Spaces:
Running on Zero
Running on Zero
File size: 4,638 Bytes
94b4398 | 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 | """pytorch3d.renderer stub with catch-all for missing attributes."""
import torch
import math
import warnings
def __getattr__(name):
"""Catch-all: return a dummy class/function for any missing attribute."""
if name.startswith("__") and name.endswith("__"):
raise AttributeError(name)
warnings.warn(f"pytorch3d.renderer stub: {name} not implemented, returning dummy", stacklevel=2)
class _Dummy:
def __init__(self, *a, **kw): pass
def __call__(self, *a, **kw): return None
def to(self, *a, **kw): return self
def forward(self, *a, **kw): return None
_Dummy.__name__ = _Dummy.__qualname__ = name
return _Dummy
def look_at_view_transform(dist=1.0, elev=0.0, azim=0.0, degrees=True, eye=None,
at=((0, 0, 0),), up=((0, 1, 0),), device="cpu"):
if eye is not None:
if not isinstance(eye, torch.Tensor):
eye = torch.tensor(eye, dtype=torch.float32, device=device)
if eye.dim() == 1:
eye = eye.unsqueeze(0)
else:
elev_r = math.radians(float(elev)) if degrees else float(elev)
azim_r = math.radians(float(azim)) if degrees else float(azim)
x = dist * math.cos(elev_r) * math.sin(azim_r)
y = dist * math.sin(elev_r)
z = dist * math.cos(elev_r) * math.cos(azim_r)
eye = torch.tensor([[x, y, z]], dtype=torch.float32, device=device)
if not isinstance(at, torch.Tensor):
at = torch.tensor(at, dtype=torch.float32, device=device)
if at.dim() == 1: at = at.unsqueeze(0)
if not isinstance(up, torch.Tensor):
up = torch.tensor(up, dtype=torch.float32, device=device)
if up.dim() == 1: up = up.unsqueeze(0)
z_axis = eye - at
z_axis = z_axis / z_axis.norm(dim=-1, keepdim=True).clamp(min=1e-8)
x_axis = torch.cross(up.expand_as(z_axis), z_axis, dim=-1)
x_axis = x_axis / x_axis.norm(dim=-1, keepdim=True).clamp(min=1e-8)
y_axis = torch.cross(z_axis, x_axis, dim=-1)
R = torch.stack([x_axis, y_axis, z_axis], dim=-1)
T = -torch.bmm(R.transpose(1, 2), eye.unsqueeze(-1)).squeeze(-1)
return R, T
def ray_bundle_to_ray_points(ray_bundle):
return None
class CamerasBase:
pass
class PerspectiveCameras(CamerasBase):
def __init__(self, focal_length=None, principal_point=None, R=None, T=None,
image_size=None, device="cpu", in_ndc=True, **kwargs):
self.device = device
self.focal_length = focal_length
self.principal_point = principal_point
self.R = R if R is not None else torch.eye(3, device=device).unsqueeze(0)
self.T = T if T is not None else torch.zeros(1, 3, device=device)
self.image_size = image_size
self.in_ndc = in_ndc
def to(self, device):
self.device = device; return self
class RasterizationSettings:
def __init__(self, image_size=256, blur_radius=0.0, faces_per_pixel=1, **kwargs):
self.image_size = image_size; self.blur_radius = blur_radius; self.faces_per_pixel = faces_per_pixel
class BlendParams:
def __init__(self, sigma=1e-4, gamma=1e-4, background_color=(0.0, 0.0, 0.0)):
self.sigma = sigma; self.gamma = gamma; self.background_color = background_color
class SoftSilhouetteShader:
def __init__(self, blend_params=None):
self.blend_params = blend_params or BlendParams()
class MeshRasterizer(torch.nn.Module):
def __init__(self, cameras=None, raster_settings=None):
super().__init__()
self.cameras = cameras; self.raster_settings = raster_settings
def forward(self, meshes, **kw):
raise NotImplementedError("MeshRasterizer stub")
class MeshRenderer(torch.nn.Module):
def __init__(self, rasterizer=None, shader=None):
super().__init__()
self.rasterizer = rasterizer; self.shader = shader
def forward(self, meshes, **kw):
raise NotImplementedError("MeshRenderer stub")
class TexturesVertex:
def __init__(self, verts_features=None):
self.verts_features_list = verts_features if isinstance(verts_features, list) else [verts_features]
def to(self, device): return self
class TexturesAtlas:
def __init__(self, atlas=None, **kw): self.atlas = atlas
def to(self, device): return self
class TexturesUV:
def __init__(self, **kw): pass
def to(self, device): return self
class HeterogeneousRayBundle:
def __init__(self, *a, **kw): pass
class RayBundle:
def __init__(self, origins=None, directions=None, lengths=None, xys=None, **kw):
self.origins = origins; self.directions = directions; self.lengths = lengths; self.xys = xys
|