# Detect and remove outliers outliers = detect_outliers(mesh.vertices) cleaned_vertices = remove_outliers(mesh.vertices, outliers)
To provide a useful feature, I'll assume you're referring to a software or tool used for registering or aligning 3D meshes, possibly in computer vision, robotics, or 3D scanning applications. Meshcam Registration Code
Implement an automatic outlier detection and removal algorithm to improve the robustness of the mesh registration process. # Detect and remove outliers outliers = detect_outliers(mesh
Here's a feature idea:
def detect_outliers(points, threshold=3): mean = np.mean(points, axis=0) std_dev = np.std(points, axis=0) distances = np.linalg.norm(points - mean, axis=1) outliers = distances > (mean + threshold * std_dev) return outliers outliers) To provide a useful feature
The Meshcam Registration Code! That's a fascinating topic.
Automatic Outlier Detection and Removal