--- title: Image Matching Webui emoji: 🤗 colorFrom: red colorTo: yellow sdk: gradio sdk_version: 5.4.0 app_file: app.py pinned: true license: apache-2.0 --- [![Contributors][contributors-shield]][contributors-url] [![Forks][forks-shield]][forks-url] [![Stargazers][stars-shield]][stars-url] [![Issues][issues-shield]][issues-url]


Image Matching WebUI
Identify matching points between two images

## Description This simple tool efficiently matches image pairs using multiple famous image matching algorithms. The tool features a Graphical User Interface (GUI) designed using [gradio](https://gradio.app/). You can effortlessly select two images and a matching algorithm and obtain a precise matching result. **Note**: the images source can be either local images or webcam images. Try it on Open In Studio Here is a demo of the tool: ![demo](assets/demo.gif) The tool currently supports various popular image matching algorithms, namely: - [x] [EfficientLoFTR](https://github.com/zju3dv/EfficientLoFTR), CVPR 2024 - [x] [MASt3R](https://github.com/naver/mast3r), CVPR 2024 - [x] [DUSt3R](https://github.com/naver/dust3r), CVPR 2024 - [x] [OmniGlue](https://github.com/Vincentqyw/omniglue-onnx), CVPR 2024 - [x] [XFeat](https://github.com/verlab/accelerated_features), CVPR 2024 - [x] [RoMa](https://github.com/Vincentqyw/RoMa), CVPR 2024 - [x] [DeDoDe](https://github.com/Parskatt/DeDoDe), 3DV 2024 - [ ] [Mickey](https://github.com/nianticlabs/mickey), CVPR 2024 - [x] [GIM](https://github.com/xuelunshen/gim), ICLR 2024 - [ ] [DUSt3R](https://github.com/naver/dust3r), arXiv 2023 - [x] [LightGlue](https://github.com/cvg/LightGlue), ICCV 2023 - [x] [DarkFeat](https://github.com/THU-LYJ-Lab/DarkFeat), AAAI 2023 - [x] [SFD2](https://github.com/feixue94/sfd2), CVPR 2023 - [x] [IMP](https://github.com/feixue94/imp-release), CVPR 2023 - [ ] [ASTR](https://github.com/ASTR2023/ASTR), CVPR 2023 - [ ] [SEM](https://github.com/SEM2023/SEM), CVPR 2023 - [ ] [DeepLSD](https://github.com/cvg/DeepLSD), CVPR 2023 - [x] [GlueStick](https://github.com/cvg/GlueStick), ICCV 2023 - [ ] [ConvMatch](https://github.com/SuhZhang/ConvMatch), AAAI 2023 - [x] [LoFTR](https://github.com/zju3dv/LoFTR), CVPR 2021 - [x] [SOLD2](https://github.com/cvg/SOLD2), CVPR 2021 - [ ] [LineTR](https://github.com/yosungho/LineTR), RA-L 2021 - [x] [DKM](https://github.com/Parskatt/DKM), CVPR 2023 - [ ] [NCMNet](https://github.com/xinliu29/NCMNet), CVPR 2023 - [x] [TopicFM](https://github.com/Vincentqyw/TopicFM), AAAI 2023 - [x] [AspanFormer](https://github.com/Vincentqyw/ml-aspanformer), ECCV 2022 - [x] [LANet](https://github.com/wangch-g/lanet), ACCV 2022 - [ ] [LISRD](https://github.com/rpautrat/LISRD), ECCV 2022 - [ ] [REKD](https://github.com/bluedream1121/REKD), CVPR 2022 - [x] [CoTR](https://github.com/ubc-vision/COTR), ICCV 2021 - [x] [ALIKE](https://github.com/Shiaoming/ALIKE), TMM 2022 - [x] [RoRD](https://github.com/UditSinghParihar/RoRD), IROS 2021 - [x] [SGMNet](https://github.com/vdvchen/SGMNet), ICCV 2021 - [x] [SuperPoint](https://github.com/magicleap/SuperPointPretrainedNetwork), CVPRW 2018 - [x] [SuperGlue](https://github.com/magicleap/SuperGluePretrainedNetwork), CVPR 2020 - [x] [D2Net](https://github.com/Vincentqyw/d2-net), CVPR 2019 - [x] [R2D2](https://github.com/naver/r2d2), NeurIPS 2019 - [x] [DISK](https://github.com/cvlab-epfl/disk), NeurIPS 2020 - [ ] [Key.Net](https://github.com/axelBarroso/Key.Net), ICCV 2019 - [ ] [OANet](https://github.com/zjhthu/OANet), ICCV 2019 - [x] [SOSNet](https://github.com/scape-research/SOSNet), CVPR 2019 - [x] [HardNet](https://github.com/DagnyT/hardnet), NeurIPS 2017 - [x] [SIFT](https://docs.opencv.org/4.x/da/df5/tutorial_py_sift_intro.html), IJCV 2004 ## How to use ### HuggingFace / Lightning AI Just try it on Open In Studio or deploy it locally following the instructions below. ### Requirements ``` bash git clone --recursive https://github.com/Vincentqyw/image-matching-webui.git cd image-matching-webui conda env create -f environment.yaml conda activate imw ``` or using [docker](https://hub.docker.com/r/vincentqin/image-matching-webui): ``` bash docker pull vincentqin/image-matching-webui:latest docker run -it -p 7860:7860 vincentqin/image-matching-webui:latest python app.py --server_name "0.0.0.0" --server_port=7860 ``` ### Run demo ``` bash python3 ./app.py ``` then open http://localhost:7860 in your browser. ![](assets/gui.jpg) ### Add your own feature / matcher I provide an example to add local feature in [hloc/extractors/example.py](hloc/extractors/example.py). Then add feature settings in `confs` in file [hloc/extract_features.py](hloc/extract_features.py). Last step is adding some settings to `model_zoo` in file [ui/config.yaml](ui/config.yaml). ## Contributions welcome! External contributions are very much welcome. Please follow the [PEP8 style guidelines](https://www.python.org/dev/peps/pep-0008/) using a linter like flake8 (reformat using command `python -m black .`). This is a non-exhaustive list of features that might be valuable additions: - [x] add webcam support - [x] add [line feature matching](https://github.com/Vincentqyw/LineSegmentsDetection) algorithms - [x] example to add a new feature extractor / matcher - [x] ransac to filter outliers - [ ] add [rotation images](https://github.com/pidahbus/deep-image-orientation-angle-detection) options before matching - [ ] support export matches to colmap ([#issue 6](https://github.com/Vincentqyw/image-matching-webui/issues/6)) - [ ] add config file to set default parameters - [ ] dynamically load models and reduce GPU overload Adding local features / matchers as submodules is very easy. For example, to add the [GlueStick](https://github.com/cvg/GlueStick): ``` bash git submodule add https://github.com/cvg/GlueStick.git third_party/GlueStick ``` If remote submodule repositories are updated, don't forget to pull submodules with `git submodule update --remote`, if you only want to update one submodule, use `git submodule update --remote third_party/GlueStick`. ## Resources - [Image Matching: Local Features & Beyond](https://image-matching-workshop.github.io) - [Long-term Visual Localization](https://www.visuallocalization.net) ## Acknowledgement This code is built based on [Hierarchical-Localization](https://github.com/cvg/Hierarchical-Localization). We express our gratitude to the authors for their valuable source code. 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