Models

What is YOLOv5 Instance Segmentation?

YOLOv5 Instance Segmentation is a version of YOLOv5 that can be used for instance segmentation tasks.

About the model

Here is an overview of the

YOLOv5 Instance Segmentation

model:

Date of Release Sep 01, 2022
Model Type Instance Segmentation
Architecture CNN, YOLO
Framework Used PyTorch
Annotation Format
Stars on GitHub 33200+

YOLOv5 for Instance Segmentation

YOLOv5 was released by Glenn Jocher on June 9, 2020 for object detection. Recently, YOLOv5 added support for instance segmentation (September 2022) and classification (August 2022).

Instance Segmentation results for YOLOv5

Instance Segmentation with YOLOv5

Instance segmentation (also known as image segmentation) is the computer vision task of recognizing objects in images along with their associated shape. It's useful in cases where you need to measure the size of detected objects, cut them out of their background, or more accurately detect oblong rotated objects.

YOLOv5 instance segmentation

Find a free instance segmentation dataset to try YOLOv5 for instance segmentation.

If you have your own data, label your images for free using Roboflow Annotate.

Labeling and annotation for YOLOv5 Instance segmentation

YOLOv5 benefits

YOLOv5 is regarded as smaller and generally easier to use in production thanks to being implemented in Pytorch. Read more about YOLOv5 performance.

YOLOv5 performance
YOLOv5 Size

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

Explore this model on Roboflow

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YOLOv5 Instance Segmentation Annotation Format

YOLOv5 Instance Segmentation

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 YOLOv5 Instance Segmentation

You can automatically label a dataset using

YOLOv5 Instance Segmentation

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

YOLOv5 Instance Segmentation

to train a computer vision model.

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