YOLOv8 Classification

An image classification model built using YOLOv8.

Overview

YOLOv8 is a state-of-the-art object detection and image segmentation model created by Ultralytics, the developers of YOLOv5. YOLOv8 has native support for image classification tasks, too. YOLOv8, launched on January 10, 2023, features:

A new backbone network;
A design that makes it easy to compare model performance with older models in the YOLO family;
A new loss function and;
A new anchor-free detection head.

Performance

Use This Model

You can run fine-tuned YOLOv8 classification models with Inference.

First, install Inference:‍


pip install inference

Retrieve your Roboflow API key and save it in an environment variable called ROBOFLOW_API_KEY:


export ROBOFLOW_API_KEY="your-api-key"

To use your model, run the following code:


import inference
model = inference.load_roboflow_model("model-name/version")
results = model.infer(image="YOUR_IMAGE.jpg")

Above, replace:

YOUR_IMAGE.jpg with the path to your image.
model_id/version with the YOLOv8 model ID and version you want to use. Learn how to retrieve your model and version ID

Label Data Automatically with YOLOv8 Classification

You can automatically label a dataset using YOLOv8 Classification 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 YOLOv8 Classification to train a computer vision model.

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