Awesome
GridMixup
A GridMixup augmentation, inspired by GridMask and CutMix
Easy install
pip install git+https://github.com/IlyaDobrynin/GridMixup.git
Overview
This simple augmentation is inspired by the GridMask and CutMix augmentations. The combination of this two augmentations forms proposed method.
Example
To run simple examples notebooks, you should install requirements:
pip install -r requirements.txt
Simple examples are here: demo and pipeline demo
TlDr:
from gridmix import GridMixupLoss
gridmix_cls = GridMixupLoss(
alpha=(0.4, 0.7),
hole_aspect_ratio=1.,
crop_area_ratio=(0.5, 1),
crop_aspect_ratio=(0.5, 2),
n_holes_x=(2, 6)
)
images, targets = batch['images'], batch['targets']
images_mixed, targets_mixed = gridmix_cls.get_sample(images=images, targets=targets)
preds = model(images_mixed)
loss = criterion(preds, targets_mixed)
Before<br> <br>
After<br>
GridMixup loss defined as:
lam * CrossEntropyLoss(preds, trues1) + (1 - lam) * CrossEntropyLoss(preds, trues2)
where:
lam
- the area of the main image(1 - lam)
- area of the secondary image
Parameters
GridMixupLoss takes follow arguments:
alpha
- parameter define area of the main image in mixed image. Could befloat
orTuple[float, float]
.- if
float
: lambda parameter gets from the beta-dictribution np.random.beta(alpha, alpha); - if
Tuple[float, float]
: lambda parameter gets from the uniform distribution np.random.uniform(alpha[0], alpha[1]).
- if
n_holes_x
- number of holes in crop by X axis.hole_aspect_ratio
- aspect ratio of holes.crop_area_ratio
- parameter define area of the secondary image on a mixed image.crop_aspect_ratio
- aspect ratio of crop.