What is DETR?

Detection Transformer (DETR) is an end-to-end object detection model implemented using the Transformer architecture.

About the model

Here is an overview of the

DETR

model:

Date of Release
Model Type Object Detection
Architecture Transformers
Framework Used PyTorch
Annotation Format COCO JSON
Stars on GitHub 10700+

Detection Transformer (DETR) is an end-to-end object detection model implemented using the Transformer architecture. DETR was developed by Facebook Research. The baseline DETR model has an AP score of 42.0% on COCO.

Check out YOLOv8, defining a new state-of-the-art in computer vision

YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.

Learn about YOLOv8

Check out YOLOv8, defining a new state-of-the-art in computer vision

YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.

Learn about YOLOv8

Check out YOLOv8, defining a new state-of-the-art in computer vision

YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.

Learn about YOLOv8

Check out YOLOv8, defining a new state-of-the-art in computer vision

YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.

Learn about YOLOv8

Model Performance

name backbone schedule inf_time box AP url size
0 DETR R50 500 0.036 42.0 model | logs 159Mb
1 DETR-DC5 R50 500 0.083 43.3 model | logs 159Mb
2 DETR R101 500 0.050 43.5 model | logs 232Mb
3 DETR-DC5 R101 500 0.097 44.9 model | logs 232Mb

Explore this model on Roboflow

Deploy DETR to production

Roboflow offers a range of SDKs with which you can deploy your model to production.

No items found.

DETR Annotation Format

DETR

uses the

uses the

COCO JSON

annotation format. If your annotation is in a different format, you can use Roboflow's annotation conversion tools to get your data into the right format.

Convert data between formats

Label data automatically with DETR

You can automatically label a dataset using

DETR

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

DETR

to train a computer vision model.

Compare to related models

Curious about how this model compares to others? Check out our model comparisons.

We have not created any model comparisons yet for this model.

Deploy a computer vision model today

Join 100k developers curating high quality datasets and deploying better models with Roboflow.

Get started
MANAGING over 100 million images for companies of all sizes

Join over 250,000 developers managing computer vision data on Roboflow.

VentureBeatTechCrunchInteresting EngineeringInternational Business TimesU.S. News & World ReportYahoo Finance