#include<opencv2/opencv.hpp> using namespace cv; using namespace std; int main() { Mat src; // set a src lei src = imread("C:/Users\520\Desktop\image", IMREAD_UNCHANGED); if (!src.data) { cout << "could not load image..4." << endl; return -1; } namedWindow("input image", WINDOW_AUTOSIZE); imshow("input image", src); waitKey(0); return 0; }
时间: 2024-03-04 09:49:07 浏览: 15
您的代码中存在一个问题,即在读取图像的路径时,路径中的反斜杠(\)没有使用转义符号,会导致编译器无法正确识别路径。
您可以将读取图像的路径改为以下形式:
```
src = imread("C:/Users/520/Desktop/image.png", IMREAD_UNCHANGED);
```
另外,您的代码中没有指定要读取的图像的文件名和文件格式,这可能会导致读取失败。请确保指定了正确的文件名和文件格式(例如image.png、image.jpg等)。
如果您还遇到其他问题,请提供详细的报错信息,我可以更好地帮助您解决问题。
相关问题
#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。
调用freetype在opencv图片上绘制文字例程
我可以帮您解决这个问题。您可以参考以下代码示例:
```
#include <ft2build.h>
#include FT_FREETYPE_H
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
using namespace cv;
int main()
{
Mat img = Mat::zeros(Size(800, 600), CV_8UC3);
FT_Library ft;
if (FT_Init_FreeType(&ft))
{
std::cerr << "Error initializing FreeType library" << std::endl;
return -1;
}
FT_Face face;
if (FT_New_Face(ft, "arial.ttf", 0, &face)) // "arial.ttf"为您所用字体文件的路径
{
std::cerr << "Error loading font" << std::endl;
return -1;
}
FT_Set_Pixel_Sizes(face, 0, 48);
putText(img, "Hello, world!", Point(50, 50), FONT_HERSHEY_SIMPLEX, 1, Scalar(255, 255, 255), 2, LINE_8);
FT_Done_Face(face);
FT_Done_FreeType(ft);
imshow("Image", img);
waitKey(0);
return 0;
}
```
这段代码使用FreeType库在OpenCV图片上绘制“Hello, world!”文字,并将结果显示出来。请确保要在程序所在目录下有相应的字体文件。