ScanNet数据集转rosbag的脚本

简介

ScanNet是一个RGB-D视频数据集，但其提供的方式为文件，即深度图像是单独存放在一个文件夹下面的。对于机器人领域的使用者不太方便，因此制作了一个脚本，将其按照时间转化为rosbag存储下来。

脚本功能

读取ScanNet数据集中某一场景的深度图像序列文件夹下所有深度图像和轨迹文件，将深度图像转为三维点云（sensor_msgs/PointCloud2类型消息），轨迹文件转为tf（tf2_msgs/TFMessage类型消息），并保存在指定的rosbag中。其中轨迹文件的消息类型也可自行修改为geometry_msgs/TransformStamped、geometry_msgs/TransformStamped、nav_msgs::Odometry等其他可以表示位姿的消息。

代码使用方法

需要将第58行和第70行的文件目录修改为自己的目录，然后运行即可。
因为需要使用到rospy，建议在ros自带的python2上运行。

代码

代码链接：Scannet2bag
代码文本：

# -*- coding:UTF-8 -*-
import cv2
import time, sys, os
from ros import rosbag
import roslib
import rospy
roslib.load_manifest('sensor_msgs')
from sensor_msgs.msg import Image, PointCloud2, PointField
from std_msgs.msg import Header
import sensor_msgs.point_cloud2 as pcl2
from tf2_msgs.msg import TFMessage
from geometry_msgs.msg import Pose, PoseStamped, TransformStamped, Transform
import numpy as np
from pyquaternion import Quaternion
import tf

# import ImageFile
from PIL import ImageFile
from PIL import Image as ImagePIL


def ReadImages(filename):
    all = []
    files = os.listdir(filename)
    all_num = 0
    for f in sorted(files):
        if os.path.splitext(f)[1] in ['.png']:
            all_num = all_num+1
    for i in range(all_num):
        all.append(filename+str(i)+'.png')
    return all


def ReadPose(filename):
    file = open(filename,'r')
    all = file.readlines()
    posedata = []
    for f in all:
        line = f.rstrip('\n').split(' ')
        line = np.array(line).astype(float).reshape(4,4)
        posedata.append(line)
    return posedata


def depth2xyz(depth_map,fx,fy,cx,cy,flatten=False,depth_scale=1000):
    h,w=np.mgrid[0:depth_map.shape[0],0:depth_map.shape[1]]
    z=depth_map/depth_scale
    x=(w-cx)*z/fx
    y=(h-cy)*z/fy
    xyz=np.dstack((x,y,z)) if flatten==False else np.dstack((x,y,z)).reshape(-1,3)
    #xyz=cv2.rgbd.depthTo3d(depth_map,depth_cam_matrix)
    return xyz


def CreateBag():#img,imu, bagname, timestamps
    '''read time stamps'''
    # 所转化场景的根目录
    root_dir = "/media/dyn/DYN1/Research/dataset/iSDF/seqs/scene0004_00/"
    # 返回所有图片的位置
    imgs = ReadImages(root_dir+"frames/depth/")
    print("The length of images:",len(imgs))
    imagetimestamps=[]
    # 返回一个列表，每个元素为一个4*4数组
    posedata = ReadPose(root_dir+"traj.txt") #the url of  IMU data
    print("The length of poses:",len(posedata))
    # 帧率30
    imagetimestamps = np.linspace(0+1.0/30.0,(len(imgs))/30.0, len(imgs))
    # print(imagetimestamps)
    # 所创建rosbag的目录和名称
    bag = rosbag.Bag("/media/dyn/DYN1/Research/dataset/iSDF/rosbag/scene_0004.bag", 'w')

    try:
        for i in range(len(posedata)):

            '''posestamped消息'''
            # posestamped = PoseStamped()
            # pose = Pose()
            # pose_numpy = posedata[i]
            # # 坐标直接写入
            # pose.position.x = pose_numpy[0,3]
            # pose.position.y = pose_numpy[1,3]
            # pose.position.z = pose_numpy[2,3]
            # # 四元数由旋转矩阵得到
            # rotate_numpy = pose_numpy[0:3,0:3]
            # # print(np.linalg.inv(rotate_numpy))
            # # print(rotate_numpy)
            # # q = Quaternion(matrix=rotate_numpy)
            # q = tf.transformations.quaternion_from_matrix(pose_numpy)
            # pose.orientation.x = q[0]
            # pose.orientation.y = q[1]
            # pose.orientation.z = q[2]
            # pose.orientation.w = q[3]
            # poseStamp = rospy.rostime.Time.from_sec(float(imagetimestamps[i]))
            # # print(poseStamp)
            # posestamped.header.stamp = poseStamp
            # posestamped.pose = pose
            # bag.write("/camera_pose",posestamped,poseStamp)

            '''tf消息'''
            tf_oxts_msg = TFMessage()
            tf_oxts_transform = TransformStamped() 
            oxts_tf = Transform()           
            tf_oxts_transform.header.stamp = rospy.rostime.Time.from_sec(float(imagetimestamps[i]))
            tf_oxts_transform.header.frame_id = '/world'
            tf_oxts_transform.child_frame_id = '/camera'
            pose_numpy = posedata[i]
            # 坐标直接写入
            oxts_tf.translation.x = pose_numpy[0,3]
            oxts_tf.translation.y = pose_numpy[1,3]
            oxts_tf.translation.z = pose_numpy[2,3]
            # 四元数由旋转矩阵得到
            rotate_numpy = pose_numpy[0:3,0:3]
            # print(np.linalg.inv(rotate_numpy))
            # print(rotate_numpy)
            # q = Quaternion(matrix=rotate_numpy)
            q = tf.transformations.quaternion_from_matrix(pose_numpy)
            oxts_tf.rotation.x = q[0]
            oxts_tf.rotation.y = q[1]
            oxts_tf.rotation.z = q[2]
            oxts_tf.rotation.w = q[3]
            tf_oxts_transform.transform = oxts_tf
            tf_oxts_msg.transforms.append(tf_oxts_transform)

            bag.write("/camera_pose",tf_oxts_transform,tf_oxts_transform.header.stamp)

        for i in range(len(imgs)):
            print("Adding %s" % imgs[i])

            raw_depth = cv2.imread(imgs[i], -1)
            [H, W] = raw_depth.shape

            raw_depth_np = raw_depth.astype(np.float32)
            pc = depth2xyz(raw_depth_np, 570.021362, 570.021362, 319.500000, 239.500000, flatten=True)
            # pc = pointcloud_from_depth_torch(depth, 570.021362, 570.021362, 319.500000, 239.500000)

            header = Header()
            header.frame_id = "/camera"
            header.stamp = rospy.Time.from_sec(float(imagetimestamps[i]))
            fields = [PointField('x', 0, PointField.FLOAT32, 1),
                    PointField('y', 4, PointField.FLOAT32, 1),
                    PointField('z', 8, PointField.FLOAT32, 1),]

            pcl_msg = pcl2.create_cloud(header, fields, pc)

            bag.write('/camera_point', pcl_msg, pcl_msg.header.stamp)


    finally:
        bag.close()

if __name__ == "__main__":
    # 分别输入图像的文件夹、轨迹的文件夹、要保存的包位置
    # print(sys.argv)
    CreateBag()
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