英文:
YOLOv8 - What is the clean and correct way to specify augmentation parameter?
问题
正如标题所说，我在使用YOLOv8时如何设置数据增强的参数？我想使用Python SDK而不是CLI命令。
仓库的维护者多次提到了以下链接：
https://docs.ultralytics.com/modes/predict/#arguments
但我不明白这些参数应该存储在哪里？
此外，我找到了这个。
[来自此网站的评论部分](https://i.stack.imgur.com/4qWX2.png)
将设置与data.yaml文件分开会很好，但首要任务是找到一个可行的解决方案。
英文:
as the title says, how do I set parameters for augmentation while using YOLOv8? I want to use the Python SDK and not the CLI commands.
The mantainer of the repo refer several times to
https://docs.ultralytics.com/modes/predict/#arguments
but I don't understand where to store these parameters?
Also, I found this.
[Comment section from this site](https://i.stack.imgur.com/4qWX2.png)
It would be nice to seperate the settings from data.yaml, but a working solution is the priority
答案1
得分: 0
你可以直接将增强参数存储到训练函数中，像这样：
results = model.train(data='coco128.yaml', epochs=300, degrees=0.25, scale=0.3, perspective=0.0001)
增强参数的列表可以在这里找到：https://docs.ultralytics.com/usage/cfg/#augmentation
英文:
You can store the augmentation parameters directly to the train function like this:
results = model.train(data='coco128.yaml', epochs=300, degrees=0.25, scale=0.3, perspective=0.0001)
List of augmentation parameters: https://docs.ultralytics.com/usage/cfg/#augmentation
答案2
得分: 0
在YOLOv8中，可以在ultralytics/yolo/cfg/default.yaml中找到数据增强的配置。
你可以直接更改YAML文件，或者在model.train()中设置参数，就像上面提到的那样。
英文:
In YOLOv8, the augmentation configuration can be found at ultralytics/yolo/cfg/default.yaml.
You can change the YAML file directly or set the parameter in model.train() as mentioned above.
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