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hog.cpp
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#pragma package <opencv>
#include <iostream>
#include <cstdio>
#include <unistd.h>
#include <time.h>
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/nonfree/nonfree.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include<opencv2/core/core.hpp>
#include<opencv2/ml/ml.hpp>
#include<vector>
#define PI 3.14159265
using namespace cv;
using namespace std;
const int rw=32,rh=32;
Mat resize2(Mat m) {
int h=m.rows;
int w=m.cols;
Mat tmp = Mat::zeros( rh,rw, m.type() );
Rect roi;
if(w<h) {
roi.height=rh;
roi.width=(w*rh)/h;
roi.x=(rw-roi.width)/2;
}
else {
roi.width=rw;
roi.height=(h*rw)/w;
roi.y=(rh-roi.height)/2;
}
//printf("%d %d %d %d %d %d\n",roi.x,roi.y,roi.width,roi.height,tmp.cols,tmp.rows);
resize(m,tmp(roi),roi.size());
return tmp;
}
void normalize2(double *res,int h[][4][9]){
double val=0.0;
int k=0;
for(int i=0;i<7;i++) {
for(int j=0;j<3;j++) {
//Calculating norm denominator
val=0.0;
for(int n=0;n<9;n++) {
val+=(h[i][j][n]*h[i][j][n]);
}
for(int n=0;n<9;n++) {
val+=(h[i+1][j][n]*h[i+1][j][n]);
}
for(int n=0;n<9;n++) {
val+=(h[i][j+1][n]*h[i][j+1][n]);
}
for(int n=0;n<9;n++) {
val+=(h[i+1][j+1][n]*h[i+1][j+1][n]);
}
val=sqrt(val);
//Normalizing 4 9x1 Vectors
for(int n=0;n<9;n++) {
res[k++]+=((double) h[i][j][n])/val;
}
for(int n=0;n<9;n++) {
res[k++]+=((double) h[i+1][j][n])/val;
}
for(int n=0;n<9;n++) {
res[k++]+=((double) h[i][j+1][n])/val;
}
for(int n=0;n<9;n++) {
res[k++]+=((double) h[i+1][j+1][n])/val;
}
}
}
printf("k=%d\n",k);
}
void train(Mat m,int i) {
}
void recognize(Mat m) {
//Normalizing size of each character
Mat img=resize2(m);
HOGDescriptor hog;
vector<float> featV;
vector<Point>locs;
hog.compute (img,featV,Size(8,8),Size(0,0),locs);
//Computing vertical and horizontal gradient in Polar coordinates
/*img.convertTo(img, CV_32F, 1/255.0);
Mat gx, gy;
Sobel(img, gx, CV_32F, 1, 0, 1);
Sobel(img, gy, CV_32F, 0, 1, 1);
Mat mag, angle;
cartToPolar(gx, gy, mag, angle, 1);
imshow("1",gx);
imshow("2",gy);
//Calculating histograms of 8x8 patches in 9 bins.
int h1[8][4][9];
int i1=0,j1=0;
for(int i=0;i<64;i+=8) {
for(int j=0;j<32;j+=8) {
for(int l=0;l<8;l++) {
for(int m=0;m<8;m++) {
//int vx=gx.at<uchar>(Point(i+l,j+m));
//int vy=gy.at<uchar>(Point(i+l,j+m));
//int vmag=mags[i+l][j+m];
// int ang=angs[i+l][j+m];
double gxv=(double) gx.at<uchar>(Point(i,j));
double gyv=(double) gy.at<uchar>(Point(i,j));
int vmag=sqrt(gxv*gxv+gyv*gyv);
double angss=atan2(gyv,gxv)*180/PI;;
if(angss<0) angss=180+angss;
int ang=(int) angss;
printf("%d %d\n",vmag,ang);
int bno=(ang%180)/20;
int bdiff=ang%20;
if(bdiff==0) {
h1[i1][j1][bno]+=vmag;
}
else {
h1[i1][j1][bno]+=(vmag*20-vmag*bdiff)/20;
h1[i1][j1][(bno+1)%9]+=(vmag*bdiff)/20;
}
}
}
j1++;
}
i1++;
}
//Normalizing histograms
double *res=new double[756];
normalize2(res,h1);*/
printf("hello\n");
return;
}
Mat skeleton(Mat img) {
Mat element = cv::getStructuringElement(cv::MORPH_CROSS, cv::Size(3, 3));
Mat skel(img.size(), CV_8UC1, cv::Scalar(0));
Mat temp(img.size(), CV_8UC1);
bool done;
do
{
morphologyEx(img, temp, cv::MORPH_OPEN, element);
bitwise_not(temp, temp);
bitwise_and(img, temp, temp);
bitwise_or(skel, temp, skel);
erode(img, img, element);
double max;
cv::minMaxLoc(img, 0, &max);
done = (max == 0);
} while (!done);
return skel;
}
vector<float> featD(Mat m) {
SIFT sf;
Mat desc;
vector<KeyPoint> vc;
sf(m,Mat(),vc,desc);
vector<float> res;
for(int i=0; i<desc.cols; i++) {
float v=0;
for(int j=0; j<desc.rows; j++) {
v+=desc.at<float>(j,i);
}
res.push_back(v);
}
return res;
}
void hog_train2(Mat m,Mat o,Rect r)
{
vector<vector<float>> featV; //store feature vectors of each character
vector<vector<Point>> locs; // store location of each character
HOGDescriptor hog;
hog.winSize=Size(rw,rh);
int thresh=0;
int *ch=new int[1000];
int ind=0;
int *a=new int[r.width];
for (int i = 0; i < r.width; i++)
{
a[i]=0;
for(int j=0;j<r.height;j++) {
Scalar myColor = m.at<uchar>(Point(i+r.x,j+r.y));
int pixelValue = myColor.val[0]/255;
a[i]+=pixelValue;
}
}
int flag=1,strt=0,i;
Mat drawing = Mat::zeros( m.size(), CV_8UC3 );
o.copyTo(drawing);
for(i=0;i<r.width;i++)
{
if(a[i]>thresh)
flag=2;
else if(a[i]<=thresh&&flag==2)
{
Rect rec(r.x+strt,r.y,i-strt,r.height);
rectangle(drawing,rec, Scalar(0,0,255), 1);
Mat tmp=m(rec);
Mat cc= Mat::zeros( tmp.size(), CV_8UC1 );
tmp.copyTo(cc);
Mat img=resize2(cc);
vector<float> fv;
vector<Point> lc;
//fv=featD(img);
hog.compute (img,fv,Size(8,8),Size(0,0),lc);
featV.push_back(fv);
locs.push_back(lc);
char ctmp;
int chh=0;
int base=1;
imshow("dd",img);
while((ctmp=waitKey(0))!=' ' || chh==0) {
if(ctmp==8) {
if(base!=100) {
base=base/100;
chh=chh%base;
}
else {
base =1;
chh=0;
}
continue;
}
if(ctmp<32) continue;
ctmp=ctmp%256 - 32;
chh=(ctmp%256)*base+chh;
base=base*100;
}
printf("%d\n",chh);
ch[ind++]=chh;
flag=1;
strt=i;
}
else if(a[i]<=thresh)
{ flag=1; strt=i; }
namedWindow("char", CV_WINDOW_AUTOSIZE);
imshow("char",drawing);
}
if(strt!=i && flag==2) { //Checking end of word.
Rect rec(r.x+strt,r.y,i-strt,r.height);
rectangle(drawing,rec, Scalar(0,0,255), 1);
Mat tmp=m(rec);
Mat cc= Mat::zeros( tmp.size(), CV_8UC1 );
tmp.copyTo(cc);
Mat img=resize2(cc);
vector<float> fv;
vector<Point> lc;
//fv=featD(img);
hog.compute (img,fv,Size(8,8),Size(0,0),lc);
featV.push_back(fv);
locs.push_back(lc);
char ctmp;
int chh=0;
int base=1;
imshow("dd",img);
while((ctmp=waitKey(0))!=' ' || chh==0) {
if(ctmp==8) {
if(base!=100) {
base=base/100;
chh=chh%base;
}
else {
base =1;
chh=0;
}
continue;
}
if(ctmp<32) continue;
ctmp=ctmp%256 - 32;
chh=(ctmp%256)*base+chh;
base=base*100;
}
printf("%d\n",chh);
ch[ind++]=chh;
flag=1;
strt=i;
}
imwrite("char.png",drawing);
FileStorage fs2("train.yml", FileStorage::READ);
Mat rfeaV, rLab; //read from File Mats
fs2["feav"] >> rfeaV;
fs2["label"] >> rLab;
fs2.release();
int cols=featV[0].size();
Mat feaV(featV.size(),cols,CV_32FC1); //Mat Create during this call
for(int i=0; i<feaV.rows; i++)
for(int j=0; j<cols; j++)
feaV.at<float>(i, j) = featV[i][j];
Mat labMat(ind, 1, CV_32SC1, ch);
printf("a: %d\n",feaV.rows);
Mat mfeaV,mLab; //Merging read and created Mats
if(!rfeaV.empty())
vconcat(rfeaV,feaV,mfeaV);
else mfeaV=feaV;
if(!rLab.empty())
vconcat(rLab,labMat,mLab);
else mLab=labMat;
FileStorage fs("train.yml", FileStorage::WRITE);
fs << "feav" << mfeaV;
fs << "label" << mLab;
fs.release();
}
void hog_train(Mat m,Mat o,Rect r)
{
vector<vector<float>> featV; //store feature vectors of each character
vector<vector<Point>> locs; // store location of each character
HOGDescriptor hog;
hog.winSize=Size(rw,rh);
int thresh=0;
int ch[]={33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,17,18,19,20,21,22,23,24,25,16,27,7,12,14,13,8,9};
int ind=69;
int *a=new int[r.width];
for (int i = 0; i < r.width; i++)
{
a[i]=0;
for(int j=0;j<r.height;j++) {
Scalar myColor = m.at<uchar>(Point(i+r.x,j+r.y));
int pixelValue = myColor.val[0]/255;
a[i]+=pixelValue;
}
}
int flag=1,strt=0,i;
Mat drawing = Mat::zeros( m.size(), CV_8UC3 );
o.copyTo(drawing);
for(i=0;i<r.width;i++)
{
if(a[i]>thresh)
flag=2;
else if(a[i]<=thresh&&flag==2)
{
Rect rec(r.x+strt,r.y,i-strt,r.height);
rectangle(drawing,rec, Scalar(0,0,255), 1);
Mat tmp=m(rec);
Mat cc= Mat::zeros( tmp.size(), CV_8UC1 );
tmp.copyTo(cc);
Mat img=resize2(cc);
vector<float> fv;
vector<Point> lc;
//fv=featD(img);
hog.compute (img,fv,Size(8,8),Size(0,0),lc);
featV.push_back(fv);
locs.push_back(lc);
//int chh=waitKey(0)%256;
//printf("%d\n",chh);
//ch[ind++]=chh;
flag=1;
strt=i;
}
else if(a[i]<=thresh)
{ flag=1; strt=i; }
namedWindow("char", CV_WINDOW_AUTOSIZE);
imshow("char",drawing);
}
if(strt!=i && flag==2) { //Checking end of word.
Rect rec(r.x+strt,r.y,i-strt,r.height);
rectangle(drawing,rec, Scalar(0,0,255), 1);
Mat tmp=m(rec);
Mat cc= Mat::zeros( tmp.size(), CV_8UC1 );
tmp.copyTo(cc);
Mat img=resize2(cc);
vector<float> fv;
vector<Point> lc;
//fv=featD(img);
hog.compute (img,fv,Size(8,8),Size(0,0),lc);
featV.push_back(fv);
locs.push_back(lc);
//int chh=waitKey(0);
//printf("%c\n",chh);
//ch[ind++]=chh;
flag=1;
strt=i;
}
imwrite("char.png",drawing);
FileStorage fs2("train.yml", FileStorage::READ);
Mat rfeaV, rLab; //read from File Mats
fs2["feav"] >> rfeaV;
fs2["label"] >> rLab;
fs2.release();
int cols=featV[0].size();
Mat feaV(featV.size(),cols,CV_32FC1); //Mat Create during this call
for(int i=0; i<feaV.rows; i++)
for(int j=0; j<cols; j++)
feaV.at<float>(i, j) = featV[i][j];
Mat labMat(ind, 1, CV_32SC1, ch);
printf("a: %d\n",feaV.rows);
Mat mfeaV,mLab; //Merging read and created Mats
if(!rfeaV.empty())
vconcat(rfeaV,feaV,mfeaV);
else mfeaV=feaV;
if(!rLab.empty())
vconcat(rLab,labMat,mLab);
else mLab=labMat;
FileStorage fs("train.yml", FileStorage::WRITE);
fs << "feav" << mfeaV;
fs << "label" << mLab;
fs.release();
}
void hog(Mat m,Mat o,Rect r,char *c,int *ind)
{
FileStorage fs("train.yml", FileStorage::READ);
Mat rfeaV, rLab; //read from File Mats
fs["feav"] >> rfeaV;
fs["label"] >> rLab;
fs.release();
CvSVMParams params;
params.svm_type = CvSVM::C_SVC;
params.kernel_type = CvSVM::LINEAR;
params.term_crit = cvTermCriteria(CV_TERMCRIT_ITER, 100, 1e-6);
CvSVM SVM;
SVM.train(rfeaV, rLab, Mat(), Mat(), params);
HOGDescriptor hog;
hog.winSize=Size(rw,rh);
vector<vector<float>> featV; //store feature vectors of each character
vector<vector<Point>> locs; // store location of each character
int thresh=0;
int *a=new int[r.width];
for (int i = 0; i < r.width; i++)
{
a[i]=0;
for(int j=0;j<r.height;j++) {
Scalar myColor = m.at<uchar>(Point(i+r.x,j+r.y));
int pixelValue = myColor.val[0]/255;
a[i]+=pixelValue;
}
}
int flag=1,strt=0,i;
Mat drawing = Mat::zeros( m.size(), CV_8UC3 );
o.copyTo(drawing);
for(i=0;i<r.width;i++)
{
if(a[i]>thresh)
flag=2;
else if(a[i]<=thresh&&flag==2)
{
Rect rec(r.x+strt,r.y,i-strt,r.height);
rectangle(drawing,rec, Scalar(0,0,255), 1);
Mat tmp=m(rec);
Mat cc= Mat::zeros( tmp.size(), CV_8UC1 );
tmp.copyTo(cc);
Mat img=resize2(cc);
vector<float> fv;
vector<Point> lc;
hog.compute (img,fv,Size(8,8),Size(0,0),lc);
//fv=featD(img);
Mat fvm(fv,true);
int val=SVM.predict(fvm);
if(val<100)
c[(*ind)++]=(char) (val+32);
else {
int t22=val;
while(t22>0) {
int t33=(t22%100) + 32;
t22=t22/100;
c[(*ind)++]=(char) (t33%256);
}
}
flag=1;
strt=i;
}
else if(a[i]<=thresh)
{ flag=1; strt=i; }
namedWindow("char", CV_WINDOW_AUTOSIZE);
imshow("char",drawing);
}
if(strt!=i && flag==2) { //Checking end of word.
Rect rec(r.x+strt,r.y,i-strt,r.height);
rectangle(drawing,rec, Scalar(0,0,255), 1);
Mat tmp=m(rec);
Mat cc= Mat::zeros( tmp.size(), CV_8UC1 );
tmp.copyTo(cc);
Mat img=resize2(cc);
vector<float> fv;
vector<Point> lc;
//fv=featD(img);
hog.compute (img,fv,Size(8,8),Size(0,0),lc);
Mat fvm(fv,true);
int val=SVM.predict(fvm);
if(val<100)
c[(*ind)++]=(char) (val+32);
else {
int t22=val;
while(t22>0) {
int t33=(t22%100) + 32;
t22=t22/100;
c[(*ind)++]=(char) (t33%256);
}
}
flag=1;
strt=i;
}
//imwrite("char.png",drawing);
}