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51 lines
1.6 KiB
51 lines
1.6 KiB
## Installation |
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!!! note "Latest Stable Release" |
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``` |
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pip install ultralytics |
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``` |
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??? tip "Development and Contributing" |
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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 '.[dev]' |
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``` |
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See contributing section to know more about contributing to the project |
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## CLI |
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The command line YOLO interface let's you simply train, validate or infer models on various tasks and versions. |
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CLI requires no customization or code. You can simply run all tasks from the terminal |
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!!! tip |
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=== "Syntax" |
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```bash |
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yolo task=detect mode=train model=s.yaml epochs=1 ... |
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... ... ... |
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segment infer s-cls.pt |
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classify val s-seg.pt |
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``` |
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=== "Example training" |
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```bash |
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yolo task=detect mode=train model=s.yaml |
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``` |
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TODO: add terminal screen/gif |
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=== "Example training DDP" |
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```bash |
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yolo task=detect mode=train model=s.yaml device=\'0,1,2,3\' |
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``` |
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[CLI Guide](#){ .md-button .md-button--primary} |
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## Python API |
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Ultralytics YOLO comes with pythonic Model and Trainer interface. |
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!!! tip |
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```python |
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import ultralytics |
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from ultralytics import YOLO |
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model = YOLO() |
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model.new("s-seg.yaml") # automatically detects task type |
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model.load("s-seg.pt") # load checkpoint |
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model.train(data="coco128-segments", epochs=1, lr0=0.01, ...) |
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model.train(data="coco128-segments", epochs=1, lr0=0.01, device="0,1,2,3") # DDP mode |
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``` |
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[API Guide](#){ .md-button .md-button--primary}
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