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Use torchvision in a different way to avoid type errors #2140

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Merged
merged 3 commits into from
Jun 27, 2024
Merged

Use torchvision in a different way to avoid type errors #2140

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a1b7406
Use torchvision in a different way to avoid type errors
adamtheturtle Jun 27, 2024
1fa22b7
Use new style in a new place
adamtheturtle Jun 27, 2024
cdeb0b3
Add back a type: ignore
adamtheturtle Jun 27, 2024
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8 changes: 5 additions & 3 deletions src/mock_vws/image_matchers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
from torchmetrics.image import (
StructuralSimilarityIndexMeasure,
)
from torchvision.transforms import functional # type: ignore[import-untyped]
from torchvision import transforms # type: ignore[import-untyped]


@runtime_checkable
Expand Down Expand Up @@ -74,8 +74,10 @@ def __call__(
first_image = first_image.resize(size=target_size)
second_image = second_image.resize(size=target_size)

first_image_tensor = functional.to_tensor(pic=first_image) # pyright: ignore[reportUnknownMemberType]
second_image_tensor = functional.to_tensor(pic=second_image) # pyright: ignore[reportUnknownMemberType]
transform = transforms.ToTensor()

first_image_tensor = transform(pic=first_image)
second_image_tensor = transform(pic=second_image)

first_image_tensor_batch_dimension = first_image_tensor.unsqueeze(0)
second_image_tensor_batch_dimension = second_image_tensor.unsqueeze(0)
Expand Down
5 changes: 3 additions & 2 deletions src/mock_vws/target_raters.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@

import piq # type: ignore[import-untyped]
from PIL import Image
from torchvision.transforms import functional # type: ignore[import-untyped]
from torchvision import transforms # type: ignore[import-untyped]


@functools.cache
Expand All @@ -25,7 +25,8 @@ def _get_brisque_target_tracking_rating(image_content: bytes) -> int:
"""
image_file = io.BytesIO(initial_bytes=image_content)
image = Image.open(fp=image_file)
image_tensor = functional.to_tensor(pic=image) * 255 # pyright: ignore[reportUnknownMemberType]
transform = transforms.ToTensor()
image_tensor = transform(pic=image)
image_tensor = image_tensor.unsqueeze(0)
try:
brisque_score = piq.brisque(x=image_tensor, data_range=255)
Expand Down
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