Rosbag 制作 TUM数据集
Rosbag 制作 TUM数据集
一、创建rgb和depth文件夹和txt文件
mkdir rgb
mkdir depth
touch rgb.txt
touch depth.txt二、替换 bag 路径 和 topic
tum.py：
import os
import cv2
import numpy as np
import rosbag
from sensor_msgs.msg import Image
from cv_bridge import CvBridge# 定义文件路径
script_dir = os.getcwd()
rgb_path = os.path.join(script_dir, 'rgb')
depth_path = os.path.join(script_dir, 'depth')# 创建 CvBridge 实例
bridge = CvBridge()# 定义常量
DEPTH_ENCODING = '32FC1'
DEPTH_NORMALIZE_MIN = 0.0
DEPTH_NORMALIZE_MAX = 1.0
DEPTH_SCALE = 65535num = 1
rgb_width = None
rgb_height = None# 确保文件夹存在
if not os.path.exists(rgb_path):os.makedirs(rgb_path)
if not os.path.exists(depth_path):os.makedirs(depth_path)with rosbag.Bag(os.path.join(script_dir, 'image.bag'), 'r') as bag: #bag路径with open(os.path.join(script_dir, 'depth.txt'), 'w') as depth_time_file, open(os.path.join(script_dir, 'rgb.txt'), 'w') as rgb_time_file:for topic, msg, t in bag.read_messages():if topic == "/camera/depth/image_raw": #depth topiccv_image = bridge.imgmsg_to_cv2(msg, desired_encoding=DEPTH_ENCODING)# 将深度图像范围归一化到0-1之间cv_image_normalized = cv2.normalize(cv_image, None, DEPTH_NORMALIZE_MIN, DEPTH_NORMALIZE_MAX, cv2.NORM_MINMAX)# 获取深度图像尺寸depth_height, depth_width = cv_image_normalized.shapeif rgb_width is not None and rgb_height is not None:# 调整深度图像尺寸为与彩色图像相同cv_image_normalized = cv2.resize(cv_image_normalized, (rgb_width, rgb_height), interpolation=cv2.INTER_LINEAR)# 将深度图像范围扩展到0-65535并转换为16位无符号整数（CV_16U）cv_image_mono16 = (cv_image_normalized * DEPTH_SCALE).astype(np.uint16)# 保存深度图像image_name = str(num) + '.png'cv2.imwrite(os.path.join(depth_path, image_name), cv_image_mono16)# 写入深度图像的时间戳timestr = "%.8f" % msg.header.stamp.to_sec()depth_time_file.write(timestr + " depth/" + image_name + "\n")if topic == "/camera/rgb/image_raw": #rgb topiccv_image = bridge.imgmsg_to_cv2(msg, "bgr8")rgb_height, rgb_width, _ = cv_image.shape# 进行深度图像几何校正和对齐操作，使其与彩色图像对齐# 保存彩色图像image_name = str(num) + '.png'cv2.imwrite(os.path.join(rgb_path, image_name), cv_image)# 写入彩色图像的时间戳timestr = "%.8f" % msg.header.stamp.to_sec()rgb_time_file.write(timestr + " rgb/" + image_name + "\n")num += 1三、开始转换
1.生成图片和txt
python tum.py2.使用官方脚本得到associate.txt文件
python3 associate.py rgb.txt depth.txt > associate.txt