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// Example 19-2. Computing the fundamental matrix using RANSAC | ||
#include <opencv2/opencv.hpp> | ||
#include <iostream> | ||
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using namespace std; | ||
void help(char *argv[]) { | ||
cout << "\nExample 19-2, Computing the fundamental matrix using RANSAC relating 2 images. Show the camera a checkerboard " | ||
<< "\nCall" | ||
<< "\n./example_19-2 <1:board_w> <2:board_h> <3:# of boards> <4:delay capture this many ms between frames> <5:scale the images 0-1>" | ||
<< "\n\nExample call:" | ||
<< "\n./example_19-2 9 6 20 500 0.5" | ||
<< "\n\n -- use the checkerboard9x6.png provided" | ||
<< "\n" | ||
<< endl; | ||
} | ||
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// args: [board_w] [board_h] [number_of_boards] [delay]? [scale]? | ||
// | ||
int main(int argc, char *argv[]) { | ||
int n_boards = 0; | ||
float image_sf = 0.5f; | ||
float delay = 1.f; | ||
int board_w = 0; | ||
int board_h = 0; | ||
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// Will be set by input list | ||
if (argc != 6) { | ||
cout << "\nERROR: Wrong number of input parameters, need 5, got " << argc - 1 << "\n"; | ||
help(argv); | ||
return -1; | ||
} | ||
board_w = atoi(argv[1]); | ||
board_h = atoi(argv[2]); | ||
n_boards = atoi(argv[3]); | ||
delay = atof(argv[4]); | ||
image_sf = atof(argv[5]); | ||
int board_n = board_w * board_h; | ||
cv::Size board_sz = cv::Size(board_w, board_h); | ||
cv::VideoCapture capture(0); | ||
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if (!capture.isOpened()) { | ||
cout << "\nCouldn't open the camera\n"; | ||
help(argv); | ||
return -1; | ||
} | ||
// Allocate Storage | ||
// | ||
vector<vector<cv::Point2f> > image_points; | ||
vector<vector<cv::Point3f> > object_points; | ||
// Capture corner views; loop until we've got n_boards number of | ||
// successful captures (meaning: all corners on each | ||
// board are found). | ||
// | ||
double last_captured_timestamp = 0; | ||
cv::Size image_size; | ||
while (image_points.size() < (size_t)n_boards) { | ||
cv::Mat image0, image; | ||
capture >> image0; | ||
image_size = image0.size(); | ||
resize(image0, image, cv::Size(), image_sf, image_sf, cv::INTER_LINEAR); | ||
// Find the board | ||
// | ||
vector<cv::Point2f> corners; | ||
bool found = cv::findChessboardCorners(image, board_sz, corners); | ||
// Draw it | ||
// | ||
cv::drawChessboardCorners(image, board_sz, corners, found); | ||
// If we got a good board, add it to our data | ||
// | ||
double timestamp = (double)clock() / CLOCKS_PER_SEC; | ||
if (found && timestamp - last_captured_timestamp > 1) { | ||
last_captured_timestamp = timestamp; | ||
image ^= cv::Scalar::all(255); | ||
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cv::Mat mcorners(corners); | ||
// do not copy the data | ||
mcorners *= (1. / image_sf); | ||
// scale corner coordinates | ||
image_points.push_back(corners); | ||
object_points.push_back(vector<cv::Point3f>()); | ||
vector<cv::Point3f> &opts = object_points.back(); | ||
opts.resize(board_n); | ||
for (int j = 0; j < board_n; j++) { | ||
opts[j] = cv::Point3f((float)(j / board_w), (float)(j % board_w), 0.f); | ||
} | ||
cout << "Collected our " << (int)image_points.size() << " of " << n_boards | ||
<< " needed chessboard images\n" << endl; | ||
} | ||
// in color if we did collect the image | ||
// | ||
cv::imshow("Calibration", image); | ||
if ((cv::waitKey(30) & 255) == 27) | ||
return -1; | ||
} | ||
// end collection while() loop. | ||
cv::destroyWindow("Calibration"); | ||
cout << "\n\n*** CALIBRATING THE CAMERA...\n" << endl; | ||
// Calibrate the camera! | ||
// | ||
cv::Mat intrinsic_matrix, distortion_coeffs; | ||
double err = cv::calibrateCamera( | ||
object_points, // Vector of vectors of points | ||
// from the calibration pattern | ||
image_points, // Vector of vectors of projected | ||
// locations (on images) | ||
image_size, // Size of images used | ||
intrinsic_matrix, // Output camera matrix | ||
distortion_coeffs, // Output distortion coefficients | ||
cv::noArray(), // We'll pass on the rotation vectors... | ||
cv::noArray(), // ...and the translation vectors | ||
cv::CALIB_ZERO_TANGENT_DIST | cv::CALIB_FIX_PRINCIPAL_POINT); | ||
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// Save the intrinsics and distortions | ||
cout << " *** DONE!\n\nReprojection error is " << err | ||
<< "\nStoring Intrinsics.xml and Distortions.xml files\n\n"; | ||
cv::FileStorage fs("intrinsics.xml", cv::FileStorage::WRITE); | ||
fs << "image_width" << image_size.width << "image_height" << image_size.height | ||
<< "camera_matrix" << intrinsic_matrix << "distortion_coefficients" | ||
<< distortion_coeffs; | ||
fs.release(); | ||
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// Example of loading these matrices back in: | ||
// | ||
fs.open("intrinsics.xml", cv::FileStorage::READ); | ||
cout << "\nimage width: " << (int)fs["image_width"]; | ||
cout << "\nimage height: " << (int)fs["image_height"]; | ||
cv::Mat intrinsic_matrix_loaded, distortion_coeffs_loaded; | ||
fs["camera_matrix"] >> intrinsic_matrix_loaded; | ||
fs["distortion_coefficients"] >> distortion_coeffs_loaded; | ||
cout << "\nintrinsic matrix:" << intrinsic_matrix_loaded; | ||
cout << "\ndistortion coefficients: " << distortion_coeffs_loaded << endl; | ||
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// Compute Fundamental Matrix Between the first | ||
// and the second frames: | ||
// | ||
cv::undistortPoints( | ||
image_points[0], // Observed point coordinates (from frame 0) | ||
image_points[0], // undistorted coordinates (in this case, | ||
// the same array as above) | ||
intrinsic_matrix, // Intrinsics, from cv::calibrateCamera() | ||
distortion_coeffs, // Distortion coefficients, also | ||
// from cv::calibrateCamera() | ||
cv::Mat(), // Rectification transformation (but | ||
// here, we don't need this) | ||
intrinsic_matrix // New camera matrix | ||
); | ||
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cv::undistortPoints( | ||
image_points[1], // Observed point coordinates (from frame 1) | ||
image_points[1], // undistorted coordinates (in this case, | ||
// the same array as above) | ||
intrinsic_matrix, // Intrinsics, from cv::calibrateCamera() | ||
distortion_coeffs, // Distortion coefficients, also | ||
// from cv::calibrateCamera() | ||
cv::Mat(), // Rectification transformation (but | ||
// here, we don't need this) | ||
intrinsic_matrix // New camera matrix | ||
); | ||
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// Since all the found chessboard corners are inliers, i.e., they | ||
// must satisfy epipolar constraints, here we are using the | ||
// fastest, and the most accurate (in this case) 8-point algorithm. | ||
// | ||
cv::Mat F = cv::findFundamentalMat( // Return computed matrix | ||
image_points[0], // Points from frame 0 | ||
image_points[1], // Points from frame 1 | ||
cv::FM_8POINT // Use the 8-point algorithm | ||
); | ||
cout << "Fundamental matrix: " << F << endl; | ||
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// Build the undistort map which we will use for all | ||
// subsequent frames. | ||
// | ||
cv::Mat map1, map2; | ||
cv::initUndistortRectifyMap( | ||
intrinsic_matrix_loaded, // Our camera matrix | ||
distortion_coeffs_loaded, // Our distortion coefficients | ||
cv::Mat(), // (Optional) Rectification, don't | ||
// need. | ||
intrinsic_matrix_loaded, // "New" matrix, here it's the same | ||
// as the first argument. | ||
image_size, // Size of undistorted image we want | ||
CV_16SC2, // Specifies the format of map to use | ||
map1, // Integerized coordinates | ||
map2 // Fixed-point offsets for | ||
// elements of map1 | ||
); | ||
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// Just run the camera to the screen, now showing the raw and | ||
// the undistorted image. | ||
// | ||
for (;;) { | ||
cv::Mat image, image0; | ||
capture >> image0; | ||
if (image0.empty()) | ||
break; | ||
cv::remap(image0, // Input image | ||
image, // Output image | ||
map1, // Integer part of map | ||
map2, // Fixed point part of map | ||
cv::INTER_LINEAR, cv::BORDER_CONSTANT, | ||
cv::Scalar() // Set border values to black | ||
); | ||
cv::imshow("Undistorted", image); | ||
if ((cv::waitKey(30) & 255) == 27) | ||
break; | ||
} | ||
return 1; | ||
} |