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@@ -20,7 +20,7 @@ LADI-v2-classifier-large is based on [microsoft/swinv2-large-patch4-window12to16
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  ## Model Details
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  ### Model Description
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- The model architecture is based on swinv2 and fine-tuned on the LADI v2 dataset, which contains 10,000 aerial images labeled by volunteers from the Civil Air Patrol. The images are labeled using multi-label classification for the following classes:
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  - bridges_any
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  - buildings_any
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  - trees_damage
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  - water_any
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- This 'reference' model is trained only on the training split, which contains 8,000 images from 2015-2022. It is provided for the purpose of reproducing the results from the paper. The 'deploy' model is trained on the training, validation, and test sets, and contains 10,000 images from 2015-2023. We recommend that anyone who wishes to use this model in production use the main versions of the models [MITLL/LADI-v2-classifier-small](https://huggingface.co/MITLL/LADI-v2-classifier-small) and [MITLL/LADI-v2-classifier-large](https://huggingface.co/MITLL/LADI-v2-classifier-large).
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-
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- - **Developed by:** Jeff Liu, Sam Scheele
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- - **Funded by:** Department of the Air Force under Air Force Contract No. FA8702-15-D-0001
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- - **License:** MIT
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- - **Finetuned from model:** [microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft)
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-
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  ## How to Get Started with the Model
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  LADI-v2-classifier-large is trained to identify features of interest to disaster response managers from aerial images. Use the code below to get started with the model.
@@ -117,6 +110,12 @@ Paper forthcoming - watch this space for details
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  ---
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  DISTRIBUTION STATEMENT A. Approved for public release. Distribution is unlimited.
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  This material is based upon work supported by the Department of the Air Force under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Department of the Air Force.
 
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  ## Model Details
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  ### Model Description
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+ The model architecture is based on swinv2 and fine-tuned on the LADI v2 dataset, which contains 10,000 post-disaster aerial images from 2015-2023 labeled by volunteers from the Civil Air Patrol. The images are labeled using multi-label classification for the following classes:
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  - bridges_any
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  - buildings_any
 
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  - trees_damage
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  - water_any
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  ## How to Get Started with the Model
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  LADI-v2-classifier-large is trained to identify features of interest to disaster response managers from aerial images. Use the code below to get started with the model.
 
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  ---
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+ - **Developed by:** Jeff Liu, Sam Scheele
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+ - **Funded by:** Department of the Air Force under Air Force Contract No. FA8702-15-D-0001
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+ - **License:** MIT
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+ - **Finetuned from model:** [microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft)
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+ ---
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+
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  DISTRIBUTION STATEMENT A. Approved for public release. Distribution is unlimited.
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  This material is based upon work supported by the Department of the Air Force under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Department of the Air Force.