Final changes, experimenting with parameters
This commit is contained in:
Razvan Mihalyi
parent
285c65b6fb
commit
879494c82e
1 changed files with 144 additions and 63 deletions
207
calibrate.cc
207
calibrate.cc
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@ -19,11 +19,15 @@ enum { INTERACTIVE_MODE, PRESPECIFIED_MODE };
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#define COUNT_SQUARES_X 4
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#define COUNT_SQUARES_Y 6
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int detect_pattern(Mat frame, vector< vector<Point3f> >& object_points, vector<vector<Point2f> >& image_points)
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/**
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* Method for detecting pattern in current frame.
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* Returns world and image coordinates of detected corners via out parameters.
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*/
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bool detectPattern(Mat frame, vector< vector<Point3f> >& object_points, vector<vector<Point2f> >& image_points)
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{
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// interior number of corners
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// number of squares in the pattern, a.k.a, interior number of corners
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Size pattern_size(COUNT_SQUARES_X, COUNT_SQUARES_Y);
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// will be filled by the detected corners
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// storage for the detected corners in findChessboardConrners
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vector<Point2f> corners;
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bool pattern_found = findChessboardCorners(
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@ -33,116 +37,193 @@ int detect_pattern(Mat frame, vector< vector<Point3f> >& object_points, vector<v
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CALIB_CB_FAST_CHECK);
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if (!pattern_found)
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return -1;
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return false;
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// to tweak params: http://bit.ly/QyoU3k
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// if corners are detected, they are further refined by calculating subpixel corners from the grayscale image
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// this iterative process terminates after the given number of iterations and error epsilon
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cornerSubPix(frame, corners, Size(11, 11), Size(-1, -1),
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TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 100,
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0.1));
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// draw the detected corners as sanity check
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drawChessboardCorners(frame, pattern_size, Mat(corners),
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pattern_found);
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vector<Point3f> obj;
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for (int j = 0; j < COUNT_SQUARES_X * COUNT_SQUARES_Y; ++j)
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obj.push_back(Point3f(j / COUNT_SQUARES_X, j % COUNT_SQUARES_X, 0.0f));
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object_points.push_back(obj);
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// show detected corners in a different window
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imshow("Detected pattern", frame);
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// build a grid of 3D points (z component is 0 because the pattern is in one plane) to fit the square pattern area (COUNT_SQUARES_X * COUNT_SQUARES_Y)
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vector<Point3f> pattern_points;
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for (int j = 0; j < COUNT_SQUARES_X * COUNT_SQUARES_Y; ++j)
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pattern_points.push_back(Point3f(j / COUNT_SQUARES_X, j % COUNT_SQUARES_X, 0.0f));
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// populate image points with corners and object points with grid points
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object_points.push_back(pattern_points);
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image_points.push_back(corners);
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return 0;
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return true;
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}
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int run_interactive()
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/**
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* Main method for interactive behavior.
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* Requires user to present calibration pattern in front of camera.
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* By pressing SPACE the image is grabbed, pressing any other key loops through the camera stream, pressing ESC finishes calibration.
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*/
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int runInteractive()
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{
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cout << "Camera calibration using interactive behavior. Press SPACE to grab frame, ESC to quit.\n";
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// show camera image in a separate window
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namedWindow("Camera Image", CV_WINDOW_KEEPRATIO);
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int count = 0;
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Mat frame;
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vector<vector<Point3f> > object_points;
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vector<vector<Point2f> > image_points;
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// current camera frame and first captured frame
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Mat frame, first_frame;
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// storage for object points (world coords) and image points (image coords) for use in calibrateCamera
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vector< vector< Point3f > > object_points;
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vector< vector< Point2f > > image_points;
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// calibration parameters
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Mat intrinsic = Mat(3, 3, CV_32FC1);
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Mat distCoeffs;
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vector<Mat> rvecs, tvecs;
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// open the default camera
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VideoCapture capture(-1);
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VideoCapture capture(0);
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// check if opening camera stream succeeded
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if (!capture.isOpened()) {
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if (!capture.isOpened())
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{
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cerr << "Camera could not be found. Exiting.\n";
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return -1;
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}
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for (;;) {
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cout << "Frame: " << count << endl;
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Mat gray_frame;
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capture >> frame; // get a new frame from camera
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cvtColor(frame, gray_frame, CV_BGR2GRAY);
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imshow("Camera Image", frame);
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// set frame width and height by hand, defaults to 160x120
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capture.set (CV_CAP_PROP_FRAME_WIDTH, 640);
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capture.set (CV_CAP_PROP_FRAME_HEIGHT, 480);
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int key_pressed = waitKey(0);
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// flag for determining whether pattern was detected in at least one of the camera grabs
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bool calibration_ready = false;
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// flag for detecting first frame with pattern
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bool first_flag = true;
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for (int count_frames = 0; ; ++count_frames)
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{
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cout << "Frame: " << count_frames << endl;
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capture >> frame; // get a new frame from camera
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Mat gray_frame;
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cvtColor(frame, gray_frame, CV_BGR2GRAY); // convert current frame to grayscale
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imshow("Camera Image", frame); // update camera image
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int key_pressed = waitKey(0); // get user key press
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if (key_pressed == KEY_CLOSE_WINDOW || key_pressed == KEY_ESCAPE)
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break;
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if (key_pressed == KEY_SPACE) {
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if (detect_pattern(gray_frame, object_points, image_points) == 0) {
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cout << "Frame " << count << " grabbed." << endl;
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} else {
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cout << "pattern not found" << endl;
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}
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}
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}
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calibrateCamera(object_points, image_points, frame.size(), intrinsic,
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distCoeffs, rvecs, tvecs);
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for (;;) {
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capture >> frame;
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Mat imageUndistorted;
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undistort(frame, imageUndistorted, intrinsic, distCoeffs);
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imshow("win1", frame);
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imshow("win2", imageUndistorted);
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waitKey(1);
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if (key_pressed == KEY_SPACE)
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{
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if (detectPattern(gray_frame, object_points, image_points))
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{
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if (first_flag)
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{
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first_frame = frame; // save first frame for later use
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first_flag = false;
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}
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cout << "Frame " << count_frames << " grabbed." << endl;
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calibration_ready = true;
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}
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else cout << "Pattern not found" << endl;
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}
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else
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continue;
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}
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// if at least one video capture contains the pattern, perform calibration
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if (calibration_ready)
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{
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// perform calibration, obtain instrinsic parameters and distortion coefficients
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cout << "Calibrating..." << endl;
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calibrateCamera(object_points, image_points, frame.size(), intrinsic,
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distCoeffs, rvecs, tvecs);
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Mat undistorted_frame;
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// apply the calibration transformation to the first frame and store image on disk
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undistort(first_frame, undistorted_frame, intrinsic, distCoeffs);
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imwrite("first_frame.jpg", first_frame);
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imwrite("undistorted_frame.jpg", undistorted_frame);
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cout << "Applied undistortion to first frame (first_frame.jpg) and saved to undistorted_frame.jpg" << endl;
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cout << "Intrinsic parameters:" << endl << intrinsic << endl;
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cout << "Distortion coefficients:" << endl << distCoeffs << endl;
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}
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else
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{
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cerr << "No pattern found in any video capture. Exiting." << endl;
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}
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// release camera
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capture.release();
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}
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int run_prespecified(int argc, char **argv)
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int runPrespecified(int argc, char **argv)
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{
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int count = 0;
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Mat frame;
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// current camera frame and first captured frame
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Mat frame, first_frame;
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// storage for object points (world coords) and image points (image coords) for use in calibrateCamera
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vector<vector<Point3f> > object_points;
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vector<vector<Point2f> > image_points;
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// calibration parameters
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Mat intrinsic = Mat(3, 3, CV_32FC1);
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Mat distCoeffs;
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vector<Mat> rvecs, tvecs;
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for (int i = 0; i < argc; i++) {
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// flag for determining whether pattern was detected in at least one of the images
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bool calibration_ready = false;
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// flag for detecting first frame with pattern
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bool first_flag = true;
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// loop through the specified images
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for (int i = 0; i < argc; i++)
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{
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Mat gray_frame;
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cerr << endl << argv[i] << endl;
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frame = imread(argv[i], CV_LOAD_IMAGE_COLOR);
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cvtColor(frame, gray_frame, CV_BGR2GRAY);
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imshow("Camera Image", frame);
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if (detect_pattern(gray_frame, object_points, image_points) == 0) {
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// apply pattern detection
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if (detectPattern(gray_frame, object_points, image_points))
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{
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if (first_flag)
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{
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first_frame = frame;
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first_flag = false;
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}
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cout << "Frame " << i << " grabbed." << endl;
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} else {
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cout << "Pattern not found in frame " << i << endl;
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calibration_ready = true;
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}
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else
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cout << "Pattern not found in frame " << i << endl;
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}
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cout << "Calibrating..." << endl;
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calibrateCamera(object_points, image_points, frame.size(), intrinsic,
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distCoeffs, rvecs, tvecs);
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// if at least one image contains the pattern, perform calibration
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if (calibration_ready)
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{
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// perform calibration, obtain instrinsic parameters and distortion coefficients
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cout << "Calibrating..." << endl;
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calibrateCamera(object_points, image_points, frame.size(), intrinsic,
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distCoeffs, rvecs, tvecs);
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for (int i = 0; i < argc; i++) {
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frame = imread(argv[i], CV_LOAD_IMAGE_COLOR);
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Mat imageUndistorted;
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undistort(frame, imageUndistorted, intrinsic, distCoeffs);
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imshow("win1", frame);
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imshow("win2", imageUndistorted);
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waitKey(0);
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Mat undistorted_frame;
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// apply the calibration transformation to the first frame and store image on disk
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undistort(first_frame, undistorted_frame, intrinsic, distCoeffs);
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imwrite("first_frame.jpg", first_frame);
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imwrite("undistorted_frame.jpg", undistorted_frame);
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cout << "Applied undistortion to first frame (first_frame.jpg) and saved to undistorted_frame.jpg" << endl;
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cout << "Intrinsic parameters:" << endl << intrinsic << endl;
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cout << "Distortion coefficients:" << endl << distCoeffs << endl;
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}
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else
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{
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cerr << "No pattern found in any of the images. Exiting." << endl;
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}
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return 0;
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}
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int main(int argc, char **argv)
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@ -153,9 +234,9 @@ int main(int argc, char **argv)
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/* no arguments means interactive mode
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* one or more arguments are image filenames */
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if (argc == 1) {
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run_interactive();
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runInteractive();
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} else {
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run_prespecified(argc-1, ++argv);
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runPrespecified(argc-1, ++argv);
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}
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return 0;
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