Function opencvFundamentalMatrixFitting

examples/cpp_example.cpp:1026–1169

}

void opencvFundamentalMatrixFitting(
	double ransac_confidence_,
	double threshold_,
	std::string test_scene_,
	bool draw_results_,
	const bool with_magsac_post_processing_)
{
	// Print the name of the current test scene
	std::cout  << "Processed scene = '" << test_scene_ << "'.";

	// Load the images of the current test scene
	cv::Mat image1 = cv::imread("../data/fundamental_matrix/" + test_scene_ + "A.png");
	cv::Mat image2 = cv::imread("../data/fundamental_matrix/" + test_scene_ + "B.png");
	if (image1.cols == 0 || image2.cols == 0) // Try to load jpg files if there are no pngs
	{
		image1 = cv::imread("../data/fundamental_matrix/" + test_scene_ + "A.jpg");
		image2 = cv::imread("../data/fundamental_matrix/" + test_scene_ + "B.jpg");
	}

	// If the images are not loaded, return
	if (image1.cols == 0 || image2.cols == 0)
	{
		std::cerr << "A problem occured when loading the images for test scene " << test_scene_ << ".";
		return;
	}

	cv::Mat points; // The point correspondences, each is of format x1 y1 x2 y2
	std::vector<int> ground_truth_labels; // The ground truth labeling provided in the dataset

	// A function loading the points from files
	readAnnotatedPoints("../data/fundamental_matrix/" + test_scene_ + "_pts.txt", // The path to the labels and points
		points, // The container for the loaded points
		ground_truth_labels); // The ground thruth labeling

	// The number of points in the datasets
	const size_t point_number = points.rows; // The number of points in the scene

	if (point_number == 0) // If there are no points, return
	{
		std::cerr << "A problem occured when loading the annotated points for test scene " << test_scene_ << ".";
		return;
	}

	gcransac::utils::DefaultFundamentalMatrixEstimator estimator; // The robust homography estimator class containing the function for the fitting and residual calculation
	gcransac::FundamentalMatrix model; // The estimated model parameters

	// In this used datasets, the manually selected inliers are not all inliers but a subset of them.
	// Therefore, the manually selected inliers are augmented as follows: 
	// (i) First, the implied model is estimated from the manually selected inliers.
	// (ii) Second, the inliers of the ground truth model are selected.
	std::vector<int> refined_labels = ground_truth_labels;
	refineManualLabeling<gcransac::FundamentalMatrix, gcransac::utils::DefaultFundamentalMatrixEstimator>(
		points, // All data points
		ground_truth_labels, // The refined labeling
		estimator, // The estimator used for determining the underlying model
		0.35); // Threshold value from the LO*-RANSAC paper

	// Select the inliers from the labeling