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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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@ -29,7 +29,7 @@ keywords: Ultralytics, YOLOv8, 目标检测, 图像分割, 机器学习, 深度
- **安装** `ultralytics` 并通过 pip 在几分钟内开始运行 &nbsp; [:material-clock-fast: 开始使用](https://docs.ultralytics.com/quickstart/){ .md-button }
- **预测** 使用YOLOv8预测新的图像和视频 &nbsp; [:octicons-image-16: 在图像上预测](https://docs.ultralytics.com/predict/){ .md-button }
- **训练** 在您自己的自定义数据集上训练新的YOLOv8模型 &nbsp; [:fontawesome-solid-brain: 训练模型](https://docs.ultralytics.com/train/){ .md-button }
- **训练** 在您自己的自定义数据集上训练新的YOLOv8模型 &nbsp; [:fontawesome-solid-brain: 训练模型](https://docs.ultralytics.com/modes/train/){ .md-button }
- **探索** YOLOv8的任务，如分割、分类、姿态和跟踪 &nbsp; [:material-magnify-expand: 探索任务](https://docs.ultralytics.com/tasks/){ .md-button }
<p align="center">
@ -40,7 +40,7 @@ keywords: Ultralytics, YOLOv8, 目标检测, 图像分割, 机器学习, 深度
allowfullscreen>
</iframe>
<br>
<strong>观看：</strong> 在Google Colab中如何训练您的自定义数据集上的YOLOv8模型。
<strong>观看：</strong> 在<a href="https://colab.research.google.com/github/ultralytics/ultralytics/blob/main/examples/tutorial.ipynb" target="_blank">Google Colab</a>中如何训练您的自定义数据集上的YOLOv8模型。
</p>
## YOLO：简史