File size: 9,853 Bytes
2fe3da0 |
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 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 |
# Copyright (c) 2020-2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# NVIDIA CORPORATION, its affiliates and licensors retain all intellectual
# property and proprietary rights in and to this material, related
# documentation and any modifications thereto. Any use, reproduction,
# disclosure or distribution of this material and related documentation
# without an express license agreement from NVIDIA CORPORATION or
# its affiliates is strictly prohibited.
import os
import numpy as np
import torch
from . import obj
from . import util
######################################################################################
# Base mesh class
######################################################################################
class Mesh:
def __init__(self, v_pos=None, t_pos_idx=None, v_nrm=None, t_nrm_idx=None, v_tex=None, t_tex_idx=None, v_tng=None, t_tng_idx=None, material=None, base=None):
self.v_pos = v_pos
self.v_nrm = v_nrm
self.v_tex = v_tex
self.v_tng = v_tng
self.t_pos_idx = t_pos_idx
self.t_nrm_idx = t_nrm_idx
self.t_tex_idx = t_tex_idx
self.t_tng_idx = t_tng_idx
self.material = material
if base is not None:
self.copy_none(base)
def copy_none(self, other):
if self.v_pos is None:
self.v_pos = other.v_pos
if self.t_pos_idx is None:
self.t_pos_idx = other.t_pos_idx
if self.v_nrm is None:
self.v_nrm = other.v_nrm
if self.t_nrm_idx is None:
self.t_nrm_idx = other.t_nrm_idx
if self.v_tex is None:
self.v_tex = other.v_tex
if self.t_tex_idx is None:
self.t_tex_idx = other.t_tex_idx
if self.v_tng is None:
self.v_tng = other.v_tng
if self.t_tng_idx is None:
self.t_tng_idx = other.t_tng_idx
if self.material is None:
self.material = other.material
def clone(self):
out = Mesh(base=self)
if out.v_pos is not None:
out.v_pos = out.v_pos.clone().detach()
if out.t_pos_idx is not None:
out.t_pos_idx = out.t_pos_idx.clone().detach()
if out.v_nrm is not None:
out.v_nrm = out.v_nrm.clone().detach()
if out.t_nrm_idx is not None:
out.t_nrm_idx = out.t_nrm_idx.clone().detach()
if out.v_tex is not None:
out.v_tex = out.v_tex.clone().detach()
if out.t_tex_idx is not None:
out.t_tex_idx = out.t_tex_idx.clone().detach()
if out.v_tng is not None:
out.v_tng = out.v_tng.clone().detach()
if out.t_tng_idx is not None:
out.t_tng_idx = out.t_tng_idx.clone().detach()
return out
######################################################################################
# Mesh loeading helper
######################################################################################
def load_mesh(filename, mtl_override=None):
name, ext = os.path.splitext(filename)
if ext == ".obj":
return obj.load_obj(filename, clear_ks=True, mtl_override=mtl_override)
assert False, "Invalid mesh file extension"
######################################################################################
# Compute AABB
######################################################################################
def aabb(mesh):
return torch.min(mesh.v_pos, dim=0).values, torch.max(mesh.v_pos, dim=0).values
######################################################################################
# Compute unique edge list from attribute/vertex index list
######################################################################################
def compute_edges(attr_idx, return_inverse=False):
with torch.no_grad():
# Create all edges, packed by triangle
all_edges = torch.cat((
torch.stack((attr_idx[:, 0], attr_idx[:, 1]), dim=-1),
torch.stack((attr_idx[:, 1], attr_idx[:, 2]), dim=-1),
torch.stack((attr_idx[:, 2], attr_idx[:, 0]), dim=-1),
), dim=-1).view(-1, 2)
# Swap edge order so min index is always first
order = (all_edges[:, 0] > all_edges[:, 1]).long().unsqueeze(dim=1)
sorted_edges = torch.cat((
torch.gather(all_edges, 1, order),
torch.gather(all_edges, 1, 1 - order)
), dim=-1)
# Eliminate duplicates and return inverse mapping
return torch.unique(sorted_edges, dim=0, return_inverse=return_inverse)
######################################################################################
# Compute unique edge to face mapping from attribute/vertex index list
######################################################################################
def compute_edge_to_face_mapping(attr_idx, return_inverse=False):
with torch.no_grad():
# Get unique edges
# Create all edges, packed by triangle
all_edges = torch.cat((
torch.stack((attr_idx[:, 0], attr_idx[:, 1]), dim=-1),
torch.stack((attr_idx[:, 1], attr_idx[:, 2]), dim=-1),
torch.stack((attr_idx[:, 2], attr_idx[:, 0]), dim=-1),
), dim=-1).view(-1, 2)
# Swap edge order so min index is always first
order = (all_edges[:, 0] > all_edges[:, 1]).long().unsqueeze(dim=1)
sorted_edges = torch.cat((
torch.gather(all_edges, 1, order),
torch.gather(all_edges, 1, 1 - order)
), dim=-1)
# Elliminate duplicates and return inverse mapping
unique_edges, idx_map = torch.unique(sorted_edges, dim=0, return_inverse=True)
tris = torch.arange(attr_idx.shape[0]).repeat_interleave(3).cuda()
tris_per_edge = torch.zeros((unique_edges.shape[0], 2), dtype=torch.int64).cuda()
# Compute edge to face table
mask0 = order[:,0] == 0
mask1 = order[:,0] == 1
tris_per_edge[idx_map[mask0], 0] = tris[mask0]
tris_per_edge[idx_map[mask1], 1] = tris[mask1]
return tris_per_edge
######################################################################################
# Align base mesh to reference mesh:move & rescale to match bounding boxes.
######################################################################################
def unit_size(mesh):
with torch.no_grad():
vmin, vmax = aabb(mesh)
scale = 2 / torch.max(vmax - vmin).item()
v_pos = mesh.v_pos - (vmax + vmin) / 2 # Center mesh on origin
v_pos = v_pos * scale # Rescale to unit size
return Mesh(v_pos, base=mesh)
######################################################################################
# Center & scale mesh for rendering
######################################################################################
def center_by_reference(base_mesh, ref_aabb, scale):
center = (ref_aabb[0] + ref_aabb[1]) * 0.5
scale = scale / torch.max(ref_aabb[1] - ref_aabb[0]).item()
v_pos = (base_mesh.v_pos - center[None, ...]) * scale
return Mesh(v_pos, base=base_mesh)
######################################################################################
# Simple smooth vertex normal computation
######################################################################################
def auto_normals(imesh):
i0 = imesh.t_pos_idx[:, 0]
i1 = imesh.t_pos_idx[:, 1]
i2 = imesh.t_pos_idx[:, 2]
v0 = imesh.v_pos[i0, :]
v1 = imesh.v_pos[i1, :]
v2 = imesh.v_pos[i2, :]
face_normals = torch.cross(v1 - v0, v2 - v0)
# Splat face normals to vertices
v_nrm = torch.zeros_like(imesh.v_pos)
v_nrm.scatter_add_(0, i0[:, None].repeat(1,3), face_normals)
v_nrm.scatter_add_(0, i1[:, None].repeat(1,3), face_normals)
v_nrm.scatter_add_(0, i2[:, None].repeat(1,3), face_normals)
# Normalize, replace zero (degenerated) normals with some default value
v_nrm = torch.where(util.dot(v_nrm, v_nrm) > 1e-20, v_nrm, torch.tensor([0.0, 0.0, 1.0], dtype=torch.float32, device='cuda'))
v_nrm = util.safe_normalize(v_nrm)
if torch.is_anomaly_enabled():
assert torch.all(torch.isfinite(v_nrm))
return Mesh(v_nrm=v_nrm, t_nrm_idx=imesh.t_pos_idx, base=imesh)
######################################################################################
# Compute tangent space from texture map coordinates
# Follows http://www.mikktspace.com/ conventions
######################################################################################
def compute_tangents(imesh):
vn_idx = [None] * 3
pos = [None] * 3
tex = [None] * 3
for i in range(0,3):
pos[i] = imesh.v_pos[imesh.t_pos_idx[:, i]]
tex[i] = imesh.v_tex[imesh.t_tex_idx[:, i]]
vn_idx[i] = imesh.t_nrm_idx[:, i]
tangents = torch.zeros_like(imesh.v_nrm)
# Compute tangent space for each triangle
uve1 = tex[1] - tex[0]
uve2 = tex[2] - tex[0]
pe1 = pos[1] - pos[0]
pe2 = pos[2] - pos[0]
nom = (pe1 * uve2[..., 1:2] - pe2 * uve1[..., 1:2])
denom = (uve1[..., 0:1] * uve2[..., 1:2] - uve1[..., 1:2] * uve2[..., 0:1])
# Avoid division by zero for degenerated texture coordinates
tang = nom / torch.where(denom > 0.0, torch.clamp(denom, min=1e-6), torch.clamp(denom, max=-1e-6))
# Update all 3 vertices
for i in range(0,3):
idx = vn_idx[i][:, None].repeat(1,3)
tangents.scatter_add_(0, idx, tang) # tangents[n_i] = tangents[n_i] + tang
# Normalize and make sure tangent is perpendicular to normal
tangents = util.safe_normalize(tangents)
tangents = util.safe_normalize(tangents - util.dot(tangents, imesh.v_nrm) * imesh.v_nrm)
if torch.is_anomaly_enabled():
assert torch.all(torch.isfinite(tangents))
return Mesh(v_tng=tangents, t_tng_idx=imesh.t_nrm_idx, base=imesh)
|