Pointset Normal Estimation

from pathlib import Path
from compas.geometry import Pointcloud, Point, Line
from compas_view2.app import App
from compas_view2.collections import Collection
from compas.colors import Color
from compas_cgal.reconstruction import pointset_normal_estimation

# Define the file path for the point cloud data
FILE = Path(__file__).parent.parent.parent / "data" / "forked_branch_1.ply"

# Load the point cloud data from the PLY file
cloud = Pointcloud.from_ply(FILE)

# Estimate normals for the point cloud
points, vectors = pointset_normal_estimation(cloud, 16, True)
print(f"Original points: {len(cloud)}, Points with normals: {len(points)}, Vectors: {len(vectors)}")

# Create lines and properties for visualizing normals
lines = []
line_properties = []
line_scale = 25

# Iterate over points and vectors to create lines and color properties
for p, v in zip(points, vectors):
    lines.append(Line(Point(p[0], p[1], p[2]), Point(p[0] + v[0] * line_scale, p[1] + v[1] * line_scale, p[2] + v[2] * line_scale)))
    
    # Normalize vector components to be in the range [0, 1] for color representation
    r = (v[0] + 1) * 0.5
    g = (v[1] + 1) * 0.5
    b = (v[2] + 1) * 0.5
    
    # Store line color properties
    line_properties.append({'linecolor': Color(r, g, b)})

# Initialize the COMPAS viewer
viewer = App(width=1600, height=900)

# Adjust viewer settings
viewer.view.camera.scale = 1000
viewer.view.grid.cell_size = 1000

# Create a line collection and add it to the viewer
line_collection = Collection(lines, line_properties)
viewer.add(Pointcloud(points))
viewer.add(line_collection)

# Set the camera to zoom to fit all points and lines
viewer.view.camera.zoom_extents()

# Run the viewer
viewer.run()