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Add Fast Chinese-CLIP Processor (#37012)

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* Add Fast Chinese-CLIP Processor

* Update dummy_torchvision_objects.py

* Fix tests
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Parteek 2025-04-15 22:01:20 +05:30 committed by GitHub
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commit 4f1dbe8152
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7 changed files with 86 additions and 27 deletions
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5
docs/source/en/model_doc/chinese_clip.md
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@ -90,6 +90,11 @@ Currently, following scales of pretrained Chinese-CLIP models are available on
[[autodoc]] ChineseCLIPImageProcessor
- preprocess
## ChineseCLIPImageProcessorFast
[[autodoc]] ChineseCLIPImageProcessorFast
- preprocess
## ChineseCLIPFeatureExtractor
[[autodoc]] ChineseCLIPFeatureExtractor

5
docs/source/ja/model_doc/chinese_clip.md
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@ -86,6 +86,11 @@ Chinese-CLIP モデルは、[OFA-Sys](https://huggingface.co/OFA-Sys) によっ
[[autodoc]] ChineseCLIPImageProcessor
- preprocess
## ChineseCLIPImageProcessorFast
[[autodoc]] ChineseCLIPImageProcessorFast
- preprocess
## ChineseCLIPFeatureExtractor
[[autodoc]] ChineseCLIPFeatureExtractor

2
src/transformers/models/auto/image_processing_auto.py
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@ -64,7 +64,7 @@ else:
("blip-2", ("BlipImageProcessor", "BlipImageProcessorFast")),
("bridgetower", ("BridgeTowerImageProcessor",)),
("chameleon", ("ChameleonImageProcessor",)),
("chinese_clip", ("ChineseCLIPImageProcessor",)),
("chinese_clip", ("ChineseCLIPImageProcessor", "ChineseCLIPImageProcessorFast")),
("clip", ("CLIPImageProcessor", "CLIPImageProcessorFast")),
("clipseg", ("ViTImageProcessor", "ViTImageProcessorFast")),
("conditional_detr", ("ConditionalDetrImageProcessor",)),

1
src/transformers/models/chinese_clip/__init__.py
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@ -21,6 +21,7 @@ if TYPE_CHECKING:
from .configuration_chinese_clip import *
from .feature_extraction_chinese_clip import *
from .image_processing_chinese_clip import *
from .image_processing_chinese_clip_fast import *
from .modeling_chinese_clip import *
from .processing_chinese_clip import *
else:

40
src/transformers/models/chinese_clip/image_processing_chinese_clip_fast.py Normal file
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@ -0,0 +1,40 @@
# coding=utf-8
# Copyright 2025 The OFA-Sys Team Authors and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Fast Image processor class for Chinese-CLIP."""
from ...image_processing_utils_fast import BASE_IMAGE_PROCESSOR_FAST_DOCSTRING, BaseImageProcessorFast
from ...image_utils import OPENAI_CLIP_MEAN, OPENAI_CLIP_STD, PILImageResampling
from ...utils import add_start_docstrings
@add_start_docstrings(
"Constructs a fast ChineseCLIP image processor.",
BASE_IMAGE_PROCESSOR_FAST_DOCSTRING,
)
class ChineseCLIPImageProcessorFast(BaseImageProcessorFast):
resample = PILImageResampling.BICUBIC
image_mean = OPENAI_CLIP_MEAN
image_std = OPENAI_CLIP_STD
size = {"shortest_edge": 224}
default_to_square = False
crop_size = {"height": 224, "width": 224}
do_resize = True
do_center_crop = True
do_rescale = True
do_normalize = True
do_convert_rgb = True
__all__ = ["ChineseCLIPImageProcessorFast"]

2
src/transformers/models/chinese_clip/processing_chinese_clip.py
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@ -44,7 +44,7 @@ class ChineseCLIPProcessor(ProcessorMixin):
"""
attributes = ["image_processor", "tokenizer"]
image_processor_class = "ChineseCLIPImageProcessor"
image_processor_class = ("ChineseCLIPImageProcessor", "ChineseCLIPImageProcessorFast")
tokenizer_class = ("BertTokenizer", "BertTokenizerFast")
def __init__(self, image_processor=None, tokenizer=None, **kwargs):

58
tests/models/chinese_clip/test_image_processing_chinese_clip.py
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@ -16,7 +16,7 @@
import unittest
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_vision_available
from transformers.utils import is_torchvision_available, is_vision_available
from ...test_image_processing_common import ImageProcessingTestMixin, prepare_image_inputs
@ -24,6 +24,9 @@ from ...test_image_processing_common import ImageProcessingTestMixin, prepare_im
if is_vision_available():
from transformers import ChineseCLIPImageProcessor
if is_torchvision_available():
from transformers import ChineseCLIPImageProcessorFast
class ChineseCLIPImageProcessingTester:
def __init__(
@ -91,6 +94,7 @@ class ChineseCLIPImageProcessingTester:
@require_vision
class ChineseCLIPImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase):
image_processing_class = ChineseCLIPImageProcessor if is_vision_available() else None
fast_image_processing_class = ChineseCLIPImageProcessorFast if is_torchvision_available() else None
def setUp(self):
super().setUp()
@ -101,24 +105,26 @@ class ChineseCLIPImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase
return self.image_processor_tester.prepare_image_processor_dict()
def test_image_processor_properties(self):
image_processing = self.image_processing_class(**self.image_processor_dict)
self.assertTrue(hasattr(image_processing, "do_resize"))
self.assertTrue(hasattr(image_processing, "size"))
self.assertTrue(hasattr(image_processing, "do_center_crop"))
self.assertTrue(hasattr(image_processing, "center_crop"))
self.assertTrue(hasattr(image_processing, "do_normalize"))
self.assertTrue(hasattr(image_processing, "image_mean"))
self.assertTrue(hasattr(image_processing, "image_std"))
self.assertTrue(hasattr(image_processing, "do_convert_rgb"))
for image_processing_class in self.image_processor_list:
image_processing = image_processing_class(**self.image_processor_dict)
self.assertTrue(hasattr(image_processing, "do_resize"))
self.assertTrue(hasattr(image_processing, "size"))
self.assertTrue(hasattr(image_processing, "do_center_crop"))
self.assertTrue(hasattr(image_processing, "center_crop"))
self.assertTrue(hasattr(image_processing, "do_normalize"))
self.assertTrue(hasattr(image_processing, "image_mean"))
self.assertTrue(hasattr(image_processing, "image_std"))
self.assertTrue(hasattr(image_processing, "do_convert_rgb"))
def test_image_processor_from_dict_with_kwargs(self):
image_processor = self.image_processing_class.from_dict(self.image_processor_dict)
self.assertEqual(image_processor.size, {"height": 224, "width": 224})
self.assertEqual(image_processor.crop_size, {"height": 18, "width": 18})
for image_processing_class in self.image_processor_list:
image_processor = image_processing_class.from_dict(self.image_processor_dict)
self.assertEqual(image_processor.size, {"height": 224, "width": 224})
self.assertEqual(image_processor.crop_size, {"height": 18, "width": 18})
image_processor = self.image_processing_class.from_dict(self.image_processor_dict, size=42, crop_size=84)
self.assertEqual(image_processor.size, {"shortest_edge": 42})
self.assertEqual(image_processor.crop_size, {"height": 84, "width": 84})
image_processor = self.image_processing_class.from_dict(self.image_processor_dict, size=42, crop_size=84)
self.assertEqual(image_processor.size, {"shortest_edge": 42})
self.assertEqual(image_processor.crop_size, {"height": 84, "width": 84})
@unittest.skip(
reason="ChineseCLIPImageProcessor doesn't treat 4 channel PIL and numpy consistently yet"
@ -131,6 +137,7 @@ class ChineseCLIPImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase
@require_vision
class ChineseCLIPImageProcessingTestFourChannels(ImageProcessingTestMixin, unittest.TestCase):
image_processing_class = ChineseCLIPImageProcessor if is_vision_available() else None
fast_image_processing_class = ChineseCLIPImageProcessorFast if is_torchvision_available() else None
def setUp(self):
super().setUp()
@ -142,15 +149,16 @@ class ChineseCLIPImageProcessingTestFourChannels(ImageProcessingTestMixin, unitt
return self.image_processor_tester.prepare_image_processor_dict()
def test_image_processor_properties(self):
image_processing = self.image_processing_class(**self.image_processor_dict)
self.assertTrue(hasattr(image_processing, "do_resize"))
self.assertTrue(hasattr(image_processing, "size"))
self.assertTrue(hasattr(image_processing, "do_center_crop"))
self.assertTrue(hasattr(image_processing, "center_crop"))
self.assertTrue(hasattr(image_processing, "do_normalize"))
self.assertTrue(hasattr(image_processing, "image_mean"))
self.assertTrue(hasattr(image_processing, "image_std"))
self.assertTrue(hasattr(image_processing, "do_convert_rgb"))
for image_processing_class in self.image_processor_list:
image_processing = image_processing_class(**self.image_processor_dict)
self.assertTrue(hasattr(image_processing, "do_resize"))
self.assertTrue(hasattr(image_processing, "size"))
self.assertTrue(hasattr(image_processing, "do_center_crop"))
self.assertTrue(hasattr(image_processing, "center_crop"))
self.assertTrue(hasattr(image_processing, "do_normalize"))
self.assertTrue(hasattr(image_processing, "image_mean"))
self.assertTrue(hasattr(image_processing, "image_std"))
self.assertTrue(hasattr(image_processing, "do_convert_rgb"))
@unittest.skip(reason="ChineseCLIPImageProcessor does not support 4 channels yet") # FIXME Amy
def test_call_numpy(self):