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--- |
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license: apache-2.0 |
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language: |
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- en |
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tags: |
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- Pytorch |
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- mmsegmentation |
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- segmentation |
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- burn scars |
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- Geospatial |
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- Foundation model |
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datasets: |
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- ibm-nasa-geospatial/hls_burn_scars |
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metrics: |
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- accuracy |
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- IoU |
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- F1 Score |
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--- |
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### Model and Inputs |
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The pretrained [Prithvi-100m](https://huggingface.co/ibm-nasa-geospatial/burn-scar-Prithvi-100M) parameter model is used for finetuning over the Burn Scar task on HLS data. |
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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 |
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1. Blue |
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2. Green |
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3. Red |
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4. Narrow NIR |
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5. SWIR 1 |
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6. SWIR 2 |
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### Code |
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Code for Finetuning is available through [github](https://github.com/NASA-IMPACT/hls-foundation-os/tree/main/fine-tuning-examples) |
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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 |
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) |
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### Results |
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