Try the Model

Use the widget below to experiment with DINOv2. You can detect COCO classes such as people, vehicles, animals, household items.

Overview

DINOv2 is a self-supervised method for training computer vision models developed by Meta Research and released in April 2023. Because DINOv2 is self-supervised, the input data does not require labels, which means models based on this architecture can learn richer information about the contents of an image.

DINOv2 License

DINOv2

is licensed under a

license.

Performance

Deploy a DINOv2 API

You can use Roboflow Inference to deploy a

DINOv2

API on your hardware. You can deploy the model on CPU (i.e. Raspberry Pi, AI PCs) and GPU devices (i.e. NVIDIA Jetson, NVIDIA T4).

Below are instructions on how to deploy your own model API.

Label Data Automatically with DINOv2

You can automatically label a dataset using DINOv2 with help from Autodistill, an open source package for training computer vision models. You can label a folder of images automatically with only a few lines of code. Below, see our tutorials that demonstrate how to use DINOv2 to train a computer vision model.

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