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49 lines
1.2 KiB
49 lines
1.2 KiB
[](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(
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"yolov8n.pt"
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) # 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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