segmentation / netmets

  #include <stdlib.h>
  #include <string>
  #include <fstream>
  #include <algorithm>
  
  //OpenGL includes
  #include <GL/glut.h>
  #include <GL/freeglut.h>
  
  //STIM includes
  #include <stim/visualization/gl_network.h>
  #include <stim/biomodels/network.h>
  #include <stim/visualization/gl_aaboundingbox.h>
  #include <stim/parser/arguments.h>
  #include <stim/visualization/camera.h>
  
  #ifdef __CUDACC__
  //CUDA includes
  #include <cuda.h>
  #endif
  
  //ANN includes
  //#include <ANN/ANN.h>
  
  //BOOST includes
  #include <boost/tuple/tuple.hpp>
  
  //visualization objects
  stim::gl_aaboundingbox<float> bb;			//axis-aligned bounding box object
  stim::camera cam;					//camera object
  
  unsigned num_nets = 0;
  stim::gl_network<float> GT;			//ground truth network
  stim::gl_network<float> T;			//test network
  
  //hard-coded parameters
  float resample_rate = 0.5f;			//sample rate for the network (fraction of sigma used as the maximum sample rate)
  float camera_factor = 1.2f;			//start point of the camera as a function of X and Y size
  float orbit_factor = 0.01f;			//degrees per pixel used to orbit the camera
  
  //mouse position tracking
  int mouse_x;
  int mouse_y;
  
  //OpenGL objects
  GLuint cmap_tex = 0;				//texture name for the color map
  
  //sets an OpenGL viewport taking up the entire window
  void glut_render_single_projection(){
  
  	glMatrixMode(GL_PROJECTION);					//load the projection matrix for editing
  	glLoadIdentity();								//start with the identity matrix
  	int X = glutGet(GLUT_WINDOW_WIDTH);				//use the whole screen for rendering
  	int Y = glutGet(GLUT_WINDOW_HEIGHT);
  	glViewport(0, 0, X, Y);							//specify a viewport for the entire window
  	float aspect = (float)X / (float)Y;				//calculate the aspect ratio
  	gluPerspective(60, aspect, 0.1, 1000000);		//set up a perspective projection
  }
  
  //sets an OpenGL viewport taking up the left half of the window
  void glut_render_left_projection(){
  
  	glMatrixMode(GL_PROJECTION);					//load the projection matrix for editing
  	glLoadIdentity();								//start with the identity matrix
  	int X = glutGet(GLUT_WINDOW_WIDTH) / 2;			//only use half of the screen for the viewport
  	int Y = glutGet(GLUT_WINDOW_HEIGHT);
  	glViewport(0, 0, X, Y);							//specify the viewport on the left
  	float aspect = (float)X / (float)Y;				//calculate the aspect ratio
  	gluPerspective(60, aspect, 0.1, 1000000);		//set up a perspective projection
  }
  
  //sets an OpenGL viewport taking up the right half of the window
  void glut_render_right_projection(){
  
  	glMatrixMode(GL_PROJECTION);					//load the projection matrix for editing
  	glLoadIdentity();								//start with the identity matrix
  	int X = glutGet(GLUT_WINDOW_WIDTH) / 2;			//only use half of the screen for the viewport
  	int Y = glutGet(GLUT_WINDOW_HEIGHT);
  	glViewport(X, 0, X, Y);							//specify the viewport on the right
  	float aspect = (float)X / (float)Y;				//calculate the aspect ratio
  	gluPerspective(60, aspect, 0.1, 1000000);		//set up a perspective projection
  }
  
  void glut_render_modelview(){
  
  	glMatrixMode(GL_MODELVIEW);						//load the modelview matrix for editing
  	glLoadIdentity();								//start with the identity matrix
  	stim::vec3<float> eye = cam.getPosition();		//get the camera position (eye point)
  	stim::vec3<float> focus = cam.getLookAt();		//get the camera focal point
  	stim::vec3<float> up = cam.getUp();				//get the camera "up" orientation
  
  	gluLookAt(eye[0], eye[1], eye[2], focus[0], focus[1], focus[2], up[0], up[1], up[2]);	//set up the OpenGL camera
  }
  
  //draws the network(s)
  void glut_render(void) {
  
  	if(num_nets == 1){											//if a single network is loaded
  		glut_render_single_projection();						//fill the entire viewport
  		glut_render_modelview();								//set up the modelview matrix with camera details
  		glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT);		//clear the screen
  		GT.glCenterline(GT.nmags() - 1);						//render the GT network (the only one loaded)
  	}
  
  	if(num_nets == 2){											//if two networks are loaded	
  
  		glut_render_left_projection();							//set up a projection for the left half of the window
  		glut_render_modelview();								//set up the modelview matrix using camera details
  		glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT);		//clear the screen
  
  		glEnable(GL_TEXTURE_1D);										//enable texture mapping
  		glTexEnvf(GL_TEXTURE_ENV, GL_TEXTURE_ENV_MODE, GL_REPLACE);		//texture map will be used as the network color
  		glBindTexture(GL_TEXTURE_1D, cmap_tex);							//bind the Brewer texture map
  
  		GT.glCenterline(GT.nmags() - 1);						//render the GT network
  
  		glut_render_right_projection();							//set up a projection for the right half of the window
  		glut_render_modelview();								//set up the modelview matrix using camera details
  		T.glCenterline(T.nmags() - 1);							//render the T network
  
  	}
  
  	glutSwapBuffers();
  }
  
  // defines camera motion based on mouse dragging
  void glut_motion(int x, int y){
  	
  
  	float theta = orbit_factor * (mouse_x - x);		//determine the number of degrees along the x-axis to rotate
  	float phi = orbit_factor * (y - mouse_y);		//number of degrees along the y-axis to rotate
  
  	cam.OrbitFocus(theta, phi);						//rotate the camera around the focal point
  
  	mouse_x = x;									//update the mouse position
  	mouse_y = y;
  		
  	glutPostRedisplay();							//re-draw the visualization
  }
  
  // sets the mouse position when clicked
  void glut_mouse(int button, int state, int x, int y){
  	mouse_x = x;
  	mouse_y = y;
  }
  
  #define BREWER_CTRL_PTS 11							//number of control points in the Brewer map
  void texture_initialize(){
  
  	//define the colormap
  	static float  brewer_map[BREWER_CTRL_PTS][3] = {			//generate a Brewer color map (blue to red)
  		{0.192157f, 0.211765f, 0.584314f},
  		{0.270588f, 0.458824f, 0.705882f},
  		{0.454902f, 0.678431f, 0.819608f},
  		{0.670588f, 0.85098f, 0.913725f},
  		{0.878431f, 0.952941f, 0.972549f},
  		{1.0f, 1.0f, 0.74902f},
  		{0.996078f, 0.878431f, 0.564706f},
  		{0.992157f, 0.682353f, 0.380392f},
  		{0.956863f, 0.427451f, 0.262745f},
  		{0.843137f, 0.188235f, 0.152941f},
  		{0.647059f, 0.0f, 0.14902f}
  	};
  
  	glGenTextures(1, &cmap_tex);								//generate a texture map name
  	glBindTexture(GL_TEXTURE_1D, cmap_tex);						//bind the texture map
  
  	glTexParameteri(GL_TEXTURE_1D, GL_TEXTURE_MAG_FILTER, GL_LINEAR);		//enable linear interpolation
  	glTexParameteri(GL_TEXTURE_1D, GL_TEXTURE_MIN_FILTER, GL_LINEAR);
  	glTexParameteri(GL_TEXTURE_1D, GL_TEXTURE_WRAP_S, GL_CLAMP);			//clamp the values at the minimum and maximum
  	glTexImage1D(GL_TEXTURE_1D, 0, 3, BREWER_CTRL_PTS, 0, GL_RGB, GL_FLOAT,	//upload the texture map to the GPU
  					brewer_map);
  }
  
  //Initialize the OpenGL (GLUT) window, including starting resolution, callbacks, texture maps, and camera
  void glut_initialize(){
  	
  	int myargc = 1;					//GLUT requires arguments, so create some bogus ones
  	char* myargv[1];
  	myargv [0]=strdup ("netmets");
  
  	glutInit(&myargc, myargv);									//pass bogus arguments to glutInit()
  	glutInitDisplayMode(GLUT_DEPTH | GLUT_DOUBLE | GLUT_RGBA);	//generate a color buffer, depth buffer, and enable double buffering
  	glutInitWindowPosition(100,100);							//set the initial window position
  	glutInitWindowSize(320,320);								//set the initial window size
  	glutCreateWindow("NetMets - STIM Lab, UH");					//set the dialog box title
  
  	
  	// register callback functions
  	glutDisplayFunc(glut_render);			//function executed for rendering - renders networks
  	glutMouseFunc(glut_mouse);				//executed on a mouse click - sets starting mouse positions for rotations
  	glutMotionFunc(glut_motion);			//executed when the mouse is moved while a button is pressed
  
  	texture_initialize();					//set up texture mapping (create texture maps, enable features)
  
  	stim::vec3<float> c = bb.center();		//get the center of the network bounding box
  
  	//place the camera along the z-axis at a distance determined by the network size along x and y
  	cam.setPosition(c + stim::vec<float>(0, 0, camera_factor * std::max(bb.size()[0], bb.size()[1])));
  	cam.LookAt(c[0], c[1], c[2]);						//look at the center of the network
  
  	glClearColor(1, 1, 1, 1);
  }
  
  #ifdef __CUDACC__
  void setdevice(int &device){
  	int count;
  	cudaGetDeviceCount(&count);				// numbers of device that are available
  	if(count < device + 1){
  	std::cout<<"No such device available, please set another device"<<std::endl;
  	exit(1);
  	}
  }
  #else
  void setdevice(int &device){
  	device = -1;
  }
  #endif
  
  //compare both networks and fill the networks with error information
  void compare(float sigma, int device){
  
  	GT = GT.compare(T, sigma, device);						//compare the ground truth to the test case - store errors in GT
      T = T.compare(GT, sigma, device);						//compare the test case to the ground truth - store errors in T
  
  	//calculate the metrics
  	float FPR = GT.average(0);						//calculate the metrics
  	float FNR = T.average(0);
  	
  	std::cout << "FNR: " << FPR << std::endl;		//print false alarms and misses
  	std::cout << "FPR: " << FNR << std::endl;
  }
  
  // writes features of the networks i.e average segment length, tortuosity, branching index, contraction, fractal dimension, number of end and branch points to a csv file
  // Pranathi wrote this - saves network features to a CSV file
  void features(std::string filename){
  		double avgL_t, avgL_gt, avgT_t, avgT_gt, avgB_t, avgB_gt, avgC_t, avgC_gt, avgFD_t, avgFD_gt;
  		unsigned int e_t, e_gt, b_gt, b_t;
  		avgL_gt = GT.Lengths();
  		avgT_gt = GT.Tortuosities();
  		avgL_t = T.Lengths();
  		avgT_t = T.Tortuosities();
  		avgB_gt = GT.BranchingIndex();
  		avgB_t = T.BranchingIndex();
  		avgC_gt = GT.Contractions();
  		avgFD_gt = GT.FractalDimensions();
  		avgC_t = T.Contractions();
  		avgFD_t = T.FractalDimensions();
  		e_gt = GT.EndP();
  		e_t = T.EndP();
  		b_gt = GT.BranchP();
  		b_t = T.BranchP();
  		std::ofstream myfile;
  		myfile.open (filename.c_str());
  		myfile << "Length, Tortuosity, Contraction, Fractal Dimension, Branch Points, End points, Branching Index, \n";
  		myfile << avgL_gt << "," << avgT_gt << "," << avgC_gt << "," << avgFD_gt << "," << b_gt << "," << e_gt << "," << avgB_gt <<std::endl;
  		myfile << avgL_t << "," << avgT_t << "," << avgC_t << "," << avgFD_t << "," << b_t << "," << e_t << "," << avgB_t <<std::endl;
  		myfile.close();
  }
  
  // Output an advertisement for the lab, authors, and usage information
  void advertise(){
  	std::cout<<std::endl<<std::endl;
  	std::cout<<"========================================================================="<<std::endl;
  	std::cout<<"Thank you for using the NetMets network comparison tool!"<<std::endl;
  	std::cout<<"Scalable Tissue Imaging and Modeling (STIM) Lab, University of Houston"<<std::endl;
  	std::cout<<"Developers: Pranathi Vemuri, David Mayerich"<<std::endl;
  	std::cout<<"Source: https://git.stim.ee.uh.edu/segmentation/netmets"<<std::endl;
  	std::cout<<"========================================================================="<<std::endl<<std::endl;
  
  	std::cout<<"usage: netmets file1 file2 --sigma 3"<<std::endl;
  	std::cout<<"            compare two files with a tolerance of 3 (units defined by the network)"<<std::endl<<std::endl;
  	std::cout<<"       netmets file1 --gui"<<std::endl;
  	std::cout<<"            load a file and display it using OpenGL"<<std::endl<<std::endl;
  	std::cout<<"       netmets file1 file2 --device 0"<<std::endl;
  	std::cout<<"            compare two files using device 0 (if there isn't a gpu, use cpu)"<<std::endl<<std::endl;
  }
  
  int main(int argc, char* argv[])
  {
  	stim::arglist args;						//create an instance of arglist
  
  	//add arguments
  	args.add("help", "prints this help");
  	args.add("sigma", "force a sigma value to specify the tolerance of the network comparison", "3");
  	args.add("gui", "display the network or network comparison using OpenGL");
  	args.add("device", "choose specific device to run", "0");
  	args.add("features", "save features to a CSV file, specify file name");
  
  	args.parse(argc, argv);					//parse the user arguments
  
  	if(args["help"].is_set() || args.nargs() == 0){			//test for help
  		advertise();										//output the advertisement
  		std::cout<<args.str();								//output arguments
  		exit(1);											//exit
  	}
  	
  	if(args.nargs() >= 1){					//if at least one network file is specified
  		num_nets = 1;						//set the number of networks to one
  		GT.load_obj(args.arg(0));			//load the specified file as the ground truth
  		/*GT.to_txt("Graph.txt");*/
  	}
  	
  	if(args.nargs() == 2){			//if two files are specified, they will be displayed in neighboring viewports and compared
  		int device = args["device"].as_int();				//get the device value from the user
  		num_nets = 2;										//set the number of networks to two
  		float sigma = args["sigma"].as_float();				//get the sigma value from the user
  		T.load_obj(args.arg(1));                           //load the second (test) network
  		if(args["features"].is_set())						//if the user wants to save features
  			features(args["features"].as_string());
  		GT = GT.resample(resample_rate * sigma);			//resample both networks based on the sigma value
  		T = T.resample(resample_rate * sigma);
  		setdevice(device);
  		compare(sigma, device);										//run the comparison algorithm
  	}
  
  	//if a GUI is requested, display the network using OpenGL
  	if(args["gui"].is_set()){		
  		bb = GT.boundingbox();					//generate a bounding volume		
  		glut_initialize();						//create the GLUT window and set callback functions		
  		glutMainLoop();							// enter GLUT event processing cycle
  	}	
  }