ADD reconstruction - this package takes the most memory.

Author: petrasvestartas

CMakeLists.txt

@@ -229,3 +229,4 @@ add_nanobind_module(booleans_ext src/booleans.cpp)
 add_nanobind_module(meshing_ext src/meshing.cpp)
 add_nanobind_module(intersections_ext src/intersections.cpp)
 add_nanobind_module(measure_ext src/measure.cpp)
+add_nanobind_module(reconstruction_ext src/reconstruction.cpp)

docs/examples/example_reconstruction_pointset_normal_estimation.py

@@ -0,0 +1,61 @@
+from pathlib import Path
+
+from compas.geometry import Line
+from compas.geometry import Pointcloud
+from compas_viewer import Viewer
+from compas_viewer.config import Config
+from compas_viewer.scene import Collection
+from line_profiler import profile
+
+from compas_cgal.reconstruction import pointset_normal_estimation
+from compas_cgal.reconstruction import pointset_reduction
+
+
+@profile
+def reconstruction_pointset_normal_estimation():
+    # ==============================================================================
+    # Input geometry
+    # ==============================================================================
+
+    FILE = Path(__file__).parent.parent.parent / "data" / "forked_branch_1.ply"
+
+    cloud = Pointcloud.from_ply(FILE)
+    reduced_cloud = Pointcloud(pointset_reduction(cloud, 10))
+    points, vectors = pointset_normal_estimation(reduced_cloud, 16, True)
+
+    # ==============================================================================
+    # Compute
+    # ==============================================================================
+
+    lines = []
+    line_scale = 10
+
+    for p, v in zip(points, vectors):
+        line = Line(
+            [p[0], p[1], p[2]],
+            [
+                p[0] + v[0] * line_scale,
+                p[1] + v[1] * line_scale,
+                p[2] + v[2] * line_scale,
+            ],
+        )
+        lines.append(line)
+
+    return lines
+
+
+lines = reconstruction_pointset_normal_estimation()
+
+# ==============================================================================
+# Visualize
+# ==============================================================================
+
+config = Config()
+config.camera.target = [600, 500, 200]
+config.camera.position = [600, -1000, 1500]
+config.camera.scale = 100
+config.renderer.gridsize = (20000, 20, 20000, 20)
+
+viewer = Viewer(config=config)
+viewer.scene.add(Collection(lines))
+viewer.show()

docs/examples/example_reconstruction_pointset_normal_estimation.rst

@@ -0,0 +1,18 @@
+Point Cloud Normal Estimation
+=============================
+
+This example demonstrates how to estimate normals from a point cloud using COMPAS CGAL.
+
+Key Features:
+
+* Loading point clouds from PLY files
+* Point cloud density reduction
+* Normal estimation using k-nearest neighbors
+* Visualization of point normals as scaled lines
+
+.. figure:: /_images/example_reconstruction_pointset_normal_estimation.png
+    :figclass: figure
+    :class: figure-img img-fluid
+
+.. literalinclude:: example_reconstruction_pointset_normal_estimation.py
+   :language: python

docs/examples/example_reconstruction_pointset_outlier_removal.py

@@ -0,0 +1,50 @@
+from pathlib import Path
+
+from compas.geometry import Pointcloud
+from compas_viewer import Viewer
+from compas_viewer.config import Config
+from line_profiler import profile
+
+from compas_cgal.reconstruction import pointset_outlier_removal
+
+
+@profile
+def reconstruction_pointset_outlier_removal():
+    """Remove outliers from a point set."""
+
+    # ==============================================================================
+    # Input geometry
+    # ==============================================================================
+
+    FILE = Path(__file__).parent.parent.parent / "data" / "forked_branch_1.ply"
+    c1 = Pointcloud.from_ply(FILE)
+
+    # ==============================================================================
+    # Compute
+    # ==============================================================================
+
+    points = pointset_outlier_removal(c1, 30, 2.0)
+    c2 = Pointcloud(points)
+    c3 = c1.difference(c2)
+
+    return c2, c3
+
+
+c_outlier_removal_0, c_outlier_removal_1 = reconstruction_pointset_outlier_removal()
+
+# ==============================================================================
+# Visualize
+# ==============================================================================
+
+config = Config()
+config.camera.target = [600, 500, 200]
+config.camera.position = [600, -1000, 1500]
+config.camera.scale = 100
+config.renderer.gridsize = (20000, 20, 20000, 20)
+
+viewer = Viewer(config=config)
+
+viewer.scene.add(c_outlier_removal_0, pointcolor=(0.0, 0.0, 0.0))
+viewer.scene.add(c_outlier_removal_1, pointcolor=(1.0, 0.0, 0.0))
+
+viewer.show()

docs/examples/example_reconstruction_pointset_outlier_removal.rst

@@ -0,0 +1,18 @@
+Point Cloud Outlier Removal
+===========================
+
+This example demonstrates how to remove outliers from a point cloud using COMPAS CGAL.
+
+Key Features:
+
+* Loading point clouds from PLY files
+* Removing outliers based on neighborhood analysis
+* Visualization of inliers and outliers with different colors
+* Point cloud difference computation
+
+.. figure:: /_images/example_reconstruction_pointset_outlier_removal.png
+    :figclass: figure
+    :class: figure-img img-fluid
+
+.. literalinclude:: example_reconstruction_pointset_outlier_removal.py
+   :language: python

docs/examples/example_reconstruction_pointset_reduction.py

@@ -0,0 +1,40 @@
+from pathlib import Path
+
+from compas.geometry import Pointcloud
+from compas.geometry import Translation
+from compas.geometry import transform_points_numpy
+from compas_viewer import Viewer
+from compas_viewer.config import Config
+from line_profiler import profile
+
+from compas_cgal.reconstruction import pointset_reduction
+
+
+@profile
+def reconstruction_pointset_reduction():
+    """Reduce the number of points in a point set."""
+
+    FILE = Path(__file__).parent.parent.parent / "data" / "forked_branch_1.ply"
+    c = Pointcloud.from_ply(FILE)
+
+    points = Pointcloud(pointset_reduction(c, 50))
+    transform_points_numpy(points, Translation.from_vector([-1000, 0, 0]))
+
+    c.transform(Translation.from_vector([-1000, 0, 0]))
+
+    return c, points
+
+
+c_reduction_0, c_reduction_1 = reconstruction_pointset_reduction()
+
+config = Config()
+config.camera.target = [100, 500, 200]
+config.camera.position = [100, -1500, 2000]
+config.camera.scale = 100
+config.renderer.gridsize = (20000, 20, 20000, 20)
+
+viewer = Viewer(config=config)
+viewer.scene.add(c_reduction_0, pointcolor=(0.0, 0.0, 0.0))
+viewer.scene.add(c_reduction_1, pointcolor=(1.0, 0.0, 0.0))
+
+viewer.show()

docs/examples/example_reconstruction_pointset_reduction.rst

@@ -0,0 +1,17 @@
+Point Cloud Reduction
+=====================
+
+This example demonstrates how to reduce the density of a point cloud using COMPAS CGAL.
+
+Key Features:
+
+* Loading point clouds from PLY files
+* Point cloud density reduction with specified percentage
+* Side-by-side visualization of original and reduced point clouds
+
+.. figure:: /_images/example_reconstruction_pointset_reduction.png
+    :figclass: figure
+    :class: figure-img img-fluid
+
+.. literalinclude:: example_reconstruction_pointset_reduction.py
+   :language: python

docs/examples/example_reconstruction_pointset_smoothing.py

@@ -0,0 +1,40 @@
+from pathlib import Path
+
+from compas.geometry import Pointcloud
+from compas.geometry import Translation
+from compas.geometry import transform_points_numpy
+from compas_viewer import Viewer
+from compas_viewer.config import Config
+from line_profiler import profile
+
+from compas_cgal.reconstruction import pointset_smoothing
+
+
+@profile
+def reconstruction_pointset_smoothing():
+    """Smooth a point set."""
+
+    ply_file_path = Path(__file__).parent.parent.parent / "data" / "box.ply"
+    original_points = Pointcloud.from_ply(ply_file_path)
+
+    smoothed_points = pointset_smoothing(original_points, 1000, 3)
+
+    return Pointcloud(original_points), Pointcloud(smoothed_points)
+
+
+c_smoothing_0, c_smoothing_1 = reconstruction_pointset_smoothing()
+
+# ==============================================================================
+# Visualize
+# ==============================================================================
+
+config = Config()
+config.camera.target = [0, 5000, -10000]
+config.camera.position = [0, -10000, 30000]
+config.camera.scale = 1000
+config.renderer.gridsize = (20000, 20, 20000, 20)
+
+viewer = Viewer(config=config)
+viewer.scene.add(c_smoothing_0, pointcolor=(0.0, 0.0, 0.0))
+viewer.scene.add(c_smoothing_1, pointcolor=(1.0, 0.0, 0.0))
+viewer.show()

docs/examples/example_reconstruction_pointset_smoothing.rst

@@ -0,0 +1,17 @@
+Point Cloud Smoothing
+=====================
+
+This example demonstrates how to smooth a point cloud using COMPAS CGAL.
+
+Key Features:
+
+* Loading point clouds from PLY files
+* Point cloud smoothing with specified iterations and neighborhood size
+* Side-by-side visualization of original and smoothed point clouds
+
+.. figure:: /_images/example_reconstruction_pointset_smoothing.png
+    :figclass: figure
+    :class: figure-img img-fluid
+
+.. literalinclude:: example_reconstruction_pointset_smoothing.py
+   :language: python

docs/examples/example_reconstruction_poisson_surface_reconstruction.py

@@ -0,0 +1,48 @@
+import math
+from pathlib import Path
+
+from compas.datastructures import Mesh
+from compas.geometry import Pointcloud
+from compas.geometry import Rotation
+from compas.geometry import Scale
+from compas_viewer import Viewer
+from line_profiler import profile
+
+from compas_cgal.reconstruction import poisson_surface_reconstruction
+
+
+@profile
+def reconstruction_poisson_surface_reconstruction():
+    FILE = Path(__file__).parent.parent.parent / "data" / "oni.xyz"
+
+    points = []
+    normals = []
+    with open(FILE, "r") as f:
+        for line in f:
+            x, y, z, nx, ny, nz = line.strip().split()
+            points.append([float(x), float(y), float(z)])
+            normals.append([float(nx), float(ny), float(nz)])
+
+    V, F = poisson_surface_reconstruction(points, normals)
+    mesh = Mesh.from_vertices_and_faces(V, F)
+
+    c = Pointcloud(V)
+
+    return c, mesh
+
+
+points, mesh = reconstruction_poisson_surface_reconstruction()
+
+# ==============================================================================
+# Visualize
+# ==============================================================================
+
+viewer = Viewer()
+
+viewer.renderer.camera.target = [0, 0, 0]
+viewer.renderer.camera.position = [0, -0.2, 2.0]
+
+viewer.scene.add(points, pointsize=10, pointcolor=(255, 0, 0))
+viewer.scene.add(mesh, show_points=False)
+
+viewer.show()