PlaceRecognitionDB

PlaceRecognitionDB is a tool for creating optimally sized databases (containing the minimum number of frames covering the scene) for place recognition task from RGBD and LiDAR data.

The tool supports several basic methods for creating databases, as well as the DominatingSet method for creating optimal databases. A detailed description of all methods for creating databases can be found in our paper.

The tool also contains a global localization pipeline with CosPlace and NetVLAD. The models of these neural networks can be fine-tuned for a particular previously created database. The results of global localization can also be improved with SuperGlue. More details about the available configurations for global localization and the results are available in the paper.

We have also developed a set of metrics that can be used to evaluate the quality of created databases and the accuracy of VPR systems.

For more, please visit the PlaceRecognitionDB documentation. You can also find full information about our research on the website.

Datasets format

You can find detailed information about the data format used in the tool here.

Usage

Please check example.ipynb with a small example on creating a database.

License

This project is licensed under the Apache License — see the LICENSE file for details.

 1#  Copyright (c) 2023, Ivan Moskalenko, Anastasiia Kornilova
 2#
 3#  Licensed under the Apache License, Version 2.0 (the "License");
 4#  you may not use this file except in compliance with the License.
 5#  You may obtain a copy of the License at
 6#
 7#      http://www.apache.org/licenses/LICENSE-2.0
 8#
 9#  Unless required by applicable law or agreed to in writing, software
10#  distributed under the License is distributed on an "AS IS" BASIS,
11#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12#  See the License for the specific language governing permissions and
13#  limitations under the License.
14"""
15.. include:: ../README.md
16"""