configs/evaluation/projects/bridging/_preprocessing_coco_thingsandstuff.yaml

# @package _global_
# Preprocessing for evaluating semantic segmentation on COCO-Stuff-164k 172 thingsandstuff classes.
#
# Segmentation mask is resized to 320 pixels shorter side and center cropped to 320x320.
dataset:
  eval_transforms:
    03a_preprocessing:
      _target_: ocl.transforms.Map
      transform:
        _target_: torchvision.transforms.Compose
        transforms:
          - _target_: ocl.preprocessing.ConvertCocoStuff164kMasks
            output_key: segmentation_mask
            stuffthings_key: stuffthings_mask
            ignore_key: ignore_mask
          - _target_: ocl.preprocessing.DropEntries
            keys:
              - stuffthings_mask

      fields:
        - stuffthings_mask
      batch_transform: false
    03b_preprocessing:
      _target_: ocl.transforms.SimpleTransform
      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)'}"
            - _target_: torchvision.transforms.CenterCrop
              size: 224
            - _target_: torchvision.transforms.Normalize
              mean: [0.485, 0.456, 0.406]
              std: [0.229, 0.224, 0.225]
        segmentation_mask:
          _target_: torchvision.transforms.Compose
          transforms:
            - _target_: ocl.preprocessing.DenseMaskToTensor
            - _target_: ocl.preprocessing.ResizeNearestExact
              size: 320
            - _target_: torchvision.transforms.CenterCrop
              size: 320
        ignore_mask:
          _target_: torchvision.transforms.Compose
          transforms:
            - _target_: ocl.preprocessing.DenseMaskToTensor
            - _target_: ocl.preprocessing.ResizeNearestExact
              size: 320
            - _target_: torchvision.transforms.CenterCrop
              size: 320
      batch_transform: false