Models

What is YOLO-NAS Pose?

YOLO-NAS Pose is a keypoint detection model developed by Deci AI.

About the model

Here is an overview of the

YOLO-NAS Pose

model:

Date of Release
Model Type Keypoint Detection
Architecture
Framework Used
Annotation Format
Stars on GitHub 4000+

YOLO-NAS Pose is a keypoint detection model developed by Deci AI.

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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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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

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Deploy YOLO-NAS Pose to production

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YOLO-NAS Pose Annotation Format

YOLO-NAS Pose

uses the

uses the

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 YOLO-NAS Pose

You can automatically label a dataset using

YOLO-NAS Pose

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

YOLO-NAS Pose

to train a computer vision model.

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