QR Code detect and decode - QR 코드 리더

OpenCV 2019. 12. 15. 11:38 |
반응형

It shows how to detect and decode a QR Code.

OpenCV에서 QR코드를 감지하고 내용을 확인할 수 있다.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
#include <Windows.h>
#include <opencv2/opencv.hpp>
 
using namespace std;
using namespace cv;
 
int main()
{
    VideoCapture cap(0);
 
    if (!cap.isOpened()) {
        cerr << "Camera open failed." << endl;
 
        return -1;
    }
 
    QRCodeDetector detector;
 
    Mat frame;
    vector<Point> points;
    String msg;
 
    while (true) {
        cap >> frame;
 
        if (frame.empty()) {
            cerr << "Empty frame." << endl;
 
            break;
        }
 
        msg = detector.detectAndDecode(frame, points); // Both detects and decodes QR code.
 
        if (!msg.empty()) {
            polylines(frame, points, true, Scalar(0, 0, 255), 2);
            putText(frame, msg, Point(10, 30), FONT_HERSHEY_PLAIN, 2, Scalar(0, 0, 255), 2);
 
            if (msg.substr(0, 4) == "http") {
                imshow("QR Code", frame);
 
                if (MessageBox(NULL, (msg + " is a website address.\nDo you want to visit?").c_str(), "QR Code", MB_YESNO) == IDYES) {
                    ShellExecute(NULL, "open", msg.c_str(), NULL, NULL, SW_SHOW);
                    // Performs an operation on a specified file.
                }
                else {
                    continue;
                }
            }
        }
        else {
            putText(frame, "No QR code detected", Point(10, 30), FONT_HERSHEY_PLAIN, 2, Scalar(0, 0, 255), 2);
        }
 
        imshow("QR Code", frame);
 
        if (waitKey(10) == 27)
            break;
    }
 
    return 0;
}



Run the program. It says 'No QR code detected' at first.


QR code with a message.


QR code with a website address.


If the first 4 letters of the message are 'http', it opens the website with the default web browser.



반응형
저작자표시 비영리 변경금지

'OpenCV' 카테고리의 다른 글

OpenCV with Qt in Linux(Ubuntu) - 리눅스(우분투)에서 Qt로 OpenCV 이미지 디스플레이  (0) 2021.02.13
Haar-cascade Detection 얼굴 검출  (10) 2019.12.15
Simple color detection by Hue - Hue(HSV)값으로 특정색 검출하기  (0) 2019.11.17
Simple copy and save in cv::imshow() 간단하게 이미지 복사, 저장 하기  (0) 2019.11.17
Finding a homography matrix - OpenCV 두 평면 사이의 투영 변환 행렬  (0) 2019.11.03
Posted by J-sean
:

Simple color detection by Hue - Hue(HSV)값으로 특정색 검출하기

OpenCV 2019. 11. 17. 16:03 |
반응형

Hue is the color portion of the model, expressed as a number from 0 to 360 degrees:

Red: falls between 0 and 60 degrees.

Yellow: falls between 61 and 120 degrees.

Green: falls between 121-180 degrees.

Cyan: falls between 181-240 degrees.

Blue: falls between 241-300 degrees.

Magenta: falls between 301-360 degrees.


For HSV, OpenCV Hue range is [0,179], Saturation range is [0,255] and Value range is [0,255]. Different software uses different scales. So if you are comparing OpenCV values with them, you need to normalize these ranges.


HSV(Hue)를 이용하면 RGB를 이용하는 것 보다 간단히 특정색을 검출할 수 있다. OpenCV의 Hue값은 0~179 이다.



1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
#include <opencv2/opencv.hpp>
 
using namespace std;
using namespace cv;
 
int lowerHue = 40, upperHue = 80;    // Green
Mat src, src_hsv, mask, dst;
 
void OnHueChenaged(int pos, void* userdata)
{
    Scalar lowerb(lowerHue, 100, 0);
    Scalar upperb(upperHue, 255, 255);
 
    inRange(src_hsv, lowerb, upperb, mask);
    // Checks if array elements lie between the elements of two other arrays.
 
    dst.setTo(0);    // 매번 초기화 해 주지 않으면 이전에 선택한 색과 겹친다.
    src.copyTo(dst, mask);
    // The method copies the matrix data to another matrix. Before copying the data, the method invokes: m.create(this->size(), this->type());
    // so that the destination matrix is reallocated if needed.While m.copyTo(m); works flawlessly, the function does not handle the case of a
    // partial overlap between the sourceand the destination matrices. When the operation mask is specified, if the Mat::create call shown above
    // reallocates the matrix, the newly allocated matrix is initialized with all zeros before copying the data.
 
    imshow("mask", mask);
    imshow("dst", dst);
}
 
int main(int argc, char** argv)
{
    src = imread("candies.jpg", IMREAD_COLOR);
    if (src.empty()) {
        cerr << "Image load failed." << endl;
        
        return -1;
    }
 
    imshow("src", src);
 
    cvtColor(src, src_hsv, COLOR_BGR2HSV);
 
    namedWindow("mask");
    createTrackbar("Lower Hue", "mask", &lowerHue, 179, OnHueChenaged);
    createTrackbar("Upper Hue", "mask", &upperHue, 179, OnHueChenaged);
    OnHueChenaged(NULL, NULL);
 
    waitKey(0);
    
    return 0;
}




Original candy image.


Mask for green color.


Green candies detected.


반응형
저작자표시 비영리 변경금지

'OpenCV' 카테고리의 다른 글

Haar-cascade Detection 얼굴 검출  (10) 2019.12.15
QR Code detect and decode - QR 코드 리더  (0) 2019.12.15
Simple copy and save in cv::imshow() 간단하게 이미지 복사, 저장 하기  (0) 2019.11.17
Finding a homography matrix - OpenCV 두 평면 사이의 투영 변환 행렬  (0) 2019.11.03
Keypoint matching - OpenCV 키포인트 매칭  (0) 2019.11.02
Posted by J-sean
:

Simple copy and save in cv::imshow() 간단하게 이미지 복사, 저장 하기

OpenCV 2019. 11. 17. 11:07 |
반응형

This is a Windows backend only function but you can simply copy or save the image displayed with cv::imshow().


cv::imshow()로 이미지를 출력할 때 출력된 이미지를 간단히 클립 보드에 복사하거나 파일로 저장 할 수 있다.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
#include <opencv2/opencv.hpp>
 
using namespace std;
using namespace cv;
 
int main(int argc, char** argv)
{
    Mat src = imread("matera.jpg");
    if (src.empty()) {
        cerr << "Image load failed." << endl;
 
        return 0;
    }
 
    imshow("src", src);
    
    waitKey(0);
    
    return 0;
}



[Windows backend only]

  • Pressing Ctrl+C will copy the image to the clipboard.
  • Pressing Ctrl+S will show a dialog to save the image




반응형
저작자표시 비영리 변경금지

'OpenCV' 카테고리의 다른 글

QR Code detect and decode - QR 코드 리더  (0) 2019.12.15
Simple color detection by Hue - Hue(HSV)값으로 특정색 검출하기  (0) 2019.11.17
Finding a homography matrix - OpenCV 두 평면 사이의 투영 변환 행렬  (0) 2019.11.03
Keypoint matching - OpenCV 키포인트 매칭  (0) 2019.11.02
Detect, compute and draw keypoints - OpenCV 키포인트 찾기  (0) 2019.11.02
Posted by J-sean
:

Finding a homography matrix - OpenCV 두 평면 사이의 투영 변환 행렬

OpenCV 2019. 11. 3. 09:38 |
반응형

If we pass the set of points from the target and source images, FindHomography() will find the perspective transformation of that object. Then we can use perspectiveTransform() to find the object. It needs at least four correct points to find the transformation.


<Target>


<Source>



1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
#include <opencv2/opencv.hpp>
 
using namespace std;
using namespace cv;
 
int main(int argc, char** argv)
{
    Mat trg = imread("Target.jpg", IMREAD_GRAYSCALE);
    Mat src = imread("Source.jpg", IMREAD_GRAYSCALE);
    
    if (trg.empty() || src.empty()) {
        cerr << "Image load failed!" << endl;
        
        return -1;
    }
 
    Ptr<Feature2D> feature = ORB::create();
    
    vector<KeyPoint> trgKeypoints, srcKeypoints;
    Mat trgDesc, srcDesc;
    feature->detectAndCompute(trg, Mat(), trgKeypoints, trgDesc);
    feature->detectAndCompute(src, Mat(), srcKeypoints, srcDesc);
 
    Ptr<DescriptorMatcher> matcher = BFMatcher::create(NORM_HAMMING);
 
    vector<DMatch> matches;
    matcher->match(trgDesc, srcDesc, matches);
 
    sort(matches.begin(), matches.end());
    vector<DMatch> good_matches(matches.begin(), matches.begin() + 100);
 
    Mat dst;
    drawMatches(trg, trgKeypoints, src, srcKeypoints, good_matches, dst,
        Scalar::all(-1), Scalar(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
 
    vector<Point2f> trgPts, srcPts;
    for (size_t i = 0; i < good_matches.size(); i++) {
        trgPts.push_back(trgKeypoints[good_matches[i].queryIdx].pt);
        srcPts.push_back(srcKeypoints[good_matches[i].trainIdx].pt);
    }
 
    Mat H = findHomography(trgPts, srcPts, RANSAC);
    // Finds a perspective transformation between two planes.
 
    vector<Point2f> trgCorners, srcCorners;
    trgCorners.push_back(Point2f(0.f, 0.f));
    trgCorners.push_back(Point2f(trg.cols - 1.f, 0.f));
    trgCorners.push_back(Point2f(trg.cols - 1.f, trg.rows - 1.f));
    trgCorners.push_back(Point2f(0.f, trg.rows - 1.f));
    perspectiveTransform(trgCorners, srcCorners, H);
 
    vector<Point> dstCorners;
    for (Point2f pt : srcCorners) {
        dstCorners.push_back(Point(cvRound(pt.x + trg.cols), cvRound(pt.y)));
        // Move the corners to the right as the width of the Target image.
    }
 
    polylines(dst, dstCorners, true, Scalar(0, 255, 0), 3, LINE_AA);
 
    imshow("dst", dst);
 
    waitKey();
    
    return 0;
}



Close but not perfect. As mentioned above, it needs correct points to find the transformation.


반응형
저작자표시 비영리 변경금지

'OpenCV' 카테고리의 다른 글

Simple color detection by Hue - Hue(HSV)값으로 특정색 검출하기  (0) 2019.11.17
Simple copy and save in cv::imshow() 간단하게 이미지 복사, 저장 하기  (0) 2019.11.17
Keypoint matching - OpenCV 키포인트 매칭  (0) 2019.11.02
Detect, compute and draw keypoints - OpenCV 키포인트 찾기  (0) 2019.11.02
Screen capture - Windows API, OpenCV로 화면 캡쳐하기  (0) 2019.10.28
Posted by J-sean
:

Keypoint matching - OpenCV 키포인트 매칭

OpenCV 2019. 11. 2. 23:48 |
반응형


Keypoint matching.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
#include <opencv2/opencv.hpp>
 
using namespace std;
using namespace cv;
 
int main(int argc, char** argv)
{
    Mat trg = imread("Target.jpg", IMREAD_GRAYSCALE);
    Mat src = imread("Source.jpg", IMREAD_GRAYSCALE);
    
    if (trg.empty() || src.empty()) {
        cerr << "Image load failed!" << endl;
        
        return -1;
    }
 
    Ptr<Feature2D> feature = ORB::create();
    
    vector<KeyPoint> trgKeypoints, srcKeypoints;
    Mat trgDesc, srcDesc;
    feature->detectAndCompute(trg, Mat(), trgKeypoints, trgDesc);
    feature->detectAndCompute(src, Mat(), srcKeypoints, srcDesc);
    // Detects keypoints and computes the descriptors.
 
    Ptr<DescriptorMatcher> matcher = BFMatcher::create(NORM_HAMMING);
    // Brute-force matcher create method.
 
    vector<DMatch> matches;
    // Class for matching keypoint descriptors.
    matcher->match(trgDesc, srcDesc, matches);
    // Finds the best match for each descriptor from a query set.
 
    sort(matches.begin(), matches.end());
    vector<DMatch> good_matches(matches.begin(), matches.begin() + 100);
 
    Mat dst;
    drawMatches(trg, trgKeypoints, src, srcKeypoints, good_matches, dst,
        Scalar::all(-1), Scalar(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
    // Draws the found matches of keypoints from two images.
 
    imshow("dst", dst);
 
    waitKey();
    
    return 0;
}




100 best matches.


반응형
저작자표시 비영리 변경금지

'OpenCV' 카테고리의 다른 글

Simple copy and save in cv::imshow() 간단하게 이미지 복사, 저장 하기  (0) 2019.11.17
Finding a homography matrix - OpenCV 두 평면 사이의 투영 변환 행렬  (0) 2019.11.03
Detect, compute and draw keypoints - OpenCV 키포인트 찾기  (0) 2019.11.02
Screen capture - Windows API, OpenCV로 화면 캡쳐하기  (0) 2019.10.28
Windows dialog-based OpenCV program 윈도우 대화상자 OpenCV 프로그램 만들기  (2) 2019.10.26
Posted by J-sean
:

Detect, compute and draw keypoints - OpenCV 키포인트 찾기

OpenCV 2019. 11. 2. 22:51 |
반응형

Detect, compute and draw key points.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
#include <opencv2/opencv.hpp>
 
using namespace std;
using namespace cv;
 
int main(int argc, char** argv)
{
    Mat src = imread("Source.jpg", IMREAD_GRAYSCALE);
    
    if (src.empty()) {
        cerr << "Image load failed!" << endl;
        
        return -1;
    }
 
    Ptr<Feature2D> feature = ORB::create();
    // static Ptr<ORB> cv::ORB::create(int nfeatures = 500, float scaleFactor = 1.2f, int nlevels = 8,
    // int edgeThreshold = 31, int firstLevel = 0, int WTA_K = 2, ORB::ScoreType scoreType = ORB::HARRIS_SCORE,
    // int patchSize = 31, int fastThreshold = 20)
 
    vector<KeyPoint> keypoints;
    feature->detect(src, keypoints);
    // Detects keypoints in an image (first variant) or image set (second variant).
 
    Mat desc;
    feature->compute(src, keypoints, desc);
    // Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).
 
    cout << "keypoints.size(): " << keypoints.size() << endl;
    cout << "desc.size(): " << desc.size() << endl;
 
    Mat dst;
    drawKeypoints(src, keypoints, dst, Scalar::all(-1), DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
    // Draws keypoints.
 
    imshow("src", src);
    imshow("dst", dst);
 
    waitKey();
    
    return 0;
}




Sizes of keypoints and descriptors.


Source image.


Keypoints with sizes and orientations.


반응형
저작자표시 비영리 변경금지

'OpenCV' 카테고리의 다른 글

Finding a homography matrix - OpenCV 두 평면 사이의 투영 변환 행렬  (0) 2019.11.03
Keypoint matching - OpenCV 키포인트 매칭  (0) 2019.11.02
Screen capture - Windows API, OpenCV로 화면 캡쳐하기  (0) 2019.10.28
Windows dialog-based OpenCV program 윈도우 대화상자 OpenCV 프로그램 만들기  (2) 2019.10.26
Convert Mat to Bitmap for Windows applications with GDI+ and surface crack detection - OpenCV Mat에서 비트맵으로 변환과 표면 크랙 검출  (0) 2019.10.26
Posted by J-sean
:

Screen capture - Windows API, OpenCV로 화면 캡쳐하기

OpenCV 2019. 10. 28. 19:57 |
반응형

Screen capture with Windows API and OpenCV.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
#include <Windows.h>
#include <iostream>
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
 
using namespace std;
using namespace cv;
 
class hWnd2Mat
{
public:
    hWnd2Mat(HWND hWindow, float scale = 1);
    virtual ~hWnd2Mat();
    virtual void Read();
    Mat capture;
 
private:
    HWND hWnd;
    HDC hWindowDC, hWindowCompatibleDC;
    int height, width, srcHeight, srcWidth;
    HBITMAP hBitmap;
    BITMAPINFOHEADER bi;
};
 
hWnd2Mat::hWnd2Mat(HWND hWindow, float scale)
{
    hWnd = hWindow;
    hWindowDC = GetDC(hWnd);
    hWindowCompatibleDC = CreateCompatibleDC(hWindowDC);
    SetStretchBltMode(hWindowCompatibleDC, COLORONCOLOR);
 
    RECT windowsize;    // get the height and width of the screen
    GetClientRect(hWnd, &windowsize);
 
    srcHeight = windowsize.bottom;
    srcWidth = windowsize.right;
    height = (int)(windowsize.bottom * scale);
    width = (int)(windowsize.right * scale);
 
    capture.create(height, width, CV_8UC4);
 
    // create a bitmap
    hBitmap = CreateCompatibleBitmap(hWindowDC, width, height);
    bi.biSize = sizeof(BITMAPINFOHEADER);    // http://msdn.microsoft.com/en-us/library/windows/window/dd183402%28v=vs.85%29.aspx
    bi.biWidth = width;
    bi.biHeight = -height;  //this is the line that makes it draw upside down or not
    bi.biPlanes = 1;
    bi.biBitCount = 32;
    bi.biCompression = BI_RGB;
    bi.biSizeImage = 0;
    bi.biXPelsPerMeter = 0;
    bi.biYPelsPerMeter = 0;
    bi.biClrUsed = 0;
    bi.biClrImportant = 0;
 
    // use the previously created device context with the bitmap
    SelectObject(hWindowCompatibleDC, hBitmap);
};
 
void hWnd2Mat::Read()
{
    // copy from the window device context to the bitmap device context
    StretchBlt(hWindowCompatibleDC, 0, 0, width, height, hWindowDC, 0, 0, srcWidth, srcHeight, SRCCOPY);
    //change SRCCOPY to NOTSRCCOPY for wacky colors!
    GetDIBits(hWindowCompatibleDC, hBitmap, 0, height, capture.data, (BITMAPINFO*)&bi, DIB_RGB_COLORS);
    //copy from hWindowCompatibleDC to hBitmap
};
 
hWnd2Mat::~hWnd2Mat()
{
    DeleteObject(hBitmap);
    DeleteDC(hWindowCompatibleDC);
    ReleaseDC(hWnd, hWindowDC);
};
 
int main()
{
    HWND hWndDesktop = GetDesktopWindow();
    hWnd2Mat desktop(hWndDesktop, 1);    // scale = 1
 
    cout << "Screen capure in 3 seconds." << endl;
    
    for (int i = 3; i > 0; i--)
    {
        cout << i << ".." << endl;
        Sleep(1000);
    }
 
    desktop.Read();
    imshow("Capture", desktop.capture);
 
    waitKey();
 
    return 0;
}



It captures your desktop image in 3 seconds.


반응형
저작자표시 비영리 변경금지

'OpenCV' 카테고리의 다른 글

Keypoint matching - OpenCV 키포인트 매칭  (0) 2019.11.02
Detect, compute and draw keypoints - OpenCV 키포인트 찾기  (0) 2019.11.02
Windows dialog-based OpenCV program 윈도우 대화상자 OpenCV 프로그램 만들기  (2) 2019.10.26
Convert Mat to Bitmap for Windows applications with GDI+ and surface crack detection - OpenCV Mat에서 비트맵으로 변환과 표면 크랙 검출  (0) 2019.10.26
Windows dialog based OpenCV Perspective Transform - 윈도우 다이얼로그 기반의 OpenCV Perspective Transform  (0) 2019.10.20
Posted by J-sean
:

Windows dialog-based OpenCV program 윈도우 대화상자 OpenCV 프로그램 만들기

OpenCV 2019. 10. 26. 18:32 |
반응형

Build a Windows dialog-based OpenCV program.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
#include <Windows.h>
#include <gdiplus.h>
#include <opencv2/opencv.hpp>
#include "resource.h"
 
#pragma comment(lib, "gdiplus")
 
using namespace cv;
using namespace Gdiplus;
 
INT_PTR MainDlgProc(HWND hDlg, UINT iMessage, WPARAM wParam, LPARAM lParam);
HWND hDlgMain;
 
VideoCapture cap;
Mat frame;
RECT invalidateRect;


Prepare necessities.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
int APIENTRY WinMain(HINSTANCE hInstance, HINSTANCE hPrevInstance, LPSTR lpszCmdParam, int nCmdShow)
{
    ULONG_PTR gpToken;
    GdiplusStartupInput gpsi;
 
    if (GdiplusStartup(&gpToken, &gpsi, NULL) != Ok) {
        MessageBox(NULL, TEXT("GDI+ start-up error."), TEXT("GDI+ Error"), MB_OK);
    }
 
    DialogBox(hInstance, MAKEINTRESOURCE(IDD_DIALOG1), HWND_DESKTOP, MainDlgProc);
    
    GdiplusShutdown(gpToken);
 
    return 0;
}


Start GDI+ and create a modal dialog box from a dialog template resource.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
bool initCamera()
{
    cap.open(0);
    if (cap.isOpened()) {
        invalidateRect = { 0, 0, cvRound(cap.get(CAP_PROP_FRAME_WIDTH)), cvRound(cap.get(CAP_PROP_FRAME_HEIGHT)) };
 
        return true;
    }
    else {
        MessageBox(NULL, TEXT("Camera open failed."), TEXT("Camera Error"), MB_OK);
 
        return false;
    }    
}


Initiate a camera and set the windows update region.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
void OnPaint(HDC hdc)
{
    Graphics G(hdc);
 
    cap >> frame;
    if (frame.empty()) {
        TextOut(hdc, 300, 240, "No frame to show", 8);
 
        return;
    }
 
    if (IsDlgButtonChecked(hDlgMain, IDC_CHECK1) == BST_CHECKED) {
        cvtColor(frame, frame, COLOR_BGR2GRAY);
        Canny(frame, frame, 50, 100);
        cvtColor(frame, frame, COLOR_GRAY2BGRA);
    }
    else {
        cvtColor(frame, frame, COLOR_BGR2BGRA);
    }
 
    Bitmap bitmap(frame.size().width, frame.size().height, frame.step1(), PixelFormat32bppARGB, frame.data);
    G.DrawImage(&bitmap, 0, 0, bitmap.GetWidth(), bitmap.GetHeight());
}


Process each frame and draw it. 


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
INT_PTR MainDlgProc(HWND hDlg, UINT iMessage, WPARAM wParam, LPARAM lParam)
{
    HDC hdc;
    PAINTSTRUCT ps;
    static HANDLE hTimer;
 
    switch (iMessage) {
    case WM_INITDIALOG:
        hDlgMain = hDlg;
        if (initCamera()) {
            hTimer = (HANDLE)SetTimer(hDlg, 1, 10, NULL);
        }
        else {
            hTimer = NULL;
        }
 
        return TRUE;
 
    case WM_COMMAND:
        switch (LOWORD(wParam)) {
        case IDOK:
 
            return TRUE;
 
        case IDCANCEL:
            if (hTimer != NULL) {
                KillTimer(hDlg, 1);
            }
            EndDialog(hDlg, IDCANCEL);
 
            return TRUE;
        }
 
    case WM_PAINT:
        hdc = BeginPaint(hDlg, &ps);
        OnPaint(hdc);
        EndPaint(hDlg, &ps);
 
        return TRUE;
 
    case WM_TIMER:
        InvalidateRect(hDlg, &invalidateRect, FALSE);
        return 0;
    }
 
    return FALSE;
}


Create a timer and define the necessary variables and handle window messages.



Run the program.


Check 'Canny Edge Detection'.


반응형
저작자표시 비영리 변경금지

'OpenCV' 카테고리의 다른 글

Detect, compute and draw keypoints - OpenCV 키포인트 찾기  (0) 2019.11.02
Screen capture - Windows API, OpenCV로 화면 캡쳐하기  (0) 2019.10.28
Convert Mat to Bitmap for Windows applications with GDI+ and surface crack detection - OpenCV Mat에서 비트맵으로 변환과 표면 크랙 검출  (0) 2019.10.26
Windows dialog based OpenCV Perspective Transform - 윈도우 다이얼로그 기반의 OpenCV Perspective Transform  (0) 2019.10.20
Simple motion detection with OpenCV - 간단한 움직임 감지  (2) 2019.09.15
Posted by J-sean
:

티스토리툴바