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fixing some appveyor CI errors, added test to check dictionary serialization against all type

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This commit is contained in:
matlabbe
2025-12-23 09:52:21 -08:00
parent f7cb330e31
commit 837b08a4f3
3 changed files with 142 additions and 45 deletions
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corelib/test/test_util3d_registration.cpp
+4 -4
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@@ -284,7 +284,7 @@ TEST(Util3DRegistration, icpIdentityTransformConverges)
auto cloud_source = pcl::PointCloud<pcl::PointXYZ>::Ptr(new pcl::PointCloud<pcl::PointXYZ>());
for (float i = 0; i < 5; ++i)
{
cloud_source->emplace_back(i, i * 2.0f, 0.0f);
cloud_source->push_back(pcl::PointXYZ(i, i * 2.0f, 0.0f));
}
auto cloud_target = pcl::PointCloud<pcl::PointXYZ>::Ptr(new pcl::PointCloud<pcl::PointXYZ>());
@@ -313,7 +313,7 @@ TEST(Util3DRegistration, icpTranslatedTransformConverges)
auto cloud_source = pcl::PointCloud<pcl::PointXYZ>::Ptr(new pcl::PointCloud<pcl::PointXYZ>());
for (float i = 0; i < 5; ++i)
{
cloud_source->emplace_back(i, i * 2.0f, 0);
cloud_source->push_back(pcl::PointXYZ(i, i * 2.0f, 0));
}
// Translate the cloud
@@ -348,7 +348,7 @@ TEST(Util3DRegistration, icp2DAlignsFlatClouds)
for (float y = 0; y < 5; ++y)
{
if(y == 0 || y == 2 || y == 4 || x==0 || x==2 || x== 4){
cloud_source->emplace_back(x*0.05, y*0.05, (int)x%2==0?0.01:-0.01);
cloud_source->push_back(pcl::PointXYZ(x*0.05, y*0.05, (int)x%2==0?0.01:-0.01));
}
}
}
@@ -382,7 +382,7 @@ TEST(Util3DRegistration, icpPointToPlaneAlignsTranslatedPlane)
{
for (float y = -0.5f; y <= 0.5f; y += 0.1f)
{
cloud_source_raw->emplace_back(x, y, int(x*10)%2==0&&int(y*10)%2==0?0.01:-0.01);
cloud_source_raw->push_back(pcl::PointXYZ(x, y, int(x*10)%2==0&&int(y*10)%2==0?0.01:-0.01));
}
}
corelib/test/test_util3d_surface.cpp
+24
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@@ -35,21 +35,33 @@ TEST(Util3dSurface, computeNormalsComplexityVaryingNormals3D)
EXPECT_NEAR(complexity, 0.0f, 1e-3);
pcl::PointCloud<pcl::PointNormal> cloudA;
#if PCL_VERSION_COMPARE(>=, 1, 10, 0)
pcl::concatenate(floor, wallA, cloudA);
#else
pcl::concatenatePointCloud(floor, wallA, cloudA);
#endif
// Two perpendicular surfaces
complexity = util3d::computeNormalsComplexity(cloudA);
EXPECT_NEAR(complexity, 0.0f, 1e-3);
// Three perpendicular surfaces
pcl::PointCloud<pcl::PointNormal> cloudB;
#if PCL_VERSION_COMPARE(>=, 1, 10, 0)
pcl::concatenate(cloudA, wallB, cloudB);
#else
pcl::concatenatePointCloud(cloudA, wallB, cloudB);
#endif
complexity = util3d::computeNormalsComplexity(cloudB);
EXPECT_NEAR(complexity, 0.25f, 1e-3);
// Three perpendicular surfaces (one small)
pcl::PointCloud<pcl::PointNormal> smallCloudB;
#if PCL_VERSION_COMPARE(>=, 1, 10, 0)
pcl::concatenate(cloudA, smallWallB, smallCloudB);
#else
pcl::concatenatePointCloud(cloudA, smallWallB, smallCloudB);
#endif
complexity = util3d::computeNormalsComplexity(smallCloudB);
EXPECT_LT(complexity, 0.25f);
@@ -96,20 +108,32 @@ TEST(Util3dSurface, computeNormalsComplexityVaryingNormals2D)
EXPECT_NEAR(complexity, 0.0f, 1e-3);
pcl::PointCloud<pcl::PointNormal> cloud;
#if PCL_VERSION_COMPARE(>=, 1, 10, 0)
pcl::concatenate(wallA, wallB, cloud);
#else
pcl::concatenatePointCloud(wallA, wallB, cloud);
#endif
// Two perpendicular surfaces
complexity = util3d::computeNormalsComplexity(cloud, Transform(), true);
EXPECT_NEAR(complexity, 0.25f, 1e-3);
pcl::PointCloud<pcl::PointNormal> cloudB;
#if PCL_VERSION_COMPARE(>=, 1, 10, 0)
pcl::concatenate(wallA, smalllWallB, cloudB);
#else
pcl::concatenatePointCloud(wallA, smalllWallB, cloudB);
#endif
// Two perpendicular surfaces (one small)
complexity = util3d::computeNormalsComplexity(cloudB, Transform(), true);
EXPECT_LT(complexity, 0.25f);
EXPECT_GT(complexity, 0.01f);
pcl::PointCloud<pcl::PointNormal> corridorLikeCloud;
#if PCL_VERSION_COMPARE(>=, 1, 10, 0)
pcl::concatenate(wallA, negWallA, corridorLikeCloud);
#else
pcl::concatenatePointCloud(wallA, negWallA, corridorLikeCloud);
#endif
// Two parallel surfaces simulating a corridor
cv::Mat vector,values;
complexity = util3d::computeNormalsComplexity(corridorLikeCloud, Transform(), true, &vector, &values);
corelib/test/test_vwdictionary.cpp
+114 -41
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@@ -621,53 +621,126 @@ TEST_F(VWDictionaryTest, MemoryUsed)
TEST_F(VWDictionaryTest, SerializeDeserializeIndex)
{
// Add words and build index
cv::Mat descriptors(5, 32, CV_32F);
cv::randu(descriptors, cv::Scalar(0), cv::Scalar(1));
dict->addNewWords(descriptors, 1);
dict->update();
// Serialize
std::vector<unsigned char> data = dict->serializeIndex();
EXPECT_GT(data.size(), 0u);
// Create new dictionary and deserialize
VWDictionary dict2;
cv::Mat descriptors2(5, 32, CV_32F);
cv::randu(descriptors2, cv::Scalar(0), cv::Scalar(1));
dict2.addNewWords(descriptors2, 1);
// Deserialize should fail because we are not using the same descriptors
bool success = dict2.deserializeIndex(data);
EXPECT_FALSE(success);
success = dict2.deserializeIndex(data.data(), data.size());
EXPECT_FALSE(success);
// Test with all NNStrategy values
VWDictionary::NNStrategy strategies[] = {
VWDictionary::kNNFlannNaive,
VWDictionary::kNNFlannKdTree,
VWDictionary::kNNFlannLSH,
VWDictionary::kNNBruteForce,
VWDictionary::kNNBruteForceGPU
};
// Same descriptors
VWDictionary dict3;
dict3.addNewWords(descriptors, 1);
success = dict3.deserializeIndex(data);
EXPECT_TRUE(success);
for(VWDictionary::NNStrategy strategy : strategies)
{
// Reset dictionary for each strategy
dict->clear();
dict->setNNStrategy(strategy);
// Index should be loaded
EXPECT_GT(dict3.getIndexedWordsCount(), 0u);
if(strategy == VWDictionary::kNNBruteForceGPU)
{
#if CV_MAJOR_VERSION < 3
#ifdef HAVE_OPENCV_GPU
if(!cv::gpu::getCudaEnabledDeviceCount())
{
continue; // Skip if no GPU available
}
#else
continue; // Skip if GPU support not compiled
#endif
#else
#ifdef HAVE_OPENCV_CUDAFEATURES2D
if(!cv::cuda::getCudaEnabledDeviceCount())
{
continue; // Skip if no GPU available
}
#else
continue; // Skip if GPU support not compiled
#endif
#endif
}
// Should fail if index is already built
success = dict3.deserializeIndex(data);
EXPECT_FALSE(success);
// Add words and build index
cv::Mat descriptors(5, 32, CV_32F);
cv::randu(descriptors, cv::Scalar(0), cv::Scalar(1));
// Convert to binary if using LSH strategy
if(strategy == VWDictionary::kNNFlannLSH)
{
// Convert float descriptors to binary
descriptors = VWDictionary::convert32FToBin(descriptors, true);
}
dict->addNewWords(descriptors, 1);
dict->update();
// Serialize
std::vector<unsigned char> data = dict->serializeIndex();
if(strategy < VWDictionary::kNNBruteForce)
{
// flann strategies
EXPECT_GT(data.size(), 0u) << "Strategy: " << VWDictionary::nnStrategyName(strategy);
}
else {
EXPECT_EQ(data.size(), 0u) << "Strategy: " << VWDictionary::nnStrategyName(strategy);
}
// Create new dictionary and deserialize
VWDictionary dict2;
dict2.setNNStrategy(strategy);
cv::Mat descriptors2(5, 32, CV_32F);
cv::randu(descriptors2, cv::Scalar(0), cv::Scalar(1));
// Convert to binary if using LSH strategy
if(strategy == VWDictionary::kNNFlannLSH)
{
descriptors2 = VWDictionary::convert32FToBin(descriptors2, true);
}
dict2.addNewWords(descriptors2, 1);
// Deserialize should fail because we are not using the same descriptors
bool success = dict2.deserializeIndex(data);
EXPECT_FALSE(success) << "Strategy: " << VWDictionary::nnStrategyName(strategy);
success = dict2.deserializeIndex(data.data(), data.size());
EXPECT_FALSE(success) << "Strategy: " << VWDictionary::nnStrategyName(strategy);
// raw bytes
VWDictionary dict4;
dict4.addNewWords(descriptors, 1);
success = dict4.deserializeIndex(data.data(), data.size());
EXPECT_TRUE(success);
// Same descriptors
VWDictionary dict3;
dict3.setNNStrategy(strategy);
dict3.addNewWords(descriptors, 1);
success = dict3.deserializeIndex(data);
if(strategy < VWDictionary::kNNBruteForce)
{
// flann strategies
EXPECT_TRUE(success) << "Strategy: " << VWDictionary::nnStrategyName(strategy);
// Index should be loaded
EXPECT_GT(dict4.getIndexedWordsCount(), 0u);
// Index should be loaded
EXPECT_GT(dict3.getIndexedWordsCount(), 0u) << "Strategy: " << VWDictionary::nnStrategyName(strategy);
}
else
{
EXPECT_FALSE(success) << "Strategy: " << VWDictionary::nnStrategyName(strategy);
continue;
}
// Should fail if index is already built
success = dict4.deserializeIndex(data.data(), data.size());
EXPECT_FALSE(success);
// Should fail if index is already built
success = dict3.deserializeIndex(data);
EXPECT_FALSE(success) << "Strategy: " << VWDictionary::nnStrategyName(strategy);
// raw bytes
VWDictionary dict4;
dict4.setNNStrategy(strategy);
dict4.addNewWords(descriptors, 1);
success = dict4.deserializeIndex(data.data(), data.size());
EXPECT_TRUE(success) << "Strategy: " << VWDictionary::nnStrategyName(strategy);
// Index should be loaded
EXPECT_GT(dict4.getIndexedWordsCount(), 0u) << "Strategy: " << VWDictionary::nnStrategyName(strategy);
// Should fail if index is already built
success = dict4.deserializeIndex(data.data(), data.size());
EXPECT_FALSE(success) << "Strategy: " << VWDictionary::nnStrategyName(strategy);
}
}
TEST_F(VWDictionaryTest, IsModified)