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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
38 lines
1.2 KiB
Markdown
38 lines
1.2 KiB
Markdown
[](https://github.com/ultralytics/ultralytics/actions/workflows/ci.yaml)
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### Install
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```bash
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pip install ultralytics
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```
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Development
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```
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git clone https://github.com/ultralytics/ultralytics
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cd ultralytics
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pip install -e .
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```
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## Usage
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### 1. CLI
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To simply use the latest Ultralytics YOLO models
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```bash
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yolo task=detect mode=train model=yolov8n.yaml args=...
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classify predict yolov8n-cls.yaml args=...
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segment val yolov8n-seg.yaml args=...
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export yolov8n.pt format=onnx
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```
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### 2. Python SDK
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To use pythonic interface of Ultralytics YOLO model
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```python
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from ultralytics import YOLO
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model = YOLO.new('yolov8n.yaml') # create a new model from scratch
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model = YOLO.load('yolov8n.pt') # load a pretrained model (recommended for best training results)
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results = model.train(data='coco128.yaml', epochs=100, imgsz=640, ...)
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results = model.val()
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results = model.predict(source='bus.jpg')
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success = model.export(format='onnx')
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```
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If you're looking to modify YOLO for R&D or to build on top of it, refer to [Using Trainer]() Guide on our docs.
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