calcHist(&hsv_planes2[0], 1, channels, Mat(), hist2, 2, histSize, ranges, true, false);是什么
时间: 2024-05-29 21:11:45 浏览: 6
)The calcHist() function is an OpenCV function used to calculate the histogram of an image. A histogram is a graphical representation of the distribution of pixel intensities in an image. The calcHist() function takes an input image and returns a histogram of the image. The function allows the user to specify the number of bins for the histogram, the range of pixel values to be considered, and the channel(s) of the image to be used for calculating the histogram. The function returns a multi-dimensional array representing the histogram.
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解释calcHist(&hsv_planes2[0], 1, channels, Mat(), hist2, 2, histSize, ranges, true, false);
calcHist是OpenCV中的一个函数,用于计算一幅图像的直方图。直方图是一种统计图形,用于表示一组数据的分布情况。在图像处理中,直方图可以用于描述图像中像素的亮度分布情况。
calcHist函数的参数包括输入图像、通道数、掩码、直方图尺寸、像素值范围和是否均衡化等。函数返回一个一维数组,表示图像的直方图。
例如,以下代码可以计算一幅灰度图像的直方图:
```
cv::Mat image = cv::imread("image.png", cv::IMREAD_GRAYSCALE);
cv::Mat hist;
int histSize = 256;
float range[] = {0, 256};
const float* histRange = {range};
cv::calcHist(&image, 1, 0, cv::Mat(), hist, 1, &histSize, &histRange);
```
这里使用cv::imread函数读取一幅灰度图像,然后使用cv::calcHist函数计算图像的直方图。直方图的尺寸为256,表示像素值的范围为0到255。
#include <iostream> #include <opencv2/imgcodecs.hpp> #include <opencv2/imgproc.hpp> #include <opencv2/videoio.hpp> #include <opencv2/highgui.hpp> #include <opencv2/video.hpp> #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui_c.h> using namespace cv; using namespace std; int main(int argc, char** argv) { VideoCapture capture("D:/dvp/sample/dataset/traffic.mp4"); if (!capture.isOpened()) { //error in opening the video input cerr << "Unable to open file!" << endl; return 0; } Mat frame, roi, hsv_roi, mask; // take first frame of the video capture >> frame; // setup initial location of window Rect track_window(300, 200, 100, 50); // simply hardcoded the values // set up the ROI for tracking roi = frame(track_window); cvtColor(roi, hsv_roi, COLOR_BGR2HSV); inRange(hsv_roi, Scalar(0, 60, 32), Scalar(180, 255, 255), mask); float range_[] = { 0, 180 }; const float* range[] = { range_ }; Mat roi_hist; int histSize[] = { 180 }; int channels[] = { 0 }; calcHist(&hsv_roi, 1, channels, mask, roi_hist, 1, histSize, range); normalize(roi_hist, roi_hist, 0, 255, NORM_MINMAX); // Setup the termination criteria, either 10 iteration or move by atleast 1 pt TermCriteria term_crit(TermCriteria::EPS | TermCriteria::COUNT, 10, 1); while (true) { Mat hsv, dst; capture >> frame; if (frame.empty()) break; cvtColor(frame, hsv, COLOR_BGR2HSV); calcBackProject(&hsv, 1, channels, roi_hist, dst, range); // apply meanshift to get the new location meanShift(dst, track_window, term_crit); // Draw it on image rectangle(frame, track_window, 255, 2); imshow("img2", frame); setMouseCallback("img2", onMouse, 0); int keyboard = waitKey(30); if (keyboard == 'q' || keyboard == 27) break; } }帮我更改此段代码,使其能够通过gui使用鼠标来框选指定区域
以下是修改后的代码,可以通过GUI使用鼠标来框选指定区域:
```
#include <iostream>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/video.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui_c.h>
using namespace cv;
using namespace std;
Rect box; //定义一个矩形框,用于记录鼠标选择的区域
bool drawing_box = false; //标记是否正在通过鼠标绘制矩形框
void draw_box(Mat& img, Rect box)
{
//绘制矩形框
rectangle(img, box.tl(), box.br(), Scalar(0, 0, 255), 2);
}
void onMouse(int event, int x, int y, int flags, void* param)
{
Mat& image = *(Mat*)param;
switch (event)
{
case EVENT_MOUSEMOVE:
if (drawing_box)
{
//更新矩形框位置
box.width = x - box.x;
box.height = y - box.y;
}
break;
case EVENT_LBUTTONDOWN:
//开始绘制矩形框
drawing_box = true;
box = Rect(x, y, 0, 0);
break;
case EVENT_LBUTTONUP:
//结束绘制矩形框
drawing_box = false;
if (box.width < 0)
{
box.x += box.width;
box.width *= -1;
}
if (box.height < 0)
{
box.y += box.height;
box.height *= -1;
}
draw_box(image, box);
break;
}
}
int main(int argc, char** argv)
{
VideoCapture capture("D:/dvp/sample/dataset/traffic.mp4");
if (!capture.isOpened()) {
//error in opening the video input
cerr << "Unable to open file!" << endl;
return 0;
}
Mat frame, roi, hsv_roi, mask;
// take first frame of the video
capture >> frame;
namedWindow("img2");
setMouseCallback("img2", onMouse, &frame);
while (true) {
capture >> frame;
if (frame.empty()) break;
if (!box.empty()) {
// set up the ROI for tracking
roi = frame(box);
cvtColor(roi, hsv_roi, COLOR_BGR2HSV);
inRange(hsv_roi, Scalar(0, 60, 32), Scalar(180, 255, 255), mask);
float range_[] = { 0, 180 };
const float* range[] = { range_ };
Mat roi_hist;
int histSize[] = { 180 };
int channels[] = { 0 };
calcHist(&hsv_roi, 1, channels, mask, roi_hist, 1, histSize, range);
normalize(roi_hist, roi_hist, 0, 255, NORM_MINMAX);
// Setup the termination criteria, either 10 iteration or move by atleast 1 pt
TermCriteria term_crit(TermCriteria::EPS | TermCriteria::COUNT, 10, 1);
Mat hsv, dst;
cvtColor(frame, hsv, COLOR_BGR2HSV);
calcBackProject(&hsv, 1, channels, roi_hist, dst, range);
// apply meanshift to get the new location
meanShift(dst, box, term_crit);
// Draw it on image
rectangle(frame, box, 255, 2);
}
imshow("img2", frame);
int keyboard = waitKey(30);
if (keyboard == 'q' || keyboard == 27) break;
}
return 0;
}
```
在主函数中,我们添加了一个名为“img2”的窗口,并将其用作鼠标事件的回调函数。在主循环中,我们检查矩形框是否已经被绘制,如果是,则设置ROI并进行跟踪。最后,在每个循环迭代中,我们都显示图像,并等待用户按下“q”或“ESC”键退出程序。
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