues,
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result);
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*/
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solvePoissonEquationsFast(foreValues,
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boundaryMask,
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boundaryValues,
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result);
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// Copy result to destination image.
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result.convertTo(destination.getMat()(rbg), CV_8U);
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}
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‎clone.h

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#ifndef POISSON_CLONE_H
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#define POISSON_CLONE_H
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#include "constant.h"
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#include <opencv2/core/core.hpp>
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/**
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Determine the area of overlap.
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Computes the areas of overlap for background and foreground when foreground
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is layed over background given a translational offset.
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*/
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bool findOverlap(cv::InputArray background,
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cv::InputArray foreground,
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int offsetX, int offsetY,
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cv::Rect &rBackground,
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cv::Rect &rForeground);
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/**
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Compute Poisson guidance vector field by mixing gradients from background and foreground.
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*/
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void computeMixedGradientVectorField(cv::InputArray background,
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cv::InputArray foreground,
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cv::OutputArray vx,
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cv::OutputArray vy);
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/**
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Compute Poisson guidance vector field by averaging background and foreground gradients.
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*/
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void computeWeightedGradientVectorField(cv::InputArray background,
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cv::InputArray foreground,
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cv::OutputArray vx,
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cv::OutputArray vy,
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float weightForeground);
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/**
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Solve multi-channel Poisson equations.
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*/
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void solvePoissonEquations(cv::InputArray background,
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cv::InputArray foreground,
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cv::InputArray foregroundMask,
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cv::InputArray vx,
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cv::InputArray vy,
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cv::OutputArray destination);
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enum CloneType {
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CLONE_FOREGROUND_GRADIENTS,
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CLONE_AVERAGED_GRADIENTS,
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CLONE_MIXED_GRADIENTS
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};
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void seamlessClone(cv::InputArray background,
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cv::InputArray foreground,
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cv::InputArray foregroundMask,
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int offsetX,
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int offsetY,
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cv::OutputArray destination,
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CloneType type);
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#endif

‎constant.h

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#ifndef CONSTANT_H
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#define CONSTANT_H
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const unsigned char UNKNOWN = 0;
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const unsigned char DIRICHLET_BD = 1;
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const unsigned char NEUMANN_BD = 2;
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#endif

‎makefile

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seamless_clone: seamless_cloning.o clone.o poisson_solver.o
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g++ -I /usr/local/include/eigen3 $$(pkg-config --cflags --libs opencv) seamless_cloning.o clone.o poisson_solver.o -O2 -o seamless_clone
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seamless_cloning.o: seamless_cloning.cpp clone.h
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g++ -I /usr/local/include/eigen3 $$(pkg-config --cflags --libs opencv) -c seamless_cloning.cpp
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clone.o: clone.cpp clone.h poisson_solver.h
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g++ -I /usr/local/include/eigen3 $$(pkg-config --cflags --libs opencv) -c clone.cpp
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poisson_solver.o: poisson_solver.cpp poisson_solver.h
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g++ -I /usr/local/include/eigen3 $$(pkg-config --cflags --libs opencv) -c poisson_solver.cpp
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clean:
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rm *.o

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