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/*
* Software License Agreement (BSD License)
*
* Copyright (c) 2011, Willow Garage, 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 Willow Garage, Inc. 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.
*
* Author: Anatoly Baskeheev, Itseez Ltd, (myname.mysurname@mycompany.com)
*/
#include <numeric>
#include <algorithm>
#include <vector>
#include <gtest/gtest.h>
#if defined _MSC_VER
#pragma warning (disable: 4521)
#endif
#include <pcl/pcl_tests.h> // for EXPECT_EQ_VECTORS
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>
#include <pcl/octree/octree_search.h>
#if defined _MSC_VER
#pragma warning (default: 4521)
#endif
#include <pcl/gpu/octree/octree.hpp>
#include <pcl/gpu/containers/device_array.h>
#include <pcl/gpu/containers/initialization.h>
#include "data_source.hpp"
using namespace pcl;
using namespace pcl::gpu;
//TEST(PCL_OctreeGPU, DISABLED_hostRadiusSearch)
TEST(PCL_OctreeGPU, hostRadiusSearch)
{
DataGenerator data;
data.data_size = 871000;
data.tests_num = 10000;
data.cube_size = 1024.f;
data.max_radius = data.cube_size/15.f;
data.shared_radius = data.cube_size/20.f;
data.printParams();
//generate
data();
//prepare device cloud
pcl::gpu::Octree::PointCloud cloud_device;
cloud_device.upload(data.points);
//prepare host cloud
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_host(new pcl::PointCloud<pcl::PointXYZ>);
cloud_host->width = data.points.size();
cloud_host->height = 1;
cloud_host->points.resize (cloud_host->width * cloud_host->height);
std::transform(data.points.cbegin(), data.points.cend(), cloud_host->begin(), DataGenerator::ConvPoint<pcl::PointXYZ>());
// build device octree
pcl::gpu::Octree octree_device;
octree_device.setCloud(cloud_device);
octree_device.build();
// build host octree
float resolution = 25.f;
std::cout << "[!]Octree resolution: " << resolution << std::endl;
pcl::octree::OctreePointCloudSearch<pcl::PointXYZ> octree_host(resolution);
octree_host.setInputCloud (cloud_host);
octree_host.addPointsFromInputCloud ();
//perform bruteForceSearch
data.bruteForceSearch(true);
std::vector<int> sizes;
sizes.reserve(data.tests_num);
octree_device.internalDownload();
for(std::size_t i = 0; i < data.tests_num; ++i)
{
//search host on octree that was built on device
std::vector<int> results_host_gpu; //host search
octree_device.radiusSearchHost(data.queries[i], data.radiuses[i], results_host_gpu);
//search host
std::vector<float> dists;
pcl::Indices results_host;
octree_host.radiusSearch(pcl::PointXYZ(data.queries[i].x, data.queries[i].y, data.queries[i].z), data.radiuses[i], results_host, dists);
std::sort(results_host_gpu.begin(), results_host_gpu.end());
std::sort(results_host.begin(), results_host.end());
pcl::test::EXPECT_EQ_VECTORS (results_host_gpu, results_host);
pcl::test::EXPECT_EQ_VECTORS (results_host_gpu, data.bfresutls[i]);
sizes.push_back(results_host.size());
}
float avg_size = std::accumulate(sizes.begin(), sizes.end(), 0) * (1.f/sizes.size());;
std::cout << "avg_result_size = " << avg_size << std::endl;
ASSERT_GT(avg_size, 5);
}
int main (int argc, char** argv)
{
const int device = 0;
pcl::gpu::setDevice(device);
pcl::gpu::printShortCudaDeviceInfo(device);
testing::InitGoogleTest (&argc, argv);
return (RUN_ALL_TESTS ());
}
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