How to off the augmentation function???

[LEEGILJUN]

Hello

I'd like to experiment with the augmentation function turned off.

Also, I want to experiment with the augmente function turned on and the mosaic function off.

This is because I want to know the performance difference between the use of the augmentation method and the mosaic in the data I use.

I know to control hyp in hyp.yaml. if I changed "mosaic: 1.0 # image mosaic (probability)" to "mosaic: 0.0 # image mosaic (probability)". it is turned off the mosaic function??????

or

like below photo, if i change this function augment=True -> augment=False, it is turned off the augmentation???

Thanks

[glenn-jocher]

@LEEGILJUN 👋 Hello! Thanks for asking about image augmentation. YOLOv5 🚀 applies online imagespace and colorspace augmentations in the trainloader (but not the testloader) to present a new and unique augmented Mosaic (original image + 3 random images) each time an image is loaded for training. Images are never presented twice in the same way.

The hyperparameters used to define these augmentations are in your hyperparameter file (default data/hyp.scratch.yaml) defined when training:

python train.py --hyp hyp.scratch.yaml

https://github.com/ultralytics/yolov5/blob/90b7895d652c3bd3d361b2d6e9aee900fd67f5f7/data/hyp.scratch.yaml#L1-L33

You can view the effect of your augmentation policy in your train_batch*.jpg images once training starts. These images will be in your train logging directory, typically yolov5/runs/train/exp:

train_batch0.jpg shows train batch 0 mosaics and labels:

Good luck and let us know if you have any other questions!

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