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Deprecate AugmentationSequential wrapper #2396

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Deprecate AugmentationSequential wrapper #2396

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3 changes: 3 additions & 0 deletions pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -78,6 +78,9 @@ dependencies = [
"torchmetrics>=0.10",
# torchvision 0.14+ required for torchvision.models.swin_v2_b
"torchvision>=0.14",
# typing-extensions 4.5+ required for typing_extensions.deprecated
# can be removed once Python 3.13 is minimum supported version
"typing-extensions>=4.5",
]
dynamic = ["version"]

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1 change: 1 addition & 0 deletions requirements/min-reqs.old
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Expand Up @@ -20,6 +20,7 @@ timm==0.4.12
torch==1.13.0
torchmetrics==0.10.0
torchvision==0.14.0
typing-extensions==4.5.0

# datasets
h5py==3.6.0
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1 change: 1 addition & 0 deletions requirements/required.txt
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Expand Up @@ -20,3 +20,4 @@ timm==0.9.7
torch==2.5.1
torchmetrics==1.4.3
torchvision==0.20.1
typing-extensions==4.12.2
78 changes: 44 additions & 34 deletions tests/transforms/test_transforms.py
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Expand Up @@ -82,9 +82,10 @@ def test_augmentation_sequential_gray(batch_gray: dict[str, Tensor]) -> None:
'boxes': torch.tensor([[1.0, 0.0, 3.0, 2.0]], dtype=torch.float),
'labels': torch.tensor([[0, 1]]),
}
augs = transforms.AugmentationSequential(
K.RandomHorizontalFlip(p=1.0), data_keys=['image', 'mask', 'boxes']
)
with pytest.deprecated_call():
augs = transforms.AugmentationSequential(
K.RandomHorizontalFlip(p=1.0), data_keys=['image', 'mask', 'boxes']
)
output = augs(batch_gray)
assert_matching(output, expected)

Expand All @@ -105,9 +106,10 @@ def test_augmentation_sequential_rgb(batch_rgb: dict[str, Tensor]) -> None:
'boxes': torch.tensor([[1.0, 0.0, 3.0, 2.0]], dtype=torch.float),
'labels': torch.tensor([[0, 1]]),
}
augs = transforms.AugmentationSequential(
K.RandomHorizontalFlip(p=1.0), data_keys=['image', 'mask', 'boxes']
)
with pytest.deprecated_call():
augs = transforms.AugmentationSequential(
K.RandomHorizontalFlip(p=1.0), data_keys=['image', 'mask', 'boxes']
)
output = augs(batch_rgb)
assert_matching(output, expected)

Expand All @@ -132,9 +134,10 @@ def test_augmentation_sequential_multispectral(
'boxes': torch.tensor([[1.0, 0.0, 3.0, 2.0]], dtype=torch.float),
'labels': torch.tensor([[0, 1]]),
}
augs = transforms.AugmentationSequential(
K.RandomHorizontalFlip(p=1.0), data_keys=['image', 'mask', 'boxes']
)
with pytest.deprecated_call():
augs = transforms.AugmentationSequential(
K.RandomHorizontalFlip(p=1.0), data_keys=['image', 'mask', 'boxes']
)
output = augs(batch_multispectral)
assert_matching(output, expected)

Expand All @@ -159,9 +162,10 @@ def test_augmentation_sequential_image_only(
'boxes': torch.tensor([[0.0, 0.0, 2.0, 2.0]], dtype=torch.float),
'labels': torch.tensor([[0, 1]]),
}
augs = transforms.AugmentationSequential(
K.RandomHorizontalFlip(p=1.0), data_keys=['image']
)
with pytest.deprecated_call():
augs = transforms.AugmentationSequential(
K.RandomHorizontalFlip(p=1.0), data_keys=['image']
)
output = augs(batch_multispectral)
assert_matching(output, expected)

Expand Down Expand Up @@ -191,15 +195,16 @@ def test_sequential_transforms_augmentations(
'boxes': torch.tensor([[1.0, 0.0, 3.0, 2.0]], dtype=torch.float),
'labels': torch.tensor([[0, 1]]),
}
train_transforms = transforms.AugmentationSequential(
indices.AppendNBR(index_nir=0, index_swir=0),
indices.AppendNDBI(index_swir=0, index_nir=0),
indices.AppendNDSI(index_green=0, index_swir=0),
indices.AppendNDVI(index_red=0, index_nir=0),
indices.AppendNDWI(index_green=0, index_nir=0),
K.RandomHorizontalFlip(p=1.0),
data_keys=['image', 'mask', 'boxes'],
)
with pytest.deprecated_call():
train_transforms = transforms.AugmentationSequential(
indices.AppendNBR(index_nir=0, index_swir=0),
indices.AppendNDBI(index_swir=0, index_nir=0),
indices.AppendNDSI(index_green=0, index_swir=0),
indices.AppendNDVI(index_red=0, index_nir=0),
indices.AppendNDWI(index_green=0, index_nir=0),
K.RandomHorizontalFlip(p=1.0),
data_keys=['image', 'mask', 'boxes'],
)
output = train_transforms(batch_multispectral)
assert_matching(output, expected)

Expand All @@ -215,9 +220,12 @@ def test_extract_patches() -> None:
'image': torch.randn(size=(b, c, h, w)),
'mask': torch.randint(low=0, high=2, size=(b, h, w)),
}
train_transforms = transforms.AugmentationSequential(
_ExtractPatches(window_size=p), same_on_batch=True, data_keys=['image', 'mask']
)
with pytest.deprecated_call():
train_transforms = transforms.AugmentationSequential(
_ExtractPatches(window_size=p),
same_on_batch=True,
data_keys=['image', 'mask'],
)
output = train_transforms(batch)
assert batch['image'].shape == (b * num_patches, c, p, p)
assert batch['mask'].shape == (b * num_patches, p, p)
Expand All @@ -229,11 +237,12 @@ def test_extract_patches() -> None:
'image': torch.randn(size=(b, c, h, w)),
'mask': torch.randint(low=0, high=2, size=(b, h, w)),
}
train_transforms = transforms.AugmentationSequential(
_ExtractPatches(window_size=p, stride=s),
same_on_batch=True,
data_keys=['image', 'mask'],
)
with pytest.deprecated_call():
train_transforms = transforms.AugmentationSequential(
_ExtractPatches(window_size=p, stride=s),
same_on_batch=True,
data_keys=['image', 'mask'],
)
output = train_transforms(batch)
assert batch['image'].shape == (b * num_patches, c, p, p)
assert batch['mask'].shape == (b * num_patches, p, p)
Expand All @@ -245,11 +254,12 @@ def test_extract_patches() -> None:
'image': torch.randn(size=(b, c, h, w)),
'mask': torch.randint(low=0, high=2, size=(b, h, w)),
}
train_transforms = transforms.AugmentationSequential(
_ExtractPatches(window_size=p, stride=s, keepdim=False),
same_on_batch=True,
data_keys=['image', 'mask'],
)
with pytest.deprecated_call():
train_transforms = transforms.AugmentationSequential(
_ExtractPatches(window_size=p, stride=s, keepdim=False),
same_on_batch=True,
data_keys=['image', 'mask'],
)
output = train_transforms(batch)
for k, v in output.items():
print(k, v.shape, v.dtype)
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2 changes: 2 additions & 0 deletions torchgeo/transforms/transforms.py
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Expand Up @@ -13,9 +13,11 @@
from kornia.geometry.boxes import Boxes
from torch import Tensor
from torch.nn.modules import Module
from typing_extensions import deprecated


# TODO: contribute these to Kornia and delete this file
@deprecated('Use kornia.augmentation.AugmentationSequential instead')
class AugmentationSequential(Module):
"""Wrapper around kornia AugmentationSequential to handle input dicts.

Expand Down