SLAM

详细描述

KITTI视觉基准

实现数据集加载

"KITTI视觉基准": http://www.cvlibs.net/datasets/kitti/eval_odometry.php

用法

1. 从以上链接下载"里程计"数据集文件：data_odometry_gray\data_odometry_color\data_odometry_velodyne\data_odometry_poses\data_odometry_calib.zip.
2. 解压data_odometry_poses.zip，它会创建一个文件夹dataset/poses/。然后解压data_odometry_gray.zip, data_odometry_color.zip, data_odometry_velodyne.zip。文件夹dataset/sequences/将被创建，其中包含文件夹00/..21/。这些文件夹中的每一个都将包含：image_0/, image_1/, image_2/, image_3/, velodyne/和文件calib.txt & times.txt。最后解压data_odometry_calib.zip时，这两个文件将被替换。
3. 要加载数据，请运行

   ./opencv/build/bin/example_datasets_slam_kitti -p=/home/user/path_to_unpacked_folder/dataset/

TUM室内数据集

实现数据集加载

"TUMindoor数据集": http://www.navvis.lmt.ei.tum.de/dataset/

用法

1. 从以上链接下载数据集文件：dslr\info\ladybug\pointcloud.tar.bz2，每个数据集分别为：11-11-28 (1st floor)\11-12-13 (1st floor N1)\11-12-17a (4th floor)\11-12-17b (3rd floor)\11-12-17c (Ground I)\11-12-18a (Ground II)\11-12-18b (2nd floor)
2. 将它们解压到每个数据集的单独文件夹中。dslr.tar.bz2 -> dslr/, info.tar.bz2 -> info/, ladybug.tar.bz2 -> ladybug/, pointcloud.tar.bz2 -> pointcloud/.
3. 要加载每个数据集，请运行

   ./opencv/build/bin/example_datasets_slam_tumindoor -p=/home/user/path_to_unpacked_folders/

类
结构体	cv::datasets::pose
类	cv::datasets::SLAM_kitti
结构体	cv::datasets::SLAM_kittiObj
类	cv::datasets::SLAM_tumindoor
结构体	cv::datasets::SLAM_tumindoorObj

枚举
枚举	cv::datasets::imageType {   cv::datasets::LEFT = 0 ,   cv::datasets::RIGHT ,   cv::datasets::LADYBUG }

枚举类型文档

imageType

枚举 cv::datasets::imageType

#include <opencv2/datasets/slam_tumindoor.hpp>

枚举值
LEFT  Python: cv.datasets.LEFT
RIGHT  Python: cv.datasets.RIGHT
LADYBUG  Python: cv.datasets.LADYBUG