WebMar 1, 2024 · We can find the non-manifold edges with .extract_feature_edges (), from which we can identify cells which contain the non-manifold edges. But... then I can't think of a robust way that lets us choose which one of the 3 cells that meet at a non-manifold edge should be removed (and the process iterated until no more non-manifold edges are left).
How to extract edges from polydata as connected features?
WebMoreover, the insufficient use of multi-scale building features causes blurry edges in the predictions for buildings with complex shapes. To address these challenges, we propose a novel coarse-to-fine boundary refinement network (CBR-Net) that accurately extracts building footprints from remote sensing imagery. WebI would like to extract the subset of indices that describe the visible feature edges, i.e. a subset of the array edges = mesh.extract_feature_edges(). For example, in the images below, I want the to get the coordinates of indices of the red lines. Thanks! BetaWas this translation helpful? Give feedback. 1You must be logged in to vote Answered by magical tg transformations
Extract Edges — PyVista 0.39.dev0 documentation - The PyVista …
WebNov 15, 2024 · on Nov 15, 2024 Using following code, I tried to export feature edges as an .stl file: features = mesh.extract_feature_edges (30) features.save ("file_path.ply") Unfortunately this results in an empty .stl file: Visualization Toolkit generated SLA File NUL NUL ... Ploting the features works perfectly: p = pv.Plotter () p.add_mesh (mesh, color=True) WebJul 29, 2024 · I render a PolyData and by calling lines = mesh.extract_feature_edges () I obtain its feature lines. Of this set of lines I want to keep only the subset describing the silhouette of the original mesh. Is that possible? python vtk pyvista Share Improve this question Follow asked Jul 29, 2024 at 16:14 dba 325 1 6 16 WebThe use of fully supervised deep learning methods to extract buildings from remote sensing images has shown excellent performance, which requires large amounts of training data with laborious per-pixel labeling. Compared with pixelated intensive labeling, it is much easier to label data using scribbles, which only takes few seconds for one image. In this … kivmachinerie.com