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clean.hpp
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clean.hpp
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#ifndef CLEANTOOL
#define CLEANTOOL
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <iostream>
using namespace cv;
using namespace std;
float fcxcy[3];//SET THE CAMERA PARAMETERS F CX CY BEFORE USE calplanenormal.
int WINDOWSIZE=15;//SET SEARCH WINDOWSIZE(SUGGEST 15) BEFORE USE calplanenormal.
float Tthrehold;//SET THE threshold (SUGGEST 0.1-0.2)BEFORE USE calplanenormal.
// Ax+by+cz=D
void
CallFitPlane(const Mat& depth,int * points,int i,int j,float *plane12) {
float f =fcxcy[0];
float cx=fcxcy[1];
float cy=fcxcy[2];
vector<float>X_vector;
vector<float>Y_vector;
vector<float>Z_vector;
for(int num_point=0; num_point<WINDOWSIZE*WINDOWSIZE;num_point++ )
if (points[num_point]==1) {//search 已经处理了边界,此处不需要再处理了
int point_i,point_j;
point_i=floor(num_point/WINDOWSIZE);
point_j=num_point-(point_i*WINDOWSIZE);
point_i+=i-int(WINDOWSIZE/2);point_j+=j-int(WINDOWSIZE/2);
float x = (point_j - cx) * depth.at<float>(point_i, point_j ) * 1.0 / f;
float y = (point_i - cy) * depth.at<float>(point_i, point_j )* 1.0 / f;
float z = depth.at<float>(point_i,point_j);
X_vector.push_back(x);
Y_vector.push_back(y);
Z_vector.push_back(z);
}
CvMat*points_mat = cvCreateMat(X_vector.size(), 3, CV_32FC1);//定义用来存储需要拟合点的矩阵
if(X_vector.size()<3){ plane12[0]=-1;plane12[1]=-1;plane12[2]=-1;plane12[3]=-1;return;}
for (int ii=0;ii < X_vector.size(); ++ii){
points_mat->data.fl[ii * 3 + 0] = X_vector[ii];//矩阵的值进行初始化 X的坐标值
points_mat->data.fl[ii * 3 + 1] = Y_vector[ii];// Y的坐标值
points_mat->data.fl[ii * 3 + 2] = Z_vector[ii];//
}
// float plane12[4] = { 0 };//定义用来储存平面参数的数组
cvFitPlane(points_mat, plane12);//调用方程
if( telldirection(plane12,i,j,depth.at<float>(i,j)) ){
plane12[0]=-plane12[0];
plane12[1]=-plane12[1];
plane12[2]=-plane12[2];}
X_vector.clear();
Y_vector.clear();
Z_vector.clear();
cvReleaseMat(&points_mat);
}
void
cvFitPlane(const CvMat* points, float* plane){
// Estimate geometric centroid.
int nrows = points->rows;
int ncols = points->cols;
int type = points->type;
CvMat* centroid = cvCreateMat(1, ncols, type);
cvSet(centroid, cvScalar(0));
for (int c = 0; c<ncols; c++){
for (int r = 0; r < nrows; r++)
{
centroid->data.fl[c] += points->data.fl[ncols*r + c];
}
centroid->data.fl[c] /= nrows;
}
// Subtract geometric centroid from each point.
CvMat* points2 = cvCreateMat(nrows, ncols, type);
for (int r = 0; r<nrows; r++)
for (int c = 0; c<ncols; c++)
points2->data.fl[ncols*r + c] = points->data.fl[ncols*r + c] - centroid->data.fl[c];
// Evaluate SVD of covariance matrix.
CvMat* A = cvCreateMat(ncols, ncols, type);
CvMat* W = cvCreateMat(ncols, ncols, type);
CvMat* V = cvCreateMat(ncols, ncols, type);
cvGEMM(points2, points, 1, NULL, 0, A, CV_GEMM_A_T);
cvSVD(A, W, NULL, V, CV_SVD_V_T);
// Assign plane coefficients by singular vector corresponding to smallest singular value.
plane[ncols] = 0;
for (int c = 0; c<ncols; c++){
plane[c] = V->data.fl[ncols*(ncols - 1) + c];
plane[ncols] += plane[c] * centroid->data.fl[c];
}
// Release allocated resources.
cvReleaseMat(¢roid);
cvReleaseMat(&points2);
cvReleaseMat(&A);
cvReleaseMat(&W);
cvReleaseMat(&V);
}
void
search_plane_neighbor(Mat &img,int i,int j ,float threhold,int* result){
int cols =img.cols;
int rows =img.rows;
for (int ii=0; ii<WINDOWSIZE*WINDOWSIZE;ii++)
result[ii]=0;
float center_depth = img.at<float>(i,j);
for (int idx=0; idx<WINDOWSIZE;idx++)
for (int idy=0; idy<WINDOWSIZE;idy++){
int rx= i-int(WINDOWSIZE/2)+idx;
int ry= j-int(WINDOWSIZE/2)+idy;
if( rx>= rows || ry>=cols )continue;
if( img.at<float>(rx,ry)==0.0)continue;
if( abs(img.at<float>(rx,ry)-center_depth)<=Tthrehold*center_depth )
result[idx*WINDOWSIZE+idy]=1;
}
}
int
telldirection(float * abc,int i,int j,float d){
float f =fcxcy[0];
float cx=fcxcy[1];
float cy=fcxcy[2];
float x = (j - cx) *d * 1.0 / f;
float y = (i - cy) *d * 1.0 / f;
float z = d;
// Vec3f camera_center=Vec3f(cx,cy,0);
Vec3f cor = Vec3f(0-x, 0-y, 0-z);
Vec3f abcline = Vec3f(abc[0],abc[1],abc[2]);
float corner = cor.dot(abcline);
// float corner =(cx-x)*abc[0]+(cy-y) *abc[1]+(0-z)*abc[2];
if (corner>=0)
return 1;
else return 0;
}
Mat
calplanenormal(Mat &src){
float f =fcxcy[0];
float cx=fcxcy[1];
float cy=fcxcy[2];
Mat normals = Mat::zeros(src.size(),CV_32FC3);
src.convertTo(src,CV_32FC1);
src*=1.0;
int cols =src.cols;
int rows =src.rows;
// int plane_points[WINDOWSIZE*WINDOWSIZE]={0};
int * plane_points = new int[WINDOWSIZE*WINDOWSIZE];
float * plane12 = new float[4];
for (int i=0;i< rows;i++)
for (int j=0;j< cols;j++){
//for kitti and nyud test
if(src.at<float>(i,j)==0.0)continue;
//for:nyud train
// if(src.at<float>(i,j)<=4000.0)continue;
search_plane_neighbor(src,i,j,15.0,plane_points);
CallFitPlane(src,plane_points,i,j,plane12);
Vec3f d = Vec3f(plane12[0],plane12[1],plane12[2]);
Vec3f n = normalize(d);
normals.at<Vec3f>(i, j) = n;
}
Mat res = Mat::zeros(src.size(),CV_32FC3);
for (int i=0;i<rows;i++)
for (int j=0;j<cols;j++){
res.at<Vec3f>(i, j)[0] = -1.0 * normals.at<Vec3f>(i, j)[0];
res.at<Vec3f>(i, j)[2] = -1.0 * normals.at<Vec3f>(i, j)[1];
res.at<Vec3f>(i, j)[1] = -1.0 * normals.at<Vec3f>(i, j)[2];
}
delete[] plane12;
delete[] plane_points;
normals.release();
for (int i=0;i<rows;i++)
for (int j=0;j<cols;j++){
if(!(res.at<Vec3f>(i, j)[0]==0&&res.at<Vec3f>(i, j)[1]==0&&res.at<Vec3f>(i, j)[2]==0)){
res.at<Vec3f>(i, j)[0] += 1.0 ;
res.at<Vec3f>(i, j)[2] += 1.0 ;
res.at<Vec3f>(i, j)[1] += 1.0;
}
}
res =res * 127.5;
res.convertTo(res, CV_8UC3);
cvtColor(res, res, COLOR_BGR2RGB);
return res;
}
void
demo{
//set parameters here:fcxcy[0]=0;fcxcy[1]=0;fcxcy[2]=0;
Mat src=imread(INPUT_FILE_NAME,CV_LOAD_IMAGE_ANYDEPTH);
Mat res=calplanenormal(src);
imwrite(OUTPUT_NAME,res);
}
#endif