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* [platypus](https://github.com/maju116/platypus) - R package for object detection and image segmentation.
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* [Presto](https://github.com/nasaharvest/presto) - Lightweight, Pre-trained Transformers for Remote Sensing Timeseries.
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* [Raster Vision](https://github.com/azavea/raster-vision) - An open source framework for deep learning on satellite and aerial imagery.
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* [SamGIS](https://github.com/trincadev/samgis-be) – Image Segmentation machine learning based (Segment Anything by Meta - Facebook) applied to GIS and geo data also with GPU requirements. A Segment Anything HuggingFace demo [here](https://huggingface.co/spaces/aletrn/samgis) and an HuggingFace [demo](https://huggingface.co/spaces/aletrn/samgis-lisa-on-cuda) with natural language-based image segmentation capabilities via [LISA](https://github.com/dvlab-research/LISA).
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* [segment-geospatial](https://github.com/opengeos/segment-geospatial) - Meta AI' Segment Anything Model (SAM) for Geospatial Data
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* [sentinel-tree-cover](https://github.com/wri/sentinel-tree-cover) - Image segmentations of trees outside forest.
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* [ShelfNet](https://github.com/juntang-zhuang/ShelfNet) - Implementation of a CNN model for real-time semantic segmentation.
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