






'''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  lowerCAmelCase_       :




										@staticmethod
										def 						__snake_case					(   *SCREAMING_SNAKE_CASE_     :   List[Any] ,							**SCREAMING_SNAKE_CASE_     :   Any	):
														pass
@is_pipeline_test
@require_vision
@require_timm
@require_torch
class  lowerCAmelCase_       (				unittest.TestCase					):
							UpperCamelCase_		:List[Any]		      =    MODEL_FOR_OBJECT_DETECTION_MAPPING




							def 						__snake_case					(   self     :   int ,							SCREAMING_SNAKE_CASE_     :   Any ,							SCREAMING_SNAKE_CASE_     :   Any ,							SCREAMING_SNAKE_CASE_     :   Any	):
											lowerCAmelCase__      			=						ObjectDetectionPipeline(model=SCREAMING_SNAKE_CASE_ ,							image_processor=SCREAMING_SNAKE_CASE_	)
											return object_detector, ["./tests/fixtures/tests_samples/COCO/000000039769.png"]




							def 						__snake_case					(   self     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   str ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any]	):
											lowerCAmelCase__      			=						object_detector('''./tests/fixtures/tests_samples/COCO/000000039769.png''' ,							threshold=0.0	)

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

											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(SCREAMING_SNAKE_CASE_ ,							threshold=0.0	)

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




							@require_tf
							@unittest.skip('''Object detection not implemented in TF'''	)
							def 						__snake_case					(   self     :   List[str]	):
											pass




							@require_torch
							def 						__snake_case					(   self     :   Tuple	):
											lowerCAmelCase__      			=						'hf-internal-testing/tiny-detr-mobilenetsv3'

											lowerCAmelCase__      			=						AutoModelForObjectDetection.from_pretrained(SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						AutoFeatureExtractor.from_pretrained(SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						ObjectDetectionPipeline(model=SCREAMING_SNAKE_CASE_ ,							feature_extractor=SCREAMING_SNAKE_CASE_	)

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

											self.assertEqual(
											    nested_simplify(SCREAMING_SNAKE_CASE_ ,							decimals=4	) ,							[
											        {'''score''': 0.3_376, '''label''': '''LABEL_0''', '''box''': {'''xmin''': 159, '''ymin''': 120, '''xmax''': 480, '''ymax''': 359}},
											        {'''score''': 0.3_376, '''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(SCREAMING_SNAKE_CASE_ ,							decimals=4	) ,							[
											        [
											            {'''score''': 0.3_376, '''label''': '''LABEL_0''', '''box''': {'''xmin''': 159, '''ymin''': 120, '''xmax''': 480, '''ymax''': 359}},
											            {'''score''': 0.3_376, '''label''': '''LABEL_0''', '''box''': {'''xmin''': 159, '''ymin''': 120, '''xmax''': 480, '''ymax''': 359}},
											        ],
											        [
											            {'''score''': 0.3_376, '''label''': '''LABEL_0''', '''box''': {'''xmin''': 159, '''ymin''': 120, '''xmax''': 480, '''ymax''': 359}},
											            {'''score''': 0.3_376, '''label''': '''LABEL_0''', '''box''': {'''xmin''': 159, '''ymin''': 120, '''xmax''': 480, '''ymax''': 359}},
											        ],
											    ] ,							)




							@require_torch
							@slow
							def 						__snake_case					(   self     :   List[str]	):
											lowerCAmelCase__      			=						'facebook/detr-resnet-50'

											lowerCAmelCase__      			=						AutoModelForObjectDetection.from_pretrained(SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						AutoFeatureExtractor.from_pretrained(SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						ObjectDetectionPipeline(model=SCREAMING_SNAKE_CASE_ ,							feature_extractor=SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						object_detector('''http://images.cocodataset.org/val2017/000000039769.jpg'''	)
											self.assertEqual(
											    nested_simplify(SCREAMING_SNAKE_CASE_ ,							decimals=4	) ,							[
											        {'''score''': 0.9_982, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 70, '''xmax''': 175, '''ymax''': 117}},
											        {'''score''': 0.9_960, '''label''': '''remote''', '''box''': {'''xmin''': 333, '''ymin''': 72, '''xmax''': 368, '''ymax''': 187}},
											        {'''score''': 0.9_955, '''label''': '''couch''', '''box''': {'''xmin''': 0, '''ymin''': 1, '''xmax''': 639, '''ymax''': 473}},
											        {'''score''': 0.9_988, '''label''': '''cat''', '''box''': {'''xmin''': 13, '''ymin''': 52, '''xmax''': 314, '''ymax''': 470}},
											        {'''score''': 0.9_987, '''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(SCREAMING_SNAKE_CASE_ ,							decimals=4	) ,							[
											        [
											            {'''score''': 0.9_982, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 70, '''xmax''': 175, '''ymax''': 117}},
											            {'''score''': 0.9_960, '''label''': '''remote''', '''box''': {'''xmin''': 333, '''ymin''': 72, '''xmax''': 368, '''ymax''': 187}},
											            {'''score''': 0.9_955, '''label''': '''couch''', '''box''': {'''xmin''': 0, '''ymin''': 1, '''xmax''': 639, '''ymax''': 473}},
											            {'''score''': 0.9_988, '''label''': '''cat''', '''box''': {'''xmin''': 13, '''ymin''': 52, '''xmax''': 314, '''ymax''': 470}},
											            {'''score''': 0.9_987, '''label''': '''cat''', '''box''': {'''xmin''': 345, '''ymin''': 23, '''xmax''': 640, '''ymax''': 368}},
											        ],
											        [
											            {'''score''': 0.9_982, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 70, '''xmax''': 175, '''ymax''': 117}},
											            {'''score''': 0.9_960, '''label''': '''remote''', '''box''': {'''xmin''': 333, '''ymin''': 72, '''xmax''': 368, '''ymax''': 187}},
											            {'''score''': 0.9_955, '''label''': '''couch''', '''box''': {'''xmin''': 0, '''ymin''': 1, '''xmax''': 639, '''ymax''': 473}},
											            {'''score''': 0.9_988, '''label''': '''cat''', '''box''': {'''xmin''': 13, '''ymin''': 52, '''xmax''': 314, '''ymax''': 470}},
											            {'''score''': 0.9_987, '''label''': '''cat''', '''box''': {'''xmin''': 345, '''ymin''': 23, '''xmax''': 640, '''ymax''': 368}},
											        ],
											    ] ,							)




							@require_torch
							@slow
							def 						__snake_case					(   self     :   Dict	):
											lowerCAmelCase__      			=						'facebook/detr-resnet-50'

											lowerCAmelCase__      			=						pipeline('''object-detection''' ,							model=SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						object_detector('''http://images.cocodataset.org/val2017/000000039769.jpg'''	)
											self.assertEqual(
											    nested_simplify(SCREAMING_SNAKE_CASE_ ,							decimals=4	) ,							[
											        {'''score''': 0.9_982, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 70, '''xmax''': 175, '''ymax''': 117}},
											        {'''score''': 0.9_960, '''label''': '''remote''', '''box''': {'''xmin''': 333, '''ymin''': 72, '''xmax''': 368, '''ymax''': 187}},
											        {'''score''': 0.9_955, '''label''': '''couch''', '''box''': {'''xmin''': 0, '''ymin''': 1, '''xmax''': 639, '''ymax''': 473}},
											        {'''score''': 0.9_988, '''label''': '''cat''', '''box''': {'''xmin''': 13, '''ymin''': 52, '''xmax''': 314, '''ymax''': 470}},
											        {'''score''': 0.9_987, '''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(SCREAMING_SNAKE_CASE_ ,							decimals=4	) ,							[
											        [
											            {'''score''': 0.9_982, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 70, '''xmax''': 175, '''ymax''': 117}},
											            {'''score''': 0.9_960, '''label''': '''remote''', '''box''': {'''xmin''': 333, '''ymin''': 72, '''xmax''': 368, '''ymax''': 187}},
											            {'''score''': 0.9_955, '''label''': '''couch''', '''box''': {'''xmin''': 0, '''ymin''': 1, '''xmax''': 639, '''ymax''': 473}},
											            {'''score''': 0.9_988, '''label''': '''cat''', '''box''': {'''xmin''': 13, '''ymin''': 52, '''xmax''': 314, '''ymax''': 470}},
											            {'''score''': 0.9_987, '''label''': '''cat''', '''box''': {'''xmin''': 345, '''ymin''': 23, '''xmax''': 640, '''ymax''': 368}},
											        ],
											        [
											            {'''score''': 0.9_982, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 70, '''xmax''': 175, '''ymax''': 117}},
											            {'''score''': 0.9_960, '''label''': '''remote''', '''box''': {'''xmin''': 333, '''ymin''': 72, '''xmax''': 368, '''ymax''': 187}},
											            {'''score''': 0.9_955, '''label''': '''couch''', '''box''': {'''xmin''': 0, '''ymin''': 1, '''xmax''': 639, '''ymax''': 473}},
											            {'''score''': 0.9_988, '''label''': '''cat''', '''box''': {'''xmin''': 13, '''ymin''': 52, '''xmax''': 314, '''ymax''': 470}},
											            {'''score''': 0.9_987, '''label''': '''cat''', '''box''': {'''xmin''': 345, '''ymin''': 23, '''xmax''': 640, '''ymax''': 368}},
											        ],
											    ] ,							)




							@require_torch
							@slow
							def 						__snake_case					(   self     :   List[Any]	):
											lowerCAmelCase__      			=						0.9_985
											lowerCAmelCase__      			=						'facebook/detr-resnet-50'

											lowerCAmelCase__      			=						pipeline('''object-detection''' ,							model=SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						object_detector('''http://images.cocodataset.org/val2017/000000039769.jpg''' ,							threshold=SCREAMING_SNAKE_CASE_	)
											self.assertEqual(
											    nested_simplify(SCREAMING_SNAKE_CASE_ ,							decimals=4	) ,							[
											        {'''score''': 0.9_988, '''label''': '''cat''', '''box''': {'''xmin''': 13, '''ymin''': 52, '''xmax''': 314, '''ymax''': 470}},
											        {'''score''': 0.9_987, '''label''': '''cat''', '''box''': {'''xmin''': 345, '''ymin''': 23, '''xmax''': 640, '''ymax''': 368}},
											    ] ,							)




							@require_torch
							@require_pytesseract
							@slow
							def 						__snake_case					(   self     :   str	):
											lowerCAmelCase__      			=						'Narsil/layoutlmv3-finetuned-funsd'
											lowerCAmelCase__      			=						0.9_993

											lowerCAmelCase__      			=						pipeline('''object-detection''' ,							model=SCREAMING_SNAKE_CASE_ ,							threshold=SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						object_detector(
											    '''https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/invoice.png'''	)
											self.assertEqual(
											    nested_simplify(SCREAMING_SNAKE_CASE_ ,							decimals=4	) ,							[
											        {'''score''': 0.9_993, '''label''': '''I-ANSWER''', '''box''': {'''xmin''': 294, '''ymin''': 254, '''xmax''': 343, '''ymax''': 264}},
											        {'''score''': 0.9_993, '''label''': '''I-ANSWER''', '''box''': {'''xmin''': 294, '''ymin''': 254, '''xmax''': 343, '''ymax''': 264}},
											    ] ,							)













from math import isclose, sqrt





def 	lowerCAmelCase_		(lowercase__						:       float     ,					lowercase__						:       float     ,					lowercase__						:       float       )		->    tuple[float, float, float]:


				'''simple docstring'''




				lowerCAmelCase__      			=						point_y / 4 / point_x
				lowerCAmelCase__      			=						2 * normal_gradient / (1 + normal_gradient * normal_gradient)
				lowerCAmelCase__      			=						(1 - normal_gradient * normal_gradient) / (
				    1 + normal_gradient * normal_gradient
				)
				lowerCAmelCase__      			=						(sa - ca * incoming_gradient) / (ca + sa * incoming_gradient)

				# to find the next point, solve the simultaeneous equations:
				# y^2 + 4x^2 = 100
				# y - b = m * (x - a)
				# ==> A x^2 + B x + C = 0
				lowerCAmelCase__      			=						outgoing_gradient**2 + 4
				lowerCAmelCase__      			=						2 * outgoing_gradient * (point_y - outgoing_gradient * point_x)
				lowerCAmelCase__      			=						(point_y - outgoing_gradient * point_x) ** 2 - 1_00

				lowerCAmelCase__      			=						(
				    -linear_term - sqrt(linear_term**2 - 4 * quadratic_term * constant_term       )
				) / (2 * quadratic_term)
				lowerCAmelCase__      			=						(
				    -linear_term + sqrt(linear_term**2 - 4 * quadratic_term * constant_term       )
				) / (2 * quadratic_term)

				# two solutions, one of which is our input point
				lowerCAmelCase__      			=						x_minus if isclose(lowercase__     ,					lowercase__       ) else x_plus
				lowerCAmelCase__      			=						point_y + outgoing_gradient * (next_x - point_x)

				return next_x, next_y, outgoing_gradient





def 	lowerCAmelCase_		(lowercase__						:       float = 1.4     ,					lowercase__						:       float = -9.6       )		->    int:


				'''simple docstring'''




				lowerCAmelCase__      			=						0
				lowerCAmelCase__      			=						first_x_coord
				lowerCAmelCase__      			=						first_y_coord
				lowerCAmelCase__      			=						(10.1 - point_y) / (0.0 - point_x)

				while not (-0.01 <= point_x <= 0.01 and point_y > 0):
								lowerCAmelCase__			,		lowerCAmelCase__			,		lowerCAmelCase__      			=						next_point(lowercase__     ,					lowercase__     ,					lowercase__       )
								num_reflections += 1

				return num_reflections


if __name__ == "__main__":
			print(F'''{solution() = }''')





