{"id":15020350,"url":"https://github.com/meyerls/aruco-estimator","last_synced_at":"2025-09-09T08:48:58.392Z","repository":{"id":37794630,"uuid":"500471306","full_name":"meyerls/aruco-estimator","owner":"meyerls","description":" Automatic Scale Factor Estimation of 3D Reconstruction in COLMAP Utilizing Aruco Marker","archived":false,"fork":false,"pushed_at":"2025-08-30T13:56:21.000Z","size":58550,"stargazers_count":51,"open_issues_count":0,"forks_count":5,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-08-30T14:33:19.765Z","etag":null,"topics":["3d-reconstruction","ambiguity-resolver","aruco","aruco-markers","colmap","computer-vision","ground-control-point","opencv","python","scale-ambiguity"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/meyerls.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2022-06-06T14:40:55.000Z","updated_at":"2025-08-08T14:00:34.000Z","dependencies_parsed_at":"2025-02-10T22:32:50.482Z","dependency_job_id":"6fa460cf-5a88-4f2d-b64e-fe650f99dce1","html_url":"https://github.com/meyerls/aruco-estimator","commit_stats":null,"previous_names":[],"tags_count":17,"template":false,"template_full_name":null,"purl":"pkg:github/meyerls/aruco-estimator","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/meyerls%2Faruco-estimator","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/meyerls%2Faruco-estimator/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/meyerls%2Faruco-estimator/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/meyerls%2Faruco-estimator/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/meyerls","download_url":"https://codeload.github.com/meyerls/aruco-estimator/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/meyerls%2Faruco-estimator/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":274268373,"owners_count":25253390,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-09-09T02:00:10.223Z","response_time":80,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["3d-reconstruction","ambiguity-resolver","aruco","aruco-markers","colmap","computer-vision","ground-control-point","opencv","python","scale-ambiguity"],"created_at":"2024-09-24T19:54:57.068Z","updated_at":"2025-09-09T08:48:58.376Z","avatar_url":"https://github.com/meyerls.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\" width=\"100%\"\u003e\n    \u003cimg width=\"100%\" src=\"assets/wood.png\"\u003e\n\u003c/p\u003e\n\n# Automatic Registration Estimation Based on ArUco Markers\n\n\u003ca href=\"https://pypi.org/project/aruco-estimator/\"\u003e\u003cimg alt=\"PyPI - Python Version\" src=\"https://img.shields.io/pypi/pyversions/aruco-estimator\"\u003e\u003c/a\u003e\n\u003ca href=\"https://pypi.org/project/aruco-estimator/\"\u003e\u003cimg alt=\"PyPI\" src=\"https://img.shields.io/pypi/v/aruco-estimator\"\u003e\u003c/a\u003e\n\u003ca href=\"https://github.com/meyerls/aruco-estimator/actions\"\u003e\u003cimg alt=\"GitHub Workflow Status\" src=\"https://img.shields.io/github/workflow/status/meyerls/aruco-estimator/Python%20package\"\u003e\u003c/a\u003e\n\u003ca href=\"https://github.com/meyerls/aruco-estimator/blob/main/LICENSE\"\u003e\u003cimg alt=\"license\" src=\"https://img.shields.io/github/license/meyerls/aruco-estimator\"\u003e\u003c/a\u003e\n\n## About\n\nThis project automatically computes the correct scale and registration of 3D reconstructions generated with [COLMAP](https://colmap.github.io/) by placing one or more ArUco markers in the scene. This module does not perform the reconstruction task itself so a colmap installation isn't needed.\n\n## Installation\n\nThis repository is tested on Python 3.6+ and can be installed from PyPI:\n\n```bash\npip install aruco-estimator\n```\n\nor\n\n```\npip install git+https://github.com/meyerls/aruco-estimator\n```\n\n## Usage\n\n### Test Data\n\nDownload and extract the test dataset:\n\n```bash\nwget -O door.zip \"https://faubox.rrze.uni-erlangen.de/dl/fiUNWMmsaEAavXHfjqxfyXU9/door.zip\"\nunzip door.zip\n```\n\n### Registration\n\nTest the registration functionality with the example project:\n\n```bash\naruco-estimator register ./door --target-id 7 --dict-type 4 --show --aruco-size 0.15\n\n```\n\n\u003cp align=\"center\" width=\"100%\"\u003e\n    \u003cimg width=\"100%\" src=\"assets/door.png?raw=true\"\u003e\n\u003c/p\u003e\n\n### Merging\n\n### Scripting\n\nTest the registration functionality with the example project:\n\n```bash\naruco-estimator align .data/_park .data/_alley--target-id 7 --dict-type 4 --show --aruco-size 0.15\n\n```\n\n``` python\nfrom aruco_estimator.sfm.colmap import COLMAPProject\nfrom aruco_estimator.utils import get_transformation_between_clouds,get_corners_at_origin\nimport cv2\nproject = COLMAPProject('./door', )\n/sparse/0\ntarget_id = 7\naruco_size = .15\naruco_results = project.detect_markers(dict_type=cv2.aruco.DICT_4X4_50)\n\n# Get 3D corners for normalization\ntarget_corners_3d = aruco_results[target_id]\nprint(target_corners_3d) \n\n# Calculate 4x4 transform with scaling so tag is at the origin \ntransform = get_transformation_between_clouds(target_corners_3d, get_corners_at_origin(side_length=aruco_size))\n\n# Apply normalization to the project\nprint(\"Normalizing poses and 3D points...\")\nproject.transform(transform)\nproject.save(\"./transformed_output/\")\n\n```\n\n\u003cp align=\"center\" width=\"100%\"\u003e\n    \u003cimg width=\"100%\" src=\"assets/output.gif?raw=true\"\u003e\n\u003c/p\u003e\n\n### Dense Clouds\n\nCurrent Script expects {project_dir}/fused.ply for dense cloud alignment and viz\n\n## Known Limitations\n\n- Only SIMPLE_RADIAL and PINHOLE camera models are supported\n- Aruco boards are not uniquely supported\n- Pose estimation is not robust to false detections; ransac would be beneficial\n\n## Roadmap\n\n- [ ] Update README with multi tag examples\n- [ ] Support april tags\n- [ ] Implement the merge by tag tool\n- [ ] Support for additional camera models\n- [ ] Geo-referencing of ArUco markers with Earth coordinate system using GPS or RT\n\n## Troubleshooting\n\n### OpenCV ArUco Module Issues\n\nIf cv2 doesn't detect the ArUco marker module, try reinstalling OpenCV:\n\n```bash\npip uninstall opencv-python opencv-python-headless\npip install opencv-python opencv-contrib-python\n```\n\n## Acknowledgements\n\n- Code for reading binary COLMAP data is partly borrowed from [COLMAP Utility Scripts](https://github.com/uzh-rpg/colmap_utils) by [uzh-rpg](https://github.com/uzh-rpg)\n- Thanks to [Baptiste](https://github.com/Baptiste-AIST) for providing the wooden block reconstruction data from [[1](https://robocip-aist.github.io/sii_nerf_scans/)]\n\n## References\n\n[1] Erich, F., Bourreau, B., *Neural Scanning: Rendering and determining geometry of household objects using Neural Radiance Fields*. [sii_nerf_scans](https://robocip-aist.github.io/sii_nerf_scans/). 2022\n\n## Citation\n\nIf this work helps with your research, please cite:\n\n```bibtex\n@inproceedings{meyer2023cherrypicker,\n  title={CherryPicker: Semantic skeletonization and topological reconstruction of cherry trees},\n  author={Meyer, Lukas and Gilson, Andreas and Scholz, Oliver and Stamminger, Marc},\n  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},\n  pages={6244--6253},\n  year={2023}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmeyerls%2Faruco-estimator","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmeyerls%2Faruco-estimator","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmeyerls%2Faruco-estimator/lists"}