Enhance FLAIR-HUB dataset card with MAESTRO paper, code, and sample usage

README.md

@@ -1,5 +1,10 @@
 ---
 license: etalab-2.0
+size_categories:
+- 100K<n<1M
+task_categories:
+- image-segmentation
+pretty_name: FLAIR-HUB
 tags:
 - Multimodal
 - Earth Observation
@@ -9,11 +14,6 @@ tags:
 - Environement
 - LandCover
 - Agriculture
-task_categories:
-- image-segmentation
-pretty_name: FLAIR-HUB
-size_categories:
-- 100K<n<1M
 ---
 
 # FLAIR-HUB : Large-scale Multimodal Dataset for Land Cover and Crop Mapping
@@ -32,8 +32,10 @@ learning methods, and will continue to grow with new modalities and annotations.
 ## 🔗 Links
 
 📄 <a href="https://arxiv.org/abs/2506.07080" target="_blank"><b>Dataset Preprint</b></a><br>
+📄 <a href="https://huggingface.co/papers/2508.10894" target="_blank"><b>MAESTRO Paper (using this dataset)</b></a><br>
 📁 <a href="https://storage.gra.cloud.ovh.net/v1/AUTH_366279ce616242ebb14161b7991a8461/defi-ia/flair_hub/FLAIR-HUB_TOY_DATASET.zip" target="_blank"><b>Toy dataset (~750MB) -direct download-</b></a><br>
 💻 <a href="https://github.com/IGNF/FLAIR-HUB" target="_blank"><b>Source Code (GitHub)</b></a><br>
+💻 <a href="https://github.com/ignf/maestro" target="_blank"><b>MAESTRO Code (GitHub, uses this dataset)</b></a><br>
 🏠 <a href="https://ignf.github.io/FLAIR/" target="_blank"><b>FLAIR datasets page </b></a><br>
 ✉️ <a href="mailto:[email protected]"><b>Contact Us</b></a> – [email protected] – Questions or collaboration inquiries welcome!<br>
 <hr>
@@ -183,8 +185,6 @@ FLAIR-HUB uses an <b>official split for benchmarking, corresponding to the split
 <p align="center"><img src="datacard_imgs/FLAIR-HUB_splits_oneline.png" alt="" style="width:80%;max-width:1300px;" /></p>
 <hr>
 
-
-
 ## 🏆 Bechmark scores 
 
 
@@ -237,8 +237,25 @@ The **Model ID** can be used to retrieve the corresponding pre-trained model fro
 | LPIS-J   | ✓          | ✓    | ✓       | ✓       | 186.9  | 53  | **88.0** | 35.4 |
 | LPIS-K   |            | ✓    |         |         | 89.2   | 14  | 84.5 | 15.1 |
 
+<hr>
 
-
+## ✨ Sample Usage
+
+This dataset is extensively used by the [MAESTRO model](https://huggingface.co/papers/2508.10894) for masked autoencoding on multimodal Earth observation data. You can find the MAESTRO model's code on its [GitHub repository](https://github.com/ignf/maestro).
+
+A minimal example for using FLAIR-HUB with the MAESTRO framework:
+```bash
+poetry run python main.py \
+        model.model=mae \
+        model.model_size=medium \
+        run.exp_name=mae-m_flair \
+        run.exp_dir=/path/to/experiments/dir \
+        datasets.root_dir=/path/to/dataset/dir \
+        datasets.flair.rel_dir=FLAIR-HUB \
+        datasets.filter_pretrain=[flair] \
+        datasets.filter_finetune=[flair]
+```
+<hr>
 
 ## 📚 How to Cite
 
@@ -263,5 +280,4 @@ DOI: https://doi.org/10.48550/arXiv.2506.07080
 
 ## ⚙️ Acknowledgement
 
-Experiments have been conducted using HPC/AI resources provided by GENCI-IDRIS (Grant 2024-A0161013803, 2024-AD011014286R2 and 2025-A0181013803).
-
+Experiments have been conducted using HPC/AI resources provided by GENCI-IDRIS (Grant 2024-A0161013803, 2024-AD011014286R2 and 2025-A0181013803).