这个opencv函数是如何在c++中解释的
How this opencv function explained in c++
我确实需要了解这个函数是如何工作的，尤其是在文档中的所有函数中。以下是opencv中函数的文档：这只是其中之一。
int cv::createTrackbar (const String & trackbarname, const String & winname,
int * value, int count, TrackbarCallback onChange = 0,void * userdata = 0)
这是有人写的一个有效的代码：
createTrackbar("H_MIN", trackbarWindowName, &H_MIN, H_MAX, on_trackbar);createTrackbar("H_MAX", trackbarWindowName, &H_MAX, H_MAX, on_trackbar);createTrackbar("S_MIN", trackbarWindowName, &S_MIN, S_MAX, on_trackbar);createTrackbar("S_MAX", trackbarWindowName, &S_MAX, S_MAX, on_trackbar);createTrackbar("V_MIN", trackbarWindowName, &V_MIN, V_MAX, on_trackbar);createTrackbar("V_MAX", trackbarWindowName, &V_MAX, V_MAX, on_trackbar);
现在我的问题是：
- 有6个论点，为什么那个家伙只写了5个论点
- 文档一开始说
int，为什么createTrackbar没有int &在const String & trackbarname中的意思是什么，我可以理解"H_MIN"是一个常量字符串，它是一个trackbarname，但&是什么意思，为什么不把&也写在代码中呢- 同样的问题也出现在
const String & winname中，即&是均值吗 - 在第三个参数
int * value中，指向int的值指针，并在全局变量中声明，为什么写起来如此复杂？我们不能只写intH_MIN = 0（如果我是对的），H_MAX = 256吗 - 关于第四个参数
int count，那个代码到底在哪里 - 第五个论点，
TrackbarCallback onChange = 0，我不明白 - 最后一个论点，
void * userdata = 0他写了一个名为on_trackbar的函数，只写了这个：void on_trackbar(int, void*){}我也不明白
很抱歉问得太多了，我只需要真正理解如何正确地或自定义地从文档中编写函数。
这是所有的代码：
//objectTrackingTutorial.cpp
//Written by Kyle Hounslow 2013
//Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software")
//, to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense,
//and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
//The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
//THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
//FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
//LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
//IN THE SOFTWARE.
#include <sstream>
#include <string>
#include <iostream>
#include <opencvhighgui.h>
#include <opencvcv.h>
#include <opencv2opencv.hpp>
#include <vector>
using namespace cv;
using namespace std;
//initial min and max HSV filter values.
//these will be changed using trackbars
int H_MIN = 0;
int H_MAX = 256;
int S_MIN = 0;
int S_MAX = 256;
int V_MIN = 0;
int V_MAX = 256;
//default capture width and height
const int FRAME_WIDTH = 640;
const int FRAME_HEIGHT = 480;
//max number of objects to be detected in frame
const int MAX_NUM_OBJECTS = 50;
//minimum and maximum object area
const int MIN_OBJECT_AREA = 20 * 20;
const int MAX_OBJECT_AREA = FRAME_HEIGHT*FRAME_WIDTH / 1.5;
//names that will appear at the top of each window
const string windowName = "Original Image";
const string windowName1 = "HSV Image";
const string windowName2 = "Thresholded Image";
const string windowName3 = "After Morphological Operations";
const string trackbarWindowName = "Trackbars";
void on_trackbar(int, void*)
{//This function gets called whenever a
// trackbar position is changed
}
string intToString(int number){
std::stringstream ss;
ss << number;
return ss.str();
}
void createTrackbars(){
//create window for trackbars
namedWindow(trackbarWindowName, 0);
//create memory to store trackbar name on window
char TrackbarName[50];
sprintf_s(TrackbarName, "H_MIN", H_MIN);
sprintf_s(TrackbarName, "H_MAX", H_MAX);
sprintf_s(TrackbarName, "S_MIN", S_MIN);
sprintf_s(TrackbarName, "S_MAX", S_MAX);
sprintf_s(TrackbarName, "V_MIN", V_MIN);
sprintf_s(TrackbarName, "V_MAX", V_MAX);
//create trackbars and insert them into window
//3 parameters are: the address of the variable that is changing when the trackbar is moved(eg.H_LOW),
//the max value the trackbar can move (eg. H_HIGH),
//and the function that is called whenever the trackbar is moved(eg. on_trackbar)
// ----> ----> ---->
createTrackbar("H_MIN", trackbarWindowName, &H_MIN, H_MAX, on_trackbar);
createTrackbar("H_MAX", trackbarWindowName, &H_MAX, H_MAX, on_trackbar);
createTrackbar("S_MIN", trackbarWindowName, &S_MIN, S_MAX, on_trackbar);
createTrackbar("S_MAX", trackbarWindowName, &S_MAX, S_MAX, on_trackbar);
createTrackbar("V_MIN", trackbarWindowName, &V_MIN, V_MAX, on_trackbar);
createTrackbar("V_MAX", trackbarWindowName, &V_MAX, V_MAX, on_trackbar);
}
void drawObject(int x, int y, Mat &frame){
//use some of the openCV drawing functions to draw crosshairs
//on your tracked image!
//UPDATE:JUNE 18TH, 2013
//added 'if' and 'else' statements to prevent
//memory errors from writing off the screen (ie. (-25,-25) is not within the window!)
circle(frame, Point(x, y), 20, Scalar(0, 255, 0), 2);
if (y - 25>0)
line(frame, Point(x, y), Point(x, y - 25), Scalar(0, 255, 0), 2);
else line(frame, Point(x, y), Point(x, 0), Scalar(0, 255, 0), 2);
if (y + 25<FRAME_HEIGHT)
line(frame, Point(x, y), Point(x, y + 25), Scalar(0, 255, 0), 2);
else line(frame, Point(x, y), Point(x, FRAME_HEIGHT), Scalar(0, 255, 0), 2);
if (x - 25>0)
line(frame, Point(x, y), Point(x - 25, y), Scalar(0, 255, 0), 2);
else line(frame, Point(x, y), Point(0, y), Scalar(0, 255, 0), 2);
if (x + 25<FRAME_WIDTH)
line(frame, Point(x, y), Point(x + 25, y), Scalar(0, 255, 0), 2);
else line(frame, Point(x, y), Point(FRAME_WIDTH, y), Scalar(0, 255, 0), 2);
putText(frame, intToString(x) + "," + intToString(y), Point(x, y + 30), 1, 1, Scalar(0, 255, 0), 2);
}
void morphOps(Mat &thresh){
//create structuring element that will be used to "dilate" and "erode" image.
//the element chosen here is a 3px by 3px rectangle
Mat erodeElement = getStructuringElement(MORPH_RECT, Size(3, 3));
//dilate with larger element so make sure object is nicely visible
Mat dilateElement = getStructuringElement(MORPH_RECT, Size(8, 8));
erode(thresh, thresh, erodeElement);
erode(thresh, thresh, erodeElement);
dilate(thresh, thresh, dilateElement);
dilate(thresh, thresh, dilateElement);
}
void trackFilteredObject(int &x, int &y, Mat threshold, Mat &cameraFeed){
Mat temp;
threshold.copyTo(temp);
//these two vectors needed for output of findContours
vector< vector<Point> > contours;
vector<Vec4i> hierarchy;
//find contours of filtered image using openCV findContours function
findContours(temp, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE);
//use moments method to find our filtered object
double refArea = 0;
bool objectFound = false;
if (hierarchy.size() > 0) {
int numObjects = hierarchy.size();
//if number of objects greater than MAX_NUM_OBJECTS we have a noisy filter
if (numObjects<10){
for (int index = 0; index >= 0; index = hierarchy[index][0]) {
Moments moment = moments((cv::Mat)contours[index]);
double area = moment.m00;
//if the area is less than 20 px by 20px then it is probably just noise
//if the area is the same as the 3/2 of the image size, probably just a bad filter
//we only want the object with the largest area so we safe a reference area each
//iteration and compare it to the area in the next iteration.
if (area>400 && area<FRAME_HEIGHT*FRAME_WIDTH/1.5 && area>refArea){
printf("%f n", area);
x = moment.m10 / area;
y = moment.m01 / area;
objectFound = true;
refArea = area;
}
else objectFound = false;
}
//let user know you found an object
if (objectFound == true){
putText(cameraFeed, "Tracking Object", Point(0, 50), 2, 1, Scalar(0, 255, 0), 2);
//draw object location on screen
drawObject(x, y, cameraFeed);
}
}
else putText(cameraFeed, "TOO MUCH NOISE! ADJUST FILTER", Point(0, 50), 1, 2, Scalar(0, 0, 255), 2);
}
}
int main(int argc, char* argv[])
{
//some boolean variables for different functionality within this
//program
bool trackObjects = true;
bool useMorphOps = true;
//Matrix to store each frame of the webcam feed
Mat cameraFeed;
//matrix storage for HSV image
Mat HSV;
//matrix storage for binary threshold image
Mat threshold;
//x and y values for the location of the object
int x = 0, y = 0;
//create slider bars for HSV filtering
createTrackbars();
//video capture object to acquire webcam feed
VideoCapture capture;
//open capture object at location zero (default location for webcam)
capture.open(0);
//set height and width of capture frame
capture.set(CV_CAP_PROP_FRAME_WIDTH, FRAME_WIDTH);
capture.set(CV_CAP_PROP_FRAME_HEIGHT, FRAME_HEIGHT);
//start an infinite loop where webcam feed is copied to cameraFeed matrix
//all of our operations will be performed within this loop
while (1){
//store image to matrix
capture.read(cameraFeed);
//convert frame from BGR to HSV colorspace
cvtColor(cameraFeed, HSV, COLOR_BGR2HSV);
//filter HSV image between values and store filtered image to
//threshold matrix
inRange(HSV, Scalar(H_MIN, S_MIN, V_MIN), Scalar(H_MAX, S_MAX, V_MAX), threshold);
//perform morphological operations on thresholded image to eliminate noise
//and emphasize the filtered object(s)
if (useMorphOps)
morphOps(threshold);
//pass in thresholded frame to our object tracking function
//this function will return the x and y coordinates of the
//filtered object
if (trackObjects)
trackFilteredObject(x, y, threshold, cameraFeed);
//show frames
imshow(windowName2, threshold);
imshow(windowName, cameraFeed);
imshow(windowName1, HSV);
//delay 30ms so that screen can refresh.
//image will not appear without this waitKey() command
waitKey(30);
}
return 0;
}
按顺序：
1） 最后一个参数userdata是默认值，它可以通过函数签名中的=0来查看。这意味着，如果不为参数指定值，它将被设置为默认值0。
2） createTrackbar的返回类型为int，但是，您不将createTrackbar设置为变量，从而忽略了这些数据，这在您的情况下是可以的。
3） &显示了通过引用传递。这意味着传递函数的变量可以在函数执行期间进行修改。请参阅此处以获取更多信息。
4） 与上述相同
5） 这不一定是全球性的。这里发生的事情是，您将一个整数的内存地址传递给函数。这将允许函数取消引用该内存地址处的内容。如果你不熟悉c和c++如何处理指针/引用/内存，你应该考虑对它进行一些研究，因为它是c编程不可或缺的概念。一个好的起点是这里。就这个变量的作用而言，本质上，它是一个变量的地址，你可以引用它，它会随着滑块的位置而更新，这样，如果你只是从滑块中获取值，你就不需要每次都调用滑块函数。
6） 计数是滑块上的最大位置。这在文档中很清楚。
7） 这个onchange方法是对一个函数的回调，该函数可以在轨迹条位置发生变化时执行。它默认为0，这意味着如果在轨迹条移动时不指定要调用的函数，则不会调用任何函数。如果你只是想获得轨迹条的值，看看我为第5点写了什么，然后使用value参数。
8） 这不是userdata参数。编译器能够看到，由于on_trackbar的类型，它实际上是onchange的参数。因此，他实际上将用户数据默认为0，并在轨迹条移动时具有功能。有关这方面的更多信息，您应该阅读c中的编译器时间多态性。关于它的好文章这里
看起来你还没有很好地掌握你的C和C++基础知识。我建议你读一本关于C或C++的书，因为你可以用你谈论的一些概念做一些非常强大的东西。祝你好运！
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