Scalar类-颜色类

scalar-颜色类

函数原型如下：

template<typename _Tp> class Scalar_ : public Vec<_Tp, 4>
{public://! default constructorScalar_();Scalar_(_Tp v0, _Tp v1, _Tp v2=0, _Tp v3=0);//最常用；Scalar_(_Tp v0);Scalar_(const Scalar_& s);Scalar_(Scalar_&& s) CV_NOEXCEPT;Scalar_& operator=(const Scalar_& s);Scalar_& operator=(Scalar_&& s) CV_NOEXCEPT;template<typename _Tp2, int cn>Scalar_(const Vec<_Tp2, cn>& v);//! returns a scalar with all elements set to v0static Scalar_<_Tp> all(_Tp v0);//! conversion to another data typetemplate<typename T2> operator Scalar_<T2>() const;//! per-element productScalar_<_Tp> mul(const Scalar_<_Tp>& a, double scale=1 ) const;//! returns (v0, -v1, -v2, -v3)Scalar_<_Tp> conj() const;//! returns true iff v1 == v2 == v3 == 0bool isReal() const;
};

 Scalar_(_Tp v0, _Tp v1, _Tp v2=0, _Tp v3=0);//最常用；

#include<iostream>
#include<opencv2/opencv.hpp>using namespace std;
using namespace cv;int main()
{Scalar color(2, 3, 4);cout << "【颜色类】" << endl << color << endl;color.all(0);cout << color << endl;return 0;
}

【颜色类】
[2, 3, 4, 0]
[2, 3, 4, 0]
请按任意键继续. . .

重点：

首先需要理解以下句子：

Mat M(7,7,CV_32FC2,Scalar(1,3));

解释如下：创建一个M矩阵，7行7列，类型为CV_32F，CV_32F表示每个元素的值的类型为32位浮点数，C2表示有2个通道。Scalar(1,3)是对矩阵进行初始化赋值。第一个通道全为1，第2个通道全为3。

#include <iostream>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
using namespace std;
using namespace cv;
void scalar_demo1() {Mat M(4, 4, CV_32FC2, Scalar(1, 3));cout << M << endl;
}
void scalar_demo2() {Mat M(4, 4, CV_32FC3, Scalar(1, 2, 3));cout << M << endl;
}
void scalar_demo3() {Mat M(4, 4, CV_32FC4, Scalar(1, 2, 3));cout << M << endl;
}
int main(void)
{scalar_demo1();cout << "**********************************" << endl;scalar_demo2();cout << "**********************************" << endl;scalar_demo3();Mat M(400, 400, CV_32FC3, Scalar(255, 0, 0));/*cout << M << endl;*//*cout << M.rows << endl;cout << M.cols << endl;*/imshow("scalar_demo3", M);waitKey(0);return 0;
}

以下可以直观的了解到每一通道与Scala的关系：
M是以个像素容器，里面存放的是像素单元，通道数与BGR相对应；对于三通而言，scalar是设置bgr分量的值，相当于给每一个像素配色；
[1, 3, 1, 3, 1, 3, 1, 3;
1, 3, 1, 3, 1, 3, 1, 3;
1, 3, 1, 3, 1, 3, 1, 3;
1, 3, 1, 3, 1, 3, 1, 3]

[1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3;
1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3;
1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3;
1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3]

[1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0;
1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0;
1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0;
1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0]

成员函数all()

其作用是将图像中所用通道设置为指定数字;

#include <iostream>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
using namespace std;
using namespace cv;
int main(void)
{/*Mat scrImage(40, 40, CV_32FC3, Scalar(0, 255, 0));*/Mat scrImage(40, 40, CV_32FC3);Scalar color(0, 255, 0);  scrImage = color;                  //给每一像素赋值；imshow("scalar_demo1", scrImage);cout << scrImage << endl;scrImage =color.all(0);               /*将scrImage中每一个通道的值置成0；要将color.all(0)赋值给scrImage,否则color.all(0)没有意义；所以使用时要指定对象（通过=）；*/cout << scrImage << endl;imshow("scalar_demo", scrImage);waitKey(0);return 0;
}

Mat scrImage(4, 4, CV_32FC3);//结果如下：

[0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0;
0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0;
0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0;
0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0]
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0;
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
请按任意键继续. . .

例子：

#include <iostream>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
using namespace std;
using namespace cv;
int main(void)
{Mat M(10, 10, CV_32FC3, Scalar(255, 0, 0));cout << M << endl;/*cout << M.rows << endl;cout << M.cols << endl;*/imshow("scalar_demo3", M);waitKey(0);return 0;
}

[255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0;255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0;255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0;255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0;255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0;255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0;255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0;255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0;255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0;255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0]

每一个【255, 0, 0】代表一个蓝色像素点；

Mat M(10, 10, CV_32FC3, Scalar(255, 0, 0));

所以这句话可以理解为，创建一个10*10的像素矩阵，每一个像素RBG分量均是（255，0，0）；
修改一下代码：

Mat M(400, 400, CV_32FC3, Scalar(255, 0, 0));

Mat M(400, 400, CV_32FC3, Scalar(255, 0, 0));

Mat M(400, 400, CV_8UC3, Scalar(0, 0, 255));

Mat M(400, 400, CV_8UC3, Scalar(127,255,212));