


"""simple docstring"""






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:

							"""simple docstring"""





							@staticmethod
							def   _UpperCamelCase( *SCREAMING_SNAKE_CASE__					,				**SCREAMING_SNAKE_CASE__   )      ->	Tuple:

										"""simple docstring"""



										pass






@is_pipeline_test
@require_vision
@require_timm
@require_torch
class      A(  unittest.TestCase		):

		"""simple docstring"""





		A    =							MODEL_FOR_OBJECT_DETECTION_MAPPING
		def   _UpperCamelCase( self					,				SCREAMING_SNAKE_CASE__					,				SCREAMING_SNAKE_CASE__					,				SCREAMING_SNAKE_CASE__   )      ->	Union[str, Any]:

					"""simple docstring"""



					_UpperCamelCase					:Any					     =	ObjectDetectionPipeline(model=__lowerCamelCase					,				image_processor=__lowerCamelCase   )
					return object_detector, ["./tests/fixtures/tests_samples/COCO/000000039769.png"]
		def   _UpperCamelCase( self					,				SCREAMING_SNAKE_CASE__					,				SCREAMING_SNAKE_CASE__   )      ->	Optional[Any]:

					"""simple docstring"""



					_UpperCamelCase					:str					     =	object_detector('''./tests/fixtures/tests_samples/COCO/000000039769.png'''					,				threshold=0.0   )

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

					import datasets

					_UpperCamelCase					:str					     =	datasets.load_dataset('''hf-internal-testing/fixtures_image_utils'''					,				'''image'''					,				split='''test'''   )

					_UpperCamelCase					:List[Any]					     =	[
					    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'''],
					]
					_UpperCamelCase					:str					     =	object_detector(__lowerCamelCase					,				threshold=0.0   )

					self.assertEqual(len(__lowerCamelCase   )					,				len(__lowerCamelCase   )   )
					for outputs in batch_outputs:
								self.assertGreater(len(__lowerCamelCase   )					,				0   )
								for detected_object in outputs:
											self.assertEqual(
											    __lowerCamelCase					,				{
											        '''score''': ANY(__lowerCamelCase   ),
											        '''label''': ANY(__lowerCamelCase   ),
											        '''box''': {'''xmin''': ANY(__lowerCamelCase   ), '''ymin''': ANY(__lowerCamelCase   ), '''xmax''': ANY(__lowerCamelCase   ), '''ymax''': ANY(__lowerCamelCase   )},
											    }					,				)
		@require_tf
		@unittest.skip('''Object detection not implemented in TF'''   )
		def   _UpperCamelCase( self   )      ->	int:

					"""simple docstring"""



					pass
		@require_torch
		def   _UpperCamelCase( self   )      ->	Any:

					"""simple docstring"""



					_UpperCamelCase					:str					     =	'''hf-internal-testing/tiny-detr-mobilenetsv3'''

					_UpperCamelCase					:str					     =	AutoModelForObjectDetection.from_pretrained(__lowerCamelCase   )
					_UpperCamelCase					:Tuple					     =	AutoFeatureExtractor.from_pretrained(__lowerCamelCase   )
					_UpperCamelCase					:Optional[Any]					     =	ObjectDetectionPipeline(model=__lowerCamelCase					,				feature_extractor=__lowerCamelCase   )

					_UpperCamelCase					:Any					     =	object_detector('''http://images.cocodataset.org/val2017/000000039769.jpg'''					,				threshold=0.0   )

					self.assertEqual(
					    nested_simplify(__lowerCamelCase					,				decimals=4   )					,				[
					        {'''score''': 0.3_3_7_6, '''label''': '''LABEL_0''', '''box''': {'''xmin''': 1_59, '''ymin''': 1_20, '''xmax''': 4_80, '''ymax''': 3_59}},
					        {'''score''': 0.3_3_7_6, '''label''': '''LABEL_0''', '''box''': {'''xmin''': 1_59, '''ymin''': 1_20, '''xmax''': 4_80, '''ymax''': 3_59}},
					    ]					,				)

					_UpperCamelCase					:Optional[Any]					     =	object_detector(
					    [
					        '''http://images.cocodataset.org/val2017/000000039769.jpg''',
					        '''http://images.cocodataset.org/val2017/000000039769.jpg''',
					    ]					,				threshold=0.0					,				)

					self.assertEqual(
					    nested_simplify(__lowerCamelCase					,				decimals=4   )					,				[
					        [
					            {'''score''': 0.3_3_7_6, '''label''': '''LABEL_0''', '''box''': {'''xmin''': 1_59, '''ymin''': 1_20, '''xmax''': 4_80, '''ymax''': 3_59}},
					            {'''score''': 0.3_3_7_6, '''label''': '''LABEL_0''', '''box''': {'''xmin''': 1_59, '''ymin''': 1_20, '''xmax''': 4_80, '''ymax''': 3_59}},
					        ],
					        [
					            {'''score''': 0.3_3_7_6, '''label''': '''LABEL_0''', '''box''': {'''xmin''': 1_59, '''ymin''': 1_20, '''xmax''': 4_80, '''ymax''': 3_59}},
					            {'''score''': 0.3_3_7_6, '''label''': '''LABEL_0''', '''box''': {'''xmin''': 1_59, '''ymin''': 1_20, '''xmax''': 4_80, '''ymax''': 3_59}},
					        ],
					    ]					,				)
		@require_torch
		@slow
		def   _UpperCamelCase( self   )      ->	List[str]:

					"""simple docstring"""



					_UpperCamelCase					:Tuple					     =	'''facebook/detr-resnet-50'''

					_UpperCamelCase					:Dict					     =	AutoModelForObjectDetection.from_pretrained(__lowerCamelCase   )
					_UpperCamelCase					:Optional[Any]					     =	AutoFeatureExtractor.from_pretrained(__lowerCamelCase   )
					_UpperCamelCase					:int					     =	ObjectDetectionPipeline(model=__lowerCamelCase					,				feature_extractor=__lowerCamelCase   )

					_UpperCamelCase					:Optional[Any]					     =	object_detector('''http://images.cocodataset.org/val2017/000000039769.jpg'''   )
					self.assertEqual(
					    nested_simplify(__lowerCamelCase					,				decimals=4   )					,				[
					        {'''score''': 0.9_9_8_2, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 70, '''xmax''': 1_75, '''ymax''': 1_17}},
					        {'''score''': 0.9_9_6_0, '''label''': '''remote''', '''box''': {'''xmin''': 3_33, '''ymin''': 72, '''xmax''': 3_68, '''ymax''': 1_87}},
					        {'''score''': 0.9_9_5_5, '''label''': '''couch''', '''box''': {'''xmin''': 0, '''ymin''': 1, '''xmax''': 6_39, '''ymax''': 4_73}},
					        {'''score''': 0.9_9_8_8, '''label''': '''cat''', '''box''': {'''xmin''': 13, '''ymin''': 52, '''xmax''': 3_14, '''ymax''': 4_70}},
					        {'''score''': 0.9_9_8_7, '''label''': '''cat''', '''box''': {'''xmin''': 3_45, '''ymin''': 23, '''xmax''': 6_40, '''ymax''': 3_68}},
					    ]					,				)

					_UpperCamelCase					:Tuple					     =	object_detector(
					    [
					        '''http://images.cocodataset.org/val2017/000000039769.jpg''',
					        '''http://images.cocodataset.org/val2017/000000039769.jpg''',
					    ]   )
					self.assertEqual(
					    nested_simplify(__lowerCamelCase					,				decimals=4   )					,				[
					        [
					            {'''score''': 0.9_9_8_2, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 70, '''xmax''': 1_75, '''ymax''': 1_17}},
					            {'''score''': 0.9_9_6_0, '''label''': '''remote''', '''box''': {'''xmin''': 3_33, '''ymin''': 72, '''xmax''': 3_68, '''ymax''': 1_87}},
					            {'''score''': 0.9_9_5_5, '''label''': '''couch''', '''box''': {'''xmin''': 0, '''ymin''': 1, '''xmax''': 6_39, '''ymax''': 4_73}},
					            {'''score''': 0.9_9_8_8, '''label''': '''cat''', '''box''': {'''xmin''': 13, '''ymin''': 52, '''xmax''': 3_14, '''ymax''': 4_70}},
					            {'''score''': 0.9_9_8_7, '''label''': '''cat''', '''box''': {'''xmin''': 3_45, '''ymin''': 23, '''xmax''': 6_40, '''ymax''': 3_68}},
					        ],
					        [
					            {'''score''': 0.9_9_8_2, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 70, '''xmax''': 1_75, '''ymax''': 1_17}},
					            {'''score''': 0.9_9_6_0, '''label''': '''remote''', '''box''': {'''xmin''': 3_33, '''ymin''': 72, '''xmax''': 3_68, '''ymax''': 1_87}},
					            {'''score''': 0.9_9_5_5, '''label''': '''couch''', '''box''': {'''xmin''': 0, '''ymin''': 1, '''xmax''': 6_39, '''ymax''': 4_73}},
					            {'''score''': 0.9_9_8_8, '''label''': '''cat''', '''box''': {'''xmin''': 13, '''ymin''': 52, '''xmax''': 3_14, '''ymax''': 4_70}},
					            {'''score''': 0.9_9_8_7, '''label''': '''cat''', '''box''': {'''xmin''': 3_45, '''ymin''': 23, '''xmax''': 6_40, '''ymax''': 3_68}},
					        ],
					    ]					,				)
		@require_torch
		@slow
		def   _UpperCamelCase( self   )      ->	Optional[Any]:

					"""simple docstring"""



					_UpperCamelCase					:int					     =	'''facebook/detr-resnet-50'''

					_UpperCamelCase					:List[str]					     =	pipeline('''object-detection'''					,				model=__lowerCamelCase   )

					_UpperCamelCase					:Dict					     =	object_detector('''http://images.cocodataset.org/val2017/000000039769.jpg'''   )
					self.assertEqual(
					    nested_simplify(__lowerCamelCase					,				decimals=4   )					,				[
					        {'''score''': 0.9_9_8_2, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 70, '''xmax''': 1_75, '''ymax''': 1_17}},
					        {'''score''': 0.9_9_6_0, '''label''': '''remote''', '''box''': {'''xmin''': 3_33, '''ymin''': 72, '''xmax''': 3_68, '''ymax''': 1_87}},
					        {'''score''': 0.9_9_5_5, '''label''': '''couch''', '''box''': {'''xmin''': 0, '''ymin''': 1, '''xmax''': 6_39, '''ymax''': 4_73}},
					        {'''score''': 0.9_9_8_8, '''label''': '''cat''', '''box''': {'''xmin''': 13, '''ymin''': 52, '''xmax''': 3_14, '''ymax''': 4_70}},
					        {'''score''': 0.9_9_8_7, '''label''': '''cat''', '''box''': {'''xmin''': 3_45, '''ymin''': 23, '''xmax''': 6_40, '''ymax''': 3_68}},
					    ]					,				)

					_UpperCamelCase					:Union[str, Any]					     =	object_detector(
					    [
					        '''http://images.cocodataset.org/val2017/000000039769.jpg''',
					        '''http://images.cocodataset.org/val2017/000000039769.jpg''',
					    ]   )
					self.assertEqual(
					    nested_simplify(__lowerCamelCase					,				decimals=4   )					,				[
					        [
					            {'''score''': 0.9_9_8_2, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 70, '''xmax''': 1_75, '''ymax''': 1_17}},
					            {'''score''': 0.9_9_6_0, '''label''': '''remote''', '''box''': {'''xmin''': 3_33, '''ymin''': 72, '''xmax''': 3_68, '''ymax''': 1_87}},
					            {'''score''': 0.9_9_5_5, '''label''': '''couch''', '''box''': {'''xmin''': 0, '''ymin''': 1, '''xmax''': 6_39, '''ymax''': 4_73}},
					            {'''score''': 0.9_9_8_8, '''label''': '''cat''', '''box''': {'''xmin''': 13, '''ymin''': 52, '''xmax''': 3_14, '''ymax''': 4_70}},
					            {'''score''': 0.9_9_8_7, '''label''': '''cat''', '''box''': {'''xmin''': 3_45, '''ymin''': 23, '''xmax''': 6_40, '''ymax''': 3_68}},
					        ],
					        [
					            {'''score''': 0.9_9_8_2, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 70, '''xmax''': 1_75, '''ymax''': 1_17}},
					            {'''score''': 0.9_9_6_0, '''label''': '''remote''', '''box''': {'''xmin''': 3_33, '''ymin''': 72, '''xmax''': 3_68, '''ymax''': 1_87}},
					            {'''score''': 0.9_9_5_5, '''label''': '''couch''', '''box''': {'''xmin''': 0, '''ymin''': 1, '''xmax''': 6_39, '''ymax''': 4_73}},
					            {'''score''': 0.9_9_8_8, '''label''': '''cat''', '''box''': {'''xmin''': 13, '''ymin''': 52, '''xmax''': 3_14, '''ymax''': 4_70}},
					            {'''score''': 0.9_9_8_7, '''label''': '''cat''', '''box''': {'''xmin''': 3_45, '''ymin''': 23, '''xmax''': 6_40, '''ymax''': 3_68}},
					        ],
					    ]					,				)
		@require_torch
		@slow
		def   _UpperCamelCase( self   )      ->	Optional[Any]:

					"""simple docstring"""



					_UpperCamelCase					:Dict					     =	0.9_9_8_5
					_UpperCamelCase					:Any					     =	'''facebook/detr-resnet-50'''

					_UpperCamelCase					:Optional[int]					     =	pipeline('''object-detection'''					,				model=__lowerCamelCase   )

					_UpperCamelCase					:Dict					     =	object_detector('''http://images.cocodataset.org/val2017/000000039769.jpg'''					,				threshold=__lowerCamelCase   )
					self.assertEqual(
					    nested_simplify(__lowerCamelCase					,				decimals=4   )					,				[
					        {'''score''': 0.9_9_8_8, '''label''': '''cat''', '''box''': {'''xmin''': 13, '''ymin''': 52, '''xmax''': 3_14, '''ymax''': 4_70}},
					        {'''score''': 0.9_9_8_7, '''label''': '''cat''', '''box''': {'''xmin''': 3_45, '''ymin''': 23, '''xmax''': 6_40, '''ymax''': 3_68}},
					    ]					,				)





		@require_torch
		@require_pytesseract
		@slow
		def   _UpperCamelCase( self   )      ->	Union[str, Any]:

					"""simple docstring"""



					_UpperCamelCase					:Union[str, Any]					     =	'''Narsil/layoutlmv3-finetuned-funsd'''
					_UpperCamelCase					:Union[str, Any]					     =	0.9_9_9_3

					_UpperCamelCase					:Tuple					     =	pipeline('''object-detection'''					,				model=__lowerCamelCase					,				threshold=__lowerCamelCase   )

					_UpperCamelCase					:Dict					     =	object_detector(
					    '''https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/invoice.png'''   )
					self.assertEqual(
					    nested_simplify(__lowerCamelCase					,				decimals=4   )					,				[
					        {'''score''': 0.9_9_9_3, '''label''': '''I-ANSWER''', '''box''': {'''xmin''': 2_94, '''ymin''': 2_54, '''xmax''': 3_43, '''ymax''': 2_64}},
					        {'''score''': 0.9_9_9_3, '''label''': '''I-ANSWER''', '''box''': {'''xmin''': 2_94, '''ymin''': 2_54, '''xmax''': 3_43, '''ymax''': 2_64}},
					    ]					,				)






"""simple docstring"""






from abc import ABC, abstractmethod
from argparse import ArgumentParser



class     UpperCAmelCase    (	__SCREAMING_SNAKE_CASE  ):



   @staticmethod
   @abstractmethod
   def    __UpperCAmelCase    (       __lowerCamelCase    :	ArgumentParser				):



     """simple docstring"""
     raise NotImplementedError()





   @abstractmethod
   def    __UpperCAmelCase    (       self    :	Optional[Any]				):



     """simple docstring"""
     raise NotImplementedError()





