---
license: apache-2.0
language:
- en
tags:
- Pytorch
- mmsegmentation
- segmentation
- burn scars
- Geospatial
- Foundation model
datasets:
- ibm-nasa-geospatial/hls_burn_scars
metrics:
- accuracy
- IoU
- F1 Score
---

### Model and Inputs
The pretrained [Prithvi-100m](https://huggingface.co/ibm-nasa-geospatial/Prithvi-100M/blob/main/README.md) parameter model is finetuned to detect Burn Scars on HLS data from the [HLS Burn Scar Scenes dataset](https://huggingface.co/datasets/ibm-nasa-geospatial/hls_burn_scars).
The finetuning expected an input tile of 512x512x6, where 512 is the height and width and 6 is the number of bands. The bands are:
 
1. Blue
2. Green
3. Red
4. Narrow NIR
5. SWIR 1
6. SWIR 2

### Code
Code for Finetuning is available through [github](https://github.com/NASA-IMPACT/hls-foundation-os/tree/main/fine-tuning-examples)

Configuration used for finetuning is available through [config](https://github.com/NASA-IMPACT/hls-foundation-os/blob/main/fine-tuning-examples/configs/firescars_config.py
)


### Results