C++-OpenCV(1)-连通区域

两个点：找到组件+标记它
找到它：int nComponents = connectedComponents(imThresh, imLabels);
标记转换：imLabels.convertTo(imLabels, CV_8U);
                  Mat imColorMap;
                 applyColorMap(imLabels, imColorMap, COLORMAP_JET);
上代码

// Read image as grayscale
	Mat img = imread("D:/OpenCVPrj/WangYi/MOpenCV_class4/images/truth.png", IMREAD_GRAYSCALE);

	//1.Threshold Image 阈值化
	Mat imThresh;
	threshold(img, imThresh, 127, 255, THRESH_BINARY);
	imshow("image", imThresh);

	//2.找到连通的组件 标记它
	Mat imLabels;
	//显示连通组件的个数
	int nComponents = connectedComponents(imThresh, imLabels);
	Mat imLabelsCopy = imLabels.clone();
	Point minLoc, maxLoc;
	double min, max;

	//3.得到原始标签
    //4.转换标签为CV_8U
	//5.可视化->变成彩色的
	minMaxLoc(imLabels, &min, &max, &minLoc, &maxLoc);
	// Normalize the image so the min value is 0 and max value is 255.
	//标签转换 标签越大，灰度级别越高
	imLabels = 255 * (imLabels - min) / (max - min);

	//标签转换为 8位
	imLabels.convertTo(imLabels, CV_8U);
	imshow("image", imLabels);
	imLabels = imLabelsCopy.clone();

	for (int i = 0; i < 6; i++) {
		imshow("image", imLabels == i);
		waitKey(0);
	}

	// Make a copy of the image
	imLabels = imLabelsCopy.clone();

	// First let's find the min and max values in imLabels
	// The following line finds the min and max pixel values
	// and their locations in an image.
	double minValue, maxValue;
	minMaxLoc(imLabels, &minValue, &maxValue, &minLoc, &maxLoc);

	// Normalize the image so the min value is 0 and max value is 255.
	imLabels = 255 * (imLabels - minValue) / (maxValue - minValue);

	// Convert image to 8-bits
	imLabels.convertTo(imLabels, CV_8U);

	// Apply a color map
	Mat imColorMap;
	applyColorMap(imLabels, imColorMap, COLORMAP_JET);

	// Display colormapped labels
	imshow("image", imColorMap);
	waitKey(0);
	destroyAllWindows();