YOLOv7 was created by WongKinYiu and AlexeyAB, the creators of YOLOv4 Darknet (and the official canonical maintainers of the YOLO lineage according to pjreddie, the original inventor and maintainer of the YOLO architecture).

![YOLOv7 Instance Segmentation example](https://github.com/WongKinYiu/yolov7/blob/main)

YOLOv7 for instance segmentation (YOLOR + YOLOv5 + YOLACT)

Model: YOLOv7-seg
Test Size: 640
APbox: 51.4%
AP50box: 69.4%
AP75box: 55.8%
APmask: 41.5%
AP50mask: 65.5%
AP75mask: 43.7%

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

Explore this model on Roboflow

How to Train Detectron2 for Custom Instance Segmentation

How to train Detectron2 to segment your custom objects from any image by providing our model with example training data.

How to Train Detectron2 for Custom Instance Segmentation

How to train Detectron2 to segment your custom objects from any image by providing our model with example training data.

Launch: Instance Segmentation Project Training and Inference

Launch: Instance Segmentation Project Training and Inference

YOLOv7 - A breakdown of how it works

In this post, we break down the internals of how YOLOv7 works and the novel research involved in its construction.

What is Instance Segmentation? A Guide.

Instance segmentation allows your computer vision model to know the specific outline of an object in an image, unlocking new use cases.

Deploy YOLOv7 Instance Segmentation to production

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

Deploy YOLOv7 Instance Segmentation Models to Azure Virtual Machines

YOLOv7 Instance Segmentation Annotation Format

YOLOv7 Instance Segmentation

uses the

YOLOv7 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.
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Convert data between formats

Label data automatically with YOLOv7 Instance Segmentation

You can automatically label a dataset using

YOLOv7 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

YOLOv7 Instance Segmentation

to train a computer vision model.

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