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https://github.com/introlab/rtabmap.git
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469 lines
16 KiB
C++
469 lines
16 KiB
C++
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#include "gtest/gtest.h"
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#include "rtabmap/core/util3d.h"
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#include "rtabmap/core/util3d_correspondences.h"
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#include "rtabmap/core/CameraModel.h"
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#include "rtabmap/utilite/UException.h"
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#include "rtabmap/utilite/UConversion.h"
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#include <pcl/io/pcd_io.h>
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using namespace rtabmap;
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TEST(Util3dCorrespondencesTest, ExtractXYZCorrespondencesValidOneToOneMatch) {
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std::multimap<int, pcl::PointXYZ> words1 = {
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{1, pcl::PointXYZ(1, 2, 3)},
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{2, pcl::PointXYZ(4, 5, 6)}
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};
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std::multimap<int, pcl::PointXYZ> words2 = {
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{1, pcl::PointXYZ(1.1f, 2.1f, 3.1f)},
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{2, pcl::PointXYZ(4.1f, 5.1f, 6.1f)}
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};
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pcl::PointCloud<pcl::PointXYZ> cloud1, cloud2;
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util3d::extractXYZCorrespondences(words1, words2, cloud1, cloud2);
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ASSERT_EQ(cloud1.size(), 2);
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ASSERT_EQ(cloud2.size(), 2);
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EXPECT_EQ(cloud1.points[0].x, 1);
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EXPECT_EQ(cloud2.points[1].z, 6.1f);
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}
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TEST(Util3dCorrespondencesTest, ExtractXYZCorrespondencesDuplicateKeysIgnored) {
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std::multimap<int, pcl::PointXYZ> words1 = {
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{1, pcl::PointXYZ(0, 0, 0)},
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{1, pcl::PointXYZ(1, 1, 1)}, // duplicate
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{2, pcl::PointXYZ(2, 2, 2)}
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};
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std::multimap<int, pcl::PointXYZ> words2 = {
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{1, pcl::PointXYZ(1, 1, 1)},
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{2, pcl::PointXYZ(2.1f, 2.1f, 2.1f)}
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};
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pcl::PointCloud<pcl::PointXYZ> cloud1, cloud2;
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util3d::extractXYZCorrespondences(words1, words2, cloud1, cloud2);
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ASSERT_EQ(cloud1.size(), 1);
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ASSERT_EQ(cloud2.size(), 1);
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EXPECT_EQ(cloud1[0].x, 2);
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EXPECT_EQ(cloud2[0].z, 2.1f);
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}
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TEST(Util3dCorrespondencesTest, ExtractXYZCorrespondencesInvalidPointsIgnored) {
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pcl::PointXYZ nanPt(std::numeric_limits<float>::quiet_NaN(), 0, 0);
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std::multimap<int, pcl::PointXYZ> words1 = {
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{1, pcl::PointXYZ(1, 2, 3)},
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{2, nanPt}
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};
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std::multimap<int, pcl::PointXYZ> words2 = {
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{1, pcl::PointXYZ(1.5f, 2.5f, 3.5f)},
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{2, pcl::PointXYZ(4, 5, 6)}
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};
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pcl::PointCloud<pcl::PointXYZ> cloud1, cloud2;
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util3d::extractXYZCorrespondences(words1, words2, cloud1, cloud2);
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ASSERT_EQ(cloud1.size(), 1);
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ASSERT_EQ(cloud2.size(), 1);
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EXPECT_EQ(cloud1[0].x, 1);
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EXPECT_EQ(cloud2[0].y, 2.5f);
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}
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TEST(Util3dCorrespondencesTest, ExtractXYZCorrespondencesNoCommonIDs) {
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std::multimap<int, pcl::PointXYZ> words1 = {
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{10, pcl::PointXYZ(1, 2, 3)}
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};
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std::multimap<int, pcl::PointXYZ> words2 = {
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{20, pcl::PointXYZ(4, 5, 6)}
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};
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pcl::PointCloud<pcl::PointXYZ> cloud1, cloud2;
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util3d::extractXYZCorrespondences(words1, words2, cloud1, cloud2);
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EXPECT_TRUE(cloud1.empty());
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EXPECT_TRUE(cloud2.empty());
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}
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TEST(Util3dCorrespondencesTest, ExtractXYZCorrespondencesRANSACAcceptsCleanMatches) {
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std::multimap<int, pcl::PointXYZ> words1;
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std::multimap<int, pcl::PointXYZ> words2;
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// 10 consistent matches
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for (int i = 0; i < 10; ++i) {
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words1.insert({i, pcl::PointXYZ(i * 1.0f, exp2(i)/10.0f, 0.0f)});
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words2.insert({i, pcl::PointXYZ(i * 1.0f + 1.1f, exp2(i)/10.0f + 1.1f, 0.0f)}); // Slight noise
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}
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pcl::PointCloud<pcl::PointXYZ> cloud1, cloud2;
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util3d::extractXYZCorrespondencesRANSAC(words1, words2, cloud1, cloud2);
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EXPECT_EQ(cloud1.size(), cloud2.size());
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EXPECT_GE(cloud1.size(), 8); // At least 8 inliers from 10 consistent matches
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}
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TEST(Util3dCorrespondencesTest, ExtractXYZCorrespondencesRANSACRejectsOutliers) {
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std::multimap<int, pcl::PointXYZ> words1;
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std::multimap<int, pcl::PointXYZ> words2;
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// 8 inliers
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for (int i = 0; i < 8; ++i) {
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words1.insert({i, pcl::PointXYZ(i * 1.0f, exp2(i)/10.0f, 0.0f)});
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words2.insert({i, pcl::PointXYZ(i * 1.0f + 1.1f, exp2(i)/10.0f + 1.1f, 0.0f)}); // Slight noise
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}
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// 2 outliers
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words1.insert({100, pcl::PointXYZ(0.0f, 0.0f, 0.0f)});
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words2.insert({100, pcl::PointXYZ(100.0f, 100.0f, 0.0f)});
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words1.insert({101, pcl::PointXYZ(1.0f, 1.0f, 0.0f)});
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words2.insert({101, pcl::PointXYZ(200.0f, -50.0f, 0.0f)});
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pcl::PointCloud<pcl::PointXYZ> cloud1, cloud2;
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util3d::extractXYZCorrespondencesRANSAC(words1, words2, cloud1, cloud2);
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EXPECT_EQ(cloud1.size(), cloud2.size());
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EXPECT_EQ(cloud1.size(), 8); // RANSAC should reject 2 outliers
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}
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TEST(Util3dCorrespondencesTest, ExtractXYZCorrespondencesRANSACFailsGracefullyOnTooFewMatches) {
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std::multimap<int, pcl::PointXYZ> words1 = {
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{1, pcl::PointXYZ(0, 0, 0)},
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{2, pcl::PointXYZ(1, 1, 1)},
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{3, pcl::PointXYZ(2, 2, 2)}
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};
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std::multimap<int, pcl::PointXYZ> words2 = {
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{1, pcl::PointXYZ(0.1f, 0.1f, 0)},
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{2, pcl::PointXYZ(1.1f, 1.1f, 1)},
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{3, pcl::PointXYZ(2.1f, 2.1f, 2)}
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};
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pcl::PointCloud<pcl::PointXYZ> cloud1, cloud2;
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util3d::extractXYZCorrespondencesRANSAC(words1, words2, cloud1, cloud2);
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EXPECT_TRUE(cloud1.empty());
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EXPECT_TRUE(cloud2.empty());
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}
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TEST(Util3dCorrespondencesTest, ExtractXYZCorrespondencesValidCorrespondencesAreExtracted) {
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// Create simple 5x5 depth images with valid depth
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cv::Mat depth1 = cv::Mat::ones(5, 5, CV_32FC1) * 1.0f;
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cv::Mat depth2 = cv::Mat::ones(5, 5, CV_32FC1) * 1.5f;
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std::list<std::pair<cv::Point2f, cv::Point2f>> matches = {
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{cv::Point2f(2, 2), cv::Point2f(2, 2)},
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{cv::Point2f(1, 1), cv::Point2f(1, 1)},
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{cv::Point2f(3, 3), cv::Point2f(3, 3)}
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};
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pcl::PointCloud<pcl::PointXYZ> cloud1, cloud2;
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float fx = 1.0f, fy = 1.0f, cx = 2.0f, cy = 2.0f;
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util3d::extractXYZCorrespondences(matches, depth1, depth2, cx, cy, fx, fy, 2.0f, cloud1, cloud2);
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ASSERT_EQ(cloud1.size(), 3);
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ASSERT_EQ(cloud2.size(), 3);
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// Check one known point
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EXPECT_FLOAT_EQ(cloud1[0].z, 1.0f);
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EXPECT_FLOAT_EQ(cloud2[0].z, 1.5f);
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}
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TEST(Util3dCorrespondencesTest, ExtractXYZCorrespondencesFiltersInvalidDepth) {
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cv::Mat depth1 = cv::Mat::ones(5, 5, CV_32FC1) * 1.0f;
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cv::Mat depth2 = cv::Mat::ones(5, 5, CV_32FC1) * 1.5f;
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depth1.at<float>(2, 2) = 0.0f; // Invalid
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depth2.at<float>(1, 1) = std::numeric_limits<float>::quiet_NaN(); // Invalid
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std::list<std::pair<cv::Point2f, cv::Point2f>> matches = {
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{cv::Point2f(2, 2), cv::Point2f(2, 2)},
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{cv::Point2f(1, 1), cv::Point2f(1, 1)},
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{cv::Point2f(3, 3), cv::Point2f(3, 3)}
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};
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pcl::PointCloud<pcl::PointXYZ> cloud1, cloud2;
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util3d::extractXYZCorrespondences(matches, depth1, depth2, 2.0f, 2.0f, 1.0f, 1.0f, 2.0f, cloud1, cloud2);
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// Only the third match should remain
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ASSERT_EQ(cloud1.size(), 1);
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ASSERT_EQ(cloud2.size(), 1);
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EXPECT_FLOAT_EQ(cloud1[0].z, 1.0f);
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EXPECT_FLOAT_EQ(cloud2[0].z, 1.5f);
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}
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TEST(Util3dCorrespondencesTest, ExtractXYZCorrespondencesRespectsMaxDepthConstraint) {
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cv::Mat depth1 = cv::Mat::ones(5, 5, CV_32FC1) * 3.0f; // Exceeds maxDepth
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cv::Mat depth2 = cv::Mat::ones(5, 5, CV_32FC1) * 1.0f;
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std::list<std::pair<cv::Point2f, cv::Point2f>> matches = {
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{cv::Point2f(2, 2), cv::Point2f(2, 2)},
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{cv::Point2f(1, 1), cv::Point2f(1, 1)}
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};
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pcl::PointCloud<pcl::PointXYZ> cloud1, cloud2;
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util3d::extractXYZCorrespondences(matches, depth1, depth2, 2.0f, 2.0f, 1.0f, 1.0f, 2.5f, cloud1, cloud2);
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// All points should be rejected due to depth1 being too large
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EXPECT_TRUE(cloud1.empty());
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EXPECT_TRUE(cloud2.empty());
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}
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TEST(Util3dCorrespondencesTest, ExtractXYZCorrespondencesOrgCloudsValidCorrespondencesAreExtracted) {
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int width = 5, height = 5;
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// Create two organized point clouds
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pcl::PointCloud<pcl::PointXYZ> cloud1, cloud2;
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cloud1.width = cloud2.width = width;
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cloud1.height = cloud2.height = height;
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cloud1.is_dense = cloud2.is_dense = false;
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cloud1.points.resize(width * height);
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cloud2.points.resize(width * height);
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// Fill the clouds with some values
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for (int v = 0; v < height; ++v) {
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for (int u = 0; u < width; ++u) {
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int idx = v * width + u;
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cloud1.at(idx).x = u;
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cloud1.at(idx).y = v;
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cloud1.at(idx).z = 1.0f;
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cloud2.at(idx).x = u + 0.5f;
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cloud2.at(idx).y = v + 0.5f;
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cloud2.at(idx).z = 1.5f;
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}
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}
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// Set correspondences to valid pixel positions
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std::list<std::pair<cv::Point2f, cv::Point2f>> correspondences = {
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{cv::Point2f(1, 1), cv::Point2f(1, 1)},
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{cv::Point2f(2, 2), cv::Point2f(2, 2)},
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{cv::Point2f(3, 3), cv::Point2f(3, 3)}
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};
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pcl::PointCloud<pcl::PointXYZ> inliers1, inliers2;
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util3d::extractXYZCorrespondences(correspondences, cloud1, cloud2, inliers1, inliers2);
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ASSERT_EQ(inliers1.size(), 3);
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ASSERT_EQ(inliers2.size(), 3);
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EXPECT_FLOAT_EQ(inliers1[0].x, 1);
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EXPECT_FLOAT_EQ(inliers1[0].z, 1.0f);
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EXPECT_FLOAT_EQ(inliers2[0].x, 1.5f);
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EXPECT_FLOAT_EQ(inliers2[0].z, 1.5f);
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}
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TEST(Util3dCorrespondencesTest, ExtractXYZCorrespondencesOrgCloudsInvalidPointsAreFilteredOut) {
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int width = 3, height = 3;
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pcl::PointCloud<pcl::PointXYZ> cloud1, cloud2;
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cloud1.width = cloud2.width = width;
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cloud1.height = cloud2.height = height;
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cloud1.is_dense = cloud2.is_dense = false;
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cloud1.points.resize(width * height);
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cloud2.points.resize(width * height);
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// Set all points to NaN
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for (size_t i = 0; i < cloud1.size(); ++i) {
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cloud1[i].x = cloud1[i].y = cloud1[i].z = std::numeric_limits<float>::quiet_NaN();
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cloud2[i].x = cloud2[i].y = cloud2[i].z = std::numeric_limits<float>::quiet_NaN();
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}
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// Set one valid point at (1,1)
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int idx = 1 * width + 1;
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cloud1[idx].x = 1.0f;
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cloud1[idx].y = 1.0f;
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cloud1[idx].z = 1.0f;
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cloud2[idx].x = 2.0f;
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cloud2[idx].y = 2.0f;
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cloud2[idx].z = 2.0f;
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std::list<std::pair<cv::Point2f, cv::Point2f>> correspondences = {
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{cv::Point2f(0, 0), cv::Point2f(0, 0)}, // Invalid
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{cv::Point2f(1, 1), cv::Point2f(1, 1)}, // Valid
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{cv::Point2f(2, 2), cv::Point2f(2, 2)} // Invalid
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};
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pcl::PointCloud<pcl::PointXYZ> inliers1, inliers2;
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util3d::extractXYZCorrespondences(correspondences, cloud1, cloud2, inliers1, inliers2);
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ASSERT_EQ(inliers1.size(), 1);
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ASSERT_EQ(inliers2.size(), 1);
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EXPECT_FLOAT_EQ(inliers1[0].x, 1.0f);
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EXPECT_FLOAT_EQ(inliers2[0].x, 2.0f);
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}
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TEST(Util3dCorrespondencesTest, CountUniquePairsNoPairs) {
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std::multimap<int, pcl::PointXYZ> wordsA, wordsB;
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wordsA.insert({1, pcl::PointXYZ(1, 2, 3)});
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wordsB.insert({2, pcl::PointXYZ(1, 2, 3)}); // No overlapping key
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EXPECT_EQ(util3d::countUniquePairs(wordsA, wordsB), 0);
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}
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TEST(Util3dCorrespondencesTest, CountUniquePairsOneUniquePair) {
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std::multimap<int, pcl::PointXYZ> wordsA, wordsB;
|
||
|
|
|
||
|
|
wordsA.insert({1, pcl::PointXYZ(1, 1, 1)});
|
||
|
|
wordsB.insert({1, pcl::PointXYZ(2, 2, 2)}); // One unique pair
|
||
|
|
|
||
|
|
EXPECT_EQ(util3d::countUniquePairs(wordsA, wordsB), 1);
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST(Util3dCorrespondencesTest, CountUniquePairsMultipleUniquePairs) {
|
||
|
|
std::multimap<int, pcl::PointXYZ> wordsA, wordsB;
|
||
|
|
|
||
|
|
wordsA.insert({1, pcl::PointXYZ(1, 1, 1)});
|
||
|
|
wordsA.insert({2, pcl::PointXYZ(2, 2, 2)});
|
||
|
|
wordsA.insert({3, pcl::PointXYZ(3, 3, 3)});
|
||
|
|
|
||
|
|
wordsB.insert({1, pcl::PointXYZ(1, 1, 1)});
|
||
|
|
wordsB.insert({2, pcl::PointXYZ(2, 2, 2)});
|
||
|
|
wordsB.insert({3, pcl::PointXYZ(3, 3, 3)});
|
||
|
|
|
||
|
|
EXPECT_EQ(util3d::countUniquePairs(wordsA, wordsB), 3);
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST(Util3dCorrespondencesTest, CountUniquePairsDuplicatedPointsNotCounted) {
|
||
|
|
std::multimap<int, pcl::PointXYZ> wordsA, wordsB;
|
||
|
|
|
||
|
|
wordsA.insert({1, pcl::PointXYZ(1, 1, 1)});
|
||
|
|
wordsA.insert({1, pcl::PointXYZ(1.1f, 1.1f, 1.1f)}); // duplicate in A
|
||
|
|
wordsB.insert({1, pcl::PointXYZ(2, 2, 2)});
|
||
|
|
|
||
|
|
EXPECT_EQ(util3d::countUniquePairs(wordsA, wordsB), 0);
|
||
|
|
|
||
|
|
wordsA.clear();
|
||
|
|
wordsB.clear();
|
||
|
|
|
||
|
|
wordsA.insert({2, pcl::PointXYZ(1, 1, 1)});
|
||
|
|
wordsB.insert({2, pcl::PointXYZ(2, 2, 2)});
|
||
|
|
wordsB.insert({2, pcl::PointXYZ(3, 3, 3)}); // duplicate in B
|
||
|
|
|
||
|
|
EXPECT_EQ(util3d::countUniquePairs(wordsA, wordsB), 0);
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST(Util3dCorrespondencesTest, FilterMaxDepthFiltersByMaxDepthZ) {
|
||
|
|
pcl::PointCloud<pcl::PointXYZ> cloud1;
|
||
|
|
pcl::PointCloud<pcl::PointXYZ> cloud2;
|
||
|
|
|
||
|
|
// Add points (some above and some below maxDepth = 5.0)
|
||
|
|
cloud1.push_back(pcl::PointXYZ(1.0f, 1.0f, 4.0f));
|
||
|
|
cloud2.push_back(pcl::PointXYZ(1.1f, 1.0f, 4.0f));
|
||
|
|
cloud1.push_back(pcl::PointXYZ(2.0f, 2.0f, 6.0f)); // exceeds maxDepth
|
||
|
|
cloud2.push_back(pcl::PointXYZ(2.1f, 2.0f, 6.0f));
|
||
|
|
cloud1.push_back(pcl::PointXYZ(3.0f, 3.0f, 3.0f));
|
||
|
|
cloud2.push_back(pcl::PointXYZ(3.1f, 3.0f, 3.0f));
|
||
|
|
|
||
|
|
// Filter by maxDepth=5.0 on 'z' axis, no duplicates removal
|
||
|
|
util3d::filterMaxDepth(cloud1, cloud2, 5.0f, 'z', false);
|
||
|
|
|
||
|
|
EXPECT_EQ(cloud1.size(), 2);
|
||
|
|
EXPECT_EQ(cloud2.size(), 2);
|
||
|
|
|
||
|
|
for (const auto& pt : cloud1) {
|
||
|
|
EXPECT_LT(pt.z, 5.0f);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST(Util3dCorrespondencesTest, FilterMaxDepthRemovesDuplicates) {
|
||
|
|
pcl::PointCloud<pcl::PointXYZ> cloud1;
|
||
|
|
pcl::PointCloud<pcl::PointXYZ> cloud2;
|
||
|
|
|
||
|
|
// Duplicate points in cloud1, but different points in cloud2
|
||
|
|
cloud1.push_back(pcl::PointXYZ(1.0f, 1.0f, 1.0f));
|
||
|
|
cloud2.push_back(pcl::PointXYZ(1.1f, 1.0f, 1.0f));
|
||
|
|
cloud1.push_back(pcl::PointXYZ(1.0f, 1.0f, 1.0f)); // duplicate
|
||
|
|
cloud2.push_back(pcl::PointXYZ(1.2f, 1.0f, 1.0f));
|
||
|
|
cloud1.push_back(pcl::PointXYZ(2.0f, 2.0f, 2.0f));
|
||
|
|
cloud2.push_back(pcl::PointXYZ(2.1f, 2.0f, 2.0f));
|
||
|
|
|
||
|
|
// maxDepth large enough to keep all points, removeDuplicates = true
|
||
|
|
util3d::filterMaxDepth(cloud1, cloud2, 10.0f, 'z', true);
|
||
|
|
|
||
|
|
EXPECT_EQ(cloud1.size(), 2);
|
||
|
|
EXPECT_EQ(cloud2.size(), 2);
|
||
|
|
|
||
|
|
// Check that duplicate is removed (only one point with 1.0,1.0,1.0)
|
||
|
|
int countPoint = 0;
|
||
|
|
for (const auto& pt : cloud1) {
|
||
|
|
if (pt.x == 1.0f && pt.y == 1.0f && pt.z == 1.0f) {
|
||
|
|
countPoint++;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
EXPECT_EQ(countPoint, 1);
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST(Util3dCorrespondencesTest, FindCorrespondencesBasicMatching)
|
||
|
|
{
|
||
|
|
std::multimap<int, cv::KeyPoint> wordsA, wordsB;
|
||
|
|
std::list<std::pair<cv::Point2f, cv::Point2f>> pairs;
|
||
|
|
|
||
|
|
// Setup wordsA: IDs 1, 2, 3 (only 2 is unique)
|
||
|
|
wordsA.insert({1, cv::KeyPoint(10.0f, 10.0f, 1)});
|
||
|
|
wordsA.insert({2, cv::KeyPoint(20.0f, 20.0f, 1)});
|
||
|
|
wordsA.insert({3, cv::KeyPoint(30.0f, 30.0f, 1)});
|
||
|
|
wordsA.insert({3, cv::KeyPoint(31.0f, 31.0f, 1)});
|
||
|
|
|
||
|
|
// Setup wordsB: IDs 2, 3 (only 2 is unique in both)
|
||
|
|
wordsB.insert({2, cv::KeyPoint(20.5f, 20.5f, 1)});
|
||
|
|
wordsB.insert({3, cv::KeyPoint(30.5f, 30.5f, 1)});
|
||
|
|
wordsB.insert({3, cv::KeyPoint(32.0f, 32.0f, 1)});
|
||
|
|
|
||
|
|
util3d::findCorrespondences(wordsA, wordsB, pairs);
|
||
|
|
|
||
|
|
ASSERT_EQ(pairs.size(), 1);
|
||
|
|
EXPECT_EQ(pairs.front().first, cv::Point2f(20.0f, 20.0f));
|
||
|
|
EXPECT_EQ(pairs.front().second, cv::Point2f(20.5f, 20.5f));
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST(Util3dCorrespondencesTest, FindCorrespondencesMatchesWithDepthCheck)
|
||
|
|
{
|
||
|
|
std::multimap<int, cv::Point3f> words1, words2;
|
||
|
|
std::vector<cv::Point3f> inliers1, inliers2;
|
||
|
|
std::vector<int> correspondences;
|
||
|
|
|
||
|
|
// Insert matching and non-matching entries
|
||
|
|
words1.insert({1, cv::Point3f(1, 1, 1)});
|
||
|
|
words1.insert({2, cv::Point3f(2, 2, 2)});
|
||
|
|
words1.insert({3, cv::Point3f(100, 100, 100)}); // out of depth
|
||
|
|
|
||
|
|
words2.insert({1, cv::Point3f(1.1f, 1.1f, 1.1f)});
|
||
|
|
words2.insert({2, cv::Point3f(2.1f, 2.1f, 2.1f)});
|
||
|
|
words2.insert({3, cv::Point3f(101, 101, 101)}); // out of depth
|
||
|
|
|
||
|
|
float maxDepth = 10.0f;
|
||
|
|
|
||
|
|
util3d::findCorrespondences(words1, words2, inliers1, inliers2, maxDepth, &correspondences);
|
||
|
|
|
||
|
|
ASSERT_EQ(inliers1.size(), 2);
|
||
|
|
ASSERT_EQ(inliers2.size(), 2);
|
||
|
|
ASSERT_EQ(correspondences.size(), 2);
|
||
|
|
|
||
|
|
EXPECT_EQ(correspondences[0], 1);
|
||
|
|
EXPECT_EQ(correspondences[1], 2);
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST(Util3dCorrespondencesTest, FindCorrespondencesMatchesWithMaxDepth)
|
||
|
|
{
|
||
|
|
std::map<int, cv::Point3f> words1, words2;
|
||
|
|
std::vector<cv::Point3f> inliers1, inliers2;
|
||
|
|
std::vector<int> correspondences;
|
||
|
|
|
||
|
|
words1[1] = cv::Point3f(1, 1, 1);
|
||
|
|
words1[2] = cv::Point3f(2, 2, 2);
|
||
|
|
words1[3] = cv::Point3f(100, 100, 100); // Exceeds maxDepth
|
||
|
|
|
||
|
|
words2[1] = cv::Point3f(1.2f, 1.2f, 1.2f);
|
||
|
|
words2[2] = cv::Point3f(2.2f, 2.2f, 2.2f);
|
||
|
|
words2[3] = cv::Point3f(101, 101, 101); // Exceeds maxDepth
|
||
|
|
|
||
|
|
util3d::findCorrespondences(words1, words2, inliers1, inliers2, 10.0f, &correspondences);
|
||
|
|
|
||
|
|
ASSERT_EQ(inliers1.size(), 2);
|
||
|
|
ASSERT_EQ(inliers2.size(), 2);
|
||
|
|
ASSERT_EQ(correspondences.size(), 2);
|
||
|
|
|
||
|
|
EXPECT_EQ(correspondences[0], 1);
|
||
|
|
EXPECT_EQ(correspondences[1], 2);
|
||
|
|
}
|