configs/experiment/projects/bridging/dinosaur/_preprocessing_coco_imagenet_feature_recon.yaml

# @package dataset

# Override parts of preprocessing, imagenet model used different normalization.
train_transforms:
  03b_preprocessing:
    transforms:
      image:
        _target_: torchvision.transforms.Compose
        transforms:
          - _target_: torchvision.transforms.ToTensor
          - _target_: torchvision.transforms.Resize
            size: 224
            interpolation: ${torchvision_interpolation_mode:BICUBIC}
          - "${lambda_fn:'lambda image: image.clamp(0.0, 1.0)'}"  # Bicubic interpolation can get out of range
          - _target_: torchvision.transforms.RandomCrop
            size: 224
          - _target_: torchvision.transforms.RandomHorizontalFlip
          - _target_: torchvision.transforms.Normalize
            mean: [0.5, 0.5, 0.5]
            std: [0.5, 0.5, 0.5]
eval_transforms:
  03b_preprocessing:
    transforms:
      image:
        _target_: torchvision.transforms.Compose
        transforms:
          - _target_: torchvision.transforms.ToTensor
          - _target_: torchvision.transforms.Resize
            size: 224
            interpolation: ${torchvision_interpolation_mode:BICUBIC}
          - "${lambda_fn:'lambda image: image.clamp(0.0, 1.0)'}"  # Bicubic interpolation can get out of range
          - _target_: torchvision.transforms.CenterCrop
            size: 224
          - _target_: torchvision.transforms.Normalize
            mean: [0.5, 0.5, 0.5]
            std: [0.5, 0.5, 0.5]