YOLOS looks at patches of an image to to form "patch tokens", which are used in place of the traditional wordpiece tokens in NLP. There are 100 detection tokens on the right are learnable embeddings and feed into potential detections.

Compared to other CNN-based YOLO models, YOLOS benefits from the rising tides of transformers in computer vision, as well as inferring without the need for NMS, a tedious post-processing step that makes the deployment of other YOLO models difficult and slow.

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

Learn about YOLOv8

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

Learn about YOLOv8

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

Learn about YOLOv8

Model Performance

Model	Pre-train Epochs	ViT (DeiT) Weight / Log	Fine-tune Epochs	Eval Size	YOLOS Checkpoint / Log	AP @ COCO val
`YOLOS-Ti`	300	FB	300	512	Baidu Drive, Google Drive / Log	28.7
`YOLOS-S`	200	Baidu Drive, Google Drive / Log	150	800	Baidu Drive, Google Drive / Log	36.1
`YOLOS-S`	300	FB	150	800	Baidu Drive, Google Drive / Log	36.1
`YOLOS-S (dWr)`	300	Baidu Drive, Google Drive / Log	150	800	Baidu Drive, Google Drive / Log	37.6
`YOLOS-B`	1000	FB	150	800	Baidu Drive, Google Drive / Log	42.0

Explore this model on Roboflow

YOLOS - You Only Look At One Sequence

Unlike previous CNN based YOLO models, the YOLOS backbone is a Transformer block, much like the first vision transformer for classification.

Train YOLOS Transformer On a Custom Dataset

In this post, we showcase how to create a YOLOS object detection labeling, training, and deployment pipeline.

Deploy YOLOS to production

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

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YOLOS Annotation Format

YOLOS

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.
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Convert data between formats

Label data automatically with YOLOS

You can automatically label a dataset using

YOLOS

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

YOLOS

to train a computer vision model.

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