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vision.cpp
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vision.cpp
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#include <ctime>
#include <iostream>
#include <raspicam/raspicam_cv.h>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/opencv.hpp>
#include "opencv2/calib3d/calib3d.hpp"
#include <opencv2/imgproc.hpp>
#include <highgui.h>
#include "ros/ros.h"
#include "std_msgs/Int32.h"
#include <sstream>
// Umbrales
int lowThreshold;
int ratio = 1;//3,1
int kernel_size = 5;//3,5
int scale = 1;
int delta = 0;
int ddepth = CV_16S;
int c,rec,umbral=7;
int mx=0;
int my=0;
int start,hoja;
#define uget(x,y) at<unsigned char>(y,x)
#define uset(x,y,v) at<unsigned char>(y,x)=v;
#define fget(x,y) at<float>(y,x)
#define fset(x,y,v) at<float>(y,x)=v;
void sta_callback(const std_msgs::Int32::ConstPtr& msg1)
{
start=msg1->data;
}
using namespace std;
double calcLocalStats (cv::Mat &im, cv::Mat &map_m, cv::Mat &map_s, int winx, int winy) {
cv::Mat im_sum, im_sum_sq;
cv::integral(im,im_sum,im_sum_sq,CV_64F);
double m,s,max_s,sum,sum_sq;
int wxh = winx/2;
int wyh = winy/2;
int x_firstth= wxh;
int y_lastth = im.rows-wyh-1;
int y_firstth= wyh;
double winarea = winx*winy;
max_s = 0;
for (int j = y_firstth ; j<=y_lastth; j++){
sum = sum_sq = 0;
sum = im_sum.at<double>(j-wyh+winy,winx) - im_sum.at<double>(j-wyh,winx) - im_sum.at<double>(j-wyh+winy,0) + im_sum.at<double>(j-wyh,0);
sum_sq = im_sum_sq.at<double>(j-wyh+winy,winx) - im_sum_sq.at<double>(j-wyh,winx) - im_sum_sq.at<double>(j-wyh+winy,0) + im_sum_sq.at<double>(j-wyh,0);
m = sum / winarea;
s = sqrt ((sum_sq - m*sum)/winarea);
if (s > max_s) max_s = s;
map_m.fset(x_firstth, j, m);
map_s.fset(x_firstth, j, s);
// Shift the window, add and remove new/old values to the histogram
for (int i=1 ; i <= im.cols-winx; i++) {
// Remove the left old column and add the right new column
sum -= im_sum.at<double>(j-wyh+winy,i) - im_sum.at<double>(j-wyh,i) - im_sum.at<double>(j-wyh+winy,i-1) + im_sum.at<double>(j-wyh,i-1);
sum += im_sum.at<double>(j-wyh+winy,i+winx) - im_sum.at<double>(j-wyh,i+winx) - im_sum.at<double>(j-wyh+winy,i+winx-1) + im_sum.at<double>(j-wyh,i+winx-1);
sum_sq -= im_sum_sq.at<double>(j-wyh+winy,i) - im_sum_sq.at<double>(j-wyh,i) - im_sum_sq.at<double>(j-wyh+winy,i-1) + im_sum_sq.at<double>(j-wyh,i-1);
sum_sq += im_sum_sq.at<double>(j-wyh+winy,i+winx) - im_sum_sq.at<double>(j-wyh,i+winx) - im_sum_sq.at<double>(j-wyh+winy,i+winx-1) + im_sum_sq.at<double>(j-wyh,i+winx-1);
m = sum / winarea;
s = sqrt ((sum_sq - m*sum)/winarea);
if (s > max_s) max_s = s;
map_m.fset(i+wxh, j, m);
map_s.fset(i+wxh, j, s);
}
}
return max_s;
}
//rutina de binarización
void NiblackSauvolaWolfJolion (cv::Mat im, cv::Mat output,int winx, int winy, double k, double dR) {
double m, s, max_s;
double th=0;
double min_I, max_I;
int wxh = winx/2;
int wyh = winy/2;
int x_firstth= wxh;
int x_lastth = im.cols-wxh-1;
int y_lastth = im.rows-wyh-1;
int y_firstth= wyh;
int mx, my;
// Crea estadísticas locales y guárdalas en matrices dobles
cv::Mat map_m = cv::Mat::zeros (im.rows, im.cols, CV_32F);
cv::Mat map_s = cv::Mat::zeros (im.rows, im.cols, CV_32F);
max_s = calcLocalStats (im, map_m, map_s, winx, winy);
minMaxLoc(im, &min_I, &max_I);
cv::Mat thsurf (im.rows, im.cols, CV_32F);
// Umbralizar y obtener bordes
// ----------------------------------------------------
for (int j = y_firstth ; j<=y_lastth; j++) {
// NORMAL, área sin bordes en medio de la ventana.
for (int i=0 ; i <= im.cols-winx; i++) {
m = map_m.fget(i+wxh, j);
s = map_s.fget(i+wxh, j);
// Calcular umbral
th = m + k * (s/max_s-1) * (m-min_I);//wolf
thsurf.fset(i+wxh,j,th);
if (i==0) {
// borde izquierdo
for (int i=0; i<=x_firstth; ++i)
thsurf.fset(i,j,th);
// esquina superior izquierda
if (j==y_firstth)
for (int u=0; u<y_firstth; ++u)
for (int i=0; i<=x_firstth; ++i)
thsurf.fset(i,u,th);
// esquina inferior izquierda
if (j==y_lastth)
for (int u=y_lastth+1; u<im.rows; ++u)
for (int i=0; i<=x_firstth; ++i)
thsurf.fset(i,u,th);
}
// borde superior
if (j==y_firstth)
for (int u=0; u<y_firstth; ++u)
thsurf.fset(i+wxh,u,th);
// borde inferior
if (j==y_lastth)
for (int u=y_lastth+1; u<im.rows; ++u)
thsurf.fset(i+wxh,u,th);
}
// borde derecho
for (int i=x_lastth; i<im.cols; ++i)
thsurf.fset(i,j,th);
// esquina superior izquierda
if (j==y_firstth)
for (int u=0; u<y_firstth; ++u)
for (int i=x_lastth; i<im.cols; ++i)
thsurf.fset(i,u,th);
// esquina inferior derecha
if (j==y_lastth)
for (int u=y_lastth+1; u<im.rows; ++u)
for (int i=x_lastth; i<im.cols; ++i)
thsurf.fset(i,u,th);
}
cerr << "superficie creada" << endl;
for (int y=0; y<im.rows; ++y)
for (int x=0; x<im.cols; ++x)
{
if (im.uget(x,y) >= thsurf.fget(x,y))
{
output.uset(x,y,255);
}
else
{
output.uset(x,y,0);
}
}
}
double angle( cv::Point pt1, cv::Point pt2, cv::Point pt0 ) {
double dx1 = pt1.x - pt0.x;
double dy1 = pt1.y - pt0.y;
double dx2 = pt2.x - pt0.x;
double dy2 = pt2.y - pt0.y;
return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
}
std::vector<cv::Point> getChangePoints(const std::vector<cv::Point>& points) {
std::vector<cv::Point> changePoints;
cv::Point vec(points[0] - points[3]);
double h = sqrt(vec.ddot(vec));
changePoints.push_back(cv::Point(0, 0));
changePoints.push_back(cv::Point(int(h * 210 / 297), 0));
changePoints.push_back(cv::Point(int(h * 210 / 297), int(h)));
changePoints.push_back(cv::Point(0, int(h)));
return changePoints;
}
void sortPoints(std::vector<cv::Point>& points) {
double distance[4];
for (int i = 0; i < 4; ++i) {
distance[i] = points[i].ddot(points[i]);
}
int index = 0;
double mini = distance[0];
for (int i = 0; i < 4; ++i) {
if (distance[i] < mini) {
mini = distance[i];
index = i;
}
}
cv::Point temp(points[index]);
sort(points.begin(), points.end(), [&](cv::Point a, cv::Point b) {
return (pow(a.x - temp.x, 2) + pow(a.y - temp.y, 2)) < (pow(b.x - temp.x, 2) + pow(b.y - temp.y, 2));
});
temp = points[2];
points[2] = points[3];
points[3] = temp;
if (points[1].y > points[3].y && points[1].x < points[3].x) {
std::vector<cv::Point> vec;
// rotate points
vec.push_back(points[1]);
vec.push_back(points[0]);
vec.push_back(points[3]);
vec.push_back(points[2]);
points.clear();
points.assign(vec.begin(), vec.end());
}
}
cv::Mat getChangePicture(cv::Mat src, int rows, int cols, cv::Mat matrix) {
cv::Mat dst = cv::Mat(rows, cols, 0);
for (int i = 0; i < dst.rows; ++i) {
for (int j = 0; j < dst.cols; ++j) {
double x = matrix.at<double>(0, 0) * j + matrix.at<double>(0, 1) * i +
matrix.at<double>(0, 2);
double y = matrix.at<double>(1, 0) * j + matrix.at<double>(1, 1) * i +
matrix.at<double>(1, 2);
int a = int(x);
int b = int(y);
double u = x - a;
double v = y - b;
int pixel = int((1 - u) * (1 - v) * src.at<uchar>(b >= src.rows ? src.rows - 1 : b, a >= src.cols ? src.cols - 1 : a) +
u * (1 - v) * src.at<uchar>(b >= src.rows ? src.rows - 1 : b, a + 1 >= src.cols ? src.cols - 1 : a + 1) +
(1 - u) * v * src.at<uchar>(b + 1 >= src.rows ? src.rows - 1 : b + 1, a >= src.cols ? src.cols - 1 : a ) +
u * v * src.at<uchar>(b + 1 >= src.rows ? src.rows - 1 : b + 1, a + 1 >= src.cols ? src.cols - 1 : a + 1));
dst.at<uchar>(i, j) = pixel;
}
}
return dst;
}
int main ( int argc,char **argv ) {
ros::init(argc, argv, "vision");
ros::NodeHandle n;
ros::Subscriber ini_v = n.subscribe("capturar", 1, sta_callback);
ros::Publisher prin_p = n.advertise<std_msgs::Int32>("/escaneando",150);
raspicam::RaspiCam_Cv Camera;
std_msgs::Int32 msgsta;
//set camera params
Camera.set(CV_CAP_PROP_FRAME_WIDTH,640);
Camera.set(CV_CAP_PROP_FRAME_HEIGHT,480);
Camera.set(CV_CAP_PROP_BRIGHTNESS,50);
Camera.set(CV_CAP_PROP_CONTRAST,50);
Camera.set(CV_CAP_PROP_SATURATION,50);
Camera.set(CV_CAP_PROP_GAIN,50);
Camera.set(CV_CAP_PROP_FORMAT,CV_8UC3);
Camera.set(CV_CAP_PROP_EXPOSURE,-1);
Camera.set(CV_CAP_PROP_WHITE_BALANCE_RED_V,-1);
Camera.set(CV_CAP_PROP_WHITE_BALANCE_BLUE_U,-1);
//Open camera
if (!Camera.open()) {cerr<<"Error opening the camera"<<endl;return -1;}
cv::namedWindow("Original");
cv::namedWindow("Gray");
cv::namedWindow("Edges");
cv::namedWindow("Cut");
cv::Mat img,src,src2;
while(ros::ok()){
std::cout<<"start "<<start<<"\n";
if(start==0){ hoja=0; }
if(start==1 && hoja!=2){
hoja = 1;//buscando hoja
Camera.grab();
Camera.retrieve ( img);
cv::Mat src,src_gray,detected_edges;
img.copyTo(src);
img.copyTo(src2);
int p1=img.size().width;
int p2=img.size().height;
cv::GaussianBlur(src, src, cv::Size(3,3),0,0,cv::BORDER_DEFAULT);//15,15,7
cv::cvtColor(src,src_gray,CV_BGR2GRAY);
cv::cvtColor(src2,src2,CV_BGR2GRAY);
/// Generate grad_x and grad_y
cv::Mat grad_x, grad_y;
cv::Mat abs_grad_x, abs_grad_y;
/// Gradient X
//Scharr( src_gray, grad_x, ddepth, 1, 0, scale, delta, BORDER_DEFAULT );
cv::Sobel(src_gray, grad_x, ddepth, 1, 0, 3, scale, delta, cv::BORDER_DEFAULT );
cv::convertScaleAbs( grad_x, abs_grad_x );
/// Gradient Y
//Scharr( src_gray, grad_y, ddepth, 0, 1, scale, delta, BORDER_DEFAULT );
cv::Sobel(src_gray, grad_y, ddepth, 0, 1, 3, scale, delta, cv::BORDER_DEFAULT );
cv::convertScaleAbs( grad_y, abs_grad_y );
/// Total Gradient (approximate)
cv::addWeighted( abs_grad_x, 0.5, abs_grad_y, 0.5, 0, detected_edges );
//Find contours
cv::imshow("Edges",detected_edges);
cv::Canny(detected_edges, detected_edges, 10,30);//20,70
std::vector<std::vector<cv::Point> > contours;
std::vector<cv::Vec4i> hierarchy;
cv::findContours(detected_edges,contours,hierarchy,cv::RETR_CCOMP,cv::CHAIN_APPROX_SIMPLE);//RETR_CCOMP
//Approximate contours with linear features
// Test contours
//************************************************************************************************************
std::vector<cv::Point> approx;
std::vector<int> areasqr;//vector de areas
std::vector<std::vector<cv::Point> > squares;//vector de coordenadas
rec=0;//para evitar que se muera
for (size_t i = 0; i < contours.size(); i++)
{
cv::approxPolyDP(cv::Mat(contours[i]), approx, cv::arcLength(cv::Mat(contours[i]), true)*0.02, true);//true
if (approx.size() == 4 &&
fabs(cv::contourArea(cv::Mat(approx))) > 1000 && cv::isContourConvex(cv::Mat(approx)))
{
double maxCosine = 0;
//std::cout<<"pasa"<<"\n \n";
for (int j = 2; j < 5; j++)
{
double cosine = fabs(angle(approx[j%4], approx[j-2], approx[j-1]));
maxCosine = MAX(maxCosine, cosine);
}
if (maxCosine < 0.6){
if(rec==0){
squares.push_back(approx);
areasqr.push_back(cv::contourArea(cv::Mat(approx)));
rec=1;
}
else{
int rannx, ranpx,ranny,ranpy;
//X ***********************************************
if((squares[rec-1][0].x-umbral)>0 && (squares[rec-1][0].x+umbral)<p1){
rannx=squares[rec-1][0].x-umbral;
ranpx=squares[rec-1][0].x+umbral;
}
else if((squares[rec-1][0].x-umbral)<0 && (squares[rec-1][0].x+umbral)<p1){ //p1 is width
rannx=0;
ranpx=squares[rec-1][0].x+umbral;
}
else{
rannx=squares[rec-1][0].x-umbral;
ranpx=p1;
}
//Y ***********************************************
if((squares[rec-1][0].y-umbral)>0 && (squares[rec-1][0].y+umbral)<p2){
ranny=squares[rec-1][0].y-umbral;
ranpy=squares[rec-1][0].y+umbral;
}
else if((squares[rec-1][0].y-umbral)<0 && (squares[rec-1][0].y+umbral)<p2){ //p2 is length
ranny=0;
ranpy=squares[rec-1][0].y+umbral;
}
else{
ranny=squares[rec-1][0].y-umbral;
ranpy=p2;
}
// comparacion de rectangulos
bool comp=false;
for(int c=0;c<4;c++){
bool co=((approx[c].x)>=rannx)&&((approx[c].x)<=ranpx)&&((approx[c].y)>=ranny)&&((approx[c].y)<=ranpy);
comp=comp||co;
}
if(comp==false)
{
squares.push_back(approx);
areasqr.push_back(fabs(cv::contourArea(cv::Mat(approx))));
rec=rec+1;
}
}
}
}
}
std::cout<<"cuadrados "<<squares.size()<<" areas " <<areasqr.size()<<"\n";
if(squares.size()>0){
for (int c = 0; c < squares.size(); c++)
std::cout<<c<<" "<<squares[c]<<" area "<<areasqr[c]<<" \n";
//std::cout<<"cuadrados "<<squares<<" \n";
//DRAW RECTANGLE
for ( int i = 0; i< squares.size(); i++ ) {
// draw contour
cv::drawContours(img, squares, i, cv::Scalar(0,255,0), 1, 8, std::vector<cv::Vec4i>(), 0, cv::Point());
}
//centroid
int mic = areasqr[0];
int n=areasqr.size();
int miar=0;//area maxima
for(int u=0;u<n;u++)
{
std::cout<<"area for "<<areasqr[u]<<" inicial " <<areasqr[0]<<"\n";
if(areasqr[u]>mic){
mic=areasqr[u];
miar=u;
}
}
std::cout<<"area mas grande "<<miar<<"\n";
if(mic>28000){//areas mas grandes para descartar rectangulos dentro de la hoja
// Crear un rectangulo para definir la region de interes
//encontrar vertices mas alejados
int v1x=squares[miar][0].x,v2x=squares[miar][0].x,vxa;
int v1y=squares[miar][0].y,v2y=squares[miar][0].y,vya;
for(int i=0; i<4;i++){
vxa=squares[miar][i].x;
vya=squares[miar][i].y;
if(vxa<v1x){//menores
v1x=vxa;
}
if(vya<v1y){
v1y=vya;
}
if(vxa>v2x){//mayores
v2x=vxa;
}
if(vya>v2y){
v2y=vya;
}
}
std::cout<<"CUMPLE "<<miar<<"\n";
std::cout<<v1x<<" "<<v1y<<" "<<v2x<<" "<<v2y<<"\n";
cv::Mat transform = src2(cv::Rect(cv::Point(v1x,v1y),cv::Point(v2x,v2y)));
//******************************************************************************************
//WOLF-JOLION
char version;
int c;
int winx=0, winy=0;
float optK=0.1;//0.5
// Modificar tamaño de ventana (kernel)
if (winx==0||winy==0) {
winy = (int) (2.0 * transform.rows-1)/3;
winx = (int) transform.cols-1 < winy ? transform.cols-1 : winy;
if (winx > 70)//100
winx = winy = 20;//60
cerr << "Definiendo tamaño de ventana a [" << winx<< "," << winy << "].\n";
}
// Umbral
cv::Mat output (transform.rows, transform.cols, CV_8U);
NiblackSauvolaWolfJolion (transform, output, winx, winy, optK, 128);
// guardar imagen
cv::imshow("Cut",output);
cv::imwrite ("a_w.jpg", output);
hoja=2;//hoja encontrada
}
//centroide
mx=0;
my=0;
for(int v=0;v<4;v++){
mx=mx+squares[miar][v].x;
my=my+squares[miar][v].y;
}
mx=mx/4;
my=my/4;
cv::circle(img,cv::Point(mx,my),3,cv::Scalar( 0, 0, 255 ),8,8,0);
}
//************************************************************************************************************
cv::imshow("Original",img);
cv::imshow("Gray",src_gray);
if((cv::waitKey(10) & 255) == 27){break;}
}
msgsta.data = hoja;
prin_p.publish(msgsta);
ros::spinOnce();
}
Camera.release();
return 0;
}