Deploy with Roboflow

GroundingDINO

Grounding DINO is a zero-shot object detection model made by combining a Transformer-based DINO detector and grounded pre-training.

Try the Model

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

Overview

Grounding DINO is a zero-shot object detection model made by combining a Transformer-based DINO detector and grounded pre-training. Grounding DINO does impressively well in zero-shot object detection, where it achieves an impressive performance on COCO and LVIS without being trained on these datasets directly.

According to the Grounding DINO paper abstract, the model achieves "a 52.5 AP on the COCO detection zero-shot transfer benchmark" as well as SOTA performance on several other important benchmarks.

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Overall, GroundingDINO is a robust and flexible model for various object detection tasks, especially those requiring open-set detection capabilities.

GroundingDINO License

GroundingDINO

is licensed under a

Apache-2.0

license.

Performance

	name	backbone	Data	box AP on COCO	Checkpoint	Config
1	GroundingDINO-T	Swin-T	O365,GoldG,Cap4M	48.4 (zero-shot) / 57.2 (fine-tune)	Github link \| HF link	link

Deploy a GroundingDINO API

You can use Roboflow Inference to deploy a

GroundingDINO

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 GroundingDINO

You can automatically label a dataset using GroundingDINO 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 GroundingDINO to train a computer vision model.

Grounding DINO and YOLO-NAS

Grounding DINO and DETR

Grounding DINO and YOLOv5

Grounding DINO and YOLOv8