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Zero
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# Copyright (c) Meta Platforms, Inc. and affiliates.
from collections import namedtuple
from typing import Tuple, Optional, Union
import numpy as np
import torch
from pytorch3d.structures import Meshes
from pytorch3d.renderer.mesh.textures import TexturesVertex
from utils3d.numpy import (
depth_edge,
normals_edge,
points_to_normals,
image_uv,
image_mesh,
)
np.acos = np.arccos # sam3d_objects-3dfy version of numpy doesn't have acos
MeshAndTexture = namedtuple(
"mesh_and_texture", ["faces", "vertices", "vertex_colors", "vertex_uvs"]
)
def mesh_from_pointmap(
pointmap: np.ndarray,
image: np.ndarray,
mask: Optional[np.ndarray] = None,
depth: Optional[np.ndarray] = None,
filter_edges: bool = True,
depth_edge_rtol: float = 0.03,
depth_edge_tol: float = 5,
) -> MeshAndTexture:
"""
Create a mesh from pointmap and image.
Returns:
faces, vertices, vertex_colors, vertex_uvs: Mesh components
"""
assert pointmap.ndim == 3, pointmap.shape
assert pointmap.shape[-1] == 3, pointmap.shape
assert image.ndim == 3, image.shape
assert image.shape[-1] == 3, image.shape
if mask is None:
mask = np.ones_like(pointmap[..., 2], dtype=np.float32) > 0
if depth is None:
depth = pointmap[..., 2]
height, width = image.shape[:2]
normals, normals_mask = points_to_normals(pointmap, mask=mask)
if filter_edges:
mask = mask & ~(
depth_edge(depth, rtol=depth_edge_rtol, mask=mask)
& normals_edge(normals, tol=depth_edge_tol, mask=normals_mask)
)
faces, vertices, vertex_colors, vertex_uvs = image_mesh(
pointmap,
image.astype(np.float32),
image_uv(width=width, height=height),
mask=mask,
tri=True,
)
vertices, vertex_uvs = vertices * [1, 1, 1], vertex_uvs * [1, -1] + [0, 1]
return MeshAndTexture(faces, vertices, vertex_colors, vertex_uvs)
def create_textured_mesh(
verts: torch.Tensor,
faces: torch.Tensor,
vert_colors: torch.Tensor,
) -> Meshes:
tex = TexturesVertex(verts_features=[vert_colors])
mesh = Meshes(verts=[verts], faces=[faces], textures=tex)
return mesh
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