roboflow/inference

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

2427 stars · 310 forks observed · 2026-08-28

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

Roboflow Inference is a Python library and self-hostable inference server for deploying computer vision models on any computer or edge device. It supports fine-tuned models, foundation models like Florence-2, CLIP, and SAM2, and a Workflows engine for chaining models, logic, and integrations into production pipelines.

Use cases

• deploy a fine-tuned object detection model on an edge device
• run YOLOv8 inference on live RTSP camera streams
• self-host a computer vision inference API server
• build multi-model pipelines with CLIP and SAM2
• count and track objects in video with notifications
• blur faces or read license plates from camera feeds
• run OCR and barcode detection alongside ML models

When to choose

• you need to deploy vision models on-premise or at the edge with optional offline operation
• you want to chain multiple models and CV techniques into production pipelines
• you need GPU-accelerated inference served over an HTTP API
• you want pre-built blocks for tracking, counting, and video stream management

When to avoid

• you only need training or fine-tuning of models rather than deployment
• you need a lightweight single-model library without server infrastructure
• your project requires a permissive license without restrictions (license is custom)
• you want a fully managed cloud service without self-hosting

Facets

library · maturity active

machine-learning computer-vision llm-inference video-processing ocr sdk self-hosted api-framework computer-vision machine-learning deep-learning image-processing developer-tools python windows self-hosted cloud inference-server object-detection yolo edge-deployment foundation-models workflows rtsp sam2 clip model-serving video docker linux macos gpu

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markdown · JSON · MCP: product_card(name="roboflow/inference")