Loading modules/rgbd/include/opencv2/rgbd.hpp +19 −0 Original line number Diff line number Diff line Loading @@ -379,6 +379,25 @@ namespace rgbd { } /** Constructor * @param block_size The size of the blocks to look at for a stable MSE * @param min_size The minimum size of a cluster to be considered a plane * @param threshold The maximum distance of a point from a plane to belong to it (in meters) * @param sensor_error_a coefficient of the sensor error. 0 by default, 0.0075 for a Kinect * @param sensor_error_b coefficient of the sensor error. 0 by default * @param sensor_error_c coefficient of the sensor error. 0 by default * @param method The method to use to compute the planes. */ RgbdPlane(int method, int block_size, int min_size, double threshold, double sensor_error_a = 0, double sensor_error_b = 0, double sensor_error_c = 0); ~RgbdPlane(); CV_WRAP static Ptr<RgbdPlane> create(int method, int block_size, int min_size, double threshold, double sensor_error_a = 0, double sensor_error_b = 0, double sensor_error_c = 0); /** Find The planes in a depth image * @param points3d the 3d points organized like the depth image: rows x cols with 3 channels * @param normals the normals for every point in the depth image Loading modules/rgbd/misc/python/test/test_rgbd.py 0 → 100644 +45 −0 Original line number Diff line number Diff line #!/usr/bin/env python # Python 2/3 compatibility from __future__ import print_function import os, numpy import cv2 as cv from tests_common import NewOpenCVTests class rgbd_test(NewOpenCVTests): def test_computeRgbdPlane(self): depth_image = self.get_sample('/cv/rgbd/depth.png', cv.IMREAD_ANYDEPTH) if depth_image is None: raise unittest.SkipTest("Missing files with test data") K = numpy.array([[525, 0, 320.5], [0, 525, 240.5], [0, 0, 1]]) points3d = cv.rgbd.depthTo3d(depth_image, K) normals_computer = normals_computer = cv.rgbd.RgbdNormals_create(480, 640, 5, K) normals = normals_computer.apply(points3d) rgbd_plane = cv.rgbd.RgbdPlane_create(cv.rgbd.RgbdPlane_RGBD_PLANE_METHOD_DEFAULT, 40, 1600, 0.01, 0, 0, 0) _, planes_coeff = rgbd_plane.apply(points3d, normals) planes_coeff_expected = \ numpy.asarray([[[-0.02447728, -0.8678335 , -0.49625182, 4.02800846]], [[-0.05055107, -0.86144137, -0.50533485, 3.95456314]], [[-0.03294908, -0.86964548, -0.49257591, 3.97052431]], [[-0.02886586, -0.87153459, -0.48948362, 7.77550507]], [[-0.04455929, -0.87659335, -0.47916424, 3.93200684]], [[-0.21514639, 0.18835169, -0.95824611, 7.59479475]], [[-0.01006953, -0.86679155, -0.49856904, 4.01355648]], [[-0.00876531, -0.87571168, -0.48275498, 3.96768975]], [[-0.06395926, -0.86951321, -0.48975089, 4.08618736]], [[-0.01403128, -0.87593341, -0.48222789, 7.74559402]], [[-0.01143177, -0.87495202, -0.4840748 , 7.75355816]]], dtype=numpy.float32) eps = 0.05 self.assertLessEqual(cv.norm(planes_coeff, planes_coeff_expected, cv.NORM_L2), eps) if __name__ == '__main__': NewOpenCVTests.bootstrap() modules/rgbd/src/odometry.cpp +22 −0 Original line number Diff line number Diff line Loading @@ -1009,6 +1009,28 @@ Ptr<DepthCleaner> DepthCleaner::create(int depth_in, int window_size_in, int met return makePtr<DepthCleaner>(depth_in, window_size_in, method_in); } RgbdPlane::RgbdPlane(int method, int block_size, int min_size, double threshold, double sensor_error_a, double sensor_error_b, double sensor_error_c) : method_(method), block_size_(block_size), min_size_(min_size), threshold_(threshold), sensor_error_a_(sensor_error_a), sensor_error_b_(sensor_error_b), sensor_error_c_(sensor_error_c) {} Ptr<RgbdPlane> RgbdPlane::create(int method, int block_size, int min_size, double threshold, double sensor_error_a, double sensor_error_b, double sensor_error_c ) { return makePtr<RgbdPlane>(method, block_size, min_size, threshold, sensor_error_a, sensor_error_b, sensor_error_c); } RgbdPlane::~RgbdPlane() {} RgbdFrame::RgbdFrame() : ID(-1) {} Loading Loading
modules/rgbd/include/opencv2/rgbd.hpp +19 −0 Original line number Diff line number Diff line Loading @@ -379,6 +379,25 @@ namespace rgbd { } /** Constructor * @param block_size The size of the blocks to look at for a stable MSE * @param min_size The minimum size of a cluster to be considered a plane * @param threshold The maximum distance of a point from a plane to belong to it (in meters) * @param sensor_error_a coefficient of the sensor error. 0 by default, 0.0075 for a Kinect * @param sensor_error_b coefficient of the sensor error. 0 by default * @param sensor_error_c coefficient of the sensor error. 0 by default * @param method The method to use to compute the planes. */ RgbdPlane(int method, int block_size, int min_size, double threshold, double sensor_error_a = 0, double sensor_error_b = 0, double sensor_error_c = 0); ~RgbdPlane(); CV_WRAP static Ptr<RgbdPlane> create(int method, int block_size, int min_size, double threshold, double sensor_error_a = 0, double sensor_error_b = 0, double sensor_error_c = 0); /** Find The planes in a depth image * @param points3d the 3d points organized like the depth image: rows x cols with 3 channels * @param normals the normals for every point in the depth image Loading
modules/rgbd/misc/python/test/test_rgbd.py 0 → 100644 +45 −0 Original line number Diff line number Diff line #!/usr/bin/env python # Python 2/3 compatibility from __future__ import print_function import os, numpy import cv2 as cv from tests_common import NewOpenCVTests class rgbd_test(NewOpenCVTests): def test_computeRgbdPlane(self): depth_image = self.get_sample('/cv/rgbd/depth.png', cv.IMREAD_ANYDEPTH) if depth_image is None: raise unittest.SkipTest("Missing files with test data") K = numpy.array([[525, 0, 320.5], [0, 525, 240.5], [0, 0, 1]]) points3d = cv.rgbd.depthTo3d(depth_image, K) normals_computer = normals_computer = cv.rgbd.RgbdNormals_create(480, 640, 5, K) normals = normals_computer.apply(points3d) rgbd_plane = cv.rgbd.RgbdPlane_create(cv.rgbd.RgbdPlane_RGBD_PLANE_METHOD_DEFAULT, 40, 1600, 0.01, 0, 0, 0) _, planes_coeff = rgbd_plane.apply(points3d, normals) planes_coeff_expected = \ numpy.asarray([[[-0.02447728, -0.8678335 , -0.49625182, 4.02800846]], [[-0.05055107, -0.86144137, -0.50533485, 3.95456314]], [[-0.03294908, -0.86964548, -0.49257591, 3.97052431]], [[-0.02886586, -0.87153459, -0.48948362, 7.77550507]], [[-0.04455929, -0.87659335, -0.47916424, 3.93200684]], [[-0.21514639, 0.18835169, -0.95824611, 7.59479475]], [[-0.01006953, -0.86679155, -0.49856904, 4.01355648]], [[-0.00876531, -0.87571168, -0.48275498, 3.96768975]], [[-0.06395926, -0.86951321, -0.48975089, 4.08618736]], [[-0.01403128, -0.87593341, -0.48222789, 7.74559402]], [[-0.01143177, -0.87495202, -0.4840748 , 7.75355816]]], dtype=numpy.float32) eps = 0.05 self.assertLessEqual(cv.norm(planes_coeff, planes_coeff_expected, cv.NORM_L2), eps) if __name__ == '__main__': NewOpenCVTests.bootstrap()
modules/rgbd/src/odometry.cpp +22 −0 Original line number Diff line number Diff line Loading @@ -1009,6 +1009,28 @@ Ptr<DepthCleaner> DepthCleaner::create(int depth_in, int window_size_in, int met return makePtr<DepthCleaner>(depth_in, window_size_in, method_in); } RgbdPlane::RgbdPlane(int method, int block_size, int min_size, double threshold, double sensor_error_a, double sensor_error_b, double sensor_error_c) : method_(method), block_size_(block_size), min_size_(min_size), threshold_(threshold), sensor_error_a_(sensor_error_a), sensor_error_b_(sensor_error_b), sensor_error_c_(sensor_error_c) {} Ptr<RgbdPlane> RgbdPlane::create(int method, int block_size, int min_size, double threshold, double sensor_error_a, double sensor_error_b, double sensor_error_c ) { return makePtr<RgbdPlane>(method, block_size, min_size, threshold, sensor_error_a, sensor_error_b, sensor_error_c); } RgbdPlane::~RgbdPlane() {} RgbdFrame::RgbdFrame() : ID(-1) {} Loading