Displaying 1 to 10 from 10 results

evo - Python package for the evaluation of odometry and SLAM

  •    Python

This package provides executables and a small library for handling, evaluating and comparing the trajectory output of odometry and SLAM algorithms. See here for more infos about the formats.

Det3D - A general 3D object detection codebse.

  •    Python

A general 3D Object Detection codebase in PyTorch. Please refer to INSTALATION.md.

AB3DMOT - (IROS 2020, ECCVW 2020) Official Python Implementation for "3D Multi-Object Tracking: A Baseline and New Evaluation Metrics"

  •    Python

3D multi-object tracking (MOT) is an essential component technology for many real-time applications such as autonomous driving or assistive robotics. However, recent works for 3D MOT tend to focus more on developing accurate systems giving less regard to computational cost and system complexity. In contrast, this work proposes a simple yet accurate real-time baseline 3D MOT system. We use an off-the-shelf 3D object detector to obtain oriented 3D bounding boxes from the LiDAR point cloud. Then, a combination of 3D Kalman filter and Hungarian algorithm is used for state estimation and data association. Although our baseline system is a straightforward combination of standard methods, we obtain the state-of-the-art results. To evaluate our baseline system, we propose a new 3D MOT extension to the official KITTI 2D MOT evaluation along with two new metrics. Our proposed baseline method for 3D MOT establishes new state-of-the-art performance on 3D MOT for KITTI, improving the 3D MOTA from 72.23 of prior art to 76.47. Surprisingly, by projecting our 3D tracking results to the 2D image plane and compare against published 2D MOT methods, our system places 2nd on the official KITTI leaderboard. Also, our proposed 3D MOT method runs at a rate of 214.7 FPS, 65 times faster than the state-of-the-art 2D MOT system. 1. Clone the github repository.

kitti2bag - Convert KITTI dataset to ROS bag file the easy way!

  •    Python

This package enjoyed significant interest from more people then I could have thought at the beginning. I'm really glad to see that. I see many PRs and issues being raised but my day job does not allow me to push this repository further. In order to allow this package to prosper, I'm opening it up for the community. I'm more than happy to add you as a collaborator to this repository. Just send me an email. And by the way. To ensure we maintain the quality of the repo you are required to get the PR approval from at least one other collaborator. You can use the Gitter to communicate with others.

SARosPerceptionKitti - ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite

  •    Python

Without assigning any of the abovementioned parameters the demo scenario 0012 is replayed at 20% of its speed with a 3 second delay so RViz has enough time to boot up. If you have any questions, things you would love to add or ideas how to actualize the points in the Area of Improvements, send me an email at simonappel62@gmail.com ! More than interested to collaborate and hear any kind of feedback.

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