





import unittest

from transformers import (
    MODEL_FOR_OBJECT_DETECTION_MAPPING,
    AutoFeatureExtractor,
    AutoModelForObjectDetection,
    ObjectDetectionPipeline,
    is_vision_available,
    pipeline,
)
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_pytesseract,
    require_tf,
    require_timm,
    require_torch,
    require_vision,
    slow,
)

from .test_pipelines_common import ANY


if is_vision_available():
							from PIL import Image
else:

							class  __A       :


											@staticmethod
											def _snake_case    (						*UpperCAmelCase_				,	**UpperCAmelCase_							):
															pass

@is_pipeline_test
@require_vision
@require_timm
@require_torch
class  __A       (  unittest.TestCase      ):
				__A								=			MODEL_FOR_OBJECT_DETECTION_MAPPING


				def _snake_case    (						self				,	UpperCAmelCase_				,	UpperCAmelCase_				,	UpperCAmelCase_							):
								lowerCamelCase			=ObjectDetectionPipeline(model=UpperCAmelCase_				,	image_processor=UpperCAmelCase_							)
								return object_detector, ["./tests/fixtures/tests_samples/COCO/000000039769.png"]


				def _snake_case    (						self				,	UpperCAmelCase_				,	UpperCAmelCase_							):
								lowerCamelCase			=object_detector("""./tests/fixtures/tests_samples/COCO/000000039769.png"""				,	threshold=0.0							)

								self.assertGreater(len(UpperCAmelCase_							)				,	0							)
								for detected_object in outputs:
												self.assertEqual(
												    UpperCAmelCase_				,	{
												        """score""": ANY(UpperCAmelCase_							),
												        """label""": ANY(UpperCAmelCase_							),
												        """box""": {"""xmin""": ANY(UpperCAmelCase_							), """ymin""": ANY(UpperCAmelCase_							), """xmax""": ANY(UpperCAmelCase_							), """ymax""": ANY(UpperCAmelCase_							)},
												    }				,	)

								import datasets

								lowerCamelCase			=datasets.load_dataset("""hf-internal-testing/fixtures_image_utils"""				,	"""image"""				,	split="""test"""							)

								lowerCamelCase			=[
								    Image.open("""./tests/fixtures/tests_samples/COCO/000000039769.png"""							),
								    "http://images.cocodataset.org/val2017/000000039769.jpg",
								    # RGBA
								    dataset[0]["file"],
								    # LA
								    dataset[1]["file"],
								    # L
								    dataset[2]["file"],
								]
								lowerCamelCase			=object_detector(UpperCAmelCase_				,	threshold=0.0							)

								self.assertEqual(len(UpperCAmelCase_							)				,	len(UpperCAmelCase_							)							)
								for outputs in batch_outputs:
												self.assertGreater(len(UpperCAmelCase_							)				,	0							)
												for detected_object in outputs:
																self.assertEqual(
																    UpperCAmelCase_				,	{
																        """score""": ANY(UpperCAmelCase_							),
																        """label""": ANY(UpperCAmelCase_							),
																        """box""": {"""xmin""": ANY(UpperCAmelCase_							), """ymin""": ANY(UpperCAmelCase_							), """xmax""": ANY(UpperCAmelCase_							), """ymax""": ANY(UpperCAmelCase_							)},
																    }				,	)


				@require_tf
				@unittest.skip("""Object detection not implemented in TF"""							)
				def _snake_case    (						self							):
								pass


				@require_torch
				def _snake_case    (						self							):
								lowerCamelCase			="hf-internal-testing/tiny-detr-mobilenetsv3"

								lowerCamelCase			=AutoModelForObjectDetection.from_pretrained(UpperCAmelCase_							)
								lowerCamelCase			=AutoFeatureExtractor.from_pretrained(UpperCAmelCase_							)
								lowerCamelCase			=ObjectDetectionPipeline(model=UpperCAmelCase_				,	feature_extractor=UpperCAmelCase_							)

								lowerCamelCase			=object_detector("""http://images.cocodataset.org/val2017/000000039769.jpg"""				,	threshold=0.0							)

								self.assertEqual(
								    nested_simplify(UpperCAmelCase_				,	decimals=4							)				,	[
								        {"""score""": 0.3_3_7_6, """label""": """LABEL_0""", """box""": {"""xmin""": 159, """ymin""": 120, """xmax""": 480, """ymax""": 359}},
								        {"""score""": 0.3_3_7_6, """label""": """LABEL_0""", """box""": {"""xmin""": 159, """ymin""": 120, """xmax""": 480, """ymax""": 359}},
								    ]				,	)

								lowerCamelCase			=object_detector(
								    [
								        """http://images.cocodataset.org/val2017/000000039769.jpg""",
								        """http://images.cocodataset.org/val2017/000000039769.jpg""",
								    ]				,	threshold=0.0				,	)

								self.assertEqual(
								    nested_simplify(UpperCAmelCase_				,	decimals=4							)				,	[
								        [
								            {"""score""": 0.3_3_7_6, """label""": """LABEL_0""", """box""": {"""xmin""": 159, """ymin""": 120, """xmax""": 480, """ymax""": 359}},
								            {"""score""": 0.3_3_7_6, """label""": """LABEL_0""", """box""": {"""xmin""": 159, """ymin""": 120, """xmax""": 480, """ymax""": 359}},
								        ],
								        [
								            {"""score""": 0.3_3_7_6, """label""": """LABEL_0""", """box""": {"""xmin""": 159, """ymin""": 120, """xmax""": 480, """ymax""": 359}},
								            {"""score""": 0.3_3_7_6, """label""": """LABEL_0""", """box""": {"""xmin""": 159, """ymin""": 120, """xmax""": 480, """ymax""": 359}},
								        ],
								    ]				,	)


				@require_torch
				@slow
				def _snake_case    (						self							):
								lowerCamelCase			="facebook/detr-resnet-50"

								lowerCamelCase			=AutoModelForObjectDetection.from_pretrained(UpperCAmelCase_							)
								lowerCamelCase			=AutoFeatureExtractor.from_pretrained(UpperCAmelCase_							)
								lowerCamelCase			=ObjectDetectionPipeline(model=UpperCAmelCase_				,	feature_extractor=UpperCAmelCase_							)

								lowerCamelCase			=object_detector("""http://images.cocodataset.org/val2017/000000039769.jpg"""							)
								self.assertEqual(
								    nested_simplify(UpperCAmelCase_				,	decimals=4							)				,	[
								        {"""score""": 0.9_9_8_2, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 70, """xmax""": 175, """ymax""": 117}},
								        {"""score""": 0.9_9_6_0, """label""": """remote""", """box""": {"""xmin""": 333, """ymin""": 72, """xmax""": 368, """ymax""": 187}},
								        {"""score""": 0.9_9_5_5, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 639, """ymax""": 473}},
								        {"""score""": 0.9_9_8_8, """label""": """cat""", """box""": {"""xmin""": 13, """ymin""": 52, """xmax""": 314, """ymax""": 470}},
								        {"""score""": 0.9_9_8_7, """label""": """cat""", """box""": {"""xmin""": 345, """ymin""": 23, """xmax""": 640, """ymax""": 368}},
								    ]				,	)

								lowerCamelCase			=object_detector(
								    [
								        """http://images.cocodataset.org/val2017/000000039769.jpg""",
								        """http://images.cocodataset.org/val2017/000000039769.jpg""",
								    ]							)
								self.assertEqual(
								    nested_simplify(UpperCAmelCase_				,	decimals=4							)				,	[
								        [
								            {"""score""": 0.9_9_8_2, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 70, """xmax""": 175, """ymax""": 117}},
								            {"""score""": 0.9_9_6_0, """label""": """remote""", """box""": {"""xmin""": 333, """ymin""": 72, """xmax""": 368, """ymax""": 187}},
								            {"""score""": 0.9_9_5_5, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 639, """ymax""": 473}},
								            {"""score""": 0.9_9_8_8, """label""": """cat""", """box""": {"""xmin""": 13, """ymin""": 52, """xmax""": 314, """ymax""": 470}},
								            {"""score""": 0.9_9_8_7, """label""": """cat""", """box""": {"""xmin""": 345, """ymin""": 23, """xmax""": 640, """ymax""": 368}},
								        ],
								        [
								            {"""score""": 0.9_9_8_2, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 70, """xmax""": 175, """ymax""": 117}},
								            {"""score""": 0.9_9_6_0, """label""": """remote""", """box""": {"""xmin""": 333, """ymin""": 72, """xmax""": 368, """ymax""": 187}},
								            {"""score""": 0.9_9_5_5, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 639, """ymax""": 473}},
								            {"""score""": 0.9_9_8_8, """label""": """cat""", """box""": {"""xmin""": 13, """ymin""": 52, """xmax""": 314, """ymax""": 470}},
								            {"""score""": 0.9_9_8_7, """label""": """cat""", """box""": {"""xmin""": 345, """ymin""": 23, """xmax""": 640, """ymax""": 368}},
								        ],
								    ]				,	)


				@require_torch
				@slow
				def _snake_case    (						self							):
								lowerCamelCase			="facebook/detr-resnet-50"

								lowerCamelCase			=pipeline("""object-detection"""				,	model=UpperCAmelCase_							)

								lowerCamelCase			=object_detector("""http://images.cocodataset.org/val2017/000000039769.jpg"""							)
								self.assertEqual(
								    nested_simplify(UpperCAmelCase_				,	decimals=4							)				,	[
								        {"""score""": 0.9_9_8_2, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 70, """xmax""": 175, """ymax""": 117}},
								        {"""score""": 0.9_9_6_0, """label""": """remote""", """box""": {"""xmin""": 333, """ymin""": 72, """xmax""": 368, """ymax""": 187}},
								        {"""score""": 0.9_9_5_5, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 639, """ymax""": 473}},
								        {"""score""": 0.9_9_8_8, """label""": """cat""", """box""": {"""xmin""": 13, """ymin""": 52, """xmax""": 314, """ymax""": 470}},
								        {"""score""": 0.9_9_8_7, """label""": """cat""", """box""": {"""xmin""": 345, """ymin""": 23, """xmax""": 640, """ymax""": 368}},
								    ]				,	)

								lowerCamelCase			=object_detector(
								    [
								        """http://images.cocodataset.org/val2017/000000039769.jpg""",
								        """http://images.cocodataset.org/val2017/000000039769.jpg""",
								    ]							)
								self.assertEqual(
								    nested_simplify(UpperCAmelCase_				,	decimals=4							)				,	[
								        [
								            {"""score""": 0.9_9_8_2, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 70, """xmax""": 175, """ymax""": 117}},
								            {"""score""": 0.9_9_6_0, """label""": """remote""", """box""": {"""xmin""": 333, """ymin""": 72, """xmax""": 368, """ymax""": 187}},
								            {"""score""": 0.9_9_5_5, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 639, """ymax""": 473}},
								            {"""score""": 0.9_9_8_8, """label""": """cat""", """box""": {"""xmin""": 13, """ymin""": 52, """xmax""": 314, """ymax""": 470}},
								            {"""score""": 0.9_9_8_7, """label""": """cat""", """box""": {"""xmin""": 345, """ymin""": 23, """xmax""": 640, """ymax""": 368}},
								        ],
								        [
								            {"""score""": 0.9_9_8_2, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 70, """xmax""": 175, """ymax""": 117}},
								            {"""score""": 0.9_9_6_0, """label""": """remote""", """box""": {"""xmin""": 333, """ymin""": 72, """xmax""": 368, """ymax""": 187}},
								            {"""score""": 0.9_9_5_5, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 639, """ymax""": 473}},
								            {"""score""": 0.9_9_8_8, """label""": """cat""", """box""": {"""xmin""": 13, """ymin""": 52, """xmax""": 314, """ymax""": 470}},
								            {"""score""": 0.9_9_8_7, """label""": """cat""", """box""": {"""xmin""": 345, """ymin""": 23, """xmax""": 640, """ymax""": 368}},
								        ],
								    ]				,	)


				@require_torch
				@slow
				def _snake_case    (						self							):
								lowerCamelCase			=0.9_9_8_5
								lowerCamelCase			="facebook/detr-resnet-50"

								lowerCamelCase			=pipeline("""object-detection"""				,	model=UpperCAmelCase_							)

								lowerCamelCase			=object_detector("""http://images.cocodataset.org/val2017/000000039769.jpg"""				,	threshold=UpperCAmelCase_							)
								self.assertEqual(
								    nested_simplify(UpperCAmelCase_				,	decimals=4							)				,	[
								        {"""score""": 0.9_9_8_8, """label""": """cat""", """box""": {"""xmin""": 13, """ymin""": 52, """xmax""": 314, """ymax""": 470}},
								        {"""score""": 0.9_9_8_7, """label""": """cat""", """box""": {"""xmin""": 345, """ymin""": 23, """xmax""": 640, """ymax""": 368}},
								    ]				,	)


				@require_torch
				@require_pytesseract
				@slow
				def _snake_case    (						self							):
								lowerCamelCase			="Narsil/layoutlmv3-finetuned-funsd"
								lowerCamelCase			=0.9_9_9_3

								lowerCamelCase			=pipeline("""object-detection"""				,	model=UpperCAmelCase_				,	threshold=UpperCAmelCase_							)

								lowerCamelCase			=object_detector(
								    """https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/invoice.png"""							)
								self.assertEqual(
								    nested_simplify(UpperCAmelCase_				,	decimals=4							)				,	[
								        {"""score""": 0.9_9_9_3, """label""": """I-ANSWER""", """box""": {"""xmin""": 294, """ymin""": 254, """xmax""": 343, """ymax""": 264}},
								        {"""score""": 0.9_9_9_3, """label""": """I-ANSWER""", """box""": {"""xmin""": 294, """ymin""": 254, """xmax""": 343, """ymax""": 264}},
								    ]				,	)













import argparse
import os
import re

import packaging.version


UpperCAmelCase__  :     List[Any]   			='''examples/'''
UpperCAmelCase__  :     List[str]   			={
    '''examples''': (re.compile(r'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
    '''init''': (re.compile(r'''^__version__\s+=\s+"([^"]+)"\s*$''', re.MULTILINE), '''__version__ = "VERSION"\n'''),
    '''setup''': (re.compile(r'''^(\s*)version\s*=\s*"[^"]+",''', re.MULTILINE), r'''\1version="VERSION",'''),
    '''doc''': (re.compile(r'''^(\s*)release\s*=\s*"[^"]+"$''', re.MULTILINE), '''release = "VERSION"\n'''),
}
UpperCAmelCase__  :     List[Any]   			={
    '''init''': '''src/transformers/__init__.py''',
    '''setup''': '''setup.py''',
}
UpperCAmelCase__  :     Union[str, Any]   			='''README.md'''





def        _lowercase   (  _UpperCAmelCase     , _UpperCAmelCase     , _UpperCAmelCase			)  ->					str:
				with open(_UpperCAmelCase     , """r"""     , encoding="""utf-8"""     , newline="""\n"""			) as f:
								lowerCamelCase			=f.read()
				lowerCamelCase	,					lowerCamelCase			=REPLACE_PATTERNS[pattern]
				lowerCamelCase			=replace.replace("""VERSION"""     , _UpperCAmelCase			)
				lowerCamelCase			=re_pattern.sub(_UpperCAmelCase     , _UpperCAmelCase			)
				with open(_UpperCAmelCase     , """w"""     , encoding="""utf-8"""     , newline="""\n"""			) as f:
								f.write(_UpperCAmelCase			)





def        _lowercase   (  _UpperCAmelCase			)  ->					int:
				for folder, directories, fnames in os.walk(_UpperCAmelCase			):
								# Removing some of the folders with non-actively maintained examples from the walk
								if "research_projects" in directories:
												directories.remove("""research_projects"""			)
								if "legacy" in directories:
												directories.remove("""legacy"""			)
								for fname in fnames:
												if fname.endswith(""".py"""			):
																update_version_in_file(os.path.join(_UpperCAmelCase     , _UpperCAmelCase			)     , _UpperCAmelCase     , pattern="""examples"""			)





def        _lowercase   (  _UpperCAmelCase     , _UpperCAmelCase=False			)  ->					Any:
				for pattern, fname in REPLACE_FILES.items():
								update_version_in_file(_UpperCAmelCase     , _UpperCAmelCase     , _UpperCAmelCase			)
				if not patch:
								update_version_in_examples(_UpperCAmelCase			)





def        _lowercase   (  )  ->					Dict:
				lowerCamelCase			="""🤗 Transformers currently provides the following architectures"""
				lowerCamelCase			="""1. Want to contribute a new model?"""
				with open(_UpperCAmelCase     , """r"""     , encoding="""utf-8"""     , newline="""\n"""			) as f:
								lowerCamelCase			=f.readlines()

				# Find the start of the list.
				lowerCamelCase			=0
				while not lines[start_index].startswith(_start_prompt			):
								start_index += 1
				start_index += 1

				lowerCamelCase			=start_index
				# Update the lines in the model list.
				while not lines[index].startswith(_end_prompt			):
								if lines[index].startswith("""1."""			):
												lowerCamelCase			=lines[index].replace(
												    """https://huggingface.co/docs/transformers/main/model_doc"""     , """https://huggingface.co/docs/transformers/model_doc"""     , )
								index += 1

				with open(_UpperCAmelCase     , """w"""     , encoding="""utf-8"""     , newline="""\n"""			) as f:
								f.writelines(_UpperCAmelCase			)





def        _lowercase   (  )  ->					Optional[int]:
				with open(REPLACE_FILES["""init"""]     , """r"""			) as f:
								lowerCamelCase			=f.read()
				lowerCamelCase			=REPLACE_PATTERNS["""init"""][0].search(_UpperCAmelCase			).groups()[0]
				return packaging.version.parse(_UpperCAmelCase			)





def        _lowercase   (  _UpperCAmelCase=False			)  ->					List[str]:
				lowerCamelCase			=get_version()
				if patch and default_version.is_devrelease:
								raise ValueError("""Can't create a patch version from the dev branch, checkout a released version!"""			)
				if default_version.is_devrelease:
								lowerCamelCase			=default_version.base_version
				elif patch:
								lowerCamelCase			=F"""{default_version.major}.{default_version.minor}.{default_version.micro + 1}"""
				else:
								lowerCamelCase			=F"""{default_version.major}.{default_version.minor + 1}.0"""

				# Now let's ask nicely if that's the right one.
				lowerCamelCase			=input(F"""Which version are you releasing? [{default_version}]"""			)
				if len(_UpperCAmelCase			) == 0:
								lowerCamelCase			=default_version

				print(F"""Updating version to {version}."""			)
				global_version_update(_UpperCAmelCase     , patch=_UpperCAmelCase			)
				if not patch:
								print("""Cleaning main README, don't forget to run `make fix-copies`."""			)
								clean_main_ref_in_model_list()





def        _lowercase   (  )  ->					str:
				lowerCamelCase			=get_version()
				lowerCamelCase			=F"""{current_version.major}.{current_version.minor + 1}.0.dev0"""
				lowerCamelCase			=current_version.base_version

				# Check with the user we got that right.
				lowerCamelCase			=input(F"""Which version are we developing now? [{dev_version}]"""			)
				if len(_UpperCAmelCase			) == 0:
								lowerCamelCase			=dev_version

				print(F"""Updating version to {version}."""			)
				global_version_update(_UpperCAmelCase			)
				print("""Cleaning main README, don't forget to run `make fix-copies`."""			)
				clean_main_ref_in_model_list()


if __name__ == "__main__":
							UpperCAmelCase__  :     Optional[Any]   			=argparse.ArgumentParser()
							parser.add_argument('''--post_release''', action='''store_true''', help='''Whether this is pre or post release.''')
							parser.add_argument('''--patch''', action='''store_true''', help='''Whether or not this is a patch release.''')
							UpperCAmelCase__  :     str   			=parser.parse_args()
							if not args.post_release:
														pre_release_work(patch=args.patch)
							elif args.patch:
														print('''Nothing to do after a patch :-)''')
							else:
														post_release_work()





