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README.md

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**Meta AI' Segment Anything Model (SAM) for Geospatial Data**
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The `segment-geospatial` package draws its inspiration from [segment-anything-eo](https://github.com/aliaksandr960/segment-anything-eo) repository authored by [Aliaksandr Hancharenka](https://github.com/aliaksandr960). To facilitate the use of the Segment Anything Model (SAM) for geospatial data, I have developed the [segment-anything-py](https://github.com/opengeos/segment-anything) and [segment-geospatial](https://github.com/opengeos/segment-geospatial) Python packages, which are now available on PyPI and conda-forge. My primary objective is to simplify the process of leveraging SAM for geospatial data analysis by enabling users to achieve this with minimal coding effort. I have adapted the source code of segment-geospatial from the [segment-anything-eo](https://github.com/aliaksandr960/segment-anything-eo) repository, and credit for its original version goes to Aliaksandr Hancharenka.
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The **segment-geospatial** package draws its inspiration from [segment-anything-eo](https://github.com/aliaksandr960/segment-anything-eo) repository authored by [Aliaksandr Hancharenka](https://github.com/aliaksandr960). To facilitate the use of the Segment Anything Model (SAM) for geospatial data, I have developed the [segment-anything-py](https://github.com/opengeos/segment-anything) and [segment-geospatial](https://github.com/opengeos/segment-geospatial) Python packages, which are now available on PyPI and conda-forge. My primary objective is to simplify the process of leveraging SAM for geospatial data analysis by enabling users to achieve this with minimal coding effort. I have adapted the source code of segment-geospatial from the [segment-anything-eo](https://github.com/aliaksandr960/segment-anything-eo) repository, and credit for its original version goes to Aliaksandr Hancharenka.
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- Free software: MIT license
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- Documentation: https://samgeo.gishub.org

docs/changelog.md

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# Changelog
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## v0.0.1 - Date
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## v0.1.0 - Apr 19, 2023
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**Improvement**:
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**New Features**
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- TBD
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- Added `SamGeo` class
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- Added GitHub Actions
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- Added notebook example
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**New Features**:
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## v0.0.1 - Apr 18, 2023
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- TBD
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Initial release

docs/index.md

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**Meta AI' Segment Anything Model (SAM) for Geospatial Data** 🗺️
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The `segment-geospatial` package draws its inspiration from [segment-anything-eo](https://github.com/aliaksandr960/segment-anything-eo) repository authored by [Aliaksandr Hancharenka](https://github.com/aliaksandr960). To facilitate the use of the Segment Anything Model (SAM) for geospatial data, I have developed the [segment-anything-py](https://github.com/opengeos/segment-anything) and [segment-geospatial](https://github.com/opengeos/segment-geospatial) Python packages, which are now available on PyPI and conda-forge. My primary objective is to simplify the process of leveraging SAM for geospatial data analysis by enabling users to achieve this with minimal coding effort. I have adapted the source code of segment-geospatial from the [segment-anything-eo](https://github.com/aliaksandr960/segment-anything-eo) repository, and credit for its original version goes to Aliaksandr Hancharenka.
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The **segment-geospatial** package draws its inspiration from [segment-anything-eo](https://github.com/aliaksandr960/segment-anything-eo) repository authored by [Aliaksandr Hancharenka](https://github.com/aliaksandr960). To facilitate the use of the Segment Anything Model (SAM) for geospatial data, I have developed the [segment-anything-py](https://github.com/opengeos/segment-anything) and [segment-geospatial](https://github.com/opengeos/segment-geospatial) Python packages, which are now available on PyPI and conda-forge. My primary objective is to simplify the process of leveraging SAM for geospatial data analysis by enabling users to achieve this with minimal coding effort. I have adapted the source code of segment-geospatial from the [segment-anything-eo](https://github.com/aliaksandr960/segment-anything-eo) repository, and credit for its original version goes to Aliaksandr Hancharenka.
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- 🆓 Free software: MIT license
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- 📖 Documentation: https://samgeo.gishub.org

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