First knowledge of opencv4.x --- image histogram drawing

// Image histogram rendering 
#include <stdio.h>
#include <iostream>
#include <string>
#include <opencv2\opencv.hpp>
using namespace std;
using namespace cv;
int main()
{
    
	Mat img = imread("person1.jpeg", IMREAD_GRAYSCALE);
	// Statistics 0~255 The number of pixels of each gray value 
	const int channels[1] = {
     0 };
	Mat hist;
	const int histSize[1] = {
     256 };
	float a[2] = {
     0,255 };
	const float * ranges[1] = {
     a };
	calcHist(&img, 1, channels, Mat(), hist, 1, histSize, ranges);// Got hist It's a single channel ,width=1,height=256 Of Mat Variable 
	// Draw histogram , Draw a solid rectangle through the diagonal points of the rectangle 
	// The width of each rectangle is 2, Of the image width Should be 2*256=512, Graphic height By the maximum number of pixels max_value decision 
	//i Value 0,2,4...510, Every time you draw a rectangle , The coordinates of the lower left corner are （max_value,i）, The coordinates of the upper right corner are （max_value-hist.at(i/2),i+2）
	double min_value, max_value;
	minMaxLoc(hist, &min_value, &max_value);
	max_value = max_value / 100;// By setting the breakpoint, the maximum value is 3000+, narrow 100 times , Prevent the picture from getting too big 
	Mat img_zeros=Mat::zeros((int)max_value,512,CV_8UC1);
	for (int i = 0; i < 512; i = i + 2)
	{
    
		rectangle(img_zeros, Point(i, max_value), Point(i + 2, (int)(max_value - (hist.at<float>(i / 2)) / 100)), Scalar(255), -1);// Be careful hist The element in is float type 
	}
	namedWindow("hist", WINDOW_NORMAL);
	imshow("hist", img_zeros);
	waitKey(0);
	return 0;
}

// Image normalized histogram rendering 
#include <stdio.h>
#include <iostream>
#include <string>
#include <opencv2\opencv.hpp>
using namespace std;
using namespace cv;
int main()
{
    
	Mat img = imread("person1.jpeg", IMREAD_GRAYSCALE);
	// Statistics 0~255 The number of pixels of each gray value 
	const int channels[1] = {
     0 };
	Mat hist;
	const int histSize[1] = {
     256 };
	float a[2] = {
     0,255 };
	const float * ranges[1] = {
     a };
	
	calcHist(&img, 1, channels, Mat(), hist, 1, histSize, ranges);// Got hist It's a single channel ,width=1,height=256 Of Mat Variable 
	// normalization hist
	normalize(hist, hist, 1, 0, NORM_L1, -1);//NORM_L1 Method divides the corresponding number of a pixel by the maximum 
	// Draw histogram , Draw a solid rectangle through the diagonal points of the rectangle 
	// The width of each rectangle is 2, Of the image width Should be 2*256=512, Graphic height By the maximum number of pixels max_value decision 
	//i Value 0,2,4...510, Every time you draw a rectangle , The coordinates of the lower left corner are （max_value,i）, The coordinates of the upper right corner are （max_value-hist.at(i/2),i+2）
	double min_value, max_value;
	minMaxLoc(hist, &min_value, &max_value);
	max_value = max_value * 1000;// By setting the breakpoint, the maximum value is 0.038+, expand 1000 times , Prevent the picture from being too small 
	Mat img_zeros=Mat::zeros((int)max_value,512,CV_8UC1);
	for (int i = 0; i < 512; i = i + 2)
	{
    
		rectangle(img_zeros, Point(i, max_value), Point(i + 2, (int)(max_value - (hist.at<float>(i / 2)) * 1000)), Scalar(255), -1);// Be careful hist The element in is float type 
	}
	namedWindow("hist", WINDOW_NORMAL);
	imshow("hist", img_zeros);
	waitKey(0);
	return 0;
}

// Image histogram comparison 
#include <stdio.h>
#include <iostream>
#include <string>
#include <opencv2\opencv.hpp>
using namespace std;
using namespace cv;
int main()
{
    
	Mat img = imread("person1.jpeg", IMREAD_GRAYSCALE);
	// Statistics 0~255 The number of pixels of each gray value 
	const int channels[1] = {
     0 };
	Mat hist, hist_nor;
	const int histSize[1] = {
     256 };
	float a[2] = {
     0,255 };
	const float * ranges[1] = {
     a };
	// Directly count the number of histograms 
	calcHist(&img, 1, channels, Mat(), hist, 1, histSize, ranges);// Got hist It's a single channel ,width=1,height=256 Of Mat Variable 
	// Normalized histogram 
	normalize(hist, hist_nor, 1, 0, NORM_L1, -1);//NORM_L1 Method divides the corresponding number of a pixel by the maximum 
	double result;
	result = compareHist(hist, hist_nor, 0);// The last parameter represents the method of comparison , The results of different methods are different , A little close 1 Represents the more similar , On the contrary, some 
	cout << " The similarity of the two images is ：" << result << endl;
	waitKey(0);
	return 0;
}