Source code for allensdk.core.obj_utilities

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import numpy as np


[docs]def read_obj(path): with open(path, 'r') as obj_file: lines = obj_file.read().split('\n') output = parse_obj(lines) return output
[docs]def parse_obj(lines): '''Parse a wavefront obj file into a triplet of vertices, normals, and faces. This parser is specific to obj files generated from our annotation volumes Parameters ---------- lines : list of str Lines of input obj file Returns ------- vertices : np.ndarray Dimensions are (nSamples, nCoordinates=3). Locations in the reference space of vertices vertex_normals : np.ndarray Dimensions are (nSample, nElements=3). Vectors normal to vertices. face_vertices : np.ndarray Dimensions are (sample, nVertices=3). References are given in indices (0-indexed here, but 1-indexed in the file) of vertices that make up each face. face_normals : np.ndarray Dimensions are (sample, nNormals=3). References are given in indices (0-indexed here, but 1-indexed in the file) of vertex normals that make up each face. Notes ----- This parser is specialized to the obj files that the Allen Institute for Brain Science generates from our own structure annotations. ''' vertices = [] vertex_normals = [] face_vertices = [] face_normals = [] for line in lines: if line[:2] == 'v ': vertices.append( line.split()[1:] ) elif line[:3] == 'vn ': vertex_normals.append( line.split()[1:] ) elif line[:2] == 'f ': line = line.replace('//', ' ').split()[1:] face_vertices.append( line[::2] ) face_normals.append( line[1::2] ) vertices = np.array(vertices).astype(float) vertex_normals = np.array(vertex_normals).astype(float) face_vertices = np.array(face_vertices).astype(int) - 1 face_normals = np.array(face_normals).astype(int) - 1 return vertices, vertex_normals, face_vertices, face_normals