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