{"id":18889217,"url":"https://github.com/smartlab-purdue/selros","last_synced_at":"2025-10-06T19:14:08.538Z","repository":{"id":233048674,"uuid":"785855185","full_name":"SMARTlab-Purdue/SeLRoS","owner":"SMARTlab-Purdue","description":"Code repository for Semantic Layering in Room Segmentation via LLMs (SeLRoS). 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This repository includes 2D Map generation code and Room Information Interpreter code, and a data set containing ground truth, object information file, top view image, and room segmentation results for each environment for an experiment in 30 environments.\n\n\n## Setup\nInstall dependencies:\n```\npip install -r requirments.txt\n```\nFor more details, please check the following link [ProcTHOR](https://github.com/allenai/procthor).\n\n\n\n\n\n## Running Script\nRun the following command to interpret segmenation map and generate output. \n\n```\npython3 room_info_interpreter.py --input1 {segmented_map.png} --input2 {related_information.txt}\n```\nNote: You can use the segmented_map.png and related_information.txt in ```data\\vrf\\```.\n\n\nRun the following script to generate top view image and 2d map of environment.\n\n```\npython3 run_get_2d_map.py\n```\n\nRun the following script to get scenes of specific position.\n\n```\npython3 run_get_scenes.py\n```\nNote: If you want to change observation position, change x, z value in 52 line.\n\n\n## Dataset\nThe repository contains ground truth, object information file, top view image, and room segmentation results for each environment. \n\nRefer to ```data\\ground_truth\\``` for the ground truth of each environment.\n\nRefer to ```data\\object_information\\``` for the object information txt file of each room in each environment.\n\nRefer to ```data\\selros\\``` for the final room segmentation results using SeLRoS.\n\nRefer to ```data\\top_view\\``` for the top view image of each environment.\n\nRefer to ```data\\vrf\\``` for the room segmentation results using Voronoi Random Field algorithm and related information (each segmented room's center coordinate and color).\n\n\n\n## Citation\nIf you find this work useful for your research, please consider citing:\n```\n@article{kim2024semantic,\n  title={Semantic Layering in Room Segmentation via LLMs},\n  author={Kim, Taehyeon and Min, Byung-Cheol},\n  journal={arXiv preprint arXiv:2403.12920},\n  year={2024}\n}\n```","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsmartlab-purdue%2Fselros","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsmartlab-purdue%2Fselros","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsmartlab-purdue%2Fselros/lists"}