Bug fix, add docs example

gcc compiler warning as error (doxygen math) fix
isl-org · Nov 18, 2024 · 9f60d3d · 9f60d3d
1 parent a4f379d
commit 9f60d3d
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Showing 10 changed files with 100 additions and 38 deletions.
diff --git a/cpp/open3d/t/geometry/PointCloud.cpp b/cpp/open3d/t/geometry/PointCloud.cpp
@@ -1335,14 +1335,18 @@ int PointCloud::PCAPartition(int max_points) {
 core::Tensor PointCloud::ComputeMetrics(const PointCloud &pcd2,
                                         std::vector<Metric> metrics,
                                         MetricParameters params) const {
+    if (IsEmpty() || pcd2.IsEmpty()) {
+        utility::LogError("One or both input point clouds are empty!");
+    }
     if (!IsCPU() || !pcd2.IsCPU()) {
         utility::LogWarning(
                 "ComputeDistance is implemented only on CPU. Computing on "
                 "CPU.");
     }
     core::Tensor points1 = GetPointPositions().To(core::Device("CPU:0")),
                  points2 = pcd2.GetPointPositions().To(core::Device("CPU:0"));
-    core::Tensor indices12, distance12, indices21, distance21;
+    [[maybe_unused]] core::Tensor indices12, indices21;
+    core::Tensor sqr_distance12, sqr_distance21;
 
     core::nns::NearestNeighborSearch tree1(points1);
     core::nns::NearestNeighborSearch tree2(points2);
@@ -1354,10 +1358,11 @@ core::Tensor PointCloud::ComputeMetrics(const PointCloud &pcd2,
         utility::LogError("[ComputeDistance] Building KNN-Index failed!");
     }
 
-    std::tie(indices12, distance12) = tree2.KnnSearch(points1, 1);
-    std::tie(indices21, distance21) = tree2.KnnSearch(points2, 1);
+    std::tie(indices12, sqr_distance12) = tree2.KnnSearch(points1, 1);
+    std::tie(indices21, sqr_distance21) = tree1.KnnSearch(points2, 1);
 
-    return ComputeMetricsCommon(distance12, distance21, metrics, params);
+    return ComputeMetricsCommon(sqr_distance12.Sqrt_(), sqr_distance21.Sqrt_(),
+                                metrics, params);
 }
 
 }  // namespace geometry

diff --git a/cpp/open3d/t/geometry/PointCloud.h b/cpp/open3d/t/geometry/PointCloud.h
@@ -712,17 +712,17 @@ class PointCloud : public Geometry, public DrawableGeometry {
 
     /// \f{eqnarray*}{
     ///   \text{Chamfer Distance: } d_{CD}(X,Y) &=& \frac{1}{|X|}\sum_{i \in X}
-    ///   || x_i - n(x_i, Y) || +
-    ///   \frac{1}{|Y|}\sum_{i \in Y} || y_i - n(y_i, X) || \\
+    ///   || x_i - n(x_i, Y) || + \frac{1}{|Y|}\sum_{i \in Y} || y_i - n(y_i, X)
+    ///   || \\{}
     ///   \text{Hausdorff distance: } d_H(X,Y) &=& \max \left\{ \max_{i \in X}
     ///   || x_i - n(x_i, Y) ||, \max_{i \in Y} || y_i - n(y_i, X) || \right\}
-    ///   \\
+    ///   \\{}
     ///   \text{Precision: } P(X,Y|d) &=& \frac{100}{|X|} \sum_{i \in X} || x_i
-    ///   - n(x_i, Y) || < d \\
+    ///   - n(x_i, Y) || < d \\{}
     ///   \text{Recall: } R(X,Y|d) &=& \frac{100}{|Y|} \sum_{i \in Y} || y_i -
-    ///  n(y_i, X) || < d \\
+    ///   n(y_i, X) || < d \\{}
     ///   \text{F-Score: } F(X,Y|d) &=& \frac{2 P(X,Y|d) R(X,Y|d)}{P(X,Y|d) +
-    ///  R(X,Y|d)} \\
+    ///   R(X,Y|d)}
     /// \f}
 
     /// \param pcd2 Other point cloud to compare with.

diff --git a/cpp/open3d/t/geometry/TriangleMesh.cpp b/cpp/open3d/t/geometry/TriangleMesh.cpp
@@ -1594,6 +1594,9 @@ PointCloud TriangleMesh::SamplePointsUniformly(
 core::Tensor TriangleMesh::ComputeMetrics(const TriangleMesh &mesh2,
                                           std::vector<Metric> metrics,
                                           MetricParameters params) const {
+    if (IsEmpty() || mesh2.IsEmpty()) {
+        utility::LogError("One or both input triangle meshes are empty!");
+    }
     if (!IsCPU() || !mesh2.IsCPU()) {
         utility::LogWarning(
                 "ComputeDistance is implemented only on CPU. Computing on "

diff --git a/cpp/open3d/t/geometry/TriangleMesh.h b/cpp/open3d/t/geometry/TriangleMesh.h
@@ -1036,17 +1036,17 @@ class TriangleMesh : public Geometry, public DrawableGeometry {
 
     /// \f{eqnarray*}{
     ///   \text{Chamfer Distance: } d_{CD}(X,Y) &=& \frac{1}{|X|}\sum_{i \in X}
-    ///   || x_i - n(x_i, Y) || +
-    ///   \frac{1}{|Y|}\sum_{i \in Y} || y_i - n(y_i, X) || \\
+    ///   || x_i - n(x_i, Y) || + \frac{1}{|Y|}\sum_{i \in Y} || y_i - n(y_i, X)
+    ///   || \\{}
     ///   \text{Hausdorff distance: } d_H(X,Y) &=& \max \left\{ \max_{i \in X}
     ///   || x_i - n(x_i, Y) ||, \max_{i \in Y} || y_i - n(y_i, X) || \right\}
-    ///   \\
+    ///   \\{}
     ///   \text{Precision: } P(X,Y|d) &=& \frac{100}{|X|} \sum_{i \in X} || x_i
-    ///   - n(x_i, Y) || < d \\
+    ///   - n(x_i, Y) || < d \\{}
     ///   \text{Recall: } R(X,Y|d) &=& \frac{100}{|Y|} \sum_{i \in Y} || y_i -
-    ///  n(y_i, X) || < d \\
+    ///  n(y_i, X) || < d \\{}
     ///   \text{F-Score: } F(X,Y|d) &=& \frac{2 P(X,Y|d) R(X,Y|d)}{P(X,Y|d) +
-    ///  R(X,Y|d)} \\
+    ///  R(X,Y|d)}
     /// \f}
 
     /// As a side effect, the triangle areas are saved in the "areas" attribute.

diff --git a/cpp/open3d/t/geometry/kernel/Metrics.cpp b/cpp/open3d/t/geometry/kernel/Metrics.cpp
@@ -30,14 +30,14 @@ core::Tensor ComputeMetricsCommon(core::Tensor distance12,
     for (Metric metric : metrics) {
         switch (metric) {
             case Metric::ChamferDistance:
-                metric_val = (distance21.Reshape({-1}).Mean({0}).Item<float>() +
-                              distance12.Reshape({-1}).Mean({0}).Item<float>());
+                metric_val = distance21.Reshape({-1}).Mean({-1}).Item<float>() +
+                             distance12.Reshape({-1}).Mean({-1}).Item<float>();
                 metric_values[idx++] = metric_val;
                 break;
             case Metric::HausdorffDistance:
                 metric_val = std::max(
-                        distance12.Reshape({-1}).Max({0}).Item<float>(),
-                        distance21.Reshape({-1}).Max({0}).Item<float>());
+                        distance12.Reshape({-1}).Max({-1}).Item<float>(),
+                        distance21.Reshape({-1}).Max({-1}).Item<float>());
                 metric_values[idx++] = metric_val;
                 break;
             case Metric::FScore:

diff --git a/cpp/open3d/t/geometry/kernel/Metrics.h b/cpp/open3d/t/geometry/kernel/Metrics.h
@@ -13,10 +13,13 @@ namespace open3d {
 namespace t {
 namespace geometry {
 
+/// Common code for computing geometry metrics from pairwise point distances.
+/// This function expects Euclidean distances as input and returns the requested
+/// metrics between point clouds / meshes.
 core::Tensor ComputeMetricsCommon(core::Tensor distance12,
                                   core::Tensor distance21,
                                   std::vector<Metric> metrics,
                                   MetricParameters params);
-}
+}  // namespace geometry
 }  // namespace t
 }  // namespace open3d
diff --git a/cpp/pybind/t/geometry/pointcloud.cpp b/cpp/pybind/t/geometry/pointcloud.cpp
@@ -787,7 +787,30 @@ the partition id for each point.
     params (t.geometry.MetricParameters): This holds parameters required by different metrics.
 
 Returns:
-    Tensor containing the requested metrics.)");
+    Tensor containing the requested metrics.
+
+Example::
+
+    from open3d.t.geometry import TriangleMesh, PointCloud, Metric, MetricParameters
+    # box is a cube with one vertex at the origin and a side length 1
+    pos = TriangleMesh.create_box().vertex.positions
+    pcd1 = PointCloud(pos.clone())
+    pcd2 = PointCloud(pos * 1.1)
+
+    # (1, 3, 3, 1) vertices are shifted by (0, 0.1, 0.1*sqrt(2), 0.1*sqrt(3))
+    # respectively
+    metric_params = MetricParameters(
+        fscore_radius=o3d.utility.FloatVector((0.01, 0.11, 0.15, 0.18)))
+    metrics = pcd1.compute_metrics(
+        pcd2, (Metric.ChamferDistance, Metric.HausdorffDistance, Metric.FScore),
+        metric_params)
+
+    print(metrics)
+    np.testing.assert_allclose(
+        metrics.cpu().numpy(),
+        (0.22436734, np.sqrt(3) / 10, 100. / 8, 400. / 8, 700. / 8, 100.),
+        rtol=1e-6)
+    )");
 }
 
 }  // namespace geometry

diff --git a/cpp/pybind/t/geometry/trianglemesh.cpp b/cpp/pybind/t/geometry/trianglemesh.cpp
@@ -1113,7 +1113,27 @@ As a side effect, the triangle areas are saved in the "areas" attribute.
     params (t.geometry.MetricParameters): This holds parameters required by different metrics.
 
 Returns:
-    Tensor containing the requested metrics.)");
+    Tensor containing the requested metrics.
+
+Example::
+
+    from open3d.t.geometry import TriangleMesh, Metric, MetricParameters
+    # box is a cube with one vertex at the origin and a side length 1
+    box1 = TriangleMesh.create_box()
+    box2 = TriangleMesh.create_box()
+    box2.vertex.positions *= 1.1
+
+    # 3 faces of the cube are the same, and 3 are shifted up by 0.1
+    metric_params = MetricParameters(fscore_radius=o3d.utility.FloatVector(
+        (0.05, 0.15)), n_sampled_points=100000)
+    metrics = box1.compute_metrics(
+        box2, (Metric.ChamferDistance, Metric.HausdorffDistance, Metric.FScore),
+        metric_params)
+
+    print(metrics)
+    np.testing.assert_allclose(metrics.cpu().numpy(), (0.1, 0.17, 50, 100),
+                               rtol=0.05)
+    )");
 }
 
 }  // namespace geometry

diff --git a/python/test/t/geometry/test_pointcloud.py b/python/test/t/geometry/test_pointcloud.py
@@ -197,18 +197,22 @@ def test_pickle(device):
 
 def test_metrics():
 
-    from open3d.t.geometry import Metric, MetricParameters
-    pos = o3d.t.geometry.TriangleMesh.create_box().vertex.positions
-    pcd1 = o3d.t.geometry.PointCloud(pos.clone())
-    pcd2 = o3d.t.geometry.PointCloud(pos * 1.2)
-
+    from open3d.t.geometry import TriangleMesh, PointCloud, Metric, MetricParameters
+    # box is a cube with one vertex at the origin and a side length 1
+    pos = TriangleMesh.create_box().vertex.positions
+    pcd1 = PointCloud(pos.clone())
+    pcd2 = PointCloud(pos * 1.1)
+
+    # (1, 3, 3, 1) vertices are shifted by (0, 0.1, 0.1*sqrt(2), 0.1*sqrt(3))
+    # respectively
     metric_params = MetricParameters(
-        fscore_radius=o3d.utility.FloatVector((0.05, 0.15)))
+        fscore_radius=o3d.utility.FloatVector((0.01, 0.11, 0.15, 0.18)))
     metrics = pcd1.compute_metrics(
         pcd2, (Metric.ChamferDistance, Metric.HausdorffDistance, Metric.FScore),
         metric_params)
 
     print(metrics)
-    np.testing.assert_allclose(metrics.cpu().numpy(),
-                               (0.06, 0.12, 200. / 3, 100),
-                               rtol=1e-6)
+    np.testing.assert_allclose(
+        metrics.cpu().numpy(),
+        (0.22436734, np.sqrt(3) / 10, 100. / 8, 400. / 8, 700. / 8, 100.),
+        rtol=1e-6)
diff --git a/python/test/t/geometry/test_trianglemesh.py b/python/test/t/geometry/test_trianglemesh.py
@@ -1396,18 +1396,22 @@ def test_remove_non_manifold_edges(device, int_t, float_t):
 
 def test_metrics():
 
-    from open3d.t.geometry import Metric, MetricParameters
-    box1 = o3d.t.geometry.TriangleMesh.create_box()
-    box2 = o3d.t.geometry.TriangleMesh.create_box()
-    box2.vertex.positions *= 1.2
-
+    from open3d.t.geometry import TriangleMesh, Metric, MetricParameters
+    # box is a cube with one vertex at the origin and a side length 1
+    box1 = TriangleMesh.create_box()
+    box2 = TriangleMesh.create_box()
+    box2.vertex.positions *= 1.1
+
+    # 3 faces of the cube are the same, and 3 are shifted up by 0.1 - raycast
+    # distances should follow this.
     metric_params = MetricParameters(fscore_radius=o3d.utility.FloatVector(
         (0.05, 0.15)),
                                      n_sampled_points=100000)
+    # n_sampled_points=100000)
     metrics = box1.compute_metrics(
         box2, (Metric.ChamferDistance, Metric.HausdorffDistance, Metric.FScore),
         metric_params)
 
     print(metrics)
-    np.testing.assert_allclose(metrics.cpu().numpy(), (0.2, 0.34, 45, 53.2),
+    np.testing.assert_allclose(metrics.cpu().numpy(), (0.1, 0.17, 50, 100),
                                rtol=0.05)