opencv基础功能实现

chapter1 Read Images Videos and Webcams

#include 
#include 
#include 
#include 

using namespace std;
using namespace cv;


  Images  /

//int main() {
//	string path = "D:/代码opencv/picture/01.png";
//	Mat img = imread(path);
//	imshow("Image", img);
//	waitKey(0);
//}


  Video  /

//int main() {
//
//	string path = "D:/代码opencv/picture/test_video.mp4";
//	VideoCapture cap(path);
//
//	Mat img;
//	
//	while (true) {
//		cap.read(img);
//		imshow("Image", img);
//		waitKey(20);
//	}
//}


  Webcam  /

int main() {

	VideoCapture cap(0);

	Mat img;

	while (true) {
		cap.read(img);
		imshow("Image", img);
		waitKey(1);
		return 0;
	}
}

chapter2 Basic Functions

#include 
#include 
#include 
#include 

using namespace std;
using namespace cv;


  Basic Functions  /

int main() {
	string path = "D:/代码opencv/picture/01.png";
	Mat img = imread(path);
	Mat imgGray, imgBlur, imgCanny, imgDil, imgErode;

	cvtColor(img, imgGray, COLOR_BGR2GRAY);
	GaussianBlur(img, imgBlur, Size(7, 7), 5, 0);
	Canny(imgBlur, imgCanny, 50, 150);

	Mat kernel = getStructuringElement(MORPH_RECT, Size(5, 5));
	dilate(imgCanny, imgDil, kernel);
	erode(imgDil, imgErode, kernel);

	imshow("Image", img);
	imshow("Image Gray", imgGray);
	imshow("Image Blur", imgBlur);
	imshow("Image Canny", imgCanny);
	imshow("Image Dilation", imgDil);
	imshow("Image Erode", imgErode);
	waitKey(0);
	return 0;
}

chapter3 Resize and Crop

#include 
#include 
#include 
#include 

using namespace std;
using namespace cv;


  Resize and Crop  /

int main() {
	string path = "D:/代码opencv/picture/01.png";
	Mat img = imread(path);
	Mat imgResize, imgCrop;

	cout << img.size() << endl;
	//resize(img, imgResize, Size(200,100));
	resize(img, imgResize, Size(),0.5,0.5);

	Rect roi(100, 100, 200, 200);
	imgCrop = img(roi);

	imshow("Image", img);
	imshow("Image Resize", imgResize);
	imshow("Image Crop", imgCrop);

	waitKey(0);
	return 0;
}

chapter4 Draw Shapes and Text

#include 
#include 
#include 
#include 

using namespace std;
using namespace cv;


  Draw Shapes and Text  /

int main() {
	Mat img(512, 512, CV_8UC3, Scalar(255, 255, 0));

	circle(img, Point(256, 256), 155, Scalar(0, 69, 255), FILLED);
	rectangle(img, Point(130, 226), Point(382, 286), Scalar(255, 255, 255), FILLED);
	line(img, Point(130, 296), Point(382, 296), Scalar(255, 255, 255), 2);

	putText(img, "Murtaza's Workshop", Point(137, 262), FONT_HERSHEY_DUPLEX, 0.75, Scalar(0, 69, 255));

	imshow("Image", img);

	waitKey(0);
	return 0;
}

chapter5 Warp Images

#include 
#include 
#include 
#include 

using namespace std;
using namespace cv;

  Warp Images  /

float w = 250, h = 350;
Mat matrix, imgWarp;

int main() {

	string path = "D:/代码opencv/picture/cards.jpg";
	Mat img = imread(path);

	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);
	warpPerspective(img, imgWarp, 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 Warp", imgWarp);
	waitKey(0);
	return 0;
}

chapter6 Color Detection

#include 
#include 
#include 
#include 

using namespace std;
using namespace cv;


  Color Detection  /

Mat imgHSV, mask;
int hmin = 0, smin = 110, vmin = 153;
int hmax = 19, smax = 240, vmax = 255;

int main() {

	string path = "D:/代码opencv/picture/lambo.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 Max", "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);
	}
	return 0;
}

chapter7 Shapes/Contour Detection

#include 
#include 
#include 
#include 

using namespace std;
using namespace cv;


  Shapes/Contour Detection  /

Mat imgGray, imgBlur, imgCanny, imgDil, imgErode;

void getContours(Mat imgDil,Mat img) {

	vector<vector<Point>> contours;
	vector<Vec4i>hierarchy;

	findContours(imgDil, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
	//drawContours(img, contours, -1, Scalar(255, 0, 255), 2);

	vector<vector<Point>> conPoly(contours.size());
	vector<Rect> 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"; }
			else 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"; }

			}
			else if (objCor > 4) { 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, 69, 255),1);

		}
	}
	
}

int main() {

	string path = "D:/代码opencv/picture/shapes.png";
	Mat img = imread(path);

	//Preprocessing
	cvtColor(img, imgGray, COLOR_BGR2GRAY);
	GaussianBlur(img, 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);
	/*imshow("Image Gray", imgGray);
	imshow("Image Blur", imgBlur);
	imshow("Image Canny", imgCanny);
	imshow("Image Dilation", imgDil);*/

	waitKey(0);

	return 0;
}

chapter8 Face Detection

#include 
#include 
#include 
#include 
#include 

using namespace std;
using namespace cv;


  Face Detection  /

int main() {
	string path = "D:/代码opencv/picture/test.png";
	Mat img = imread(path);

	CascadeClassifier faceCascade;
	faceCascade.load("D:/代码opencv/picture/haarcascade_frontalface_default.xml");

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

	vector<Rect> 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);

   return 0;
}

project1 Virtual Painter

colorPicker.cpp

#include 
#include 
#include 
#include 

using namespace cv;
using namespace std;

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

VideoCapture cap(0);
Mat img;

int main()
{
	namedWindow("Trackbars", (640, 200)); // Create Window
	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 Max", "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);
		// hmin, smin, vmin, hmax, smax, vmax;
		cout << hmin << ", " << smin << ", " << vmin << ", " << hmax << ", " << smax << ", " << vmax << endl;
		imshow("Image", img);
		imshow("Mask", mask);

		waitKey(1);
	}
	return 0;
}

project1.cpp

#include 
#include 
#include 
#include 

using namespace cv;
using namespace std;

/ Project 1 – Virtual Painter //

Mat img;
VideoCapture cap(0);
vector<vector<int>> newPoints; // to store all points

/ COLOR VALUES 
// hmin, smin, vmin hmax, smax, vmax
vector<vector<int>> myColors{ {124,48,117,143,170,255}, // Purple
							  {68,72,156,102,126,255} };// Green
vector<Scalar> myColorValues{ {255,0,255}, // Purple
							  {0,255,0} };// Green


Point getContours(Mat image) {

	vector<vector<Point>> contours;
	vector<Vec4i> hierarchy;

	findContours(image, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
	//drawContours(img, contours, -1, Scalar(255, 0, 255), 2);
	vector<vector<Point>> conPoly(contours.size());
	vector<Rect> 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 > 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]);
			myPoint.x = boundRect[i].x + boundRect[i].width / 2;
			myPoint.y = boundRect[i].y;

			//drawContours(img, conPoly, i, Scalar(255, 0, 255), 2);
			//rectangle(img, boundRect[i].tl(), boundRect[i].br(), Scalar(0, 255, 0), 5);
		}
	}
	return myPoint;
}

vector<vector<int>> 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) {
			newPoints.push_back({ myPoint.x,myPoint.y,i });
		}
	}
	return newPoints;
}

void drawOnCanvas(vector<vector<int>> newPoints, vector<Scalar> 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() {

	while (true) {

		cap.read(img);
		newPoints = findColor(img);
		drawOnCanvas(newPoints, myColorValues);

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

project2 Document Scanner

#include 
#include 
#include 
#include 

using namespace cv;
using namespace std;

/// Project 2 – Document Scanner //

Mat imgOriginal, imgGray, imgBlur, imgCanny, imgThre, imgDil, imgErode, imgWarp, imgCrop;
vector<Point> 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, imgErode, kernel);
	return imgDil;
}

vector<Point> getContours(Mat image) {

	vector<vector<Point>> contours;
	vector<Vec4i> hierarchy;

	findContours(image, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
	//drawContours(img, contours, -1, Scalar(255, 0, 255), 2);
	vector<vector<Point>> conPoly(contours.size());
	vector<Rect> boundRect(contours.size());

	vector<Point> biggest;
	int maxArea = 0;

	for (int i = 0; i < contours.size(); i++)
	{
		int area = contourArea(contours[i]);
		//cout << area << endl;

		string objectType;

		if (area > 1000)
		{
			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;
			}
			//drawContours(imgOriginal, conPoly, i, Scalar(255, 0, 255), 2);
			//rectangle(imgOriginal, boundRect[i].tl(), boundRect[i].br(), Scalar(0, 255, 0), 5);
		}
	}
	return biggest;
}

void drawPoints(vector<Point> 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<Point> reorder(vector<Point> points)
{
	vector<Point> newPoints;
	vector<int> 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<Point> 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 = "D:/代码opencv/picture/paper.jpg";
	imgOriginal = imread(path);
	//resize(imgOriginal, imgOriginal, Size(), 0.5, 0.5);

	// Preprpcessing – Step 1
	imgThre = preProcessing(imgOriginal);

	// Get Contours – Biggest – Step 2
	initialPoints = getContours(imgThre);
	//drawPoints(initialPoints, Scalar(0, 0, 255));
	docPoints = reorder(initialPoints);
	//drawPoints(docPoints, Scalar(0, 255, 0));

	// Warp – Step 3
	imgWarp = getWarp(imgOriginal, docPoints, w, h);

	//Crop – Step 4
	int cropVal = 5;
	Rect roi(cropVal, cropVal, w - (2 * cropVal), h - (2 * cropVal));
	imgCrop = imgWarp(roi);

	imshow("Image", imgOriginal);
	//imshow("Image Dilation", imgThre);
	//imshow("Image Warp", imgWarp);
	imshow("Image Crop", imgCrop);
	waitKey(0);

}

project3 License Plate Detector

#include 
#include 
#include 
#include 
#include 

using namespace cv;
using namespace std;

/// Project 3 – License Plate Detector //

void main() {

	Mat img;
	VideoCapture cap(0);

	CascadeClassifier plateCascade;
	plateCascade.load("D:/代码opencv/picture/haarcascade_russian_plate_number.xml");

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

	vector<Rect> 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("Resources / Plates / " + to_string(i) + ".png", imgCrop);
			rectangle(img, plates[i].tl(), plates[i].br(), Scalar(255, 0, 255), 3);
		}

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