ultralytics

(★ 60,836)

Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking

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# Installation Guide

python
Prerequisites

Setup Steps

pip install ultralytics

Install the ultralytics package via Python package manager.

yolo predict model=yolo26n.pt source='https://ultralytics.com/images/bus.jpg'

Run object detection inference using a pretrained model.

Key Commands

pip install ultralytics

Install ultralytics and required dependencies.

yolo predict model=yolo26n.pt source='https://ultralytics.com/images/bus.jpg'

Perform prediction on images or videos using YOLO CLI.

To utilize GPU acceleration, make sure to install a CUDA-supported version of PyTorch.

# Use via CDN

jsDelivr

jsDelivr serves any public GitHub repository as a CDN with zero setup. Pick a version and a file to get a ready-to-paste link and snippet.

Link
Example

Command Glossary

Commands referenced in this DOCs, explained below.

🔍

pip install

View Details ▼

Install Python packages.

pip install {{package1 package2 ...}}

Install one or more packages:

pip install {{package1 package2 ...}} {{[-U|--upgrade]}}

Upgrade all specified packages to the latest version, installing any that are not already present:

pip install {{package}}=={{version}}

Install a specific version of a package:

🔍

yolo

View Details ▼

Train, validate, or infer models on various tasks and versions.

yolo task=init

Create a copy of the default configuration in your current working directory:

yolo task={{detect|segment|classify}} mode=train cfg={{path/to/config.yaml}}

Train the object detection, instance segment, or classification model with the specified configuration file:

// repository documentation