pytorch3d_stub/pytorch3d/renderer/__init__.py

"""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