cleanup code and add comments

Author: SSARCandy

include/CLD.h

@@ -2,36 +2,27 @@
 #include <opencv2/opencv.hpp>
 #include "ETF.h"
 
-
 using namespace std;
 
 #define M_PI 3.14159265358979323846
 #define SIGMA_RATIO 1.6 
-#define BINARIZATION_THRESHOLDING 200
-#define BIAS 200
 #define STEPSIZE 1.0
 
-class CLD
-{
+class CLD {
 public:
 	CLD();
 	CLD(cv::Size);
 	void init(cv::Size);
 	void readSrc(string);
 	void genCLD();
-
+	void combineImage();
 	// Perform eq.(6) on each pixel
 	void gradientDoG(cv::Mat& src, cv::Mat& dst, const double rho, const double sigma_c);
-
 	// Perform eq.(9) on each pixel
 	void flowDoG(cv::Mat& src, cv::Mat& dst, const double sigma_m);
- 	
 	// eq.(10)
 	void binaryThresholding(cv::Mat& src, cv::Mat& dst, const double tau);
 
-	// re-initialize the filter input by superimposing the black edge pixels of the previous binary output upon the original image I
-	void combineImage();
-
 	cv::Mat originalImg;
 	cv::Mat DoG;
 	cv::Mat FDoG;
@@ -42,5 +33,4 @@ class CLD
 	double sigma_m;
 	double rho;
 	double tau;
-
 };

include/ETF.h

@@ -8,22 +8,13 @@ class ETF {
 	ETF();
 	ETF(cv::Size);
 	void Init(cv::Size);
-	//void operator=(const ETF &in);
-	//void ReadSrc(string);
-	void ReadFlow(string, cv::Size);
-	void gen_ETF(string, cv::Size);
+	void initial_ETF(string, cv::Size);
 	void refine_ETF(int kernel);
-	//void GVF();
 	void rotateFlow(cv::Mat& src, cv::Mat& dst, float theta);
 
-	cv::Mat GVF;         // gradient vector flow
 	cv::Mat gradientMag; // Normalized gradient magnitude
 	cv::Mat flowField;   // edge tangent flow
 	cv::Mat refinedETF;  // ETF after refinement 
-	cv::Mat RotationMat;
-
-	int halfw;
-	int smoothPasses;
 
 private:
 	void resizeMat(cv::Size);
@@ -32,5 +23,4 @@ class ETF {
 	float computeWs(cv::Point2f x, cv::Point2f y, int r);
 	float computeWm(float gradmag_x, float gradmag_y);
 	float computeWd(cv::Vec3f x, cv::Vec3f y);
-
 };

include/gui.h

@@ -7,14 +7,12 @@
 #include <wx/filedlg.h>
 #include <wx/wfstream.h>
 
-class MyApp: public wxApp
-{
+class MyApp : public wxApp {
 public:
 	virtual bool OnInit();
 };
 
-class BasicDrawPane : public wxPanel
-{
+class BasicDrawPane : public wxPanel {
 
 public:
 	BasicDrawPane(wxPanel* parent, cv::Size, bool canUndo);
@@ -26,14 +24,13 @@ class BasicDrawPane : public wxPanel
 	string processingS;
 	void paintEvent(wxPaintEvent& evt);
 	void paintNow(bool);
-	void render( wxDC& dc,bool );
+	void render(wxDC& dc, bool);
 	DECLARE_EVENT_TABLE()
 private:
 	bool activateDraw;
 };
 
-class MyFrame: public wxFrame
-{
+class MyFrame : public wxFrame {
 public:
 	MyFrame(const wxString& title, const wxPoint& pos, const wxSize& size);
 	BasicDrawPane *drawPane;
@@ -87,8 +84,7 @@ class MyFrame: public wxFrame
 	wxDECLARE_EVENT_TABLE();
 };
 
-enum
-{
+enum {
 	// Menu > File
 	ID_ONOPENSRC = 1,
 	ID_ONSAVE,

include/postProcessing.h

@@ -3,8 +3,7 @@
 
 using namespace std;
 
-class PP
-{
+class PP {
 public:
 	PP(cv::Size);
 	void ETF(cv::Mat &flowfield, cv::Mat &dis);

src/CLD.cpp

@@ -56,7 +56,7 @@ void CLD::readSrc(string file) {
 	DoG = Mat::zeros(Size(originalImg.cols, originalImg.rows), CV_32FC1);
 	FDoG = Mat::zeros(Size(originalImg.cols, originalImg.rows), CV_32FC1);
 
-	etf.gen_ETF(file, originalImg.size());
+	etf.initial_ETF(file, originalImg.size());
 	//genCLD();
 }
 
@@ -193,6 +193,10 @@ void CLD::binaryThresholding(Mat & src, Mat & dst, const double tau) {
 	}
 }
 
+/**
+ * re-initialize the filter input 
+ * by superimposing the black edge pixels of the previous binary output upon the original image
+ */
 void CLD::combineImage() {
 	for (int y = 0; y < originalImg.rows; y++) {
 		for (int x = 0; x < originalImg.cols; x++) {
@@ -204,5 +208,6 @@ void CLD::combineImage() {
 		}
 	}
 
+	// Blur a little-bit to let image more smooth
 	GaussianBlur(originalImg, originalImg, Size(3, 3), 0, 0);
 }

src/ETF.cpp

@@ -16,48 +16,15 @@ ETF::ETF(Size s) {
 
 void ETF::Init(Size s) {
 	flowField = Mat::zeros(s, CV_32FC3);
-	GVF = Mat::zeros(s, CV_32FC3);
 	refinedETF = Mat::zeros(s, CV_32FC3);
 	gradientMag = Mat::zeros(s, CV_32FC3);
-
-	halfw = 4;
-	smoothPasses = 2;
-}
-
-void ETF::ReadFlow(string file, Size s) {
-	FILE *stream = fopen(file.c_str(), "rb");
-	if (!stream) {
-		//std::cout<<"ERROR!! Can't read "<<featurefile<<'\n';
-		return;
-	}
-
-	int vf_w, vf_h;
-	int sint = sizeof(int);
-
-	fread((void *)&(vf_w), sint, 1, stream);
-	fread((void *)&(vf_h), sint, 1, stream);
-
-	int sfloat = sizeof(float);
-	float *data = new float[vf_w*vf_h * 2];
-	fread((void *)(data), sfloat, vf_w*vf_h * 2, stream);
-
-	resize(flowField, flowField, Size(vf_w, vf_h), 0, 0, CV_INTER_LINEAR);
-
-
-	for (int j = 0; j < vf_h; j++) {
-		for (int i = 0; i < vf_w; i++) {
-			int index = j*vf_w + i;
-			float dx = data[index * 2 + 1];
-			float dy = data[index * 2];
-			flowField.at<Vec3f>(vf_h - j - 1, i) = Vec3f(dx, -dy, 0.0); //x,y swap??
-
-		}
-	}
-	resize(flowField, flowField, s, 0, 0, CV_INTER_LINEAR);
 }
 
-//Generate ETF of input image as flowfield
-void ETF::gen_ETF(string file, Size s) {
+/**
+ * Generate initial ETF 
+ * by taking perpendicular vectors(counter-clockwise) from gradient map
+ */
+void ETF::initial_ETF(string file, Size s) {
 	resizeMat(s);
 
 	Mat src = imread(file, 1);
@@ -70,20 +37,11 @@ void ETF::gen_ETF(string file, Size s) {
 	Mat grad_x, grad_y, abs_grad_x, abs_grad_y;
 	Sobel(src_n, grad_x, CV_32FC1, 1, 0, 5);
 	Sobel(src_n, grad_y, CV_32FC1, 0, 1, 5);
-	normalize(grad_x, abs_grad_x, 0, 1, NORM_MINMAX);
-	normalize(grad_y, abs_grad_y, 0,1,NORM_MINMAX);
-	//convertScaleAbs(grad_y, abs_grad_y);
 
 	//Compute gradient
-	Mat magn;
 	magnitude(grad_x, grad_y, gradientMag);
 	normalize(gradientMag, gradientMag, 0.0, 1.0, NORM_MINMAX);
 
-	//Show gradient
-	//imshow("Magnitude", grad_x);
-	//imshow("Magni5tude", grad_y);
-	//waitKey();
-
 	flowField = Mat::zeros(src.size(), CV_32FC3);
 	for (int i = 0; i < src.rows; i++) {
 		for (int j = 0; j < src.cols; j++) {
@@ -125,9 +83,6 @@ void ETF::computeNewVector(int x, int y, const int kernel) {
 			float w_m = computeWm(gradientMag.at<float>(y, x), gradientMag.at<float>(r, c));
 			float w_d = computeWd(t_cur_x, t_cur_y);
 			t_new += phi*t_cur_y*w_s*w_m*w_d;
-			//printf("%f, %f, %f, %f, (%f, %f)\n", phi, w_s, w_m, w_d, t_cur_y[1], t_cur_y[1]);
-
-			//if(t_new == Vec3f(0,0,0))t_new=t_cur_x;
 		}
 	}
 	refinedETF.at<Vec3f>(y, x) = normalize(t_new);
@@ -162,64 +117,6 @@ float ETF::computeWd(cv::Vec3f x, cv::Vec3f y) {
 	return abs(x.dot(y));
 }
 
-//void ETF::GVF()
-//{
-//	//Mat tmp_n = Mat::zeros(Size(256, 256), CV_32FC3);
-//
-//	////Addition_B is CV_32F ,but we need CV_32FC3 to store vec3f
-//	////create 3 same CV_32F channel and merge to create CV_32FC3 Mat
-//	//vector<Mat> channels;
-//	//Mat c = Mat::zeros(tmp_n.size(), CV_32F);
-//	//Addition_B.convertTo(c, CV_32F, 255);
-//	//channels.push_back(c);
-//	//channels.push_back(c);
-//	//channels.push_back(c);
-//	//merge(channels, tmp_n);
-//
-//	//normalize(tmp_n, tmp_n, 0.0, 1.0, NORM_MINMAX, CV_32FC3);
-//	//GaussianBlur(tmp_n, tmp_n, Size(91, 91), 0, 0);
-//
-//	///// Generate grad_x and grad_y
-//	//Mat dX, dY;
-//	//Sobel(tmp_n, dX, CV_32F, 1, 0, 3, 1, 0, 1);
-//	//Sobel(tmp_n, dY, CV_32F, 0, 1, 3, 1, 0, 1);
-//
-//	//gvf = Mat::zeros(tmp_n.size(), CV_32FC3);
-//	//for (int i = 0; i < tmp_n.rows; i++)
-//	//{
-//	//	for (int j = 0; j < tmp_n.cols; j++)
-//	//	{
-//	//		Vec3f u = dX.at<cv::Vec3f>(i, j) / 255.0; //-255~255
-//	//		Vec3f v = dY.at<cv::Vec3f>(i, j) / 255.0;
-//
-//	//		float x = u.dot(u);
-//	//		float y = v.dot(v);
-//	//		float z = v.dot(u);
-//	//		float temp = y*y - 2.0*x*y + x*x + 4.0*z*z;
-//	//		float lambda1 = 0;
-//	//		lambda1 = 0.5 * (y + x + sqrt(temp));
-//	//		gvf.at<cv::Vec3f>(i, j) = normalize(Vec3f(z,x - lambda1, 0.0));
-//
-//	//		if (gvf.at<cv::Vec3f>(i, j) == Vec3f(0.0, 0.0, 0.0))
-//	//		{
-//	//			gvf.at<cv::Vec3f>(i, j) = Vec3f(0.0, 1.0, 0.0);
-//	//		}
-//	//	}
-//	//}
-//
-//	//for (int i = 0; i < gvf.rows; i++)
-//	//{
-//	//	for (int j = 0; j < gvf.cols; j++)
-//	//	{
-//	//		Vec3f v = gvf.at<cv::Vec3f>(i, j);
-//	//		gvf.at<cv::Vec3f>(i, j) = Vec3f(-v[1], v[0], 0.0);
-//	//	}
-//	//}
-//	//resize(gvf, gvf, Mask.size(), 0, 0, CV_INTER_LINEAR);
-//	//flowField = gvf.clone();
-//
-//}
-
 void ETF::rotateFlow(Mat& src, Mat& dst, float theta) {
 	theta = theta / 180.0 * M_PI;
 
@@ -236,7 +133,6 @@ void ETF::rotateFlow(Mat& src, Mat& dst, float theta) {
 
 void ETF::resizeMat(Size s) {
 	resize(flowField, flowField, s, 0, 0, CV_INTER_LINEAR);
-	resize(GVF, GVF, s, 0, 0, CV_INTER_LINEAR);
 	resize(refinedETF, refinedETF, s, 0, 0, CV_INTER_LINEAR);
 	resize(gradientMag, gradientMag, s, 0, 0, CV_INTER_LINEAR);
 }

src/gui.cpp

@@ -164,13 +164,8 @@ MyFrame::MyFrame(const wxString& title, const wxPoint& pos, const wxSize& size)
 	leftside->Fit(drawpanel);
 	SetSizer(sizer);
 
-
-
 	this->GetSizer()->Layout();
-
-
 	render_loop_on = false;
-
 }
 void MyFrame::OnExit(wxCommandEvent& event) {
 	Close(true);

src/main.cpp

@@ -6,7 +6,6 @@ BEGIN_EVENT_TABLE(BasicDrawPane, wxPanel)
 END_EVENT_TABLE()
 
 
-
 wxBEGIN_EVENT_TABLE(MyFrame, wxFrame)
 	// Menu - File
     EVT_MENU(ID_ONOPENSRC, MyFrame::OnOpenSrc)

src/postProcessing.cpp

@@ -5,6 +5,7 @@ using namespace cv;
 
 PP::PP(Size s) {}
 
+// visualize the ETF
 void PP::ETF(Mat &flowfield, Mat &dis) {
 	const float M_PI = 3.14159265358979323846;
 	Mat noise = Mat::zeros(cv::Size(flowfield.cols / 2, flowfield.rows / 2), CV_32F);
@@ -51,6 +52,7 @@ void PP::ETF(Mat &flowfield, Mat &dis) {
 	}
 }
 
+// visualize ETF by drawing red arrowline
 void PP::FlowField(cv::Mat & flowfield, cv::Mat & dis) {
 	const int resolution = 10;