What is YOLOS?

YOLOS looks at patches of an image to to form "patch tokens", which are used in place of the traditional wordpiece tokens in NLP.

About the model

Here is an overview of the

YOLOS

model:

Date of Release Jun 01, 2021
Model Type Object Detection
Architecture Transformer, YOLO
Framework Used PyTorch
Annotation Format COCO JSON
Stars on GitHub 648+

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.

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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.

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

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

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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.

Convert data between formats

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