yolonnx

Name	yolonnx JSON
Version	0.2.0 JSON
	download
home_page	https://www.cs.aau.dk/
Summary	This package lets you run your YOLOv8 detection and classification models using ONNXRuntime.
upload_time	2024-09-06 12:23:14
maintainer	None
docs_url	None
author	None
requires_python	<3.13,>=3.10
license	MIT
keywords	onnx yolov8 onnxruntime vision
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # 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
```python
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",
    ],
)

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

## Example Classifier Usage
```python
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))

```
            

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