Commit a9e66b3b authored by narugo1992's avatar narugo1992
Browse files

dev(narugo): save the current refactor

parent 58f88bb6

imgutils/preprocess/transformers/__init__.py

+1 −0
Original line number Diff line number Diff line
@@ -11,5 +11,6 @@ from .bit import create_bit_transforms, create_transforms_from_bit_processor 
from .blip import create_blip_transforms, create_transforms_from_blip_processor

from .clip import create_clip_transforms, create_transforms_from_clip_processor

from .convnext import create_convnext_transforms, create_transforms_from_convnext_processor

from .mobilenetv2 import create_mobilenetv2_transforms, create_transforms_from_mobilenetv2_processor

from .siglip import create_siglip_transforms, create_transforms_from_siglip_processor

from .vit import create_vit_transforms, create_transforms_from_vit_processor

imgutils/preprocess/transformers/base.py

+0 −27
Original line number Diff line number Diff line
@@ -21,10 +21,6 @@ Usage: 
    )

"""



from PIL import Image



from ..pillow import PillowResize



try:

    import transformers

except (ImportError, ModuleNotFoundError):
@@ -137,26 +133,3 @@ def create_transforms_from_transformers(processor): 
            pass

    else:

        raise NotProcessorTypeError(f'Unknown transformers processor - {processor!r}.')
 




def _create_resize(size, resample=Image.BICUBIC):

    """

    Create a PillowResize transform based on the given size configuration.



    :param size: Dictionary containing size configuration, either with 'shortest_edge'

                or both 'height' and 'width' keys

    :type size: dict

    :param resample: PIL resampling filter to use for resizing, defaults to Image.BICUBIC

    :type resample: int



    :return: A PillowResize transform configured according to the size parameters

    :rtype: PillowResize



    :raises ValueError: If the size configuration is not recognized

    """

    if "shortest_edge" in size:

        return PillowResize(size["shortest_edge"], interpolation=resample)

    elif "height" in size and "width" in size:

        return PillowResize((size["height"], size["width"]), interpolation=resample)

    else:

        raise ValueError(f'Unknown size configuration - {size!r}.')  # pragma: no cover

imgutils/preprocess/transformers/bit.py

+2 −1
Original line number Diff line number Diff line
@@ -8,7 +8,8 @@ library integration. 
from PIL import Image



from .base import OPENAI_CLIP_MEAN, OPENAI_CLIP_STD, _DEFAULT, register_creators_for_transformers, _check_transformers, \

    NotProcessorTypeError, _create_resize

    NotProcessorTypeError

from .size import _create_resize

from ..pillow import PillowConvertRGB, PillowCenterCrop, PillowToTensor, PillowNormalize, PillowCompose, \

    PillowRescale

imgutils/preprocess/transformers/blip.py

+2 −1
Original line number Diff line number Diff line
@@ -9,7 +9,8 @@ all implemented using Pillow-based operations. 
from PIL import Image



from .base import OPENAI_CLIP_STD, OPENAI_CLIP_MEAN, _DEFAULT, _check_transformers, NotProcessorTypeError, \

    register_creators_for_transformers, _create_resize

    register_creators_for_transformers

from .size import _create_resize

from ..pillow import PillowConvertRGB, PillowRescale, PillowNormalize, PillowToTensor, PillowCompose



_DEFAULT_SIZE = {"height": 384, "width": 384}

imgutils/preprocess/transformers/clip.py

+2 −1
Original line number Diff line number Diff line
@@ -8,7 +8,8 @@ The module integrates with the Hugging Face transformers library and provides co 
from PIL import Image



from .base import _check_transformers, NotProcessorTypeError, register_creators_for_transformers, OPENAI_CLIP_MEAN, \

    OPENAI_CLIP_STD, _DEFAULT, _create_resize

    OPENAI_CLIP_STD, _DEFAULT

from .size import _create_resize

from ..pillow import PillowCenterCrop, PillowToTensor, PillowNormalize, PillowCompose, PillowRescale, \

    PillowConvertRGB