Cuvis.AI
Cuvis.AI is an opensource and extensible framework for building AI powered processing pipelines for hyperspectral video data. It allows you to process and structure spectral data, train and apply machine learning models, visualize and interpret results, and deploy applications in real time environments. Pipelines are built from reusable modular nodes and can be extended with custom plugins or external integrations. Cuvis.AI bridges the gap between hyperspectral hardware and real world applications and enables faster development, testing, and deployment of new solutions.
Platform
Cuvis.AI is split across three repositories:
| Repository | Role |
|---|---|
| cuvis-ai-core | Framework — base Node class, pipeline orchestration, two-phase training, gRPC services, plugin system |
| cuvis-ai-schemas | Shared Protobuf / gRPC schema definitions and generated types |
| cuvis-ai (this repo) | Catalog — 40+ domain-specific nodes for anomaly detection, preprocessing, band selection, and more |
Data I/O lives in the cuvis-ai-dataloader plugin: pluggable hyperspectral DataModules (cu3s + COCO, TIFF + paired PNG). It owns the Cuvis SDK dependency, so install it there if you need .cu3s / .cu3 reads.
Quick Start
As a library (in your own project):
uv add cuvis-ai
GPU support: For PyTorch with CUDA, see the Installation Guide for setup instructions.
For development (within this repo):
uv sync
See the Installation Guide for prerequisites and detailed setup.
Documentation
Full documentation is available at https://docs.cuvis.ai/latest/.
Links
- Website: https://www.cubert-hyperspectral.com/
- Support: http://support.cubert-hyperspectral.com/
- Issues: https://github.com/cubert-hyperspectral/cuvis-ai/issues
- Changelog: CHANGELOG.md
Apache License 2.0 — see LICENSE.
1 maintainer
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