Realidade Virtual

main.cpp

/****************************************************
OpenCV Base
Voxar Labs
Informatics Center - CIn
Federal University of Pernambuco - UFPE
http://www.cin.ufpe.br/voxarlabs

@author Rafael Roberto ([email protected])
*****************************************************/

// Basic C++ includes
#include <math.h>
#include <vector>
#include <stdio.h>
#include <fstream>
#include <iostream>
#include <string.h>
#include <windows.h>

// Project includes
#include "util\Win32Timer.h"

// OpenCV includes
#include "opencv2\core\core.hpp"
#include "opencv2\imgproc\imgproc.hpp"
#include "opencv2\highgui\highgui.hpp"


// Declare the namespaces used
using namespace std;
using namespace cv;

int main(int argc, char** argv)
{
	// Initialize the timers
	Win32Timer timer = *( new Win32Timer() );

	// Start the timer
	timer.reset();

	// Utilização básica da câmera
	//VideoCapture capture(0);
	//if(!capture.isOpened()) {
	//	cout << "Erro ao abrir camera" << endl;
	//	return -1;
	//}
	//capture.set(CV_CAP_PROP_FRAME_WIDTH, 800);
	//double width = capture.get(CV_CAP_PROP_FRAME_WIDTH);
	//Mat image;
	//capture >> image;

	// Abre imagem do disco
	string path = "../resource/image.jpg";
	Mat image_load = imread(path);
	if(!image_load.data) {
		cout << "Erro ao ler a imagem" << path << endl;
		exit(-1);
	}

	// Transforma imagem para tom de cinza
	Size image_size = image_load.size();
	Mat gray_image(image_size, CV_8U);
	cvtColor(image_load, gray_image, CV_RGB2GRAY);

	// Transforma imagem para tons de cinza (usando apenas canal Red)
	Mat red_image(image_size, CV_8U);
	for(int x = 0; x < image_size.width; x++) {
		for(int y = 0; y < image_size.height; y++) {
			red_image.at<byte>(y, x) = image_load.at<Vec3b>(y, x)[0];
		}
	}
	
	// Transforma imagem para versão binária
	Mat bin_image(image_size, CV_8U);
	threshold(gray_image, bin_image, 128, 255, CV_THRESH_BINARY);

	// Extrai arestas com Sobel
	Mat sobel_edge_image(image_size, CV_8U);
	Sobel(bin_image, sobel_edge_image, CV_8U, 1, 1);

	// Extrai arestas com Canny
	Mat canny_edge_image(image_size, CV_8U);
	Canny(bin_image, canny_edge_image, 500, 200);

	// Encontra contornos
	vector< vector<Point> > contours;
	findContours(canny_edge_image, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));

	// Pinta contornos numa imagem
	Mat final_image = image_load.clone();
	Scalar color = Scalar(0, 0, 255);
	for(int i = 0; i < 484; i++) {
		drawContours(final_image, contours, i, color, 2);
	}

	// Exibe imagens
	//imshow("First OpenCV img", image_load);
	//imshow("Gray img OpenCV conversion", gray_image);
	//imshow("Gray img OpenCV conversion Red channel only", red_image);
	//imshow("Binary img OpenCV conversion", bin_image);
	//imshow("Edge img OpenCV Sobel strategy", sobel_edge_image);
	//imshow("Edge img OpenCV Canny strategy", canny_edge_image);
	imshow("Contous colored img OpenCV", final_image);
	waitKey();

	// Print the experience time
	cout << "Mean execution time: " << timer.getMilliseconds() << " ms." << endl;
	cout << "Mean execution FPS: " << ( 1000.0 / timer.getMilliseconds() ) << endl;

	return 0;
}