---
license: apache-2.0
language:
- en
base_model:
- nasa-ibm-ai4science/Surya-1.0
---
# 🌌 Surya – Active Region Segmentation 

## 📖 Model Overview
This repository hosts **fine-tuned weights of Surya** – a heliophysics foundation model – for the task of **solar Active Region (AR) segmentation**.  
Solar Active Regions are magnetically complex structures associated with **flares** and **coronal mass ejections (CMEs)**. Within ARs, the **Polarity Inversion Line (PIL)** serves as a critical precursor of eruptions. Accurate segmentation of ARs containing PILs is essential for **space weather forecasting** and understanding solar magnetic complexity.  

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## 📊 Results
We benchmarked Surya against a standard UNet baseline on the ARPIL dataset.

| Model  | Params | IoU   | Dice Coeff |
|--------|--------|-------|------------|
| UNet   | 9.2 M  | 0.688 | 0.801      |
| **Surya (LoRA)** | **4.1 M**  | **0.768** | **0.853**      |

Surya achieves **higher segmentation quality with fewer parameters**, highlighting the benefits of foundation model pretraining and parameter-efficient adaptation.

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## 🖼 Example
<p align="center">
  <img src="ar_seg.png" width="100%">
</p>

- **Top Row**: Input SDO/HMI data (Date: 2014-02-01, Time: 08:12)  
- **Middle Row**: Surya segmentation output  
- **Bottom Row**: Ground Truth  

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## ⚡ Usage

Follow the instructions at [Surya/downstream_examples/ar_segmentation](https://github.com/NASA-IMPACT/Surya/tree/main/downstream_examples/ar_segmentation)

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## 🤝 Acknowledgements
- **NASA IMPACT** and **IBM** for developing the Surya foundation model