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b06544bd54
Add normal estimation and region growing algorithm for point cloud * Add normal estimation and region growing algorithm for point cloud * 1.Modified documentation for normal estimation;2.Converted curvature in region growing to absolute values;3.Changed the data type of threshold from float to double;4.Fixed some bugs; * Finished documentation * Add tests for normal estimation. Test the normal and curvature of each point in the plane and sphere of the point cloud. * Fix some warnings caused by to small numbers in test * Change the test to calculate the average difference instead of comparing each normal and curvature * Fixed the bugs found by testing * Redesigned the interface and fixed problems: 1. Make the interface compatible with radius search. 2. Make region growing optionally sortable on results. 3. Modified the region growing interface. 4. Format reference. 5. Removed sphere test. * Fix warnings * Remove flann dependency * Move the flann dependency to the corresponding test
110 lines
3.5 KiB
C++
110 lines
3.5 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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//
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// Copyright (C) 2021, Wanli Zhong <zhongwl2018@mail.sustech.edu.cn>
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#include "test_ptcloud_utils.hpp"
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namespace opencv_test {
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void generatePlane(OutputArray plane_pts, const vector<float> &model, float thr, int num,
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const vector<float> &limit)
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{
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if (plane_pts.channels() == 3 && plane_pts.isVector())
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{
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// std::vector<cv::Point3f>
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plane_pts.create(1, num, CV_32FC3);
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}
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else
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{
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// cv::Mat
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plane_pts.create(num, 3, CV_32F);
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}
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cv::RNG rng(0);
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auto *plane_pts_ptr = (float *) plane_pts.getMat().data;
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// Part of the points are generated for the specific model
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// The other part of the points are used to increase the thickness of the plane
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int std_num = (int) (num / 2);
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// Difference of maximum d between two parallel planes
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float d_thr = thr * sqrt(model[0] * model[0] + model[1] * model[1] + model[2] * model[2]);
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for (int i = 0; i < num; i++)
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{
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// Let d change then generate thickness
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float d = i < std_num ? model[3] : rng.uniform(model[3] - d_thr, model[3] + d_thr);
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float x, y, z;
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// c is 0 means the plane is vertical
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if (model[2] == 0)
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{
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z = rng.uniform(limit[4], limit[5]);
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if (model[0] == 0)
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{
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x = rng.uniform(limit[0], limit[1]);
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y = -d / model[1];
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}
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else if (model[1] == 0)
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{
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x = -d / model[0];
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y = rng.uniform(limit[2], limit[3]);
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}
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else
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{
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x = rng.uniform(limit[0], limit[1]);
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y = -(model[0] * x + d) / model[1];
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}
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}
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// c is not 0
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else
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{
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x = rng.uniform(limit[0], limit[1]);
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y = rng.uniform(limit[2], limit[3]);
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z = -(model[0] * x + model[1] * y + d) / model[2];
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}
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plane_pts_ptr[3 * i] = x;
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plane_pts_ptr[3 * i + 1] = y;
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plane_pts_ptr[3 * i + 2] = z;
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}
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}
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void generateSphere(OutputArray sphere_pts, const vector<float> &model, float thr, int num,
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const vector<float> &limit)
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{
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if (sphere_pts.channels() == 3 && sphere_pts.isVector())
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{
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// std::vector<cv::Point3f>
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sphere_pts.create(1, num, CV_32FC3);
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}
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else
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{
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// cv::Mat
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sphere_pts.create(num, 3, CV_32F);
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}
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cv::RNG rng(0);
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auto *sphere_pts_ptr = (float *) sphere_pts.getMat().data;
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// Part of the points are generated for the specific model
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// The other part of the points are used to increase the thickness of the sphere
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int sphere_num = (int) (num / 1.5);
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for (int i = 0; i < num; i++)
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{
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// Let r change then generate thickness
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float r = i < sphere_num ? model[3] : rng.uniform(model[3] - thr, model[3] + thr);
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// Generate a random vector and normalize it.
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Vec3f vec(rng.uniform(limit[0], limit[1]), rng.uniform(limit[2], limit[3]),
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rng.uniform(limit[4], limit[5]));
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float l = sqrt(vec.dot(vec));
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// Normalizes it to have a magnitude of r
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vec /= l / r;
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sphere_pts_ptr[3 * i] = model[0] + vec[0];
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sphere_pts_ptr[3 * i + 1] = model[1] + vec[1];
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sphere_pts_ptr[3 * i + 2] = model[2] + vec[2];
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}
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}
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} // opencv_test
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