realsense D435获取RGB-D数据集-制作.klg文件

 记录个人工作日志。恳求大佬指点简单的方法！！

1.  <利用ros记录话题，获得bag文件>

首先launch相机节点:

roslaunch realsense2_camera rs_camera.launch

rosbag获得.bag 文件:

(xxx为.bag文件的命名，后面两个是相机的rgb和depth话题)

rosbag record -O xxx /camera/color/image_raw /camera/depth/image_rect_raw

2.  <使用Python代码将bag文件转成图片png输出>

注意是Python2代码。

更改输出路径和.bag文件路径

# -*- coding: UTF-8 -*-  
import numpy
import rosbag
import cv2
import os
from sensor_msgs.msg import Image
from cv_bridge import CvBridge
from cv_bridge import CvBridgeError
rgb_path = '/home/zzj/dataset/bagfiles/rgb_images/'      # absolute path of extracted rgb images
depth_path = '/home/zzj/dataset/bagfiles/depth_images/'  # absolute path of extracted depth images
bridge = CvBridge()
with rosbag.Bag('/home/zzj/dataset/bagfiles/1220.bag', 'r') as bag:
    num = 1
    for topic,msg,t in bag.read_messages():
        if topic =="/camera/depth/image_rect_raw":
        #if topic == "/camera/depth/image_rect_raw": 
            cv_image = bridge.imgmsg_to_cv2(msg, '32FC1')
            cv_image = cv_image * 255  # 不知为何转化的深度图显示不出来。将其乘以 255 才能看到显示效果.
            # timestr = "%.8f" %  msg.header.stamp.to_sec() # 时间戳命名
            # image_name = timestr + '.png'# an extension is necessary
            image_name = str(num) + '.png'# 编号命名
            cv2.imwrite(depth_path + image_name, cv_image)  
            # 实际应用可直接保存为 numpy array
            # np.save(depth_path + image_name, cv_image)  
            print(depth_path + image_name)
        if topic == "/camera/color/image_raw": 
            cv_image = bridge.imgmsg_to_cv2(msg, "bgr8")
            timestr = "%.8f" %  msg.header.stamp.to_sec()
            image_name = str(num) + '.png'
            cv2.imwrite(rgb_path + image_name, cv_image)
        num += 1

3.   <使用Python代码制作数据集获得rgb.txt和depth.txt文件>

4.   <使用associate.py将rgb.txt数据和depth.txt数据融合

        编译png_to_klg将数据集转为klg格式>

     详情可见下方链接

./associate.py depth.txt rgb.txt > associations.txt

将TUM数据集的RGB-D数据集转化为klg格式 - Ponder-Lee - 博客园