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| //
// Created by zj on 19-11-24.
//
#include "opencv2/highgui.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
#include <array>
using namespace std;
using namespace cv;
const static array<Scalar, 3> colors = {
Scalar(255, 0, 0),
Scalar(0, 255, 0),
Scalar(0, 0, 255)
};
/**
* 计算颜色直方图，图像取值固定为[0, 255]
* @param src CV_8UC1或CV_8UC3大小图像
* @param histograms 直方图向量
* @param bins 直方图大小
*/
void calc_color_hist(const Mat &src, vector<Mat> &histograms, int bins) {
int channels = src.channels();
vector<Mat> img_planes;
if (channels == 3) {
split(src, img_planes);
} else {
// gray
img_planes.emplace_back(src);
}
float range[] = {0, 256}; //the upper boundary is exclusive
const float *histRange = {range};
bool uniform = true, accumulate = false;
for (int i = 0; i < channels; i++) {
Mat hist;
calcHist(&img_planes[i], 1, nullptr, Mat(), hist, 1, &bins, &histRange, uniform, accumulate);
// cout << hist.type() << endl;
histograms.emplace_back(hist);
}
}
/**
* 绘制直方图，首先对直方图标准化，再按比例绘制线条
*/
void draw_color_hist(const vector<Mat> &histograms, Mat &histImage, int bins) {
int hist_w = 512, hist_h = 400;
histImage = Mat(hist_h, hist_w, CV_8UC3, Scalar(0, 0, 0));
int bin_w = cvRound((double) hist_w / bins);
for (int i = 0; i < histograms.size(); i++) {
Mat hist = histograms[i];
Mat hist_tmp;
// 标准化直方图，取值为[0.0, hist_h]
normalize(hist, hist_tmp, 0, histImage.rows, NORM_MINMAX, -1, Mat());
// cout << hist_tmp.type() << endl;
Scalar color = colors[i % colors.size()];
for (int i = 1; i < bins; i++) {
line(histImage,
Point(bin_w * (i - 1), hist_h - cvRound(hist_tmp.at<float>(i - 1))),
Point(bin_w * (i), hist_h - cvRound(hist_tmp.at<float>(i))),
color,
2, 8, 0);
}
}
}
/**
* 手动计算颜色直方图
* @param src CV_8UC1或CV_8UC3
* @param histograms 颜色直方图向量
* @param bins 直方图大小
*/
void calc_color_hist_manully(const Mat &src, vector<Mat> &histograms, int bins) {
int channels = src.channels();
float ranges[] = {0.0, 256.0};
// 计算每个bin的取值范围
double range = (ranges[1] - ranges[0]) / bins;
// 分离图像
vector<Mat> img_planes;
if (channels == 1) {
img_planes.emplace_back(src);
} else {
// 分离3通道
split(src, img_planes);
}
// 遍历所有通道，计算颜色直方图
for (int i = 0; i < channels; i++) {
Mat hist = Mat::zeros(1, bins, CV_32F);
auto *hdata = hist.ptr<float>(0);
Mat plane = img_planes[i];
// 遍历所有像素，从左到右，从上到下
for (int y = 0; y < plane.rows; y++) {
auto *pdata = plane.ptr<uchar>(y);
for (int x = 0; x < plane.cols; x++) {
hdata[cvFloor(static_cast<int>(pdata[x]) / range)] += 1;
}
}
histograms.emplace_back(hist);
}
}
/**
* 绘制直方图，首先手动对直方图标准化，再按比例绘制线条
* @param histograms 直方图列表
* @param histImage 绘制直方图
* @param bins 直方图大小
*/
void draw_color_hist_manully(const vector<Mat> &histograms, Mat &histImage, int bins) {
int hist_w = 512, hist_h = 400;
histImage = Mat(hist_h, hist_w, CV_8UC3, Scalar(0, 0, 0));
auto channels = histograms.size();
// 手动标准化直方图
vector<Mat> hist_tmps;
for (int i = 0; i < channels; i++) {
double min, max;
cv::minMaxLoc(histograms[i], &min, &max);
Mat hist_tmp = Mat::zeros(histograms[i].size(), CV_32F);
auto *hdata = histograms[i].ptr<float>(0);
auto *hdata_tmp = hist_tmp.ptr<float>(0);
for (int j = 0; j < bins; j++) {
hdata_tmp[j] = static_cast<float>(hist_h * (hdata[j] - min) / (max - min));
}
hist_tmps.emplace_back(hist_tmp);
}
int bin_w = cvRound(1.0 * hist_w / bins);
for (int i = 0; i < channels; i++) {
Scalar color = colors[i % colors.size()];
auto *hdata = hist_tmps[i].ptr<float>(0);
for (int j = 1; j < bins; j++) {
line(histImage,
Point(bin_w * (j - 1), cvRound(hist_h - hdata[j - 1])),
Point(bin_w * (j), cvRound(hist_h - hdata[j])),
color,
2, 8, 0);
}
}
}
int main(int argc, char **argv) {
CommandLineParser parser(argc, argv, "{@input | ../lena.jpg | input image}");
Mat src = imread(parser.get<String>("@input"), IMREAD_COLOR);
if (src.empty()) {
return -1;
}
// Mat gray;
// cvtColor(src, gray, COLOR_BGR2GRAY);
// src = gray;
int bins = 256;
vector<Mat> histograms, histograms2;
Mat histImage, histImage2;
// 调用OpenCV提供的直方图计算和标准化函数
double t1 = (double) getTickCount();
calc_color_hist(src, histograms, bins);
draw_color_hist(histograms, histImage, bins);
// 手动计算和标准化直方图
double t2 = (double) getTickCount();
calc_color_hist_manully(src, histograms2, bins);
draw_color_hist_manully(histograms2, histImage2, bins);
double t3 = (double) getTickCount();
double time1 = (t2 - t1) / getTickFrequency();
double time2 = (t3 - t2) / getTickFrequency();
cout << time1 << endl;
cout << time2 << endl;
// 判断绘制图像是否相等
cv::Mat diff = histImage != histImage2;
cout << sum(diff) << endl;
imshow("Source image", src);
imshow("OpenCV API", histImage);
imshow("手动实现", histImage2);
waitKey();
return 0;
}
|
