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| import torch | |
| from scipy.spatial.transform import Rotation as R | |
| from utils.commons.tensor_utils import convert_to_tensor | |
| def rot2euler(rot, use_radian=True): | |
| r = R.from_matrix(rot) | |
| return r.as_euler('xyz', degrees=not use_radian) | |
| def euler2rot(euler, use_radian=True): | |
| r = R.from_euler('xyz',euler, degrees=not use_radian) | |
| return r.as_matrix() | |
| def c2w_to_euler_trans(c2w): | |
| if c2w.ndim == 3: | |
| e = rot2euler(c2w[:, :3, :3]) # [B, 3] | |
| t = c2w[:, :3, 3].reshape([-1, 3]) | |
| else: | |
| e = rot2euler(c2w[:3, :3]) # [B, 3] | |
| t = c2w[:3, 3].reshape([3]) | |
| return e, t # [3+3] | |
| def euler_trans_2_c2w(euler, trans): | |
| if euler.ndim == 2: | |
| rot = euler2rot(euler) # [b, 3, 3] | |
| bs = trans.shape[0] | |
| trans = trans.reshape([bs, 3, 1]) | |
| rot = convert_to_tensor(rot).float() | |
| trans = convert_to_tensor(trans).float() | |
| c2w = torch.cat([rot, trans], dim=-1) # [b, 3, 4] | |
| else: | |
| rot = euler2rot(euler) # [3, 3] | |
| trans = trans.reshape([3, 1]) | |
| rot = convert_to_tensor(rot).float() | |
| trans = convert_to_tensor(trans).float() | |
| c2w = torch.cat([rot, trans], dim=-1) # [3, 4] | |
| return c2w |