int main() {
cv::VideoCapture capWebcam(0); // declare a VideoCapture object and associate to webcam, 0 => use 1st webcam
if (capWebcam.isOpened() == false) { // check if VideoCapture object was associated to webcam successfully
std::cout << "error: capWebcam not accessed successfully\n\n"; // if not, print error message to std out
return(0); // and exit program
}
cv::Mat imgOriginal; // input image
cv::Mat imgGrayscale; // grayscale of input image
cv::Mat imgBlurred; // intermediate blured image
cv::Mat imgCanny; // Canny edge image
char charCheckForEscKey = 0;
while (charCheckForEscKey != 27 && capWebcam.isOpened()) { // until the Esc key is pressed or webcam connection is lost
bool blnFrameReadSuccessfully = capWebcam.read(imgOriginal); // get next frame
if (!blnFrameReadSuccessfully || imgOriginal.empty()) { // if frame not read successfully
std::cout << "error: frame not read from webcam\n"; // print error message to std out
break; // and jump out of while loop
}
cv::cvtColor(imgOriginal, imgGrayscale, CV_BGR2GRAY); // convert to grayscale
cv::GaussianBlur(imgGrayscale, // input image
imgBlurred, // output image
cv::Size(5, 5), // smoothing window width and height in pixels
1.8); // sigma value, determines how much the image will be blurred
cv::Canny(imgBlurred, // input image
imgCanny, // output image
50, // low threshold
100); // high threshold
// declare windows
cv::namedWindow("imgOriginal", CV_WINDOW_NORMAL); // note: you can use CV_WINDOW_NORMAL which allows resizing the window
cv::namedWindow("imgCanny", CV_WINDOW_NORMAL); // or CV_WINDOW_AUTOSIZE for a fixed size window matching the resolution of the image
// CV_WINDOW_AUTOSIZE is the default
cv::imshow("imgOriginal", imgOriginal); // show windows
cv::imshow("imgCanny", imgCanny);
charCheckForEscKey = cv::waitKey(1); // delay (in ms) and get key press, if any
} // end while
return(0);
}
int main() {
cv::VideoCapture capWebcam(0); // declare a VideoCapture object and associate to webcam, 0 => use 1st webcam
if (capWebcam.isOpened() == false) { // check if VideoCapture object was associated to webcam successfully
std::cout << "error: capWebcam not accessed successfully\n\n"; // if not, print error message to std out
return(0); // and exit program
}
cv::Mat matOriginal; // input image
cv::Mat matProcessed; // output image
std::vector<cv::Vec3f> v3fCircles; // 3 element vector of floats, this will be the pass by reference output of HoughCircles()
char charCheckForEscKey = 0;
while (charCheckForEscKey != 27 && capWebcam.isOpened()) { // until the Esc key is pressed or webcam connection is lost
bool blnFrameReadSuccessfully = capWebcam.read(matOriginal); // get next frame
if (!blnFrameReadSuccessfully || matOriginal.empty()) { // if frame not read successfully
std::cout << "error: frame not read from webcam\n"; // print error message to std out
break; // and jump out of while loop
}
// smooth the image
cv::GaussianBlur(matOriginal, // function input
matProcessed, // function output
cv::Size(5, 5), // smoothing window width and height in pixels
2); // sigma value, determines how much the image will be blurred
// filter on color
cv::inRange(matProcessed, // funcion input
cv::Scalar(0, 0, 175), // min filtering value (if greater than or equal to this) (in BGR format)
cv::Scalar(100, 100, 256), // max filtering value (and if less than this) (in BGR format)
matProcessed); // function output
// smooth again
cv::GaussianBlur(matProcessed, // function input
matProcessed, // function output
cv::Size(5, 5), // smoothing window width and height in pixels
2); // sigma value, determines how much the image will be blurred
cv::dilate(matProcessed, matProcessed, cv::getStructuringElement(cv::MORPH_RECT, cv::Size(5, 5))); // close image (dilate, then erode)
cv::erode(matProcessed, matProcessed, cv::getStructuringElement(cv::MORPH_RECT, cv::Size(5, 5))); // closing "closes" (i.e. fills in) foreground gaps
// fill circles vector with all circles in processed image
cv::HoughCircles(matProcessed, // input image
v3fCircles, // function output (must be a standard template library vector
CV_HOUGH_GRADIENT, // two-pass algorithm for detecting circles, this is the only choice available
2, // size of image / this value = "accumulator resolution", i.e. accum res = size of image / 2
matProcessed.rows / 4, // min distance in pixels between the centers of the detected circles
100, // high threshold of Canny edge detector (called by cvHoughCircles)
50, // low threshold of Canny edge detector (set at 1/2 previous value)
10, // min circle radius (any circles with smaller radius will not be returned)
400); // max circle radius (any circles with larger radius will not be returned)
for (int i = 0; i < v3fCircles.size(); i++) { // for each circle . . .
// show ball position x, y, and radius to command line
std::cout << "ball position x = " << v3fCircles[i][0] // x position of center point of circle
<< ", y = " << v3fCircles[i][1] // y position of center point of circle
<< ", radius = " << v3fCircles[i][2] << "\n"; // radius of circle
// draw small green circle at center of detected object
cv::circle(matOriginal, // draw on original image
cv::Point((int)v3fCircles[i][0], (int)v3fCircles[i][1]), // center point of circle
3, // radius of circle in pixels
cv::Scalar(0, 255, 0), // draw pure green (remember, its BGR, not RGB)
CV_FILLED); // thickness, fill in the circle
// draw red circle around the detected object
cv::circle(matOriginal, // draw on original image
cv::Point((int)v3fCircles[i][0], (int)v3fCircles[i][1]), // center point of circle
(int)v3fCircles[i][2], // radius of circle in pixels
cv::Scalar(0, 0, 255), // draw pure red (remember, its BGR, not RGB)
3); // thickness of circle in pixels
} // end for
// declare windows
cv::namedWindow("Original", CV_WINDOW_AUTOSIZE); // note: you can use CV_WINDOW_NORMAL which allows resizing the window
cv::namedWindow("Processed", CV_WINDOW_AUTOSIZE); // or CV_WINDOW_AUTOSIZE for a fixed size window matching the resolution of the image
// CV_WINDOW_AUTOSIZE is the default
cv::imshow("Original", matOriginal); // show windows
cv::imshow("Processed", matProcessed);
charCheckForEscKey = cv::waitKey(1); // delay (in ms) and get key press, if any
} // end while
return(0);
}
