configs/evaluation/slate/_preprocessing_coco.yaml
# @package _global_
dataset:
eval_transforms:
03a_preprocessing:
_target_: ocl.transforms.Map
transform:
_target_: torchvision.transforms.Compose
transforms:
- _target_: ocl.preprocessing.InstanceMasksToDenseMasks
- _target_: ocl.preprocessing.AddSegmentationMaskFromInstanceMask
- _target_: ocl.preprocessing.AddEmptyMasks
mask_keys:
- instance_mask
- segmentation_mask
# Drop instance_category again as some images do not contain it
- _target_: ocl.preprocessing.DropEntries
keys:
- instance_category
fields:
- image
- instance_mask
- instance_category
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: 128
interpolation: ${torchvision_interpolation_mode:BILINEAR}
- _target_: torchvision.transforms.CenterCrop
size: 128
- _target_: torchvision.transforms.Normalize
mean: [0.5, 0.5, 0.5]
std: [0.5, 0.5, 0.5]
instance_mask:
_target_: torchvision.transforms.Compose
transforms:
- _target_: ocl.preprocessing.DenseMaskToTensor
- _target_: ocl.preprocessing.ResizeNearestExact
size: 128
- _target_: torchvision.transforms.CenterCrop
size: 128
segmentation_mask:
_target_: torchvision.transforms.Compose
transforms:
- _target_: ocl.preprocessing.DenseMaskToTensor
- _target_: ocl.preprocessing.ResizeNearestExact
size: 128
- _target_: torchvision.transforms.CenterCrop
size: 128
batch_transform: false
train_transforms:
03b_preprocessing:
_target_: ocl.transforms.SimpleTransform
transforms:
image:
_target_: torchvision.transforms.Compose
transforms:
- _target_: torchvision.transforms.ToTensor
- _target_: torchvision.transforms.Resize
size: 128
interpolation: ${torchvision_interpolation_mode:BILINEAR}
- _target_: torchvision.transforms.CenterCrop
size: 128
- _target_: torchvision.transforms.RandomHorizontalFlip
- _target_: torchvision.transforms.Normalize
mean: [0.5, 0.5, 0.5]
std: [0.5, 0.5, 0.5]
batch_transform: false