azavea/raster-vision

Health v2 · maintenance only

Adoption not part of the score

2240 stars · 397 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Raster Vision is an open source Python library and low-code framework for building computer vision models on satellite, aerial, and other large georeferenced imagery sets. It provides built-in support for chip classification, object detection, and semantic segmentation with PyTorch backends, and orchestrates the full ML pipeline from training-data analysis through model bundling for deployment.

Use cases

• train object detection models on satellite imagery
• run semantic segmentation on aerial or drone images
• classify land cover from remote sensing data
• build repeatable deep learning pipelines for large imagery sets
• process georeferenced raster data for machine learning
• scale geospatial ML experiments on AWS Batch or SageMaker
• make predictions on oblique drone imagery

When to choose

• You need to train or apply CV models on georeferenced satellite, aerial, or drone imagery
• You want a low-code way to configure end-to-end pipelines: chipping, training, prediction, evaluation, and model bundling
• You need outputs written back in geo-referenced formats
• You want to run experiments repeatably in the cloud via AWS Batch or SageMaker
• You prefer a pip-installable library with utilities for reading geo-referenced data on top of PyTorch

When to avoid

• Your task is general-purpose computer vision on ordinary photos with no geo-referencing
• You need CV tasks beyond classification, object detection, or semantic segmentation, such as instance segmentation or generative models
• You need a GUI-based annotation or labeling tool rather than a training pipeline
• You work primarily in a non-Python or non-PyTorch ecosystem
• You need real-time streaming inference rather than batch-oriented workflows

Facets

framework · maturity active

deep-learning machine-learning computer-vision image-processing deep-learning computer-vision machine-learning data-science python cloud geospatial remote-sensing satellite-imagery aerial-imagery pytorch object-detection semantic-segmentation image-classification chip-classification raster-data aws-batch aws-sagemaker gis drone-imagery low-code docker gpu

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markdown · JSON · MCP: product_card(name="azavea/raster-vision")