https://github.com/smartlab-purdue/selros

Code repository for Semantic Layering in Room Segmentation via LLMs (SeLRoS). 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.
https://github.com/smartlab-purdue/selros

Last synced: 5 months ago
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Code repository for Semantic Layering in Room Segmentation via LLMs (SeLRoS). 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.

• Host: GitHub
• URL: https://github.com/smartlab-purdue/selros
• Owner: SMARTlab-Purdue
• License: mit
• Created: 2024-04-12T19:12:30.000Z (about 1 year ago)
• Default Branch: master
• Last Pushed: 2024-04-12T21:08:54.000Z (about 1 year ago)
• Last Synced: 2024-11-08T07:47:48.767Z (6 months ago)
• Language: Python
• Homepage: https://sites.google.com/view/selros
• Size: 33.4 MB
• Stars: 7
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# **Semantic Layering in Room Segmentation via LLMs (SeLRoS)**

[Taehyeon Kim](https://github.com/QualiaT) and Byung-Cheol Min.

[Project Page](https://sites.google.com/view/selros)

Code repository for Semantic Layering in Room Segmentation via LLMs (SeLRoS). 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.

## Setup

Install dependencies:

```

pip install -r requirments.txt

```

For more details, please check the following link [ProcTHOR](https://github.com/allenai/procthor).

## Running Script

Run the following command to interpret segmenation map and generate output. 

```

python3 room_info_interpreter.py --input1 {segmented_map.png} --input2 {related_information.txt}

```

Note: You can use the segmented_map.png and related_information.txt in ```data\vrf\```.

Run the following script to generate top view image and 2d map of environment.

```

python3 run_get_2d_map.py

```

Run the following script to get scenes of specific position.

```

python3 run_get_scenes.py

```

Note: If you want to change observation position, change x, z value in 52 line.

## Dataset

The repository contains ground truth, object information file, top view image, and room segmentation results for each environment. 

Refer to ```data\ground_truth\``` for the ground truth of each environment.

Refer to ```data\object_information\``` for the object information txt file of each room in each environment.

Refer to ```data\selros\``` for the final room segmentation results using SeLRoS.

Refer to ```data\top_view\``` for the top view image of each environment.

Refer to ```data\vrf\``` for the room segmentation results using Voronoi Random Field algorithm and related information (each segmented room's center coordinate and color).

## Citation

If you find this work useful for your research, please consider citing:

```

@article{kim2024semantic,

  title={Semantic Layering in Room Segmentation via LLMs},

  author={Kim, Taehyeon and Min, Byung-Cheol},

  journal={arXiv preprint arXiv:2403.12920},

  year={2024}

}

```