"""
-Transformers Integration Module
-
-This module provides functionality for integrating with the transformers library,
-particularly for image processing tasks. It includes constants for standard image
-normalization values and utilities for creating image transforms from transformers
-processors.
+Transformers Integration Module for Image Processing
+
+This module provides functionality for integrating with the Hugging Face transformers library,
+particularly focused on image processing tasks. It includes standard image normalization
+constants and utilities for creating image transforms from transformers processors.
+
+Usage:
+ >>> from transformers import AutoImageProcessor
+ >>> from imgutils.preprocess.transformers import create_transforms_from_transformers
+ >>>
+ >>> processor = AutoImageProcessor.from_pretrained("openai/clip-vit-base-patch32")
+ >>> transforms = create_transforms_from_transformers(processor)
+ >>> transforms
+ PillowCompose(
+ PillowConvertRGB(force_background='white')
+ PillowResize(size=224, interpolation=bicubic, max_size=None, antialias=True)
+ PillowCenterCrop(size=(224, 224))
+ PillowToTensor()
+ PillowNormalize(mean=[0.48145467 0.4578275 0.40821072], std=[0.26862955 0.2613026 0.2757771 ])
+ )
"""
+from PIL import Image
+
+from ..pillow import PillowResize
+
try:
import transformers
except (ImportError, ModuleNotFoundError):
@@ -121,9 +139,9 @@
def _check_transformers():
"""
- Check if transformers library is available.
+ Check if the transformers library is available in the current environment.
- :raises EnvironmentError: If transformers is not installed
+ :raises EnvironmentError: If transformers is not installed, with instructions for installation
"""
if not _HAS_TRANSFORMERS:
raise EnvironmentError('No torchvision available.\n'
@@ -143,10 +161,13 @@
[docs]class NotProcessorTypeError(TypeError):
"""
-
Exception raised when a processor type is not recognized or supported.
+
Exception raised when an unsupported processor type is encountered.
+
+
This custom exception is used when the system cannot create transforms
+
from a given transformers processor, either because the processor type
+
is not recognized or is not supported by any registered transform creators.
-
This error occurs when attempting to create transforms from an unsupported
-
or unknown transformers processor type.
+
:inherits: TypeError
"""
pass
@@ -156,21 +177,23 @@
diff --git a/dev/transformers/_modules/imgutils/preprocess/transformers/bit.html b/dev/transformers/_modules/imgutils/preprocess/transformers/bit.html
index ee686df8051f170fc89520d17b60b6a964f96daa..63d87df490b044b2bcb81b3c7e08c6f21d40cc2e 100644
--- a/dev/transformers/_modules/imgutils/preprocess/transformers/bit.html
+++ b/dev/transformers/_modules/imgutils/preprocess/transformers/bit.html
@@ -112,8 +112,8 @@
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}
@@ -180,12 +180,7 @@
# 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:
diff --git a/dev/transformers/_modules/imgutils/preprocess/transformers/blip.html b/dev/transformers/_modules/imgutils/preprocess/transformers/blip.html
index 2e99306bbcda6043c5bcc0c91da116a0426fa876..55a43b14ab68ca556b3e4832830c90a66bdbb8d0 100644
--- a/dev/transformers/_modules/imgutils/preprocess/transformers/blip.html
+++ b/dev/transformers/_modules/imgutils/preprocess/transformers/blip.html
@@ -113,8 +113,8 @@
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}
@@ -171,7 +171,7 @@
# 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())
diff --git a/dev/transformers/_modules/imgutils/preprocess/transformers/clip.html b/dev/transformers/_modules/imgutils/preprocess/transformers/clip.html
index 9cf180089166f433cb7f4ef73da94e7b423cdb46..56c4b3c8faafe945e5157d43b27d8fb023ae9ef2 100644
--- a/dev/transformers/_modules/imgutils/preprocess/transformers/clip.html
+++ b/dev/transformers/_modules/imgutils/preprocess/transformers/clip.html
@@ -112,8 +112,8 @@
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}
@@ -173,10 +173,7 @@
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"])))
diff --git a/dev/transformers/_modules/imgutils/preprocess/transformers/siglip.html b/dev/transformers/_modules/imgutils/preprocess/transformers/siglip.html
index 17e48c18f81c6904c7abc76cccc92c243ae55fb2..32a3e742aceb6f42499f5d85eaa14a3921d2620b 100644
--- a/dev/transformers/_modules/imgutils/preprocess/transformers/siglip.html
+++ b/dev/transformers/_modules/imgutils/preprocess/transformers/siglip.html
@@ -111,8 +111,8 @@
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}
@@ -174,7 +174,7 @@
# 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())
diff --git a/dev/transformers/_modules/imgutils/preprocess/transformers/vit.html b/dev/transformers/_modules/imgutils/preprocess/transformers/vit.html
index 752f81b19734de6943da90f0dcc146735d0e107d..cfc5762965ba2cb9013d8e2e4e6edc54eab08254 100644
--- a/dev/transformers/_modules/imgutils/preprocess/transformers/vit.html
+++ b/dev/transformers/_modules/imgutils/preprocess/transformers/vit.html
@@ -114,8 +114,8 @@
from PIL import Image
from .base import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, _DEFAULT, register_creators_for_transformers, \
- _check_transformers, NotProcessorTypeError
-from ..pillow import PillowRescale, PillowResize, PillowToTensor, PillowNormalize, PillowCompose
+ _check_transformers, NotProcessorTypeError, _create_resize
+from ..pillow import PillowRescale, PillowToTensor, PillowNormalize, PillowCompose
_DEFAULT_SIZE = {"height": 224, "width": 224}
@@ -166,12 +166,7 @@
# Add resize transform if enabled
if do_resize:
- transform_list.append(
- PillowResize(
- (size["height"], size["width"]),
- interpolation=resample
- )
- )
+ transform_list.append(_create_resize(size, resample=resample))
# Convert to tensor (always needed)
transform_list.append(PillowToTensor())
diff --git a/dev/transformers/_sources/information/environment.result.ipynb.txt b/dev/transformers/_sources/information/environment.result.ipynb.txt
index 6c5231046df29860650abf87d32f5d99a1237303..578d0263221a19e720bf67b56561cc2adb144e1d 100644
--- a/dev/transformers/_sources/information/environment.result.ipynb.txt
+++ b/dev/transformers/_sources/information/environment.result.ipynb.txt
@@ -29,10 +29,10 @@
"execution_count": 1,
"metadata": {
"execution": {
- "iopub.execute_input": "2025-02-16T07:48:21.979051Z",
- "iopub.status.busy": "2025-02-16T07:48:21.978838Z",
- "iopub.status.idle": "2025-02-16T07:48:23.142071Z",
- "shell.execute_reply": "2025-02-16T07:48:23.141296Z"
+ "iopub.execute_input": "2025-02-16T09:57:25.938203Z",
+ "iopub.status.busy": "2025-02-16T09:57:25.937715Z",
+ "iopub.status.idle": "2025-02-16T09:57:27.103274Z",
+ "shell.execute_reply": "2025-02-16T09:57:27.102566Z"
},
"pycharm": {
"name": "#%%\n"
@@ -53,7 +53,7 @@
"text": [
"CPU Brand: AMD EPYC 7763 64-Core Processor\n",
"CPU Count: 4\n",
- "CPU Freq: 3245.3525 MHz\n",
+ "CPU Freq: 3189.9635000000007 MHz\n",
"Memory Size: 15.615 GiB\n",
"Has CUDA: No\n"
]
diff --git a/dev/transformers/api_doc/preprocess/transformers.html b/dev/transformers/api_doc/preprocess/transformers.html
index 2b0e41111acfa63d8fb28a7c65b5f417bd8482c1..5eecb4b9e5388a89ce7bb5e3776d3790578f31c0 100644
--- a/dev/transformers/api_doc/preprocess/transformers.html
+++ b/dev/transformers/api_doc/preprocess/transformers.html
@@ -468,22 +468,25 @@
-
imgutils.preprocess.transformers.register_creators_for_transformers()[source]
-Decorator for registering transform creator functions.
-This decorator adds the decorated function to the list of available
-transform creators that will be tried when creating transforms from
+
Decorator that registers functions as transform creators for transformers processors.
+This decorator system allows for extensible support of different processor types.
+When a function is decorated with this decorator, it is added to the list of
+available transform creators that will be tried when creating transforms from
a transformers processor.
- Returns:
-Decorator function
+Decorator function that registers the decorated function
- Return type:
callable
- Example:
>>> @register_creators_for_transformers()
->>> def my_transform_creator(processor):
-... # Create and return transforms
-... pass
+>>> def create_clip_transforms(processor):
+... if not hasattr(processor, 'feature_extractor'):
+... raise NotProcessorTypeError()
+... # Create and return transforms for CLIP
+... return transforms
-
class imgutils.preprocess.transformers.NotProcessorTypeError[source]
-Exception raised when a processor type is not recognized or supported.
-This error occurs when attempting to create transforms from an unsupported
-or unknown transformers processor type.
+Exception raised when an unsupported processor type is encountered.
+This custom exception is used when the system cannot create transforms
+from a given transformers processor, either because the processor type
+is not recognized or is not supported by any registered transform creators.
+
+- Inherits:
+TypeError
+
@@ -507,21 +516,22 @@ or unknown transformers processor type.
-
imgutils.preprocess.transformers.create_transforms_from_transformers(processor)[source]
-Create image transforms from a transformers processor.
-This function attempts to create appropriate image transforms by trying
-each registered creator function until one succeeds.
+Create appropriate image transforms from a given transformers processor.
+This function attempts to create image transforms by iterating through
+registered creator functions until one successfully creates transforms
+for the given processor type.
- Parameters:
-processor (object) – A transformers processor object
+processor (transformers.ImageProcessor or similar) – A processor instance from the transformers library
- Returns:
-Image transforms appropriate for the given processor
+A composition of image transforms suitable for the given processor
- Return type:
-object
+PillowCompose or similar transform object
- Raises:
-NotProcessorTypeError – If no suitable creator is found for the processor
+NotProcessorTypeError – If no registered creator can handle the processor type
- Example:
>>> from transformers import AutoImageProcessor
diff --git a/dev/transformers/information/environment.html b/dev/transformers/information/environment.html
index 37fab513ade5cf278441f94c022e6825c4e5ac4f..445914543f0175270c694e98a8c72f28ed463ec1 100644
--- a/dev/transformers/information/environment.html
+++ b/dev/transformers/information/environment.html
@@ -139,7 +139,7 @@ OS: Linux-6.8.0-1021-azure-x86_64-with-glibc2.34
Python: CPython 3.8.18
CPU Brand: AMD EPYC 7763 64-Core Processor
CPU Count: 4
-CPU Freq: 2938.5409999999997 MHz
+CPU Freq: 3105.2147499999996 MHz
Memory Size: 15.615 GiB
Has CUDA: No