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

// Image histogram equalization 
#include <stdio.h>
#include <iostream>
#include <string>
#include <opencv2\opencv.hpp>
using namespace std;
using namespace cv;
void drawHist(Mat &hist, int hist_w, int hist_h, int type, string name);
int main()
{
    
	/*  Histogram equalization can change the original gray concentration into dispersion , This will prevent the image from being too dark or too bright , Make the outline of the image clearer  */
	Mat img = imread("gearwheel.jpg", 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 
	// Normalized histogram comparison 
	drawHist(hist, 512, 400, NORM_INF, "hist_nor");
	Mat img_equ;
	equalizeHist(img, img_equ);
	calcHist(&img_equ, 1, channels, Mat(), hist, 1, histSize, ranges);// Got hist It's a single channel ,width=1,height=256 Of Mat Variable 
	drawHist(hist, 512, 400, NORM_INF, "hist_equ_nor");
	// Gray image comparison after equalization 
	imshow("img", img);
	imshow("img_equ", img_equ);
	waitKey(0);
	return 0;
}
// Draw histogram function , Pass in the parameter ：hist, Image width , High image , Normalization mode , Window name 
void drawHist(Mat &hist, int hist_w, int hist_h,int type, string name)// This function is suitable for NORM_INF Method 
{
    
	int width = 2;
	Mat histImage = Mat::zeros(hist_h, hist_w, CV_8UC3);
	normalize(hist, hist, 1, 0, type, -1, Mat());
	for (int i = 1; i <= hist.rows; i++)
	{
    
		rectangle(histImage, Point(width*(i - 1), hist_h - 1),
			Point(width*i - 1, hist_h - cvRound(hist_h*hist.at<float>(i - 1)) - 1),
			Scalar(255, 255, 255), -1);
	}
	imshow(name, histImage);
}