Python VTK计算曲面的高斯曲率和平均曲率

mport numpy as np import vtk from vtk.util import numpy_support from vtkmodules.numpy_interface import dataset_adapter as dsa def main(argv): colors = vtk.vtkNamedColors() #产生曲面 torus = vtk.vtkSuperquadricSource() torus.SetCenter(0.0, 0.0, 0.0) torus.SetScale(1.0, 1.0, 1.0) torus.SetPhiResolution(64) torus.SetThetaResolution(64) torus.SetThetaRoundness(1) torus.SetThickness(0.5) torus.SetSize(0.5) torus.SetToroidal(1) # 改变观察视角 toroid_transform = vtk.vtkTransform() toroid_transform.RotateX(55) toroid_transform_filter = vtk.vtkTransformFilter() toroid_transform_filter.SetInputConnection(torus.GetOutputPort()) toroid_transform_filter.SetTransform(toroid_transform) # The quadric is made of strips, so pass it through a triangle filter as # the curvature filter only operates on polys tri = vtk.vtkTriangleFilter() tri.SetInputConnection(toroid_transform_filter.GetOutputPort()) #二次曲面在生成边的方式上存在严重的不连续性，因此让我们将其通过CleanPolyDataFilter并合并 #任何重合或非常接近的点 cleaner = vtk.vtkCleanPolyData() cleaner.SetInputConnection(tri.GetOutputPort()) cleaner.SetTolerance(0.005) cleaner.Update() # 生成覆盖随机放置的山丘的曲面 rh = vtk.vtkParametricRandomHills() rh_fn_src = vtk.vtkParametricFunctionSource() rh_fn_src.SetParametricFunction(rh) rh_fn_src.Update() sources = list() for i in range(0, 4): cc = vtk.vtkCurvatures() if i <2: cc.setinputconnection(cleaner.getoutputport()) else: cc.setinputconnection(rh_fn_src.getoutputport()) if i % 2== 0: cc.setcurvaturetypetogaussian() curvature_name='Gauss_Curvature' cc.setcurvaturetypetomean() 'mean_curvature' cc.update() adjust_edge_curvatures(cc.getoutput(), curvature_name) sources.append(cc.getoutput()) curvatures={ 'gauss_curvature', 1: 'mean_curvature', 2: 3: } # lut=get_diverging_lut() get_diverging_lut1() renderers=list() mappers=list() actors=list() text_mappers=list() text_actors=list() scalar_bars=list() create a common text property. text_property=vtk.vtkTextProperty() text_property.setfontsize(24) text_property.setjustificationtocentered() renderwindow dimensions renderer_size=512 grid_dimensions window_width=renderer_size * window_height=renderer_size for idx, source in enumerate(sources): curvatures[idx].replace('_', '\n') source.getpointdata().setactivescalars(curvatures[idx]) scalar_range=source.GetPointData().GetScalars(curvatures[idx]).GetRange() mappers.append(vtk.vtkpolydatamapper()) mappers[idx].setinputdata(source) mappers[idx].setscalarmodetousepointfielddata() mappers[idx].selectcolorarray(curvatures[idx]) mappers[idx].setscalarrange(scalar_range) mappers[idx].setlookuptable(lut) actors.append(vtk.vtkactor()) actors[idx].setmapper(mappers[idx]) text_mappers.append(vtk.vtktextmapper()) text_mappers[idx].setinput(curvature_name) text_mappers[idx].settextproperty(text_property) text_actors.append(vtk.vtkactor2d()) text_actors[idx].setmapper(text_mappers[idx]) text_actors[idx].setposition(250, 16) scalar bar scalar_bars.append(vtk.vtkscalarbaractor()) scalar_bars[idx].setlookuptable(mappers[idx].getlookuptable()) scalar_bars[idx].settitle(curvature_name) scalar_bars[idx].unconstrainedfontsizeon() scalar_bars[idx].setnumberoflabels(5) scalar_bars[idx].setmaximumwidthinpixels(window_width> (len(sources) - 1): continue renderers[idx].SetViewport(viewport) render_window.AddRenderer(renderers[idx]) renderers[idx].AddActor(actors[idx]) renderers[idx].AddActor(text_actors[idx]) renderers[idx].AddActor(scalar_bars[idx]) renderers[idx].SetBackground(colors.GetColor3d('SlateGray')) interactor = vtk.vtkRenderWindowInteractor() interactor.SetRenderWindow(render_window) style = vtk.vtkInteractorStyleTrackballCamera() interactor.SetInteractorStyle(style) render_window.Render() interactor.Start() def get_diverging_lut(): ctf = vtk.vtkColorTransferFunction() ctf.SetColorSpaceToDiverging() # Cool to warm. ctf.AddRGBPoint(0.0, 0.230, 0.299, 0.754) ctf.AddRGBPoint(0.5, 0.865, 0.865, 0.865) ctf.AddRGBPoint(1.0, 0.706, 0.016, 0.150) table_size = 256 lut = vtk.vtkLookupTable() lut.SetNumberOfTableValues(table_size) lut.Build() for i in range(0, table_size): rgba = list(ctf.GetColor(float(i) / table_size)) rgba.append(1) lut.SetTableValue(i, rgba) return lut def get_diverging_lut1(): colors = vtk.vtkNamedColors() # Colour transfer function. ctf = vtk.vtkColorTransferFunction() ctf.SetColorSpaceToDiverging() p1 = [0.0] + list(colors.GetColor3d('MidnightBlue')) p2 = [0.5] + list(colors.GetColor3d('Gainsboro')) p3 = [1.0] + list(colors.GetColor3d('DarkOrange')) ctf.AddRGBPoint(*p1) ctf.AddRGBPoint(*p2) ctf.AddRGBPoint(*p3) table_size = 256 lut = vtk.vtkLookupTable() lut.SetNumberOfTableValues(table_size) lut.Build() for i in range(0, table_size): rgba = list(ctf.GetColor(float(i) / table_size)) rgba.append(1) lut.SetTableValue(i, rgba) return lut def vtk_version_ok(major, minor, build): requested_version = (100 * int(major) + int(minor)) * 100000000 + int(build) ver = vtk.vtkVersion() actual_version = (100 * ver.GetVTKMajorVersion() + ver.GetVTKMinorVersion()) \ * 100000000 + ver.GetVTKBuildVersion() if actual_version >= requested_version: return True else: return False def adjust_edge_curvatures(source, curvature_name, epsilon=1.0e-08): def point_neighbourhood(pt_id): cell_ids = vtk.vtkIdList() source.GetPointCells(pt_id, cell_ids) neighbour = set() for cell_idx in range(0, cell_ids.GetNumberOfIds()): cell_id = cell_ids.GetId(cell_idx) cell_point_ids = vtk.vtkIdList() source.GetCellPoints(cell_id, cell_point_ids) for cell_pt_idx in range(0, cell_point_ids.GetNumberOfIds()): neighbour.add(cell_point_ids.GetId(cell_pt_idx)) return neighbour def compute_distance(pt_id_a, pt_id_b): #计算距离. pt_a = np.array(source.GetPoint(pt_id_a)) pt_b = np.array(source.GetPoint(pt_id_b)) return np.linalg.norm(pt_a - pt_b) # 获取活动标量 source.GetPointData().SetActiveScalars(curvature_name) np_source = dsa.WrapDataObject(source) curvatures = np_source.PointData[curvature_name] #  获得边缘点的ID array_name = 'ids' id_filter = vtk.vtkIdFilter() id_filter.SetInputData(source) id_filter.SetPointIds(True) id_filter.SetCellIds(False) id_filter.SetPointIdsArrayName(array_name) id_filter.SetCellIdsArrayName(array_name) id_filter.Update() edges = vtk.vtkFeatureEdges() edges.SetInputConnection(id_filter.GetOutputPort()) edges.BoundaryEdgesOn() edges.ManifoldEdgesOff() edges.NonManifoldEdgesOff() edges.FeatureEdgesOff() edges.Update() edge_array = edges.GetOutput().GetPointData().GetArray(array_name) boundary_ids = [] for i in range(edges.GetOutput().GetNumberOfPoints()): boundary_ids.append(edge_array.GetValue(i)) # Remove duplicate Ids. p_ids_set = set(boundary_ids) #迭代边缘点并计算曲率作为相邻点的加权平均值。 count_invalid = 0 for p_id in boundary_ids: p_ids_neighbors = point_neighbourhood(p_id) # Keep only interior points. p_ids_neighbors -= p_ids_set # Compute distances and extract curvature values. curvs = [curvatures[p_id_n] for p_id_n in p_ids_neighbors] dists = [compute_distance(p_id_n, p_id) for p_id_n in p_ids_neighbors] curvs = np.array(curvs) dists = np.array(dists) curvs = curvs[dists > 0] dists = dists[dists > 0] if len(curvs) > 0: weights = 1 / np.array(dists) weights /= weights.sum() new_curv = np.dot(curvs, weights) else: # Corner case. count_invalid += 1 # Assuming the curvature of the point is planar. new_curv = 0.0 # Set the new curvature value. curvatures[p_id] = new_curv #  将小值设置为0 if epsilon != 0.0: curvatures = np.where(abs(curvatures)