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_target_: data.augmentation.ImageAugmentation
names: "standard_augmentation,geometric_augmentation,clip_transform"

# always apply clip_transform at the end
clip_transform:
  _target_: torchvision.transforms.Compose
  transforms:
    - _target_: torchvision.transforms.Resize
      size: 224
      interpolation: 3
      antialias: true
    - _target_: torchvision.transforms.CenterCrop
      size: 224
    - _target_: torchvision.transforms.ToTensor
    - _target_: torchvision.transforms.Normalize
      mean: [0.48145466, 0.4578275, 0.40821073]
      std: [0.26862954, 0.26130258, 0.27577711]

standard_augmentation:
  _target_: data.augmentation.StandardAugmentation
  # by default, we all augmentation methods
  names: "brightness,contrast,sharpness,color,blur,gaussian_noise"

  # random PIL brigtness
  brightness:
    _target_: data.augmentation.PillowBrightness
    p: 0.2
    factor_interval: [0.5, 1.5]

  # random PIL contrast
  contrast:
    _target_: data.augmentation.PillowContrast
    p: 0.2
    factor_interval: [0.3, 3]

  # random PIL sharpness
  sharpness:
    _target_: data.augmentation.PillowSharpness
    p: 0.2
    factor_interval: [0.5, 30.0]

  # random PIL color
  color:
    _target_: data.augmentation.PillowColor
    p: 0.2
    factor_interval: [0.0, 2.0]

  # random PIL blur
  blur:
    _target_: data.augmentation.PillowBlur
    p: 0.2
    factor_interval: [1, 2]

  # random numpy gaussian noise
  gaussian_noise:
    _target_: data.augmentation.NumpyGaussianNoise
    p: 0.2
    factor_interval: [0.1, 0.04]

geometric_augmentation:
  _target_: data.augmentation.GeometricAugmentation
  # by default, we all augmentation methods
  names: "random_rotation,random_resized_crop,random_horizontal_flip"

  # random rotation
  random_rotation:
    _target_: torchvision.transforms.RandomRotation
    degrees: [-15, 15]

  # random crop
  random_resized_crop:
    _target_: torchvision.transforms.RandomResizedCrop
    scale: [0.5, 1.0]
    ratio: [0.9, 1.1]
    size: 224

  # random horizontal flip
  random_horizontal_flip:
    _target_: torchvision.transforms.RandomHorizontalFlip
    p: 0.5

  # random vertical flip
  random_vertical_flip:
    _target_: torchvision.transforms.RandomVerticalFlip
    p: 0.5