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igl/python/tutorial/705_MarchingCubes.py
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2018-11-28 08:29:23 -05:00

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Python
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#!/usr/bin/env python
#
# This file is part of libigl, a simple c++ geometry processing library.
#
# Copyright (C) 2017 Sebastian Koch <s.koch@tu-berlin.de> and Daniele Panozzo <daniele.panozzo@gmail.com>
#
# This Source Code Form is subject to the terms of the Mozilla Public License
# v. 2.0. If a copy of the MPL was not distributed with this file, You can
# obtain one at http://mozilla.org/MPL/2.0/.
import sys, os
# Add the igl library to the modules search path
sys.path.insert(0, os.getcwd() + "/../")
import pyigl as igl
from shared import TUTORIAL_SHARED_PATH, check_dependencies, print_usage
dependencies = ["copyleft", "glfw"]
check_dependencies(dependencies)
def key_down(viewer, key, modifier):
if key == ord('1'):
viewer.data().clear()
viewer.data().set_mesh(V, F)
elif key == ord('2'):
viewer.data().clear()
viewer.data().set_mesh(SV, SF)
elif key == ord('3'):
viewer.data().clear()
viewer.data().set_mesh(BV, BF)
return True
if __name__ == "__main__":
keys = {"1": "show original mesh",
"2": "show marching cubes contour of signed distance",
"3": "show marching cubes contour of indicator function"}
print_usage(keys)
V = igl.eigen.MatrixXd()
F = igl.eigen.MatrixXi()
# Read in inputs as double precision floating point meshes
igl.read_triangle_mesh(TUTORIAL_SHARED_PATH + "armadillo.obj", V, F)
# number of vertices on the largest side
s = 50
Vmin = V.colwiseMinCoeff()
Vmax = V.colwiseMaxCoeff()
h = (Vmax - Vmin).maxCoeff() / s
res = (s * ((Vmax - Vmin) / (Vmax - Vmin).maxCoeff())).castint()
def lerp(res, Vmin, Vmax, di, d):
return Vmin[d] + float(di) / (res[d] - 1) * (Vmax[d] - Vmin[d])
# create grid
print("Creating grid...")
GV = igl.eigen.MatrixXd(res[0] * res[1] * res[2], 3)
for zi in range(res[2]):
z = lerp(res, Vmin, Vmax, zi, 2)
for yi in range(res[1]):
y = lerp(res, Vmin, Vmax, yi, 1)
for xi in range(res[0]):
x = lerp(res, Vmin, Vmax, xi, 0)
GV.setRow(xi + res[0] * (yi + res[1] * zi), igl.eigen.MatrixXd([[x, y, z]]))
# compute values
print("Computing distances...")
S = igl.eigen.MatrixXd()
B = igl.eigen.MatrixXd()
I = igl.eigen.MatrixXi()
C = igl.eigen.MatrixXd()
N = igl.eigen.MatrixXd()
igl.signed_distance(GV, V, F, igl.SIGNED_DISTANCE_TYPE_PSEUDONORMAL, S, I, C, N)
# Convert distances to binary inside-outside data --> aliasing artifacts
B = S.copy()
for e in range(B.rows()):
if B[e] > 0:
B[e] = 1
else:
if B[e] < 0:
B[e] = -1
else:
B[e] = 0
print("Marching cubes...")
SV = igl.eigen.MatrixXd()
BV = igl.eigen.MatrixXd()
SF = igl.eigen.MatrixXi()
BF = igl.eigen.MatrixXi()
igl.copyleft.marching_cubes(S, GV, res[0], res[1], res[2], SV, SF)
igl.copyleft.marching_cubes(B, GV, res[0], res[1], res[2], BV, BF)
# Plot the generated mesh
viewer = igl.glfw.Viewer()
viewer.data().set_mesh(SV, SF)
viewer.callback_key_down = key_down
viewer.launch()