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681b3db | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | import numpy as np
from scipy.ndimage import distance_transform_edt, gaussian_filter, zoom, median_filter
import matplotlib.pyplot as plt
from skimage.measure import marching_cubes
from scipy.ndimage import binary_fill_holes, label
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
from scipy.spatial import Delaunay
from scipy.interpolate import griddata
# import trimesh
def compute_sdf(voxel_matrix):
inside_dist = distance_transform_edt(voxel_matrix)
outside_dist = distance_transform_edt(1 - voxel_matrix)
sdf = outside_dist - inside_dist
# sdf = gaussian_filter(sdf, sigma=3.0)
sdf = sdf / 32.0
sdf = sdf.clip(-0.2, 0.2)
return sdf
def sdf_to_voxel(sdf, level=0.02):
sdf_smoothed = gaussian_filter(sdf, sigma=0.5)
binary_mask = binary_fill_holes(sdf_smoothed <= level).astype(np.uint8)
# structuring_element = ball(radius=1)
# binary_mask_opened = binary_opening(binary_mask, footprint=structuring_element)
# binary_mask_closed = binary_closing(binary_mask_opened, footprint=structuring_element)
# binary_mask_eroded = binary_erosion(binary_mask_closed, structure=structuring_element)
# binary_mask_dilated = binary_dilation(binary_mask_eroded, structure=structuring_element)
# filled_voxel = gaussian_filter(binary_mask_dilated.astype(np.float32), sigma=1.0)
# filled_voxel = filled_voxel > 0.5
filled_voxel = binary_mask
return filled_voxel
# def sdf_to_voxel(sdf, level=0.02):
# sdf = gaussian_filter(sdf, sigma=3.0)
# sdf = median_filter(sdf, size=5)
# filled_voxel = binary_fill_holes(sdf <= level).astype(np.uint8)
# return filled_voxel |