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OpenCV
3.4.20
Open Source Computer Vision
|
Classes | |
struct | cv::datasets::pose |
class | cv::datasets::SLAM_kitti |
struct | cv::datasets::SLAM_kittiObj |
class | cv::datasets::SLAM_tumindoor |
struct | cv::datasets::SLAM_tumindoorObj |
Enumerations | |
enum | cv::datasets::imageType { cv::datasets::LEFT = 0, cv::datasets::RIGHT, cv::datasets::LADYBUG } |
Implements loading dataset:
"KITTI Vision Benchmark": http://www.cvlibs.net/datasets/kitti/eval_odometry.php
Usage:
data_odometry_gray\data_odometry_color\data_odometry_velodyne\data_odometry_poses\data_odometry_calib.zip
.data_odometry_poses.zip
, it creates folder dataset/poses/
. After that unpack data_odometry_gray.zip
, data_odometry_color.zip
, data_odometry_velodyne.zip
. Folder dataset/sequences/
will be created with folders 00/..21/
. Each of these folders will contain: image_0/
, image_1/
, image_2/
, image_3/
, velodyne/
and files calib.txt
& times.txt
. These two last files will be replaced after unpacking data_odometry_calib.zip
at the end.Implements loading dataset:
"TUMindoor Dataset": http://www.navvis.lmt.ei.tum.de/dataset/
Usage:
dslr\info\ladybug\pointcloud.tar.bz2
for each dataset: 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)
dslr.tar.bz2 -> dslr/
, info.tar.bz2 -> info/
, ladybug.tar.bz2 -> ladybug/
, pointcloud.tar.bz2 -> pointcloud/
.#include <opencv2/datasets/slam_tumindoor.hpp>
Enumerator | |
---|---|
LEFT Python: cv.datasets.LEFT | |
RIGHT Python: cv.datasets.RIGHT | |
LADYBUG Python: cv.datasets.LADYBUG |