ultralytics 8.0.141 create new SettingsManager (#3790)
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@ -46,10 +46,10 @@ To train a YOLOv8n model on the Global Wheat Head Dataset for 100 epochs with an
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```python
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from ultralytics import YOLO
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# Load a model
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model = YOLO('yolov8n.pt') # load a pretrained model (recommended for training)
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# Train the model
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model.train(data='GlobalWheat2020.yaml', epochs=100, imgsz=640)
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```
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@ -84,4 +84,4 @@ If you use the Global Wheat Head Dataset in your research or development work, p
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}
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```
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We would like to acknowledge the researchers and institutions that contributed to the creation and maintenance of the Global Wheat Head Dataset as a valuable resource for the plant phenotyping and crop management research community. For more information about the dataset and its creators, visit the [Global Wheat Head Dataset website](http://www.global-wheat.com/).
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We would like to acknowledge the researchers and institutions that contributed to the creation and maintenance of the Global Wheat Head Dataset as a valuable resource for the plant phenotyping and crop management research community. For more information about the dataset and its creators, visit the [Global Wheat Head Dataset website](http://www.global-wheat.com/).
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