Open-CD: A Comprehensive Toolbox for Change Detection

TL;DR

Open-CD is a comprehensive, open-source toolbox that integrates numerous change detection methods, supporting research and development with benchmarking, data analysis, and algorithm descriptions to advance the change detection community.

Contribution

It introduces the most complete change detection toolbox combining various methods, modules, and benchmarking tools in a unified platform for the first time.

Findings

Benchmarking of different change detection methods

Support for a wide range of algorithms and modules

Facilitates reimplementation and development of new change detectors

Abstract

We present Open-CD, a change detection toolbox that contains a rich set of change detection methods as well as related components and modules. The toolbox started from a series of open source general vision task tools, including OpenMMLab Toolkits, PyTorch Image Models, etc. It gradually evolves into a unified platform that covers many popular change detection methods and contemporary modules. It not only includes training and inference codes, but also provides some useful scripts for data analysis. We believe this toolbox is by far the most complete change detection toolbox. In this report, we introduce the various features, supported methods and applications of Open-CD. In addition, we also conduct a benchmarking study on different methods and components. We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new change detectors. Code and models are available at https://github.com/likyoo/open-cd. Pioneeringly, this report also includes brief descriptions of the algorithms supported in Open-CD, mainly contributed by their authors. We sincerely encourage researchers in this field to participate in this project and work together to create a more open community. This toolkit and report will be kept updated.