yolonnx 0.3.0

This package lets you run your YOLOv8 detection and classification models using ONNXRuntime.

You Only Look ONNX

This repository is a light weight library to ease the use of ONNX models exported by the Ultralytics YOLOv8 framework.

Example Detector Usage

from pathlib import Path

from onnxruntime import InferenceSession
from PIL import Image

from yolonnx.services import Detector
from yolonnx.to_tensor_strategies import PillowToTensorContainStrategy

model = Path("path/to/file.onnx")
session = InferenceSession(
    model.as_posix(),
    providers=[
        "CUDAExecutionProvider",
        "CPUExecutionProvider",
    ],
)

# For backward compatibility reasons the Yolo8ModelOutputParser is used by default
predictor = Detector(session, PillowToTensorContainStrategy(), ModelOutputParser=Yolo26ModelOutputParser())
img = Image.open("path/to/image.jpg")
print(predictor.run(img))

Example Classifier Usage

from pathlib import Path

from onnxruntime import InferenceSession
from PIL import Image

from yolonnx.services import Classifier
from yolonnx.to_tensor_strategies import PillowToTensorContainStrategy

model = Path("path/to/file.onnx")
session = InferenceSession(
    model.as_posix(),
    providers=[
        "CUDAExecutionProvider",
        "CPUExecutionProvider",
    ],
)

predictor = Classifier(session, PillowToTensorContainStrategy())
img = Image.open("path/to/image.jpg")
print(predictor.run(img))