Use the widget below to experiment with YOLOv8 Classification. You can detect COCO classes such as people, vehicles, animals, household items.
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:
there are many YOLOv8 classication models released. These include:
• YOLOv8n-cls (Nano): Approximately 3.2 million parameters
• YOLOv8s-cls (Small): Approximately 11.2 million parameters
• YOLOv8m-cls (Medium): Approximately 25.9 million parameters
• YOLOv8l-cls (Large): Approximately 43.7 million parameters
• YOLOv8x-cls (Extra Large): Approximately 68.2 million parameters
YOLOv8 Classification
is licensed under a
AGPL-3.0
license.
You can use Roboflow Inference to deploy a
YOLOv8 Classification
API on your hardware. You can deploy the model on CPU (i.e. Raspberry Pi, AI PCs) and GPU devices (i.e. NVIDIA Jetson, NVIDIA T4).
Below are instructions on how to deploy your own model API.
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