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Merge pull request #3323 from taketwo/fix-uniform-sampling
Fix a bug in removed index extraction in `UniformSampling`
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/* | ||
* Software License Agreement (BSD License) | ||
* | ||
* Point Cloud Library (PCL) - www.pointclouds.org | ||
* Copyright (c) 2019-, Open Perception, Inc. | ||
* | ||
* All rights reserved. | ||
* | ||
* Redistribution and use in source and binary forms, with or without | ||
* modification, are permitted provided that the following conditions | ||
* are met: | ||
* | ||
* * Redistributions of source code must retain the above copyright | ||
* notice, this list of conditions and the following disclaimer. | ||
* * Redistributions in binary form must reproduce the above | ||
* copyright notice, this list of conditions and the following | ||
* disclaimer in the documentation and/or other materials provided | ||
* with the distribution. | ||
* * Neither the name of the copyright holder(s) nor the names of its | ||
* contributors may be used to endorse or promote products derived | ||
* from this software without specific prior written permission. | ||
* | ||
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS | ||
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT | ||
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS | ||
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE | ||
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, | ||
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, | ||
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER | ||
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT | ||
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN | ||
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE | ||
* POSSIBILITY OF SUCH DAMAGE. | ||
*/ | ||
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#include <gtest/gtest.h> | ||
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#include <pcl/common/generate.h> | ||
#include <pcl/common/random.h> | ||
#include <pcl/filters/uniform_sampling.h> | ||
#include <pcl/point_types.h> | ||
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TEST(UniformSampling, extractRemovedIndices) | ||
{ | ||
using namespace pcl::common; | ||
const int SEED = 1234; | ||
CloudGenerator<pcl::PointXYZ, UniformGenerator<float>> generator; | ||
UniformGenerator<float>::Parameters x_params(0, 1, SEED + 1); | ||
generator.setParametersForX(x_params); | ||
UniformGenerator<float>::Parameters y_params(0, 1, SEED + 2); | ||
generator.setParametersForY(y_params); | ||
UniformGenerator<float>::Parameters z_params(0, 1, SEED + 3); | ||
generator.setParametersForZ(z_params); | ||
pcl::PointCloud<pcl::PointXYZ>::Ptr xyz(new pcl::PointCloud<pcl::PointXYZ>); | ||
generator.fill(100, 100, *xyz); | ||
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// The generated cloud points are distributed in the unit cube. By using 0.1 sized | ||
// voxels for sampling, we divide each side of the cube into 1 / 0.1 = 10 cells, in | ||
// total 10^3 = 1000 cells. Since we generated a large amount of points, we can be | ||
// sure that each cell has at least one point. As a result, we expect 1000 points in | ||
// the output cloud and the rest in removed indices. | ||
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pcl::UniformSampling<pcl::PointXYZ> us(true); // extract removed indices | ||
us.setInputCloud(xyz); | ||
us.setRadiusSearch(0.1); | ||
pcl::PointCloud<pcl::PointXYZ> output; | ||
us.filter(output); | ||
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auto removed_indices = us.getRemovedIndices(); | ||
ASSERT_EQ(output.size(), 1000); | ||
EXPECT_EQ(removed_indices->size(), xyz->size() - 1000); | ||
std::set<int> removed_indices_set(removed_indices->begin(), removed_indices->end()); | ||
ASSERT_TRUE(removed_indices_set.size() == removed_indices->size()); | ||
} | ||
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int | ||
main(int argc, char** argv) | ||
{ | ||
testing::InitGoogleTest(&argc, argv); | ||
return (RUN_ALL_TESTS()); | ||
} |