Commit 062664e7 authored by narugo1992's avatar narugo1992
Browse files

dev(narugo): unify the _create_resize function

parent 6a947642

imgutils/preprocess/transformers/base.py

+12 −0
Original line number Diff line number Diff line
@@ -6,6 +6,9 @@ particularly for image processing tasks. It includes constants for standard imag 
normalization values and utilities for creating image transforms from transformers

processors.

"""

from PIL import Image



from ..pillow import PillowResize



try:

    import transformers
@@ -111,3 +114,12 @@ def create_transforms_from_transformers(processor): 
            pass

    else:

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





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

    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

+3 −8
Original line number Diff line number Diff line
@@ -8,8 +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

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

    NotProcessorTypeError, _create_resize

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

    PillowRescale



_DEFAULT_SIZE = {"shortest_edge": 224}
@@ -76,12 +76,7 @@ def create_bit_transforms( 


    # Resize

    if do_resize:

        if "shortest_edge" in size:

            transform_list.append(PillowResize(size["shortest_edge"], interpolation=resample))

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

            transform_list.append(PillowResize((size["height"], size["width"]), interpolation=resample))

        else:

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

        transform_list.append(_create_resize(size, resample=resample))



    # Center crop

    if do_center_crop:

imgutils/preprocess/transformers/blip.py

+3 −3
Original line number Diff line number Diff line
@@ -9,8 +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

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

    register_creators_for_transformers, _create_resize

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



_DEFAULT_SIZE = {"height": 384, "width": 384}
@@ -67,7 +67,7 @@ def create_blip_transforms( 


    # Resize if needed

    if do_resize:

        transform_list.append(PillowResize((size["height"], size["width"]), interpolation=resample))

        transform_list.append(_create_resize(size, resample=resample))



    # Convert PIL to tensor (which automatically scales to [0,1])

    transform_list.append(PillowToTensor())

imgutils/preprocess/transformers/clip.py

+3 −6
Original line number Diff line number Diff line
@@ -8,8 +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

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

    OPENAI_CLIP_STD, _DEFAULT, _create_resize

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

    PillowConvertRGB



_DEFAULT_SIZE = {"shortest_edge": 224}
@@ -69,10 +69,7 @@ def create_clip_transforms( 
        transform_list.append(PillowConvertRGB())



    if do_resize:

        if "shortest_edge" in size:

            transform_list.append(PillowResize(size["shortest_edge"], interpolation=resample))

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

            transform_list.append(PillowResize((size["height"], size["width"]), interpolation=resample))

        transform_list.append(_create_resize(size, resample=resample))



    if do_center_crop:

        transform_list.append(PillowCenterCrop((crop_size["height"], crop_size["width"])))

imgutils/preprocess/transformers/siglip.py

+3 −3
Original line number Diff line number Diff line
@@ -7,8 +7,8 @@ resizing, rescaling, normalization, and RGB conversion. 
from PIL import Image



from .base import IMAGENET_STANDARD_MEAN, IMAGENET_STANDARD_STD, _DEFAULT, _check_transformers, NotProcessorTypeError, \

    register_creators_for_transformers

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

    register_creators_for_transformers, _create_resize

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



_DEFAULT_SIZE = {"height": 224, "width": 224}
@@ -70,7 +70,7 @@ def create_siglip_transforms( 


    # Resize

    if do_resize:

        transforms_list.append(PillowResize((size["height"], size["width"]), interpolation=resample))

        transforms_list.append(_create_resize(size, resample=resample))



    # Convert to tensor (implicitly rescales to 0-1)

    transforms_list.append(PillowToTensor())