Try the Model

Use the widget below to experiment with Florence 2 Object Detection. You can detect COCO classes such as people, vehicles, animals, household items.

Overview

Florence-2 is a lightweight vision-language model open-sourced by Microsoft under the MIT license. The model demonstrates strong zero-shot and fine-tuning capabilities across tasks such as captioning, object detection, grounding, and segmentation.

Florence-2 represents a significant advancement in vision-language models by combining lightweight architecture with robust capabilities, making it highly accessible and versatile. Its unified representation approach, supported by the extensive FLD-5B dataset, enables it to excel in multiple vision tasks without the need for separate models. This efficiency makes Florence-2 a strong contender for real-world applications, particularly on devices with limited resources.

Florence 2 Object Detection License

Florence 2 Object Detection

is licensed under a

MIT

license.

Performance

Deploy a Florence 2 Object Detection API

You can use Roboflow Inference to deploy a

Florence 2 Object Detection

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 Florence 2 Object Detection

You can automatically label a dataset using Florence 2 Object Detection 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 Florence 2 Object Detection to train a computer vision model.

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