What is YOLOR?

YOLOR (You Only Learn One Representation) is an object detection model that uses both implicit and explicit knowledge to make predictions.

About the model

Here is an overview of the

YOLOR

model:

Date of Release May 10, 2021
Model Type Object Detection
Architecture CNN, YOLO
Framework Used PyTorch
Annotation Format YOLOv5 PyTorch TXT
Stars on GitHub 1800+

What is YOLOR?

You Only Learn One Representation (YOLOR) is a state-of-the-art object detection model. YOLOR pre-trains an implicit knowledge network with all of the tasks present in the COCO dataset, namely object detection, instance segmentation, panoptic segmentation, keypoint detection, stuff segmentation, image caption, multi-label image classification, and long-tail object recognition. When optimizing for the COCO dataset, YOLOR trains another set of parameters that represent explicit knowledge. For prediction, both implicit and explicit knowledge is used.

YOLOR Architecture

YOLOR Architecture

Vision Transformer Performance

This novel approach propels YOLOR to the state-of-the-art for object detection in the speed/accuracy tradeoff landscape.

YOLOR Performance


Images in Courtesy of Wong-Kin-Yiu

Further Reading

Train YOLOR on a Custom Dataset: https://blog.roboflow.com/train-yolor-on-a-custom-dataset/
YOLOR Research Paper: https://arxiv.org/abs/2105.04206

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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.

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Model Performance

Explore this model on Roboflow

Deploy YOLOR to production

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

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YOLOR Annotation Format

YOLOR

uses the

uses the

YOLOv5 PyTorch TXT

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 YOLOR

You can automatically label a dataset using

YOLOR

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

YOLOR

to train a computer vision model.

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