c++ opencv 基本操作

下载地址：

https://opencv.org/releases/

归一化，转vector：

Opencv C++ 归一化_jacke121的专栏-CSDN博客_c++ opencv 归一化

opencv c++ 贴图补齐实战

opencv c++ 贴图_jacke121的专栏-CSDN博客

c++ transpose：

nanodet onnx踩坑记录_jacke121的专栏-CSDN博客

c++读取视频：

python opencv 读取图片和视频_AI视觉网奇的博客-CSDN博客

目录

c++ 图像旋转 缩放

通道转换

创建图片，rect贴图，读取rect

读图，裁剪(其实是引用)，画矩形框，

矩形框：

读取字符串，resize，减法，除法

最大值，最小值

乘法

除法

转flost32类型

打印类型

打印输出

float*内存拷贝

遍历图片

mat引用传参，函数内修改 初始化Mat

opencv c++ 单通道图像：

---

c++ 图像旋转 缩放

opencv 旋转_AI视觉网奇的博客-CSDN博客_opencv 旋转

缩放示例

#include  
int main()
{
    cv::Mat src = cv::imread("./tu/马.jpg", cv::IMREAD_UNCHANGED); 
    float scaleW = 0.8; // 定义新图像的大小，宽度缩小到80%
    float scaleH = 0.8;  //定义新图像的大小，高度缩小到80%
    int width = int(src.cols * scaleW);
    int height = int(src.rows * scaleH);
    cv::Mat dst;
    resize(src, dst, cv::Size(width, height));//缩放图像
    cv::imshow("src", src);
    cv::imshow("dst", dst);
    cv::waitKey();
}

通道转换

c++ opencv 通道转换_jacke121的专栏-CSDN博客_c++通道

创建图片，rect贴图，读取rect

	int width = 360;
	int height = 30;
	int width_crop = 180;
	cv::Mat img(height, width, CV_8UC3, cv::Scalar(0, 0, 255));

	cv::Mat img2(height, width_crop, CV_8UC3, cv::Scalar(0,255, 0));
	cv::Rect rect(0, 0, width_crop, height);

	cv::Mat imageROI = img(rect);

	img2.copyTo(imageROI, img2);

	cv::imshow("result", img);
	cv::waitKey(0);

读图，裁剪(其实是引用)，画矩形框，

	Mat img = imread(R"(D:\data\tiaosheng\imgs\0001.jpg)");

    int iw = img.cols;
	int ih = img.rows;

	int width = 360;
	int height = 30;
	int width_crop = 180;
	cv::Mat img1(height, width, CV_8UC3, cv::Scalar(0, 0, 255));

	cv::Mat img2(height, width_crop, CV_8UC3, cv::Scalar(0, 255, 0));
	cv::Rect rect(0, 0, width_crop, height);

	cv::Mat imageROI = img(rect);


	cv::rectangle(imageROI, Rect(10, 10, 20, 30), Scalar(0, 255, 0), 1, 1, 0);
	//img2.copyTo(imageROI, img2);

	cv::imshow("result", img);
	cv::waitKey(0);

读取rect

					float aaa = r.rect.x;
					float bbb = r.rect.y;
					float ccc = r.rect.width;
					float ddd = r.rect.height;

					std::cout << "aaa " << aaa << " bbb:" << bbb<< " ccc:" << ccc << " ddd:" << ddd << std::endl;

矩形框：

int x = 50;
int y = 50;
int width = 50;
int height = 50;
cv::Rect rect(x, y, width, height);

cv::rectangle(matImage,Rect(100,300,20,200),Scalar(0,0,255),1,1,0);

读取字符串，resize，减法，除法

	cv::Mat row_img = cv::imread(R"(G:\rgb/000000.jpg)");
	int iw = row_img.cols;
	int ih = row_img.rows;

	cv::Mat image;
	cv::resize(row_img, image,cv::Size(INPUT_SIZE,INPUT_SIZE));


	cv::Mat dst = cv::Mat::zeros(row_img.size(), CV_32FC3);
	row_img.convertTo(dst, CV_32FC3);// , 10, -1);

	dst = dst - 128.0;
	dst = dst / 128.0;

	std::cout << dst.type() << std::endl;

	for (int a = 0; a < 20; a++) {
		//cout << (dst.data)[a] << " ";
		cout << ((float*)(dst.data))[a] << " ";
	}

最大值，最小值

opencv4可以多通道计算，opencv3.4只能计算单通道图像。

Mat image1, image3;
	image1 = imread("D:\\zhengjian.jpg");
	if (!image1.data)
	{
		return 0;
	}
	
	double minv = 0.0, maxv = 0.0;
	minMaxIdx(image1, &minv, &maxv);

	cout << "Mat minv = " << minv << endl;
	cout << "Mat maxv = " << maxv << endl;

    
    //归一化
	image_new = (image_new - minVal) / (maxVal - minVal)*255;

    //转化类型
	Mat dst = Mat::zeros(image_new.size(), CV_8U);
	image_new.convertTo(dst, CV_8U);// , NULL, 0);
	//image_new.convertTo(image_new, CV_8U, 255.0 / (maxVal - minVal), 0);

//建立空的黑图

Mat atom_image = Mat::zeros(w, w, CV_8UC3);

乘法

#include
#include
#include
#include
#include

using namespace std;
using namespace cv;

int main()
{
	Mat image1, image2, image3;
	image1 = imread("C:\\Users\\Dell\\Desktop\\5.jpg");
	if (!image1.data)
	{
		return 0;
	}
	image2 = imread("C:\\Users\\Dell\\Desktop\\4.jpg");
	if (!image2.data)
	{
		return 0;
	}
	resize(image2, image3, image1.size());
	namedWindow("Image 1");
	imshow("Image 1", image1);
	namedWindow("Image 3");
	imshow("Image 3", image3);
	Mat result;
	image3 = image3 * 0.3;
	image1 = image1 * 0.9;
	add(image1, image3, result);
	namedWindow("result");
	imshow("result", result);
	waitKey(0);
	return 0;
}

除法

Mat result1;
    imshow("result_o", image1);
    image1 = image1 / 2;
    imshow("result", image1);

转flost32类型

	cv::Mat image0 = cv::imread("../configs/bus.jpg", cv::IMREAD_UNCHANGED);
 
	cv::Mat dst = cv::Mat::zeros(image0.size(), CV_32FC3);
	image0.convertTo(dst, CV_32FC3);// , 10, -1);

打印类型

以下内容转自：

Package | OpenCV C++ cv::Mat 数据类型type对应的输出值_iLOVEJohnny的博客-CSDN博客_opencv 输出mat数据类型

std::cout << img.type() << std::endl;

id对应数据类型：

+--------+----+----+----+----+------+------+------+------+
|        | C1 | C2 | C3 | C4 | C(5) | C(6) | C(7) | C(8) |
+--------+----+----+----+----+------+------+------+------+
| CV_8U  |  0 |  8 | 16 | 24 |   32 |   40 |   48 |   56 |
| CV_8S  |  1 |  9 | 17 | 25 |   33 |   41 |   49 |   57 |
| CV_16U |  2 | 10 | 18 | 26 |   34 |   42 |   50 |   58 |
| CV_16S |  3 | 11 | 19 | 27 |   35 |   43 |   51 |   59 |
| CV_32S |  4 | 12 | 20 | 28 |   36 |   44 |   52 |   60 |
| CV_32F |  5 | 13 | 21 | 29 |   37 |   45 |   53 |   61 |
| CV_64F |  6 | 14 | 22 | 30 |   38 |   46 |   54 |   62 |
+--------+----+----+----+----+------+------+------+------+
 

打印输出

注意，每行结尾有 error 标注。

	Mat srcResize = imread(imgpath);
	
	for (int a = 0; a < 20; a++) {
		
			cout << (int)srcimg.at(0, a) << " ";// ok int

			cout << ((float*)(srcimg.data))[a] << " ";//error
		
	}

	cout << "int \n";
	cv::Mat dst = cv::Mat::zeros(srcResize.size(), CV_32FC3);
	srcResize.convertTo(dst, CV_32FC3);// , 10, -1);


	for (int a = 0; a < 20; a++) {
		cout << (float)dst.at(0, a) << " ";// ok float

		cout << ((float*)(dst.data))[a] << " ";// ok float
		//cout << setprecision(3) << ((float*)(srcimg.data))[a] << " ";
	}
	cout << "\n CV_32FC3 \n";
	for (int a = 0; a < 20; a++) {
		cout << setprecision(3) << ((double*)(dst.data))[a] << " ";//error
	}

这个输出错误： 

cout << (dst.data)[a] << " ";

float*内存拷贝

转自：memcpy - how to copy float* to float* variable - 鹅要长大 - 博客园

float* seg_segmap = new float[OUTPUT_H * OUTPUT_W];
float* temp = new float[OUTPUT_H * OUTPUT_W];
//memcpy(temp, seg_segmap, sizeof(seg_segmap));//error
memcpy(temp, seg_segmap, OUTPUT_H * OUTPUT_W*sizeof(float));

遍历图片

	cv::String path = R"(E:\data\Circle-detection-master\train_repeat\image/)";
	cv::String dst = "result/";
	//cv::String GT = "D:/astudy/dataset/circle/temp/GT/";


	T test_threshold;

	vector Filenames;
	cv::glob(path, Filenames);
	float fmeasureSum = 0.0;
	float precisionSum = 0.0;
	float recallSum = 0.0;
	float timeSum = 0.0;

	// Detect each image in the directory 'Images1'
	for (int i = 0; i < Filenames.size(); i++)
	{
		//read images
		cv::String file = Filenames[i];

mat引用传参，函数内修改 初始化Mat

void to_mat(Mat& out) {
	//out = Mat::eye(300, 400, CV_8UC1);
	out = Mat(300, 600, CV_8UC3);
	randu(out, Scalar::all(0), Scalar::all(255));
}

int main()
{

	Mat in_mat;
	to_mat(in_mat);

	cv::imshow("image_" + std::to_string(0), in_mat);
    cv::waitKey(0);
}

初始化Mat

1. 首先是 eye, ones, zeros

    Mat eye   = Mat::eye(4,4,CV_8U);
    Mat ones  = Mat::ones(4,4,CV_8U);
    Mat zeros = Mat::zeros(4,4,CV_8U);

2. 直接初始化Mat的元素，小矩阵很方便
 

   Mat img = (Mat_(3,3) << 1, 2, 3, 4, 5, 6, 7, 8, 9);

3. create分配内存，不初始化元素

    Mat m;
    m.create(4, 4, CV_8U);
    cout << m << endl;

4. 随机数矩阵 randn

    Mat r = Mat(3,3,CV_8UC3);
    randu(r, Scalar::all(0), Scalar::all(255));
    cout << r << endl;

原文链接：https://blog.csdn.net/billbliss/article/details/44699641

opencv c++ 单通道图像：

赋值与遍历：

	cv::Mat mat_box(128, 128, CV_32FC1);

		for (int ii = 0; ii < mat_box.rows; ++ii)
		{
			for (int j = 0; j < mat_box.cols; ++j)
			{
				if (ii % 2 == 0 ) {
					if (j % 2 == 0) {
						mat_box.at(ii, j) = 0.1f;
					}
					else {
						mat_box.at(ii, j) = 0.2f;
					}
				}
				else {
					if (j % 2 == 0) {
						mat_box.at(ii, j) = 0.3f;
					}
					else {
						mat_box.at(ii, j) = 0.4f;
					}
				}
				
			}
		}

		unsigned char* pimage = image.data;
		float* box_img = (float*)mat_box.data;
		float* phost_b = input_data_host + image_area * 0 +i * input_channel * input_height * input_width;
		float* phost_g = input_data_host + image_area * 1 + i * input_channel * input_height * input_width;
		float* phost_r = input_data_host + image_area * 2 + i * input_channel * input_height * input_width;
		float* phost_box = input_data_host + image_area * 3 + i * input_channel * input_height * input_width;
		for (int i = 0; i < image_area; ++i, pimage +=3) {
			*phost_r++ = (pimage[0] / 255.0f - mean[0]) / std[0];
			*phost_g++ = (pimage[1] / 255.0f - mean[1]) / std[1];
			*phost_b++ = (pimage[2] / 255.0f - mean[2]) / std[2];
			box_img += 1;
			*phost_box++ = box_img[0];
		}
	}