roboflow/inference
Turn any computer or edge device into a command center for your computer vision projects.
What it solves
Inference simplifies the deployment of computer vision models by turning any computer or edge device into a centralized command center. It removes the complexity of managing hardware acceleration, video decoding, and multiprocessing, allowing developers to move from local development to production-scale systems seamlessly.
How it works
The system operates as an inference server that can be run locally via Docker or in the cloud. It uses "Workflows"—composable blocks of functionality—to chain models together and perform complex tasks like object detection, segmentation, and tracking. It can ingest video streams from RTSP or webcams and can be extended with custom Python code, external APIs, or traditional computer vision methods like OCR and barcode reading.
Who it’s for
- Computer Vision Engineers looking to deploy fine-tuned models on edge devices like Raspberry Pi or NVIDIA Jetson.
- AI Developers wanting to build complex visual agents using foundation models like SAM2 or CLIP.
- Enterprise Operations requiring scalable, monitored, and managed video processing pipelines for manufacturing or logistics.
Highlights
- Hardware Agnostic: Runs on everything from cloud servers to tiny edge devices.
- Composable Workflows: Chain multiple models and logic blocks to create complex vision micro-services.
- Foundation Model Support: Native access to state-of-the-art models like Florence-2 and SAM2.
- Stream Management: Handles video decoding and GPU batching for real-time RTSP and webcam processing.