手敲的murtazahassan的OpenCV教程代码C++

看了murtazahassan的OpenCV C++教程代码，感觉讲的很好，把他的所有代码都手敲了一遍，代码如下：

以下每段代码前都加上如下：

#include
#include
#include
#include
#include 
using namespace cv;
using namespace std;

Chapter5 image wrap

int main()
{
    string path = "D:/OneDrive - zju.edu.cn/VS/OpenCV-test/Resources/cards.jpg";
    Mat img = imread(path);
    Mat matrix, imgWrap;
    float w = 250, h = 350;
    Point2f src[4] = { {529,142},{771,190},{405,395},{674,457} };
    Point2f dst[4] = { {0.0f,0.0f},{w,0.0f},{0.0f,h},{w,h} };

    matrix = getPerspectiveTransform(src, dst);//变换矩阵
    warpPerspective(img, imgWrap, matrix, Point(w, h));

    for (int i = 0; i < 4; i++)
    {
        circle(img, src[i], 10, Scalar(0, 0, 255), FILLED);
    }

    imshow("image", img);
    imshow("image Wrap", imgWrap);
    waitKey(0);
}

Chapter6 Color Detection

int main()
{
    int hmin = 0, smin = 0, vmin = 0;
    int hmax = 179, smax = 255, vmax = 255;
    Mat imgHSV, mask;

    string path = "D:/OneDrive - zju.edu.cn/VS/OpenCV-test/Resources/shapes.png";
    Mat img = imread(path);
       
    cvtColor(img, imgHSV, COLOR_BGR2HSV);

    namedWindow("Trackbars", (640, 200));
    createTrackbar("Hue Min", "Trackbars", &hmin, 179);
    createTrackbar("Hue Max", "Trackbars", &hmax, 179);
    createTrackbar("Sat Min", "Trackbars", &smin, 255);
    createTrackbar("Sat Max", "Trackbars", &smax, 255);
    createTrackbar("Val Min", "Trackbars", &vmin, 255);
    createTrackbar("Val Min", "Trackbars", &vmax, 255);

    while (true)
    {
        Scalar lower(hmin, smin, vmin);
        Scalar upper(hmax, smax, vmax);
        inRange(imgHSV, lower, upper, mask);

        imshow("image", img);
        imshow("image hsv", imgHSV);
        imshow("image mask", mask);
        waitKey(1);
    }    
}

Chapter7 Shape Detection

void getContours(Mat imgDil,Mat img)
{
    vector> contours;    
    vector hierarchy;
    findContours(imgDil, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE); 
    //drawContours(img, contours, -1, Scalar(255, 0, 255), 2);
    vector> conPoly(contours.size());
    vector boundRect(contours.size());
    string  objectType;
    for (int i = 0; i < contours.size(); i++)
    {
        int area = contourArea(contours[i]);
        cout << area << endl;
        if (area > 1000)
        {
            float peri = arcLength(contours[i], true);
            approxPolyDP(contours[i], conPoly[i], 0.02 * peri, true);
            
            cout << conPoly[i].size() << endl;
            boundRect[i] = boundingRect(conPoly[i]);

            int objCor = (int)conPoly[i].size();
            if (objCor == 3) { objectType = "Tri"; }
            if (objCor == 4)
            {
                float aspRatio = (float)boundRect[i].width / (float)boundRect[i].height;
                cout << aspRatio << endl;
                if (aspRatio > 0.95 && aspRatio < 1.05)
                {
                    objectType = "square";
                }
                else
                {
                    objectType = "Rect";
                }
            }
            
            if (objCor == 3) { objectType = "Circle"; }

            drawContours(img, conPoly, i, Scalar(255, 0, 255), 2);
            rectangle(img, boundRect[i].tl(), boundRect[i].br(), Scalar(0, 255, 0), 5);
            putText(img, objectType, { boundRect[i].x,boundRect[i].y - 5 }, FONT_HERSHEY_PLAIN, 1, Scalar(0, 65, 255),2);
        }
    }
}

int main()
{  
    Mat imgGray, imgBlur, imgCanny, imgDil, imgErode;
    string path = "C:/Users/28463/OneDrive - zju.edu.cn/VS/OpenCV-test/Resources/shapes.png";
    Mat img = imread(path);
   //预处理 Preprocessing
    cvtColor(img, imgGray, COLOR_BGR2GRAY);
    GaussianBlur(imgGray, imgBlur, Size(3, 3), 3, 0);
    Canny(imgBlur, imgCanny, 25, 75);
    Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3));
    dilate(imgCanny, imgDil, kernel);

    getContours(imgDil,img);

    imshow("image", img);    
  
    waitKey(0);   
}

Chapter8 Face Detection

void main()
{
    string path = "C:/Users/28463/OneDrive - zju.edu.cn/VS/OpenCV-test/Resources/test.png";
    Mat img = imread(path);

    CascadeClassifier faceCascade;
    faceCascade.load("C:/Users/28463/OneDrive - zju.edu.cn/VS/OpenCV-test/Resources/haarcascade_frontalface_default.xml");

    if (faceCascade.empty())
    {
        cout << "XML file not loaded" << endl;
    }

    vector faces;
    faceCascade.detectMultiScale(img, faces, 1.1, 10);

    for (int i = 0; i < faces.size(); i++)
    {
        rectangle(img, faces[i].tl(), faces[i].br(), Scalar(255, 0, 255), 3);
    }
    
    imshow("image", img);   
    waitKey(0);
}

ColorPicker

int hmin = 0, smin = 0, vmin = 0;
int hmax = 179, smax = 255, vmax = 255;
Mat imgHSV, mask, imgColor;

VideoCapture cap(0);
Mat img;

int main()
{
    namedWindow("Trackbars", (640, 200));
    createTrackbar("Hue Min", "Trackbars", &hmin, 179);
    createTrackbar("Hue Max", "Trackbars", &hmax, 179);
    createTrackbar("Sat Min", "Trackbars", &smin, 255);
    createTrackbar("Sat Max", "Trackbars", &smax, 255);
    createTrackbar("Val Min", "Trackbars", &vmin, 255);
    createTrackbar("Val Min", "Trackbars", &vmax, 255);

    while (true)
    {
        cap.read(img);
        cvtColor(img, imgHSV, COLOR_BGR2HSV);
        Scalar lower(hmin, smin, vmin);
        Scalar upper(hmax, smax, vmax);
        inRange(imgHSV, lower, upper, mask);
        cout << hmin << "," << smin << "," << vmin << "," << hmax << "," << smax << "," << vmax << endl;
        imshow("image", img);
        //imshow("image hsv", imgHSV);
        imshow("image mask", mask);
        waitKey(1);
    }
}

PROJECT 1 Virtual Paint

Mat img;
vector> newPoints;
vector>myColors{ {16,175,168,40,255,255},{124,36,43,169,255,255} };
vector myColorValues{ {0,255,255},{255,0,255} };

Point  getContours(Mat imgDil)
{
	vector>contours;
	vector hierarchy;
	findContours(imgDil, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
	vector> conPoly(contours.size());
	vector boundRect(contours.size());
	Point myPoint(0, 0);
	for (int i = 0; i < contours.size();i++)
	{
		int area = contourArea(contours[i]);
		cout << area << endl;
		string objectType;

		if (area > 500)
		{
			float peri = arcLength(contours[i], true);
			approxPolyDP(contours[i], conPoly[i], 0.02 * peri, true);
			cout << conPoly[i].size() << endl;
			boundRect[i] = boundingRect(conPoly[i]);
			myPoint.x = boundRect[i].x + boundRect[i].width / 2;
			myPoint.y = boundRect[i].y;
			drawContours(img, conPoly, i, Scalar(255, 0, 255), 2);

		}
	}
	return myPoint;

}
vector>  findColor(Mat img)
{
	Mat imgHSV;
	cvtColor(img, imgHSV, COLOR_BGR2HSV);

	for (int i = 0; i < myColors.size(); i++)
	{
		Scalar lower(myColors[i][0], myColors[i][1], myColors[i][2]);
		Scalar upper(myColors[i][3], myColors[i][4], myColors[i][5]);
		Mat mask;
		inRange(imgHSV, lower, upper, mask);
		//imshow(to_string(i), mask);
		Point myPoint= getContours(mask);
		if (myPoint.x != 0 && myPoint.y != 0)
		{
			newPoints.push_back({ myPoint.x,myPoint.y,i });
		}	
		
	}	
	return newPoints;
}

void drawOnCanvas(vector> newPoints, vector myColorValues)
{
	for (int i = 0; i < newPoints.size(); i++)
	{
		circle(img, Point(newPoints[i][0], newPoints[i][1]),10,myColorValues[newPoints[i][2]],FILLED);
	}

}

void main()
{
	VideoCapture cap(0);

	while (true)
	{
		cap.read(img);
		newPoints= findColor(img);
		drawOnCanvas(newPoints,myColorValues);
		imshow("Image", img);
		waitKey(1);
	}
}

PROJECT 2 Document Scanner

Mat imgOriginal, imgGray, imgBlur, imgCanny, imgDil, imgErod, imgThre, imgWarp,imgCrop;
vector initialPoints, docPoints;
float w = 420, h = 596;
Mat preProcessing(Mat img)
{
	cvtColor(img, imgGray, COLOR_BGR2GRAY);
	GaussianBlur(imgGray, imgBlur, Size(3, 3), 3, 0);
	Canny(imgBlur, imgCanny, 25, 75);
	Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3));
	dilate(imgCanny, imgDil, kernel);
	//erode(imgDil, imgErod, kernel);
	return imgDil;
}

vector  getContours(Mat imgDil)
{
	vector>contours;
	vector hierarchy;
	findContours(imgDil, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
	vector> conPoly(contours.size());
	vector boundRect(contours.size());

	vector  Biggest;
	int maxArea=0;
	for (int i = 0; i < contours.size();i++)
	{
		int area = contourArea(contours[i]);
		cout << area << endl;
		string objectType;

		if (area > 500)
		{
			float peri = arcLength(contours[i], true);
			approxPolyDP(contours[i], conPoly[i], 0.02 * peri, true);
			
			if (area > maxArea && conPoly[i].size()==4)
			{
				//drawContours(imgOriginal, conPoly, i, Scalar(255, 0, 255), 5);
				Biggest = { conPoly[i][0],conPoly[i][1] ,conPoly[i][2] ,conPoly[i][3] };
				maxArea = area;
			}	
		}
	}
	return Biggest;
}

void drawPoints(vector points,Scalar color)
{
	for (int i = 0; i < points.size(); i++)
	{
		circle(imgOriginal, points[i], 10, color, FILLED);
		putText(imgOriginal, to_string(i), points[i], FONT_HERSHEY_PLAIN, 4, color, 4);
	}
}

vector reorder(vector points)
{
	vector newPoints;
	vector sumPoints, subPoints;
	for (int i = 0; i < 4; i++)
	{
		sumPoints.push_back(points[i].x + points[i].y);
		subPoints.push_back(points[i].x - points[i].y);
	}
	newPoints.push_back(points[min_element(sumPoints.begin(), sumPoints.end()) - sumPoints.begin()]);//0
	newPoints.push_back(points[max_element(subPoints.begin(), subPoints.end()) - subPoints.begin()]);//1
	newPoints.push_back(points[min_element(subPoints.begin(), subPoints.end()) - subPoints.begin()]);//2
	newPoints.push_back(points[max_element(sumPoints.begin(), sumPoints.end()) - sumPoints.begin()]);//3
	return newPoints;
}

Mat getWarp(Mat img, vector points, float w, float h)
{
	Point2f src[4] = { points[0],points[1], points[2], points[3] };
	Point2f dst[4] = { {0.0f,0.0f}, {w,0.0f}, {0.0f,h}, {w,h} };
	Mat matrix = getPerspectiveTransform(src, dst);
	warpPerspective(img, imgWarp, matrix, Point(w, h));

	return imgWarp;
}

void main()	
{	
	string path= "C:/Users/28463/OneDrive - zju.edu.cn/VS/OpenCV-test/Resources/paper.jpg";
	imgOriginal = imread(path);
	//resize(imgOriginal, imgOriginal, Size(), 0.5, 0.5);
	//Preprocessing
	imgThre = preProcessing(imgOriginal);
	//Get Contours - Biggest
	initialPoints=getContours(imgThre);
	//drawPoints(initialPoints, Scalar(0, 0, 255));
	docPoints = reorder(initialPoints);
	//drawPoints(docPoints, Scalar(0, 255, 0));
	//Warp
	imgWarp = getWarp(imgOriginal, docPoints, w, h);

	//Crop
	int cropVal = 5;
	Rect roi(cropVal, cropVal, w - (2 * cropVal), h - (2 * cropVal));
	imgCrop = imgWarp(roi);

	imshow("Image", imgOriginal);
	imshow("Image Dil", imgDil);
	imshow("Image Wrap", imgWarp);
	imshow("Image Crop", imgCrop);
	waitKey(0);	
}

PROJECT 3 License Plate Detector

void main()
{
    VideoCapture cap(0);
    Mat img;

    CascadeClassifier plateCascade;
    plateCascade.load("C:/Users/28463/OneDrive - zju.edu.cn/VS/OpenCV-test/Resources/haarcascade_russian_plate_number.xml");

    if (plateCascade.empty())
    {
        cout << "XML file not loaded" << endl;
    }

    vector plates;

    while (true)
    {
        cap.read(img);    

        plateCascade.detectMultiScale(img, plates, 1.1, 10);

		for (int i = 0; i < plates.size(); i++)
		{
            Mat imgCrop = img(plates[i]);
            //imshow(to_string(i), imgCrop);
            imwrite("C:/Users/28463/OneDrive - zju.edu.cn/VS/OpenCV-test/Resources/" + to_string(i) + ".png", imgCrop);
            rectangle(img, plates[i].tl(), plates[i].br(), Scalar(255, 0, 255), 3);
		}

		imshow("image", img);
		waitKey(1);
    }
}

手敲的murtazahassan的OpenCV教程代码C++

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