对相机位姿 导出 Tum 格式的位姿

2023-12-21 06:11:52

需求：针对 [N,4,4] 格式的 poses np.darray 导出其 Tum 格式 的位姿。
时间戳根据 N 的值，线性得到。

import numpy as np
import os
import torch
from scipy.spatial.transform import Rotation

def rotation_matrix_to_tum_format(rotation_matrix):
    rotation = Rotation.from_matrix(rotation_matrix)
    quaternion = rotation.as_quat()
    return quaternion

def convert_to_tum_format(poses, timestamps):
    tum_poses = []
    for i in range(poses.shape[0]):
        pose = poses[i]
        quaternion = rotation_matrix_to_tum_format(pose[:3, :3])
        tum_timestamp = timestamps[i] * 0.1  # Scaling factor of 0.1 to convert timestamps to seconds
        tum_pose = f"{tum_timestamp:.6f} {' '.join(map(str, pose[:3, 3]))} {' '.join(map(str, quaternion))}" 
        tum_poses.append(tum_pose)
    return tum_poses
def write_tum_poses_to_file(file_path, tum_poses):
    with open(file_path, 'w') as f:
        for pose in tum_poses:
            f.write(pose + '\n')
def convert_and_write_tum_poses(c2w_variable, output_filename, timestamps):
    # 调用适当的函数将变量转换为 TUM 格式
    tum_poses = convert_to_tum_format(c2w_variable, timestamps)
    
    # 将 TUM 格式的位姿写入文件
    write_tum_poses_to_file(output_filename, tum_poses)
n_poses = c2w_GT_traj.shape[0]
custom_timestamps = np.arange(n_poses)
convert_and_write_tum_poses(c2w_GT_traj, 'tum_c2w_GT_traj.txt', custom_timestamps)

文章来源:https://blog.csdn.net/OrdinaryMatthew/article/details/135107566
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