






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			:



     """simple docstring"""



     @staticmethod
     def 					__magic_name__							(      *UpperCamelCase__    :    List[str]			,		**UpperCamelCase__    :    List[str]):






            '''simple docstring'''







            pass


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



    """simple docstring"""



    _lowercase				:   Union[str, Any]      =  MODEL_FOR_OBJECT_DETECTION_MAPPING



    def 					__magic_name__							(      self    :    Union[str, Any]			,		UpperCamelCase__    :    Any			,		UpperCamelCase__    :    int			,		UpperCamelCase__    :    str):






           '''simple docstring'''







           snake_case__	  =       ObjectDetectionPipeline(model=__UpperCamelCase			,		image_processor=__UpperCamelCase)
           return object_detector, ["./tests/fixtures/tests_samples/COCO/000000039769.png"]



    def 					__magic_name__							(      self    :    Optional[Any]			,		UpperCamelCase__    :    int			,		UpperCamelCase__    :    Optional[int]):






           '''simple docstring'''







           snake_case__	  =       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

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

           snake_case__	  =       [
               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"""],
           ]
           snake_case__	  =       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 					__magic_name__							(      self    :    Optional[Any]):






           '''simple docstring'''







           pass



    @require_torch
    def 					__magic_name__							(      self    :    Tuple):






           '''simple docstring'''







           snake_case__	  =       """hf-internal-testing/tiny-detr-mobilenetsv3"""

           snake_case__	  =       AutoModelForObjectDetection.from_pretrained(__UpperCamelCase)
           snake_case__	  =       AutoFeatureExtractor.from_pretrained(__UpperCamelCase)
           snake_case__	  =       ObjectDetectionPipeline(model=__UpperCamelCase			,		feature_extractor=__UpperCamelCase)

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

           self.assertEqual(
               nested_simplify(__UpperCamelCase			,		decimals=4)			,		[
                   {"""score""": 0.33_76, """label""": """LABEL_0""", """box""": {"""xmin""": 1_5_9, """ymin""": 1_2_0, """xmax""": 4_8_0, """ymax""": 3_5_9}},
                   {"""score""": 0.33_76, """label""": """LABEL_0""", """box""": {"""xmin""": 1_5_9, """ymin""": 1_2_0, """xmax""": 4_8_0, """ymax""": 3_5_9}},
               ]			,		)

           snake_case__	  =       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""": 0.33_76, """label""": """LABEL_0""", """box""": {"""xmin""": 1_5_9, """ymin""": 1_2_0, """xmax""": 4_8_0, """ymax""": 3_5_9}},
                       {"""score""": 0.33_76, """label""": """LABEL_0""", """box""": {"""xmin""": 1_5_9, """ymin""": 1_2_0, """xmax""": 4_8_0, """ymax""": 3_5_9}},
                   ],
                   [
                       {"""score""": 0.33_76, """label""": """LABEL_0""", """box""": {"""xmin""": 1_5_9, """ymin""": 1_2_0, """xmax""": 4_8_0, """ymax""": 3_5_9}},
                       {"""score""": 0.33_76, """label""": """LABEL_0""", """box""": {"""xmin""": 1_5_9, """ymin""": 1_2_0, """xmax""": 4_8_0, """ymax""": 3_5_9}},
                   ],
               ]			,		)



    @require_torch
    @slow
    def 					__magic_name__							(      self    :    int):






           '''simple docstring'''







           snake_case__	  =       """facebook/detr-resnet-50"""

           snake_case__	  =       AutoModelForObjectDetection.from_pretrained(__UpperCamelCase)
           snake_case__	  =       AutoFeatureExtractor.from_pretrained(__UpperCamelCase)
           snake_case__	  =       ObjectDetectionPipeline(model=__UpperCamelCase			,		feature_extractor=__UpperCamelCase)

           snake_case__	  =       object_detector("""http://images.cocodataset.org/val2017/000000039769.jpg""")
           self.assertEqual(
               nested_simplify(__UpperCamelCase			,		decimals=4)			,		[
                   {"""score""": 0.99_82, """label""": """remote""", """box""": {"""xmin""": 4_0, """ymin""": 7_0, """xmax""": 1_7_5, """ymax""": 1_1_7}},
                   {"""score""": 0.99_60, """label""": """remote""", """box""": {"""xmin""": 3_3_3, """ymin""": 7_2, """xmax""": 3_6_8, """ymax""": 1_8_7}},
                   {"""score""": 0.99_55, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 6_3_9, """ymax""": 4_7_3}},
                   {"""score""": 0.99_88, """label""": """cat""", """box""": {"""xmin""": 1_3, """ymin""": 5_2, """xmax""": 3_1_4, """ymax""": 4_7_0}},
                   {"""score""": 0.99_87, """label""": """cat""", """box""": {"""xmin""": 3_4_5, """ymin""": 2_3, """xmax""": 6_4_0, """ymax""": 3_6_8}},
               ]			,		)

           snake_case__	  =       object_detector(
               [
                   """http://images.cocodataset.org/val2017/000000039769.jpg""",
                   """http://images.cocodataset.org/val2017/000000039769.jpg""",
               ])
           self.assertEqual(
               nested_simplify(__UpperCamelCase			,		decimals=4)			,		[
                   [
                       {"""score""": 0.99_82, """label""": """remote""", """box""": {"""xmin""": 4_0, """ymin""": 7_0, """xmax""": 1_7_5, """ymax""": 1_1_7}},
                       {"""score""": 0.99_60, """label""": """remote""", """box""": {"""xmin""": 3_3_3, """ymin""": 7_2, """xmax""": 3_6_8, """ymax""": 1_8_7}},
                       {"""score""": 0.99_55, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 6_3_9, """ymax""": 4_7_3}},
                       {"""score""": 0.99_88, """label""": """cat""", """box""": {"""xmin""": 1_3, """ymin""": 5_2, """xmax""": 3_1_4, """ymax""": 4_7_0}},
                       {"""score""": 0.99_87, """label""": """cat""", """box""": {"""xmin""": 3_4_5, """ymin""": 2_3, """xmax""": 6_4_0, """ymax""": 3_6_8}},
                   ],
                   [
                       {"""score""": 0.99_82, """label""": """remote""", """box""": {"""xmin""": 4_0, """ymin""": 7_0, """xmax""": 1_7_5, """ymax""": 1_1_7}},
                       {"""score""": 0.99_60, """label""": """remote""", """box""": {"""xmin""": 3_3_3, """ymin""": 7_2, """xmax""": 3_6_8, """ymax""": 1_8_7}},
                       {"""score""": 0.99_55, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 6_3_9, """ymax""": 4_7_3}},
                       {"""score""": 0.99_88, """label""": """cat""", """box""": {"""xmin""": 1_3, """ymin""": 5_2, """xmax""": 3_1_4, """ymax""": 4_7_0}},
                       {"""score""": 0.99_87, """label""": """cat""", """box""": {"""xmin""": 3_4_5, """ymin""": 2_3, """xmax""": 6_4_0, """ymax""": 3_6_8}},
                   ],
               ]			,		)



    @require_torch
    @slow
    def 					__magic_name__							(      self    :    Any):






           '''simple docstring'''







           snake_case__	  =       """facebook/detr-resnet-50"""

           snake_case__	  =       pipeline("""object-detection"""			,		model=__UpperCamelCase)

           snake_case__	  =       object_detector("""http://images.cocodataset.org/val2017/000000039769.jpg""")
           self.assertEqual(
               nested_simplify(__UpperCamelCase			,		decimals=4)			,		[
                   {"""score""": 0.99_82, """label""": """remote""", """box""": {"""xmin""": 4_0, """ymin""": 7_0, """xmax""": 1_7_5, """ymax""": 1_1_7}},
                   {"""score""": 0.99_60, """label""": """remote""", """box""": {"""xmin""": 3_3_3, """ymin""": 7_2, """xmax""": 3_6_8, """ymax""": 1_8_7}},
                   {"""score""": 0.99_55, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 6_3_9, """ymax""": 4_7_3}},
                   {"""score""": 0.99_88, """label""": """cat""", """box""": {"""xmin""": 1_3, """ymin""": 5_2, """xmax""": 3_1_4, """ymax""": 4_7_0}},
                   {"""score""": 0.99_87, """label""": """cat""", """box""": {"""xmin""": 3_4_5, """ymin""": 2_3, """xmax""": 6_4_0, """ymax""": 3_6_8}},
               ]			,		)

           snake_case__	  =       object_detector(
               [
                   """http://images.cocodataset.org/val2017/000000039769.jpg""",
                   """http://images.cocodataset.org/val2017/000000039769.jpg""",
               ])
           self.assertEqual(
               nested_simplify(__UpperCamelCase			,		decimals=4)			,		[
                   [
                       {"""score""": 0.99_82, """label""": """remote""", """box""": {"""xmin""": 4_0, """ymin""": 7_0, """xmax""": 1_7_5, """ymax""": 1_1_7}},
                       {"""score""": 0.99_60, """label""": """remote""", """box""": {"""xmin""": 3_3_3, """ymin""": 7_2, """xmax""": 3_6_8, """ymax""": 1_8_7}},
                       {"""score""": 0.99_55, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 6_3_9, """ymax""": 4_7_3}},
                       {"""score""": 0.99_88, """label""": """cat""", """box""": {"""xmin""": 1_3, """ymin""": 5_2, """xmax""": 3_1_4, """ymax""": 4_7_0}},
                       {"""score""": 0.99_87, """label""": """cat""", """box""": {"""xmin""": 3_4_5, """ymin""": 2_3, """xmax""": 6_4_0, """ymax""": 3_6_8}},
                   ],
                   [
                       {"""score""": 0.99_82, """label""": """remote""", """box""": {"""xmin""": 4_0, """ymin""": 7_0, """xmax""": 1_7_5, """ymax""": 1_1_7}},
                       {"""score""": 0.99_60, """label""": """remote""", """box""": {"""xmin""": 3_3_3, """ymin""": 7_2, """xmax""": 3_6_8, """ymax""": 1_8_7}},
                       {"""score""": 0.99_55, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 6_3_9, """ymax""": 4_7_3}},
                       {"""score""": 0.99_88, """label""": """cat""", """box""": {"""xmin""": 1_3, """ymin""": 5_2, """xmax""": 3_1_4, """ymax""": 4_7_0}},
                       {"""score""": 0.99_87, """label""": """cat""", """box""": {"""xmin""": 3_4_5, """ymin""": 2_3, """xmax""": 6_4_0, """ymax""": 3_6_8}},
                   ],
               ]			,		)



    @require_torch
    @slow
    def 					__magic_name__							(      self    :    List[str]):






           '''simple docstring'''







           snake_case__	  =       0.99_85
           snake_case__	  =       """facebook/detr-resnet-50"""

           snake_case__	  =       pipeline("""object-detection"""			,		model=__UpperCamelCase)

           snake_case__	  =       object_detector("""http://images.cocodataset.org/val2017/000000039769.jpg"""			,		threshold=__UpperCamelCase)
           self.assertEqual(
               nested_simplify(__UpperCamelCase			,		decimals=4)			,		[
                   {"""score""": 0.99_88, """label""": """cat""", """box""": {"""xmin""": 1_3, """ymin""": 5_2, """xmax""": 3_1_4, """ymax""": 4_7_0}},
                   {"""score""": 0.99_87, """label""": """cat""", """box""": {"""xmin""": 3_4_5, """ymin""": 2_3, """xmax""": 6_4_0, """ymax""": 3_6_8}},
               ]			,		)



    @require_torch
    @require_pytesseract
    @slow
    def 					__magic_name__							(      self    :    Union[str, Any]):






           '''simple docstring'''







           snake_case__	  =       """Narsil/layoutlmv3-finetuned-funsd"""
           snake_case__	  =       0.99_93

           snake_case__	  =       pipeline("""object-detection"""			,		model=__UpperCamelCase			,		threshold=__UpperCamelCase)

           snake_case__	  =       object_detector(
               """https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/invoice.png""")
           self.assertEqual(
               nested_simplify(__UpperCamelCase			,		decimals=4)			,		[
                   {"""score""": 0.99_93, """label""": """I-ANSWER""", """box""": {"""xmin""": 2_9_4, """ymin""": 2_5_4, """xmax""": 3_4_3, """ymax""": 2_6_4}},
                   {"""score""": 0.99_93, """label""": """I-ANSWER""", """box""": {"""xmin""": 2_9_4, """ymin""": 2_5_4, """xmax""": 3_4_3, """ymax""": 2_6_4}},
               ]			,		)








from __future__ import annotations


class    _lowerCAmelCase			:



				"""simple docstring"""



				def __init__(      self    :    Optional[int]			,		UpperCamelCase__    :    int):






											'''simple docstring'''







											snake_case__	  =       data
											snake_case__	  =       None
											snake_case__	  =       None


def _UpperCAmelCase   (	a						:	Node | None ):  # In Order traversal of the tree
							if tree:
														display(tree.left )
														print(tree.data )
														display(tree.right )

def _UpperCAmelCase   (	a						:	Node | None ):
							return 1 + max(depth_of_tree(tree.left )  ,					depth_of_tree(tree.right ) ) if tree else 0

def _UpperCAmelCase   (	a						:	Node ):
							if not tree:
														return True
							if tree.left and tree.right:
														return is_full_binary_tree(tree.left ) and is_full_binary_tree(tree.right )
							else:
														return not tree.left and not tree.right

def _UpperCAmelCase   (	):  # Main function for testing.
							snake_case__	  =       Node(1 )
							snake_case__	  =       Node(2 )
							snake_case__	  =       Node(3 )
							snake_case__	  =       Node(4 )
							snake_case__	  =       Node(5 )
							snake_case__	  =       Node(6 )
							snake_case__	  =       Node(7 )
							snake_case__	  =       Node(8 )
							snake_case__	  =       Node(9 )

							print(is_full_binary_tree(a ) )
							print(depth_of_tree(a ) )
							print("""Tree is: """ )
							display(a )


if __name__ == "__main__":
	main()
