301 lines
9.5 KiB
Python
301 lines
9.5 KiB
Python
import numpy as np
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from ..constants import log_time
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from .. import remesh
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from .. import grouping
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from .. import util
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from .. import transformations as tr
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from . import base
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from . import encoding as enc
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@log_time
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def voxelize_subdivide(mesh,
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pitch,
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max_iter=10,
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edge_factor=2.0):
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"""
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Voxelize a surface by subdividing a mesh until every edge is
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shorter than: (pitch / edge_factor)
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Parameters
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-----------
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mesh: Trimesh object
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pitch: float, side length of a single voxel cube
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max_iter: int, cap maximum subdivisions or None for no limit.
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edge_factor: float,
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Returns
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-----------
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VoxelGrid instance representing the voxelized mesh.
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"""
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max_edge = pitch / edge_factor
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if max_iter is None:
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longest_edge = np.linalg.norm(mesh.vertices[mesh.edges[:, 0]] -
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mesh.vertices[mesh.edges[:, 1]],
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axis=1).max()
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max_iter = max(int(np.ceil(np.log2(longest_edge / max_edge))), 0)
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# get the same mesh sudivided so every edge is shorter
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# than a factor of our pitch
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v, f = remesh.subdivide_to_size(mesh.vertices,
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mesh.faces,
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max_edge=max_edge,
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max_iter=max_iter)
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# convert the vertices to their voxel grid position
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hit = v / pitch
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# Provided edge_factor > 1 and max_iter is large enough, this is
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# sufficient to preserve 6-connectivity at the level of voxels.
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hit = np.round(hit).astype(int)
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# remove duplicates
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unique, inverse = grouping.unique_rows(hit)
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# get the voxel centers in model space
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occupied_index = hit[unique]
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origin_index = occupied_index.min(axis=0)
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origin_position = origin_index * pitch
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return base.VoxelGrid(
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enc.SparseBinaryEncoding(occupied_index - origin_index),
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transform=tr.scale_and_translate(
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scale=pitch, translate=origin_position))
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def local_voxelize(mesh,
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point,
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pitch,
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radius,
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fill=True,
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**kwargs):
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"""
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Voxelize a mesh in the region of a cube around a point. When fill=True,
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uses proximity.contains to fill the resulting voxels so may be meaningless
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for non-watertight meshes. Useful to reduce memory cost for small values of
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pitch as opposed to global voxelization.
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Parameters
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-----------
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mesh : trimesh.Trimesh
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Source geometry
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point : (3, ) float
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Point in space to voxelize around
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pitch : float
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Side length of a single voxel cube
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radius : int
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Number of voxel cubes to return in each direction.
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kwargs : parameters to pass to voxelize_subdivide
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Returns
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-----------
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voxels : VoxelGrid instance with resolution (m, m, m) where m=2*radius+1
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or None if the volume is empty
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"""
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from scipy import ndimage
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# make sure point is correct type/shape
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point = np.asanyarray(point, dtype=np.float64).reshape(3)
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# this is a gotcha- radius sounds a lot like it should be in
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# float model space, not int voxel space so check
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if not isinstance(radius, int):
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raise ValueError('radius needs to be an integer number of cubes!')
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# Bounds of region
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bounds = np.concatenate((point - (radius + 0.5) * pitch,
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point + (radius + 0.5) * pitch))
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# faces that intersect axis aligned bounding box
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faces = list(mesh.triangles_tree.intersection(bounds))
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# didn't hit anything so exit
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if len(faces) == 0:
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return None
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local = mesh.submesh([[f] for f in faces], append=True)
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# Translate mesh so point is at 0,0,0
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local.apply_translation(-point)
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# sparse, origin = voxelize_subdivide(local, pitch, **kwargs)
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vox = voxelize_subdivide(local, pitch, **kwargs)
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origin = vox.transform[:3, 3]
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matrix = vox.encoding.dense
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# Find voxel index for point
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center = np.round(-origin / pitch).astype(np.int64)
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# pad matrix if necessary
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prepad = np.maximum(radius - center, 0)
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postpad = np.maximum(center + radius + 1 - matrix.shape, 0)
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matrix = np.pad(matrix, np.stack((prepad, postpad), axis=-1),
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mode='constant')
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center += prepad
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# Extract voxels within the bounding box
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voxels = matrix[center[0] - radius:center[0] + radius + 1,
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center[1] - radius:center[1] + radius + 1,
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center[2] - radius:center[2] + radius + 1]
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local_origin = point - radius * pitch # origin of local voxels
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# Fill internal regions
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if fill:
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regions, n = ndimage.measurements.label(~voxels)
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distance = ndimage.morphology.distance_transform_cdt(~voxels)
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representatives = [
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np.unravel_index((distance * (regions == i)).argmax(),
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distance.shape) for i in range(1, n + 1)]
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contains = mesh.contains(
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np.asarray(representatives) *
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pitch +
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local_origin)
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where = np.where(contains)[0] + 1
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# use in1d vs isin for older numpy versions
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internal = np.in1d(regions.flatten(), where).reshape(regions.shape)
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voxels = np.logical_or(voxels, internal)
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return base.VoxelGrid(voxels, tr.translation_matrix(local_origin))
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@log_time
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def voxelize_ray(mesh,
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pitch,
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per_cell=[2, 2]):
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"""
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Voxelize a mesh using ray queries.
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Parameters
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-------------
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mesh : Trimesh object
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Mesh to be voxelized
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pitch : float
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Length of voxel cube
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per_cell : (2,) int
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How many ray queries to make per cell
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Returns
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-------------
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VoxelGrid instance representing the voxelized mesh.
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"""
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# how many rays per cell
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per_cell = np.array(per_cell).astype(np.int).reshape(2)
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# edge length of cube voxels
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pitch = float(pitch)
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# create the ray origins in a grid
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bounds = mesh.bounds[:, :2].copy()
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# offset start so we get the requested number per cell
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bounds[0] += pitch / (1.0 + per_cell)
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# offset end so arange doesn't short us
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bounds[1] += pitch
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# on X we are doing multiple rays per voxel step
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step = pitch / per_cell
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# 2D grid
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ray_ori = util.grid_arange(bounds, step=step)
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# a Z position below the mesh
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z = np.ones(len(ray_ori)) * (mesh.bounds[0][2] - pitch)
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ray_ori = np.column_stack((ray_ori, z))
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# all rays are along positive Z
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ray_dir = np.ones_like(ray_ori) * [0, 0, 1]
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# if you have pyembree this should be decently fast
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hits = mesh.ray.intersects_location(ray_ori, ray_dir)[0]
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# just convert hit locations to integer positions
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voxels = np.round(hits / pitch).astype(np.int64)
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# offset voxels by min, so matrix isn't huge
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origin_index = voxels.min(axis=0)
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voxels -= origin_index
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encoding = enc.SparseBinaryEncoding(voxels)
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origin_position = origin_index * pitch
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return base.VoxelGrid(
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encoding,
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tr.scale_and_translate(scale=pitch, translate=origin_position))
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@log_time
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def voxelize_binvox(
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mesh, pitch=None, dimension=None, bounds=None, **binvoxer_kwargs):
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"""
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Voxelize via binvox tool.
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Parameters
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--------------
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mesh : trimesh.Trimesh
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Mesh to voxelize
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pitch : float
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Side length of each voxel. Ignored if dimension is provided
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dimension: int
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Number of voxels along each dimension. If not provided, this is
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calculated based on pitch and bounds/mesh extents
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bounds: (2, 3) float
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min/max values of the returned `VoxelGrid` in each instance. Uses
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`mesh.bounds` if not provided.
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**binvoxer_kwargs:
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Passed to `trimesh.exchange.binvox.Binvoxer`.
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Should not contain `bounding_box` if bounds is not None.
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Returns
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--------------
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`VoxelGrid` instance
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Raises
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--------------
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`ValueError` if `bounds is not None and 'bounding_box' in binvoxer_kwargs`.
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"""
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from trimesh.exchange import binvox
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if dimension is None:
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# pitch must be provided
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if bounds is None:
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extents = mesh.extents
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else:
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mins, maxs = bounds
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extents = maxs - mins
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dimension = int(np.ceil(np.max(extents) / pitch))
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if bounds is not None:
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if 'bounding_box' in binvoxer_kwargs:
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raise ValueError('Cannot provide both bounds and bounding_box')
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binvoxer_kwargs['bounding_box'] = np.asanyarray(bounds).flatten()
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binvoxer = binvox.Binvoxer(dimension=dimension, **binvoxer_kwargs)
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return binvox.voxelize_mesh(mesh, binvoxer)
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voxelizers = util.FunctionRegistry(
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ray=voxelize_ray,
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subdivide=voxelize_subdivide,
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binvox=voxelize_binvox)
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def voxelize(mesh, pitch, method='subdivide', **kwargs):
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"""
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Voxelize the given mesh using the specified implementation.
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See `voxelizers` for available implementations or to add your own, e.g. via
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`voxelizers['custom_key'] = custom_fn`.
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`custom_fn` should have signature `(mesh, pitch, **kwargs) -> VoxelGrid`
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and should not modify encoding.
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Parameters
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--------------
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mesh: Trimesh object (left unchanged).
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pitch: float, side length of each voxel.
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method: implementation method. Must be in `fillers`.
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**kwargs: additional kwargs passed to the specified implementation.
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Returns
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--------------
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A VoxelGrid instance.
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"""
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return voxelizers(method, mesh=mesh, pitch=pitch, **kwargs)
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