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CString CurrentDirectoryToCString() { TCHAR buff[MAX_PATH]; memset(buff, 0, MAX_PATH); ::GetCurrentDirectory(MAX_PATH, buff); CString strFolder = buff; return strFolder; }..
5/30/2018
How to get current directory in window application.
Example source code to get current directory in window application
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OpenCV, Dash line drawing example source code.
I can know all coordinate from A point to B point using "LineIterator" function in OpenCV.
So this source code is applied by this "LineIterator".
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So this source code is applied by this "LineIterator".
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Mat DrawDashLine(Mat inMat, Point start, Point end, int gap, Scalar color) { Mat rMat; rMat = inMat.clone(); cv::LineIterator it(rMat, start, end, 8); vector< pair<cv::Point, cv::Point> > vecPt_pair; vector< cv::Point > vecPt; Point A, B; A = start; for (int i = 0, j = 0; i < it.count; i++, it++) { if (i % gap == 0) { //update end point B = it.pos(); if(j%2) line(rMat, A, B, color, 2); //update start point A = B; j++; } } return rMat; } int main() { Mat img(500, 500, CV_8UC3); img.setTo(0); Mat rImg = DrawDashLine(img, Point(20, 20), Point(300, 300), 10, CV_RGB(255, 0, 0)); namedWindow("test", 0); cv::imshow("test", rImg); waitKey(0); return 0; }..
5/27/2018
OpenCV Integral Test source code
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int main(int, char) { Mat img = Mat(10, 10, CV_8UC1); randu(img, 0, 10); cout << "origin" << endl << img << endl; //int x=3, y=4, w=4, h=4; int x = 1, y = 1, w = 2, h = 2; int sum = 0; for (int i = 0; i < w; ++i) { for (int j = 0; j < h; ++j) { sum = sum + img.at<unsigned char>((y + j), (x + i)); } } printf("for loop : sum = %d \n", sum); /////////////////////////////////////////////////////////////////////// Mat integralImg; integral(img, integralImg, CV_64F); cout << endl << "integral" << endl << integralImg << endl; double p1 = integralImg.at<double>((y), (x)); double p2 = integralImg.at<double>((y), (x + w)); double p3 = integralImg.at<double>((y + h), (x)); double p4 = integralImg.at<double>((y + h), (x + w)); printf("\n p1:%lf, p2:%lf, p3:%lf, p4:%lf\n", p1, p2, p3, p4); printf("integral : sum = %lf \n", (p1 + p4) - (p2 + p3)); ////////////////////////////////////////////////////////////////////////// }...
result
AdaptiveThreshold test code in opencv
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#include "opencv2/opencv.hpp" #include "opencv2/highgui.hpp" #include "opencv2/cudaarithm.hpp" #include <iostream> #include <vector> #ifdef _DEBUG #pragma comment(lib, "opencv_core331d.lib") #pragma comment(lib, "opencv_highgui331d.lib") #pragma comment(lib, "opencv_imgcodecs331d.lib") #pragma comment(lib, "opencv_objdetect331d.lib") #pragma comment(lib, "opencv_imgproc331d.lib") #pragma comment(lib, "opencv_videoio331d.lib") #pragma comment(lib, "opencv_cudaarithm331d.lib") #else #pragma comment(lib, "opencv_core331.lib") #pragma comment(lib, "opencv_highgui331.lib") #pragma comment(lib, "opencv_imgcodecs331.lib") #pragma comment(lib, "opencv_objdetect331.lib") #pragma comment(lib, "opencv_imgproc331.lib") #pragma comment(lib, "opencv_videoio331.lib") #pragma comment(lib, "opencv_cudaarithm331.lib") #endif using namespace std; using namespace cv; int main(int, char) { namedWindow("img", 0); namedWindow("threshold", 0); namedWindow("mean_thres", 0); namedWindow("gauss_thres", 0); Mat img = imread("otzu.jpg"); Mat gray, binary, binary1, binary2; cvtColor(img, gray, CV_RGB2GRAY); threshold(gray, binary, 128, 255, CV_THRESH_BINARY); adaptiveThreshold(gray, binary1, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 5, 5); adaptiveThreshold(gray, binary2, 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, 5, 5); imshow("img", img); imshow("threshold", binary); imshow("mean_thres", binary1); imshow("gauss_thres", binary2); waitKey(0); return 0; }...
result
Threshold demo in OpenCV
Threshold test for
0: Binary
1: Binary Inverted
2: Threshold Truncated
3: Threshold to Zero
4: Threshold to Zero Inverted
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0: Binary
1: Binary Inverted
2: Threshold Truncated
3: Threshold to Zero
4: Threshold to Zero Inverted
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#include "opencv2/opencv.hpp" #include "opencv2/highgui.hpp" #include "opencv2/cudaarithm.hpp" #include <iostream> #include <vector> #ifdef _DEBUG #pragma comment(lib, "opencv_core331d.lib") #pragma comment(lib, "opencv_highgui331d.lib") #pragma comment(lib, "opencv_imgcodecs331d.lib") #pragma comment(lib, "opencv_objdetect331d.lib") #pragma comment(lib, "opencv_imgproc331d.lib") #pragma comment(lib, "opencv_videoio331d.lib") #pragma comment(lib, "opencv_cudaarithm331d.lib") #else #pragma comment(lib, "opencv_core331.lib") #pragma comment(lib, "opencv_highgui331.lib") #pragma comment(lib, "opencv_imgcodecs331.lib") #pragma comment(lib, "opencv_objdetect331.lib") #pragma comment(lib, "opencv_imgproc331.lib") #pragma comment(lib, "opencv_videoio331.lib") #pragma comment(lib, "opencv_cudaarithm331.lib") #endif using namespace std; using namespace cv; int threshold_value = 0; int threshold_type = 3;; int const max_value = 255; int const max_type = 4; int const max_BINARY_value = 255; Mat src, src_gray, dst; char* window_name = "Threshold Demo"; char* trackbar_type = "Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted"; char* trackbar_value = "Value"; /// Function headers void Threshold_Demo(int, void*); void main() { /// Load an image src = imread("blade.jpg", 1); /// Convert the image to Gray cvtColor(src, src_gray, CV_BGR2GRAY); /// Create a window to display results namedWindow(window_name, 0); resizeWindow(window_name, 500, 500); /// Create Trackbar to choose type of Threshold printf("%s", trackbar_type); createTrackbar(trackbar_type, window_name, &threshold_type, max_type, Threshold_Demo); createTrackbar(trackbar_value, window_name, &threshold_value, max_value, Threshold_Demo); /// Call the function to initialize Threshold_Demo(0, 0); //origin namedWindow("origin", 0); imshow("origin", src); /// Wait until user finishes program while (true) { int c; c = waitKey(20); if ((char)c == 27) { break; } } } void Threshold_Demo(int, void*) { // 0: Binary //1: Binary Inverted //2: Threshold Truncated //3: Threshold to Zero //4: Threshold to Zero Inverted threshold(src_gray, dst, threshold_value, max_BINARY_value, threshold_type); imshow(window_name, dst); }...
Image binary simple example for image & video
OpenCV Binary simple source code for image and video
Image
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Video (threshold and adpativeThreshold)
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Image
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int main(int, char) { namedWindow("img", 0); namedWindow("binary", 0); Mat img = imread("book.jpg"); Mat gray, binary; cvtColor(img, gray, CV_RGB2GRAY); threshold(gray, binary, 128, 200, CV_THRESH_BINARY); imshow("img", img); imshow("binary", binary); waitKey(0); return 0; }...
Video (threshold and adpativeThreshold)
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int main(int, char) { VideoCapture stream1(0); //0:note book, 1:usb webcam Mat frame; //current frame Mat gray, binary_otsu, binary_th, binary_ad_m, binary_ad_g; namedWindow("img", 0); namedWindow("otsu", 0); namedWindow("binary_th", 0); namedWindow("binary_adaptive_mean", 0); namedWindow("binary_adaptive_gaussian", 0); //unconditional loop while (true) { if (!(stream1.read(frame))) //get one frame form video break; //printf("%d %d \n", frame.cols, frame.rows); resize(frame, frame, Size(frame.cols / 2, frame.rows / 2)); cvtColor(frame, gray, CV_RGB2GRAY); threshold(gray, binary_th, 128, 255, CV_THRESH_BINARY); adaptiveThreshold(gray, binary_ad_m, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 9, 5); adaptiveThreshold(gray, binary_ad_g, 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, 9, 5); GaussianBlur(gray, gray, Size(7, 7), 0); threshold(gray, binary_otsu, 0, 255, CV_THRESH_BINARY + THRESH_OTSU); imshow("img", frame); imshow("otsu", binary_otsu); imshow("binary_th", binary_th); imshow("binary_adaptive_mean", binary_ad_m); imshow("binary_adaptive_gaussian", binary_ad_g); if (waitKey(10)> 0) break; } return 0; }...
OpenCV LUT(look up table) example code
OpenCV LUT example source code
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int LUTexample() { Mat img = imread("AbyssCGI2.jpg"); Mat lookUpTable(1, 256, CV_8U); uchar* p = lookUpTable.data; int factor = 256 / 5; for (int i = 0; i < 256; ++i) { p[i] = factor * (i / factor); printf("[%d] = %d \n", i, p[i]); } Mat reduced; LUT(img, lookUpTable, reduced); namedWindow("img", 0); imshow("img", img); namedWindow("reduced", 0); imshow("reduced", reduced); /* //////////////////// gray & color test!! Mat img2(1, 1, CV_8UC3); img2.setTo(Scalar(0, 128, 255)); Mat im_color3; LUT(img2, lookUpTable, im_color3); cout << im_color3 << endl; //namedWindow("im_color3", 0); //imshow("im_color3", im_color3); //different result with color!! Mat img2_gray; cvtColor(img2, img2_gray, CV_BGR2GRAY); Mat im_color4; LUT(img2_gray, lookUpTable, im_color4); cout << im_color4 << endl; //namedWindow("im_color4", 0); //imshow("im_color4", im_color4); //////////////////////*/ waitKey(0); return 0; }...
Video frame difference (frame subtraction), opencv example source code
video frame subtraction example source code using opencv
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#include "opencv2/opencv.hpp" #include "opencv2/highgui.hpp" #include "opencv2/cudaarithm.hpp" #include <iostream> #include <vector> #ifdef _DEBUG #pragma comment(lib, "opencv_core331d.lib") #pragma comment(lib, "opencv_highgui331d.lib") #pragma comment(lib, "opencv_imgcodecs331d.lib") #pragma comment(lib, "opencv_objdetect331d.lib") #pragma comment(lib, "opencv_imgproc331d.lib") #pragma comment(lib, "opencv_videoio331d.lib") #pragma comment(lib, "opencv_cudaarithm331d.lib") #else #pragma comment(lib, "opencv_core331.lib") #pragma comment(lib, "opencv_highgui331.lib") #pragma comment(lib, "opencv_imgcodecs331.lib") #pragma comment(lib, "opencv_objdetect331.lib") #pragma comment(lib, "opencv_imgproc331.lib") #pragma comment(lib, "opencv_videoio331.lib") #pragma comment(lib, "opencv_cudaarithm331.lib") #endif using namespace std; using namespace cv; int main(int, char) { Mat frame; Mat old_frame; Mat sub_frame; //Mat absdiff_frame; VideoCapture stream1(0); if (!stream1.isOpened()) { //check if video device has been initialised cout << "cannot open camera 1"; return 0; } while (1) { if (!(stream1.read(frame))) //get one frame form video break; if (old_frame.empty()) { old_frame = frame.clone(); continue; } subtract(old_frame, frame, sub_frame); //absdiff(old_frame, frame, absdiff_frame); imshow("frame", frame); imshow("sub_frame", sub_frame); //imshow("absdiff_frame", absdiff_frame); //subtraction every frame old_frame = frame.clone(); if (waitKey(5) >= 0) break; } return 0; }...
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This is dithering example, it make image like a stippling effect. I referenced to blew website. wiki page: https://en.wikipedia.org/wik... -
As you can see in the following video, I created a class that stitching n cameras in real time. https://www.youtube.com/user/feelmare/sear...
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Image size of origin is 320*240. Processing time is 30.96 second took. The result of stitching The resul... -
* Introduction - The solution shows panorama image from multi images. The panorama images is processing by real-time stitching algorithm... -
//Singular value decomposition : Mat w, u, v; SVDecomp(data, w, u, v); // A = U W V^T //The flags cause U and V to be returned transpose...
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Background subtractor example souce code. OpenCV support about 3 types subtraction algorithm. Those are MOG, MOG2, GMG algorithms. Det... -
This is data acquisition source code of LMS511(SICK co.) Source code is made by MFC(vs 2008). The sensor is communicated by TCP/IP. ... -
Logistic Classifier The logistic classifier is similar to equation of the plane. W is weight vector, X is input vector and y is output... -
make well divided linear coordinate And make pair coordinate Please see code for detail explanation. import numpy as np import cv2 ... -
RTSP(Real Time Streaming Protocol) is video streaming, it usually sent from network camera. VideoCapture function in opencv also can get r...
