dev(narugo): prepare for the clip preprocessor (7697fc29) · Commits · git-mirror / Imgutils

.github/workflows/doc.yml

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Original line number	Diff line number	Diff line
		@@ -47,6 +47,7 @@ jobs:
		python -m pip install -r requirements-model.txt
		python -m pip install -r requirements-doc.txt
		python -m pip install -r requirements-torchvision.txt
		python -m pip install -r requirements-transformers.txt
		- name: Prepare dataset
		uses: nick-fields/retry@v2
		if: ${{ github.event_name == 'push' }}

+1 −0

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		@@ -101,6 +101,7 @@ jobs:
		run: \|
		pip install -r requirements-model.txt
		pip install -r requirements-torchvision.txt
		pip install -r requirements-transformers.txt
		- name: Test the basic environment
		shell: bash
		run: \|

+27 −0

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		@@ -19,6 +19,7 @@ import numpy as np
		from PIL import Image

		from .base import NotParseTarget
		from ..data import load_image

		# noinspection PyUnresolvedReferences
		_INT_TO_PILLOW = {
		@@ -651,6 +652,32 @@ def _parse_normalize(obj: PillowNormalize):
		}


		class PillowConvertRGB:
		def __init__(self, force_background: Optional[str] = 'white'):
		self.force_background = force_background

		def forward(self, pic):
		if not isinstance(pic, Image.Image):
		raise TypeError('pic should be PIL Image. Got {}'.format(type(pic)))
		return load_image(pic, mode='RGB', force_background=self.force_background)

		def __repr__(self):
		return f'{self.__class__.__name__}(force_background={self.force_background!r})'


		class PillowRescale:
		def __init__(self, rescale_factor: float = 1 / 255):
		self.rescale_factor = rescale_factor

		def __call__(self, array):
		if not isinstance(array, np.ndarray):
		raise TypeError('Input should be a numpy.ndarray')
		return array * self.rescale_factor

		def __repr__(self):
		return f'{self.__class__.__name__}(rescale_factor={self.rescale_factor!r})'


		class PillowCompose:
		"""
		Composes several transforms together into a single transform.

+22 −10

Original line number	Diff line number	Diff line
		@@ -13,6 +13,13 @@ from typing import Union

		from .base import NotParseTarget

		try:
		import torchvision
		except (ImportError, ModuleNotFoundError):
		_HAS_TORCHVISION = False
		else:
		_HAS_TORCHVISION = True


		def _check_torchvision():
		"""
		@@ -20,9 +27,7 @@ def _check_torchvision():

		:raises EnvironmentError: If torchvision is not installed
		"""
		try:
		import torchvision
		except (ImportError, ModuleNotFoundError):
		if not _HAS_TORCHVISION:
		raise EnvironmentError('No torchvision available.\n'
		'Please install it by `pip install dghs-imgutils[torchvision]`.')

		@@ -210,14 +215,10 @@ def _parse_center_crop(obj):
		}


		@_register_transform('maybe_to_tensor', safe=False)
		def _create_maybe_to_tensor():
		"""
		Create a MaybeToTensor transform that converts input to tensor if not already a tensor.

		:return: MaybeToTensor transform
		"""
		if _HAS_TORCHVISION:
		from torchvision.transforms import ToTensor


		class MaybeToTensor(ToTensor):
		def __init__(self) -> None:
		super().__init__()
		@@ -232,6 +233,17 @@ def _create_maybe_to_tensor():
		def __repr__(self) -> str:
		return f"{self.__class__.__name__}()"

		else:
		MaybeToTensor = None


		@_register_transform('maybe_to_tensor', safe=False)
		def _create_maybe_to_tensor():
		"""
		Create a MaybeToTensor transform that converts input to tensor if not already a tensor.

		:return: MaybeToTensor transform
		"""
		return MaybeToTensor()

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