Principle:Roboflow Rf detr Serverless Inference
| Knowledge Sources | |
|---|---|
| Domains | Deployment, Inference |
| Last Updated | 2026-02-08 15:00 GMT |
Overview
The process of running object detection inference on images via a deployed model's API endpoint without managing infrastructure.
Description
Serverless inference allows running a deployed RF-DETR model through the Roboflow platform without needing local GPU resources or PyTorch. The inference API accepts images in various formats and returns structured detection results (bounding boxes, class labels, confidence scores).
Usage
Use this principle after deploying a model to Roboflow to run inference in production applications, particularly when clients lack GPU hardware or cannot install PyTorch.
Theoretical Basis
Serverless inference abstracts the model execution behind an API, providing:
- Scalability: Auto-scaling based on request volume
- Simplicity: No GPU/driver management required on the client
- Consistency: Same model version serves all requests
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