CedarandClaude Opus 4.6
0e35c7a575
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
55 lines
1.7 KiB
Python
55 lines
1.7 KiB
Python
# utils/rotation_utils.py
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import torch
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import math
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def euler_to_rotation_matrix(pitch_deg, yaw_deg, roll_deg):
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"""Pure-torch euler (YXZ order) to 3x3 rotation matrix.
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Args:
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pitch_deg: Rotation around X axis in degrees.
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yaw_deg: Rotation around Y axis in degrees.
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roll_deg: Rotation around Z axis in degrees.
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Returns: (3, 3) rotation matrix.
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"""
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p = torch.tensor(math.radians(pitch_deg))
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y = torch.tensor(math.radians(yaw_deg))
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r = torch.tensor(math.radians(roll_deg))
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cp, sp = torch.cos(p), torch.sin(p)
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cy, sy = torch.cos(y), torch.sin(y)
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cr, sr = torch.cos(r), torch.sin(r)
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Rx = torch.tensor([[1, 0, 0], [0, cp, -sp], [0, sp, cp]], dtype=torch.float32)
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Ry = torch.tensor([[cy, 0, sy], [0, 1, 0], [-sy, 0, cy]], dtype=torch.float32)
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Rz = torch.tensor([[cr, -sr, 0], [sr, cr, 0], [0, 0, 1]], dtype=torch.float32)
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return Ry @ Rx @ Rz
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def compute_vertex_normals(vertices, triangles):
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"""Compute area-weighted per-vertex normals.
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Args:
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vertices: (B, V, 3) vertex positions.
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triangles: (T, 3) int32 triangle indices.
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Returns: (B, V, 3) unit normals per vertex.
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"""
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B, V, _ = vertices.shape
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T = triangles.shape[0]
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v0 = vertices[:, triangles[:, 0]] # (B, T, 3)
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v1 = vertices[:, triangles[:, 1]]
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v2 = vertices[:, triangles[:, 2]]
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face_normals = torch.cross(v1 - v0, v2 - v0, dim=-1) # (B, T, 3)
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vertex_normals = torch.zeros_like(vertices) # (B, V, 3)
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for i in range(3):
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idx = triangles[:, i].long().unsqueeze(0).unsqueeze(-1).expand(B, T, 3)
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vertex_normals.scatter_add_(1, idx, face_normals)
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return torch.nn.functional.normalize(vertex_normals, dim=-1)
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