| | --- |
| | base_model: |
| | - zheng95z/rgb-to-x |
| | - prs-eth/marigold-iid-appearance-v1-1 |
| | - prs-eth/marigold-iid-lighting-v1-1 |
| | datasets: |
| | - GDAOSU/Olbedo |
| | --- |
| | |
| | # Olbedo: An Albedo and Shading Aerial Dataset for Large-Scale Outdoor Environments |
| |
|
| | [](https://gdaosu.github.io/olbedo/) |
| | [](https://huggingface.co/spaces/GDAOSU/olbedo) |
| | [](https://huggingface.co/GDAOSU/olbedo) |
| | [](https://huggingface.co/datasets/GDAOSU/Olbedo) |
| | [](https://arxiv.org/abs/2602.22025) |
| |
|
| | This repository contains the official implementation and inference code for **Olbedo**. |
| |
|
| | ## π Resources |
| |
|
| | We provide a comprehensive suite of resources for this project: |
| |
|
| | * **Project Page:** [https://gdaosu.github.io/olbedo/](https://gdaosu.github.io/olbedo/) |
| | * **Interactive Demo:** [Hugging Face Spaces](https://huggingface.co/spaces/GDAOSU/olbedo) |
| | * **Pre-trained Models:** [Hugging Face Model Hub](https://huggingface.co/GDAOSU/olbedo) |
| | * **Dataset:** [Hugging Face Datasets](https://huggingface.co/datasets/GDAOSU/Olbedo) |
| | * **Paper:** [arXiv:2602.22025](https://arxiv.org/abs/2602.22025) |
| |
|
| | ## π Usage |
| |
|
| | We provide Docker support to ensure a consistent environment for running inference. |
| |
|
| | ### 1. Build the Environment |
| |
|
| | First, clone this repository and build the Docker image. This will set up all necessary dependencies. |
| |
|
| | ```bash |
| | bash build_docker.sh |
| | ``` |
| |
|
| | ### 2. Run Inference |
| |
|
| | To run inference on your own images, use the run_inference.sh script. You must specify the input directory containing your images and the output directory where results will be saved. |
| | |
| | ```bash |
| | bash run_inference.sh <input_directory> <output_directory> |
| | ``` |
| | |
| | ## π Data & Models |
| | |
| | If you wish to use the data or models separately, they are hosted on Hugging Face: |
| | |
| | | Resource | Link | Description | |
| | | :--- | :--- | :--- | |
| | | **Model Weights** | [Download Here](https://huggingface.co/GDAOSU/olbedo) | Pre-trained checkpoints for the Olbedo architecture. | |
| | | **Dataset** | [Download Here](https://huggingface.co/datasets/GDAOSU/Olbedo) | The dataset used for training and evaluation. | |
| | |
| | |
| | ## π Citation |
| | |
| | If you find this project useful for your research, please consider citing our work: |
| | |
| | ``` |
| | @misc{song2026olbedoalbedoshadingaerial, |
| | title={Olbedo: An Albedo and Shading Aerial Dataset for Large-Scale Outdoor Environments}, |
| | author={Shuang Song and Debao Huang and Deyan Deng and Haolin Xiong and Yang Tang and Yajie Zhao and Rongjun Qin}, |
| | year={2026}, |
| | eprint={2602.22025}, |
| | archivePrefix={arXiv}, |
| | primaryClass={cs.CV}, |
| | url={[https://arxiv.org/abs/2602.22025](https://arxiv.org/abs/2602.22025)}, |
| | } |
| | ``` |
| | |
| | ## π Acknowledgements |
| |
|
| | This codebase is largely built upon the following excellent projects: |
| |
|
| | * **[Marigold](https://github.com/prs-eth/Marigold)** |
| | * **[RGBX](https://github.com/zheng95z/rgbx)** |
| |
|
| | We thank the authors for their open-source contributions. |
| |
|
| | ## π« License |
| |
|
| | The dataset associated with this work is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0) (as defined in [LICENSE-DATA](LICENSE-DATA.txt)). |
| |
|
| | This code of this work is licensed under the Apache License, Version 2.0 (as defined in the [LICENSE](LICENSE.txt)). |
| |
|
| | The Marigold pretrained and fine-tuned models are licensed under RAIL++-M License (as defined in the [LICENSE-MODEL](LICENSE-MODEL.txt)). |
| |
|
| | The RGBX pretrained and fine-tuned models are licensed under ADOBE RESEARCH LICENSE(as defined in the [LICENSE-ADOBE](LICENSE-ADOBE.txt)). |
| |
|
| | By downloading and using the dataset, code and models you agree to the terms in [LICENSE-DATA](LICENSE-DATA.txt), [LICENSE](LICENSE.txt), [LICENSE-MODEL](LICENSE-MODEL.txt), and [LICENSE-ADOBE](LICENSE-ADOBE.txt) respectively. |