open-edge-platform/geti
Build, train, optimize, and run computer vision models locally, from raw images to live inference. Open source, with CPU, Intel XPU, and NVIDIA CUDA support. observed · 2026-08-28
Health v2 · maintenance only
98/100
- Activity 99
- Release rhythm 97
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: 28.5
- age_days: 2868
- days_rel: 20
- days_push: 7
- n_releases_24m: 15
Adoption not part of the score
1317 stars · 477 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Geti is an open-source, end-to-end Vision AI application from Intel that takes users from raw images to deployed computer vision models, running locally as a single container or native Windows app. It includes the getitune training engine (formerly OpenVINO Training Extensions/otx) with 67+ state-of-the-art model architectures for object detection, segmentation, and classification, optimized for inference on Intel XPU, CPU, and NVIDIA CUDA hardware.
Use cases
- train object detection models on my own images
- build an image classification model with minimal data
- train image segmentation models locally
- optimize and quantize vision models for edge inference with OpenVINO
- run AutoML to find the best computer vision model for my dataset
- deploy a vision model for live inference on Intel GPU
- do transfer learning from pretrained YOLO or DETR models
- annotate images and manage datasets for vision training
When to choose
- you want an end-to-end local workflow from raw images to deployed vision models
- you target Intel hardware (CPU, XPU) or NVIDIA CUDA for training and inference
- you need state-of-the-art detection, segmentation, or classification architectures without writing training code
- you want OpenVINO-optimized models for edge deployment
- you prefer a self-hosted GUI application or REST API over notebooks
When to avoid
- you need tasks beyond computer vision such as NLP, audio, or LLMs
- you require cloud-scale distributed training across many nodes
- you want a lightweight Python library only - though getitune covers that, the full app is heavyweight
- you depend on non-Intel accelerators other than NVIDIA CUDA
- you need the deprecated otx package API specifically
Facets
application · maturity active
machine-learning deep-learning computer-vision image-processing llm-training computer-vision machine-learning deep-learning image-processing windows python self-hosted openvino automl object-detection image-segmentation image-classification model-optimization quantization transfer-learning edge-ai intel-xpu nvidia-cuda vision-ai docker linux gpu
10 sources
- readme: https://github.com/open-edge-platform/geti · fetched 2026-08-28 · 8f933e9871f7
- homepage: https://docs.geti.intel.com · fetched 2026-08-29 · 53a184193773
- site_page: https://docs.geti.intel.com/docs/rest-api/openapi-specification · fetched 2026-08-29 · f9b535bc6b6f
- site_page: https://docs.geti.intel.com/docs/2.0/user-guide/getting-started/introduction · fetched 2026-08-29 · f9b535bc6b6f
- site_page: https://docs.geti.intel.com/docs/user-guide/learn-geti/computer-vision-tasks/ai-fundamentals-tasks · fetched 2026-08-29 · f9b535bc6b6f
- site_page: https://docs.geti.intel.com/docs/user-guide/geti-fundamentals/datasets/dataset-management · fetched 2026-08-29 · f9b535bc6b6f
- site_page: https://docs.geti.intel.com/docs/user-guide/geti-fundamentals/model-training-and-optimization · fetched 2026-08-29 · f9b535bc6b6f
- site_page: https://docs.geti.intel.com/docs/user-guide/getting-started/introduction · fetched 2026-08-29 · f9b535bc6b6f
- site_page: https://docs.geti.intel.com/docs/rest-api/get-started · fetched 2026-08-29 · f9b535bc6b6f
- site_page: https://docs.geti.intel.com/docs/2.0/rest-api/openapi-specification · fetched 2026-08-29 · f9b535bc6b6f
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| open-edge-platform/geti | main | 98 |
For agents
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Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem