LHRS-Align
LHRS‑Align is a large‑scale, semantically rich and feature‑diverse remote‑sensing image‑text alignment dataset. It leverages volunteer geographic information (VGI) from OpenStreetMap and remote‑sensing images from Google Earth, containing 1.15 million high‑quality RS image‑text pairs.
Description
LHRS‑Bot Dataset Overview
Dataset Introduction
LHRS‑Bot is a multimodal large language model (MLLM) that utilizes globally available volunteer geographic information (VGI) and remote‑sensing (RS) images. The model demonstrates deep understanding of RS images and capabilities for complex reasoning in the RS domain.
Dataset Release Information
- 15 July 2024: Updated paper available on arXiv.
- 9 July 2024: Evaluation benchmark LHRS‑Bench released.
- 2 July 2024: Paper accepted at ECCV 2024; training scripts and data open‑sourced.
- 7 Feb 2024: Model weights available on Google Drive and Baidu Disk.
- 2 Feb 2024: Code and checkpoint released.
Dataset Preparation
Installation
- Clone the repository:
git clone git@github.com:NJU-LHRS/LHRS-Bot.git cd LHRS-Bot - Create a virtual environment:
conda create -n lhrs python=3.10 conda activate lhrs - Install dependencies:
pip install -e .
Checkpoints
- LLaMA2‑7B‑Chat:
- Automatic download via Hugging Face token.
- Manual download from the provided links if needed.
- LHRS‑Bot checkpoints (stages 1‑3) are hosted on Baidu Disk and Google Drive; ensure the
TextLoRAfolder andFINAL.ptreside in the same directory.
Training
Data preparation and formatting follow the instructions in [DataPrepare/README.md]. Training stages 1‑3 use distinct scripts and directories.
Demonstration
- Web UI (Gradio):
python lhrs_webui.py -c Config/multi_modal_eval.yaml \ --checkpoint-path ${PathToCheckpoint}.pt \ --server-port 8000 \ --server-name 127.0.0.1 \ --share - CLI:
python cli_qa.py -c Config/multi_modal_eval.yaml \ --model-path ${PathToCheckpoint}.pt \ --image-file ${TheImagePathYouWantToChat} \ --accelerator "gpu" \ --temperature 0.4 \ --max-new-tokens 512
Acknowledgements
We thank the following repositories for their excellent work:
Disclaimer
If you find our work useful, please star the GitHub repository and consider citing our paper:
@misc{2402.02544,
Author = {Dilxat Muhtar and Zhenshi Li and Feng Gu and Xueliang Zhang and Pengfeng Xiao},
Title = {LHRS‑Bot: Empowering Remote Sensing with VGI‑Enhanced Large Multimodal Language Model},
Year = {2024},
Eprint = {arXiv:2402.02544},
}
License: Apache
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Topics
Source
Organization: github
Created: 2/4/2024
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