opencv 例子 opencv简单例子

<二>经典例子

这一次这几个例子要我自己一下子写出来应该是不可能的，先主要感受以下OpenCV的一些有趣的功能吧。（溜走

（1）彩色目标跟踪：Camshift

①Cameshift算法：根据鼠标框区域的色度光谱来进行摄像头读入的视频目标追踪。
②代码和示例往往能够更生动形象的进行理解
注：代码来源于OpenCV官方例程，每个用户的下载里面都有，这里的代码文件名为：camshiftdemo.cpp。

#include <opencv2/core/utility.hpp>
#include "opencv2/video/tracking.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"

#include <iostream>
#include <ctype.h>

using namespace cv;
using namespace std;

Mat image;

bool backprojMode = false;
bool selectObject = false;
int trackObject = 0;
bool showHist = true;
Point origin;
Rect selection;
int vmin = 10, vmax = 256, smin = 30;

// User draws box around object to track. This triggers CAMShift to start tracking
static void onMouse(int event, int x, int y, int, void*)
{
	if (selectObject)
	{
		selection.x = MIN(x, origin.x);
		selection.y = MIN(y, origin.y);
		selection.width = std::abs(x - origin.x);
		selection.height = std::abs(y - origin.y);

		selection &= Rect(0, 0, image.cols, image.rows);
	}

	switch (event)
	{
	case EVENT_LBUTTONDOWN:
		origin = Point(x, y);
		selection = Rect(x, y, 0, 0);
		selectObject = true;
		break;
	case EVENT_LBUTTONUP:
		selectObject = false;
		if (selection.width > 0 && selection.height > 0)
			trackObject = -1;   // Set up CAMShift properties in main() loop
		break;
	}
}

string hot_keys =
"\n\nHot keys: \n"
"\tESC - quit the program\n"
"\tc - stop the tracking\n"
"\tb - switch to/from backprojection view\n"
"\th - show/hide object histogram\n"
"\tp - pause video\n"
"To initialize tracking, select the object with mouse\n";

static void help()
{
	cout << "\nThis is a demo that shows mean-shift based tracking\n"
		"You select a color objects such as your face and it tracks it.\n"
		"This reads from video camera (0 by default, or the camera number the user enters\n"
		"Usage: \n"
		"   ./camshiftdemo [camera number]\n";
	cout << hot_keys;
}

const char* keys =
{
	"{help h | | show help message}{@camera_number| 0 | camera number}"
};

int main(int argc, const char** argv)
{
	VideoCapture cap;
	Rect trackWindow;
	int hsize = 16;
	float hranges[] = { 0,180 };
	const float* phranges = hranges;
	CommandLineParser parser(argc, argv, keys);
	if (parser.has("help"))
	{
		help();
		return 0;
	}
	int camNum = parser.get<int>(0);
	cap.open(camNum);

	if (!cap.isOpened())
	{
		help();
		cout << "***Could not initialize capturing...***\n";
		cout << "Current parameter's value: \n";
		parser.printMessage();
		return -1;
	}
	cout << hot_keys;
	namedWindow("Histogram", 0);
	namedWindow("CamShift Demo", 0);
	setMouseCallback("CamShift Demo", onMouse, 0);
	createTrackbar("Vmin", "CamShift Demo", &vmin, 256, 0);
	createTrackbar("Vmax", "CamShift Demo", &vmax, 256, 0);
	createTrackbar("Smin", "CamShift Demo", &smin, 256, 0);

	Mat frame, hsv, hue, mask, hist, histimg = Mat::zeros(200, 320, CV_8UC3), backproj;
	bool paused = false;

	for (;;)
	{
		if (!paused)
		{
			cap >> frame;
			if (frame.empty())
				break;
		}

		frame.copyTo(image);

		if (!paused)
		{
			cvtColor(image, hsv, COLOR_BGR2HSV);

			if (trackObject)
			{
				int _vmin = vmin, _vmax = vmax;

				inRange(hsv, Scalar(0, smin, MIN(_vmin, _vmax)),
					Scalar(180, 256, MAX(_vmin, _vmax)), mask);
				int ch[] = { 0, 0 };
				hue.create(hsv.size(), hsv.depth());
				mixChannels(&hsv, 1, &hue, 1, ch, 1);

				if (trackObject < 0)
				{
					// Object has been selected by user, set up CAMShift search properties once
					Mat roi(hue, selection), maskroi(mask, selection);
					calcHist(&roi, 1, 0, maskroi, hist, 1, &hsize, &phranges);
					normalize(hist, hist, 0, 255, NORM_MINMAX);

					trackWindow = selection;
					trackObject = 1; // Don't set up again, unless user selects new ROI

					histimg = Scalar::all(0);
					int binW = histimg.cols / hsize;
					Mat buf(1, hsize, CV_8UC3);
					for (int i = 0; i < hsize; i++)
						buf.at<Vec3b>(i) = Vec3b(saturate_cast<uchar>(i*180. / hsize), 255, 255);
					cvtColor(buf, buf, COLOR_HSV2BGR);

					for (int i = 0; i < hsize; i++)
					{
						int val = saturate_cast<int>(hist.at<float>(i)*histimg.rows / 255);
						rectangle(histimg, Point(i*binW, histimg.rows),
							Point((i + 1)*binW, histimg.rows - val),
							Scalar(buf.at<Vec3b>(i)), -1, 8);
					}
				}

				// Perform CAMShift
				calcBackProject(&hue, 1, 0, hist, backproj, &phranges);
				backproj &= mask;
				RotatedRect trackBox = CamShift(backproj, trackWindow,
					TermCriteria(TermCriteria::EPS | TermCriteria::COUNT, 10, 1));
				if (trackWindow.area() <= 1)
				{
					int cols = backproj.cols, rows = backproj.rows, r = (MIN(cols, rows) + 5) / 6;
					trackWindow = Rect(trackWindow.x - r, trackWindow.y - r,
						trackWindow.x + r, trackWindow.y + r) &
						Rect(0, 0, cols, rows);
				}

				if (backprojMode)
					cvtColor(backproj, image, COLOR_GRAY2BGR);
				ellipse(image, trackBox, Scalar(0, 0, 255), 3, LINE_AA);
			}
		}
		else if (trackObject < 0)
			paused = false;

		if (selectObject && selection.width > 0 && selection.height > 0)
		{
			Mat roi(image, selection);
			bitwise_not(roi, roi);
		}

		imshow("CamShift Demo", image);
		imshow("Histogram", histimg);

		char c = (char)waitKey(10);
		if (c == 27)
			break;
		switch (c)
		{
		case 'b':
			backprojMode = !backprojMode;
			break;
		case 'c':
			trackObject = 0;
			histimg = Scalar::all(0);
			break;
		case 'h':
			showHist = !showHist;
			if (!showHist)
				destroyWindow("Histogram");
			else
				namedWindow("Histogram", 1);
			break;
		case 'p':
			paused = !paused;
			break;
		default:
			;
		}
	}

	return 0;
}

③结论
1.通过我的实践，粗略的了解了Camshift算法的实现功能：用鼠标圈出一个图像，然后会把整个摄像头捕捉到的界面里所有相同颜色的图形圈出来，同时我发现每次界面只有一个圈，如果人为圈的内容有多种颜色，那么会使范围变大很多，色柱也会更多。
2.对于生成的框里面有三个参数的含义的理解：嘤嘤嘤？？？我还没理解欸（逃
3.这个博客比较适合理解Camshift算法，之后有空可以看看（如有侵权冒犯，请告知，纯学习使用）

（2）光流

①含义：当物体运动时，图像上对应的亮点也在运动，检测图像亮度模式这种表观运动就是光流，它包含了物体的图像运动变化信息。
②代码和图像示例

#include <iostream>  
#include <opencv2/opencv.hpp>
#include <opencv2/core/core.hpp>  
#include <opencv2/highgui/highgui.hpp> 
#include <opencv2/imgproc/imgproc.hpp>  // Gaussian Blur
#include <opencv2/ml/ml.hpp>
using namespace cv;
using namespace std;
void duan_OpticalFlow(Mat &frame, Mat & result);
bool addNewPoints();
bool acceptTrackedPoint(int i);
Mat curgray;    // 当前图片
Mat pregray;    // 预测图片
vector<Point2f> point[2];   // point0为特征点的原来位置，point1为特征点的新位置
vector<Point2f> initPoint;  // 初始化跟踪点的位置
vector<Point2f> features;   // 检测的特征
int maxCount = 500;         // 检测的最大特征数
double qLevel = 0.01;   // 特征检测的等级
double minDist = 10.0;  // 两特征点之间的最小距离
vector<uchar> status;   // 跟踪特征的状态，特征的流发现为1，否则为0
vector<float> err;
int main()
{
	Mat matSrc;
	Mat matRst;
	VideoCapture cap(0);
	//int totalFrameNumber = cap.get(CV_CAP_PROP_FRAME_COUNT);
	// perform the tracking process
	printf("Start the tracking process, press ESC to quit.\n");
	while (cap.isOpened())
	 {
		// get frame from the video
		cap >> matSrc;
		if (!matSrc.empty())
		{
			duan_OpticalFlow(matSrc, matRst);
		}
		else
		{
			cout << "Error : Get picture is empty!" << endl;
		}
		if (waitKey(1) == 27) break;
	}
	waitKey(0);
	return 0;
}
void duan_OpticalFlow(Mat &frame, Mat & result)
{
	cvtColor(frame, curgray, CV_BGR2GRAY);
	frame.copyTo(result);
	if (addNewPoints())
	{
		goodFeaturesToTrack(curgray, features, maxCount, qLevel, minDist);
		point[0].insert(point[0].end(), features.begin(), features.end());
		initPoint.insert(initPoint.end(), features.begin(), features.end());
	}
	if (pregray.empty())
	{
		curgray.copyTo(pregray);
	}
	calcOpticalFlowPyrLK(pregray, curgray, point[0], point[1], status, err);
	int k = 0;
	for (size_t i = 0; i < point[1].size(); i++)
	{
		if (acceptTrackedPoint(i))
		{
			initPoint[k] = initPoint[i];
			point[1][k++] = point[1][i];
		}
	}
	point[1].resize(k);
	initPoint.resize(k);
	for (size_t i = 0; i < point[1].size(); i++)
	{
		line(result, initPoint[i], point[1][i], Scalar(0, 0, 255));
		circle(result, point[1][i], 3, Scalar(0, 255, 0), -1);
	}
	swap(point[1], point[0]);
	swap(pregray, curgray);
	imshow("Optical Flow Demo", result);
	//waitKey(50);
}
bool addNewPoints()
{
	return point[0].size() <= 10;
}
bool acceptTrackedPoint(int i)
{
	return status[i] && ((abs(point[0][i].x - point[1][i].x) + abs(point[0][i].y - point[1][i].y)) > 2);//检测是否为移动点
}

③calcOpticalFlowPyrLK()函数：跟光流金字塔有关，喵喵喵？？？之后了解以下。

（3）点追踪

①含义：用鼠标点下要追踪的点，然后随着这个点所在物体的移动可以检测到点的移动。
②代码和示例

#include "opencv2/video/tracking.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"

#include <iostream>
#include <ctype.h>

using namespace cv;
using namespace std;

static void help()
{
	// print a welcome message, and the OpenCV version
	cout << "\nThis is a demo of Lukas-Kanade optical flow lkdemo(),\n"
		"Using OpenCV version " << CV_VERSION << endl;
	cout << "\nIt uses camera by default, but you can provide a path to video as an argument.\n";
	cout << "\nHot keys: \n"
		"\tESC - quit the program\n"
		"\tr - auto-initialize tracking\n"
		"\tc - delete all the points\n"
		"\tn - switch the \"night\" mode on/off\n"
		"To add/remove a feature point click it\n" << endl;
}

Point2f point;
bool addRemovePt = false;

static void onMouse(int event, int x, int y, int /*flags*/, void* /*param*/)
{
	if (event == EVENT_LBUTTONDOWN)
	{
		point = Point2f((float)x, (float)y);
		addRemovePt = true;
	}
}

int main(int argc, char** argv)
{
	VideoCapture cap;
	TermCriteria termcrit(TermCriteria::COUNT | TermCriteria::EPS, 20, 0.03);
	Size subPixWinSize(10, 10), winSize(31, 31);

	const int MAX_COUNT = 500;
	bool needToInit = false;
	bool nightMode = false;

	help();
	cv::CommandLineParser parser(argc, argv, "{@input|0|}");
	string input = parser.get<string>("@input");

	if (input.size() == 1 && isdigit(input[0]))
		cap.open(input[0] - '0');
	else
		cap.open(input);

	if (!cap.isOpened())
	{
		cout << "Could not initialize capturing...\n";
		return 0;
	}

	namedWindow("LK Demo", 1);
	setMouseCallback("LK Demo", onMouse, 0);

	Mat gray, prevGray, image, frame;
	vector<Point2f> points[2];

	for (;;)
	{
		cap >> frame;
		if (frame.empty())
			break;

		frame.copyTo(image);
		cvtColor(image, gray, COLOR_BGR2GRAY);

		if (nightMode)
			image = Scalar::all(0);

		if (needToInit)
		{
			// automatic initialization
			goodFeaturesToTrack(gray, points[1], MAX_COUNT, 0.01, 10, Mat(), 3, 3, 0, 0.04);
			cornerSubPix(gray, points[1], subPixWinSize, Size(-1, -1), termcrit);
			addRemovePt = false;
		}
		else if (!points[0].empty())
		{
			vector<uchar> status;
			vector<float> err;
			if (prevGray.empty())
				gray.copyTo(prevGray);
			calcOpticalFlowPyrLK(prevGray, gray, points[0], points[1], status, err, winSize,
				3, termcrit, 0, 0.001);
			size_t i, k;
			for (i = k = 0; i < points[1].size(); i++)
			{
				if (addRemovePt)
				{
					if (norm(point - points[1][i]) <= 5)
					{
						addRemovePt = false;
						continue;
					}
				}

				if (!status[i])
					continue;

				points[1][k++] = points[1][i];
				circle(image, points[1][i], 3, Scalar(0, 255, 0), -1, 8);
			}
			points[1].resize(k);
		}

		if (addRemovePt && points[1].size() < (size_t)MAX_COUNT)
		{
			vector<Point2f> tmp;
			tmp.push_back(point);
			cornerSubPix(gray, tmp, winSize, Size(-1, -1), termcrit);
			points[1].push_back(tmp[0]);
			addRemovePt = false;
		}

		needToInit = false;
		imshow("LK Demo", image);

		char c = (char)waitKey(10);
		if (c == 27)
			break;
		switch (c)
		{
		case 'r':
			needToInit = true;
			break;
		case 'c':
			points[0].clear();
			points[1].clear();
			break;
		case 'n':
			nightMode = !nightMode;
			break;
		}

		std::swap(points[1], points[0]);
		cv::swap(prevGray, gray);
	}

	return 0;
}

（4）人脸识别

①含义：识别人脸。
②代码和示例
代码是自带的，但是由于我还缺少PDB文件配置，所以没能在今天实现人脸检测，这里其实仅仅只能实现人脸检测，示例择日再传好了（?

#include "opencv2/objdetect.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"

#include <stdio.h>

using namespace std;
using namespace cv;

/** Function Headers */
void detectAndDisplay( Mat frame );

/** Global variables */
String face_cascade_name, eyes_cascade_name;
CascadeClassifier face_cascade;
CascadeClassifier eyes_cascade;
String window_name = "Capture - Face detection";

/** @function main */
int main( int argc, const char** argv )
{
    CommandLineParser parser(argc, argv,
        "{help h||}"
        "{face_cascade|../../data/haarcascades/haarcascade_frontalface_alt.xml|}"
        "{eyes_cascade|../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml|}");

    parser.about( "\nThis program demonstrates using the cv::CascadeClassifier class to detect objects (Face + eyes) in a video stream.\n"
                  "You can use Haar or LBP features.\n\n" );
    parser.printMessage();

    face_cascade_name = parser.get<String>("face_cascade");
    eyes_cascade_name = parser.get<String>("eyes_cascade");
    VideoCapture capture;
    Mat frame;

    //-- 1. Load the cascades
    if( !face_cascade.load( face_cascade_name ) ){ printf("--(!)Error loading face cascade\n"); return -1; };
    if( !eyes_cascade.load( eyes_cascade_name ) ){ printf("--(!)Error loading eyes cascade\n"); return -1; };

    //-- 2. Read the video stream
    capture.open( 0 );
    if ( ! capture.isOpened() ) { printf("--(!)Error opening video capture\n"); return -1; }

    while ( capture.read(frame) )
    {
        if( frame.empty() )
        {
            printf(" --(!) No captured frame -- Break!");
            break;
        }

        //-- 3. Apply the classifier to the frame
        detectAndDisplay( frame );

        if( waitKey(10) == 27 ) { break; } // escape
    }
    return 0;
}

/** @function detectAndDisplay */
void detectAndDisplay( Mat frame )
{
    std::vector<Rect> faces;
    Mat frame_gray;

    cvtColor( frame, frame_gray, COLOR_BGR2GRAY );
    equalizeHist( frame_gray, frame_gray );

    //-- Detect faces
    face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CASCADE_SCALE_IMAGE, Size(60, 60) );

    for ( size_t i = 0; i < faces.size(); i++ )
    {
        Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 );
        ellipse( frame, center, Size( faces[i].width/2, faces[i].height/2 ), 0, 0, 360, Scalar( 255, 0, 255 ), 4, 8, 0 );

        Mat faceROI = frame_gray( faces[i] );
        std::vector<Rect> eyes;

        //-- In each face, detect eyes
        eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CASCADE_SCALE_IMAGE, Size(30, 30) );

        for ( size_t j = 0; j < eyes.size(); j++ )
        {
            Point eye_center( faces[i].x + eyes[j].x + eyes[j].width/2, faces[i].y + eyes[j].y + eyes[j].height/2 );
            int radius = cvRound( (eyes[j].width + eyes[j].height)*0.25 );
            circle( frame, eye_center, radius, Scalar( 255, 0, 0 ), 4, 8, 0 );
        }
    }
    //-- Show what you got
    imshow( window_name, frame );
}

（5）支持向量机引导（？？？黑人问号