azavea/raster-vision
An open source library and framework for deep learning on satellite and aerial imagery.
This tool helps geospatial analysts and remote sensing specialists automatically identify and categorize features within large satellite and aerial images. You provide your imagery and some example labels, and it outputs maps with classified areas, detected objects, or segmented regions, making sense of vast datasets efficiently. It's designed for professionals working with Earth observation data.
2,210 stars. No commits in the last 6 months.
Use this if you need to build and run deep learning models on satellite, aerial, or drone imagery without being a deep learning expert, especially for tasks like classifying land cover, detecting specific objects, or segmenting areas.
Not ideal if your primary task involves processing standard photographic images rather than geo-referenced geospatial data, or if you need to develop deep learning models from scratch without a framework.
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2,210
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395
Language
Python
License
Apache-2.0
Category
Last pushed
Sep 29, 2025
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