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--- |
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license: cc-by-nc-sa-4.0 |
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tags: |
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- image-segmentation |
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widget: |
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- example_title: Manhattan |
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src: https://i.imgur.com/Xhh8j1B.jpg |
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- example_title: Artshack |
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src: https://i.imgur.com/zDQdmfr.jpg |
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- example_title: Cesario |
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src: https://i.imgur.com/XLQKyf0.jpg |
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- example_title: Oakland |
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src: https://i.imgur.com/buKTQvJ.jpg |
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datasets: |
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- thiagohersan/satellite-trees |
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--- |
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Experimental model for segmenting vegetation on satellite images. |
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And that is it. It just labels pixels as "vegetation" OR "other". |
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Created by finetuning the [facebook/maskformer-swin-base-ade model](https://huggingface.co/facebook/maskformer-swin-base-ade), and training with **a small number (~25)** of manually labeled satellite images of urban-ish areas. |
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## BIAS WARNING: |
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This model was created for a **personal** art and urbanism project and while the training set included images from geographically diverse cities of personal importance to me, it is in **no way exhaustive**. There are no cities in Asia, Africa, Central America or Oceania. |
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The urban areas included were of, or around, these cities: |
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- São Paulo, BR |
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- Rio de Janeiro, BR |
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- New York, US |
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- Pittsburgh, US |
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- Oakland, US |
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- Berlin, DE |
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- Milan, IT |
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- Riyadh, SA |
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## EVALUATION WARNING: |
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**Anecdotally** speaking, it seems more precise than the original [facebook/maskformer-swin-base-ade model](https://huggingface.co/facebook/maskformer-swin-base-ade) model when used to get masks for vegetation. |
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It works with images of other cities, but success criteria is **qualitative**. |
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