from scipy.spatial.transform import Rotation as R import torch, numpy as np BOF_body = np.array([ [-120.0, -130.0, -80.0, # left shoulder -120.0, 0.0, -80.0, # right shoulder -180.0, -160.0, -180.0, # left elbow -180.0, 0.0, -180.0, # right elbow -120.0, -50.0, -90.0, # left wrist -120.0, -50.0, -90.0, # right wrist ], [90.0, 0.0, 80.0, # left shoulder 90.0, 130.0, 80.0, # right shoulder 180.0, 0.0, 180.0, # left elbow 180.0, 160.0, 180.0, # right elbow 90.0, 50.0, 90.0, # left wrist 90.0, 50.0, 90.0]]) / 180 * np.pi def _to_numpy_flat_last3(x: torch.Tensor): dev, dt = x.device, x.dtype x_np = x.detach().cpu().numpy().reshape(-1, 3) return x_np, x.shape, dev, dt def _from_numpy(x_np: np.ndarray, shape, dev, dt): y = torch.from_numpy(x_np.reshape(*shape)) if dt in (torch.float32, torch.float64): y = y.to(dt) return y.to(dev) def euler_XYZ_to_axis_angle_scipy(e: torch.Tensor, degrees: bool = False) -> torch.Tensor: e_np, shape, dev, dt = _to_numpy_flat_last3(e) aa_np = R.from_euler('XYZ', e_np, degrees=degrees).as_rotvec() return _from_numpy(aa_np, shape, dev, dt) def axis_angle_to_euler_XYZ_scipy(aa: torch.Tensor): aa_np, shape, dev, dt = _to_numpy_flat_last3(aa) e_np = R.from_rotvec(aa_np).as_euler('XYZ', degrees=False) return _from_numpy(e_np, shape, dev, dt) def apply_angular_constraints(body_pose): # body_pose: (B, 63) axis-angle for 21 joints device = body_pose.device B = body_pose.shape[0] body_pose = body_pose.view(B, 21, 3) # your bounds (6×3) in radians, defined for joints [15..20] in intrinsic 'XYZ' minC = torch.tensor(BOF_body[0], dtype=body_pose.dtype, device=device).view(6,3) maxC = torch.tensor(BOF_body[1], dtype=body_pose.dtype, device=device).view(6,3) aa_arms = body_pose[:, 15:, :] e_arms = axis_angle_to_euler_XYZ_scipy(aa_arms) # (B,6,3) intrinsic 'XYZ' e_clamp = torch.clamp(e_arms, minC, maxC) aa_new = euler_XYZ_to_axis_angle_scipy(e_clamp) body_pose[:, 15:, :] = aa_new return body_pose.view(B, -1)