


"""simple docstring"""
import unittest

from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    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 						lowerCAmelCase    (			*UpperCAmelCase_							: Any						,    **UpperCAmelCase_							: List[str]    )   ->Optional[int]:



																		"""simple docstring"""



																		pass





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





							'''simple docstring'''

							__lowercase:						Optional[Any]							 =      MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING



							def 						lowerCAmelCase    (			self							: int						,    UpperCAmelCase_							: str						,    UpperCAmelCase_							: List[Any]						,    UpperCAmelCase_							: Union[str, Any]    )   ->Dict:



														"""simple docstring"""



														snake_case_          =						pipeline(
														    """zero-shot-object-detection"""						,    model="""hf-internal-testing/tiny-random-owlvit-object-detection"""    )

														snake_case_          =						[
														    {
														        """image""": """./tests/fixtures/tests_samples/COCO/000000039769.png""",
														        """candidate_labels""": ["""cat""", """remote""", """couch"""],
														    }
														]
														return object_detector, examples



							def 						lowerCAmelCase    (			self							: Optional[Any]						,    UpperCAmelCase_							: str						,    UpperCAmelCase_							: Union[str, Any]    )   ->Any:



														"""simple docstring"""



														snake_case_          =						object_detector(examples[0]						,    threshold=0.0    )

														snake_case_          =						len(__A    )
														self.assertGreater(__A						,    0    )
														self.assertEqual(
														    __A						,    [
														        {
														            """score""": ANY(__A    ),
														            """label""": ANY(__A    ),
														            """box""": {"""xmin""": ANY(__A    ), """ymin""": ANY(__A    ), """xmax""": ANY(__A    ), """ymax""": ANY(__A    )},
														        }
														        for i in range(__A    )
														    ]						,    )



							@require_tf
							@unittest.skip("""Zero Shot Object Detection not implemented in TF"""    )
							def 						lowerCAmelCase    (			self							: Union[str, Any]    )   ->Tuple:



														"""simple docstring"""



														pass



							@require_torch
							def 						lowerCAmelCase    (			self							: Optional[int]    )   ->Union[str, Any]:



														"""simple docstring"""



														snake_case_          =						pipeline(
														    """zero-shot-object-detection"""						,    model="""hf-internal-testing/tiny-random-owlvit-object-detection"""    )

														snake_case_          =						object_detector(
														    """./tests/fixtures/tests_samples/COCO/000000039769.png"""						,    candidate_labels=["""cat""", """remote""", """couch"""]						,    threshold=0.64						,    )

														self.assertEqual(
														    nested_simplify(__A						,    decimals=4    )						,    [
														        {"""score""": 0.7_235, """label""": """cat""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
														        {"""score""": 0.7_218, """label""": """remote""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
														        {"""score""": 0.7_184, """label""": """couch""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
														        {"""score""": 0.6_748, """label""": """remote""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
														        {"""score""": 0.6_656, """label""": """cat""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
														        {"""score""": 0.6_614, """label""": """couch""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
														        {"""score""": 0.6_456, """label""": """remote""", """box""": {"""xmin""": 494, """ymin""": 105, """xmax""": 521, """ymax""": 127}},
														        {"""score""": 0.642, """label""": """remote""", """box""": {"""xmin""": 67, """ymin""": 274, """xmax""": 93, """ymax""": 297}},
														        {"""score""": 0.6_419, """label""": """cat""", """box""": {"""xmin""": 494, """ymin""": 105, """xmax""": 521, """ymax""": 127}},
														    ]						,    )

														snake_case_          =						object_detector(
														    [
														        {
														            """image""": """./tests/fixtures/tests_samples/COCO/000000039769.png""",
														            """candidate_labels""": ["""cat""", """remote""", """couch"""],
														        }
														    ]						,    threshold=0.64						,    )

														self.assertEqual(
														    nested_simplify(__A						,    decimals=4    )						,    [
														        [
														            {"""score""": 0.7_235, """label""": """cat""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
														            {"""score""": 0.7_218, """label""": """remote""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
														            {"""score""": 0.7_184, """label""": """couch""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
														            {"""score""": 0.6_748, """label""": """remote""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
														            {"""score""": 0.6_656, """label""": """cat""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
														            {"""score""": 0.6_614, """label""": """couch""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
														            {"""score""": 0.6_456, """label""": """remote""", """box""": {"""xmin""": 494, """ymin""": 105, """xmax""": 521, """ymax""": 127}},
														            {"""score""": 0.642, """label""": """remote""", """box""": {"""xmin""": 67, """ymin""": 274, """xmax""": 93, """ymax""": 297}},
														            {"""score""": 0.6_419, """label""": """cat""", """box""": {"""xmin""": 494, """ymin""": 105, """xmax""": 521, """ymax""": 127}},
														        ]
														    ]						,    )



							@require_torch
							@slow
							def 						lowerCAmelCase    (			self							: List[str]    )   ->int:



														"""simple docstring"""



														snake_case_          =						pipeline("""zero-shot-object-detection"""    )

														snake_case_          =						object_detector(
														    """http://images.cocodataset.org/val2017/000000039769.jpg"""						,    candidate_labels=["""cat""", """remote""", """couch"""]						,    )
														self.assertEqual(
														    nested_simplify(__A						,    decimals=4    )						,    [
														        {"""score""": 0.2_868, """label""": """cat""", """box""": {"""xmin""": 324, """ymin""": 20, """xmax""": 640, """ymax""": 373}},
														        {"""score""": 0.277, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 72, """xmax""": 177, """ymax""": 115}},
														        {"""score""": 0.2_537, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 55, """xmax""": 315, """ymax""": 472}},
														        {"""score""": 0.1_474, """label""": """remote""", """box""": {"""xmin""": 335, """ymin""": 74, """xmax""": 371, """ymax""": 187}},
														        {"""score""": 0.1_208, """label""": """couch""", """box""": {"""xmin""": 4, """ymin""": 0, """xmax""": 642, """ymax""": 476}},
														    ]						,    )

														snake_case_          =						object_detector(
														    [
														        {
														            """image""": """http://images.cocodataset.org/val2017/000000039769.jpg""",
														            """candidate_labels""": ["""cat""", """remote""", """couch"""],
														        },
														        {
														            """image""": """http://images.cocodataset.org/val2017/000000039769.jpg""",
														            """candidate_labels""": ["""cat""", """remote""", """couch"""],
														        },
														    ]						,    )
														self.assertEqual(
														    nested_simplify(__A						,    decimals=4    )						,    [
														        [
														            {"""score""": 0.2_868, """label""": """cat""", """box""": {"""xmin""": 324, """ymin""": 20, """xmax""": 640, """ymax""": 373}},
														            {"""score""": 0.277, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 72, """xmax""": 177, """ymax""": 115}},
														            {"""score""": 0.2_537, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 55, """xmax""": 315, """ymax""": 472}},
														            {"""score""": 0.1_474, """label""": """remote""", """box""": {"""xmin""": 335, """ymin""": 74, """xmax""": 371, """ymax""": 187}},
														            {"""score""": 0.1_208, """label""": """couch""", """box""": {"""xmin""": 4, """ymin""": 0, """xmax""": 642, """ymax""": 476}},
														        ],
														        [
														            {"""score""": 0.2_868, """label""": """cat""", """box""": {"""xmin""": 324, """ymin""": 20, """xmax""": 640, """ymax""": 373}},
														            {"""score""": 0.277, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 72, """xmax""": 177, """ymax""": 115}},
														            {"""score""": 0.2_537, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 55, """xmax""": 315, """ymax""": 472}},
														            {"""score""": 0.1_474, """label""": """remote""", """box""": {"""xmin""": 335, """ymin""": 74, """xmax""": 371, """ymax""": 187}},
														            {"""score""": 0.1_208, """label""": """couch""", """box""": {"""xmin""": 4, """ymin""": 0, """xmax""": 642, """ymax""": 476}},
														        ],
														    ]						,    )



							@require_tf
							@unittest.skip("""Zero Shot Object Detection not implemented in TF"""    )
							def 						lowerCAmelCase    (			self							: Optional[Any]    )   ->int:



														"""simple docstring"""



														pass



							@require_torch
							@slow
							def 						lowerCAmelCase    (			self							: Dict    )   ->List[Any]:



														"""simple docstring"""



														snake_case_          =						0.2
														snake_case_          =						pipeline("""zero-shot-object-detection"""    )

														snake_case_          =						object_detector(
														    """http://images.cocodataset.org/val2017/000000039769.jpg"""						,    candidate_labels=["""cat""", """remote""", """couch"""]						,    threshold=__A						,    )
														self.assertEqual(
														    nested_simplify(__A						,    decimals=4    )						,    [
														        {"""score""": 0.2_868, """label""": """cat""", """box""": {"""xmin""": 324, """ymin""": 20, """xmax""": 640, """ymax""": 373}},
														        {"""score""": 0.277, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 72, """xmax""": 177, """ymax""": 115}},
														        {"""score""": 0.2_537, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 55, """xmax""": 315, """ymax""": 472}},
														    ]						,    )



							@require_torch
							@slow
							def 						lowerCAmelCase    (			self							: int    )   ->Tuple:



														"""simple docstring"""



														snake_case_          =						2
														snake_case_          =						pipeline("""zero-shot-object-detection"""    )

														snake_case_          =						object_detector(
														    """http://images.cocodataset.org/val2017/000000039769.jpg"""						,    candidate_labels=["""cat""", """remote""", """couch"""]						,    top_k=__A						,    )
														self.assertEqual(
														    nested_simplify(__A						,    decimals=4    )						,    [
														        {"""score""": 0.2_868, """label""": """cat""", """box""": {"""xmin""": 324, """ymin""": 20, """xmax""": 640, """ymax""": 373}},
														        {"""score""": 0.277, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 72, """xmax""": 177, """ymax""": 115}},
														    ]						,    )










"""simple docstring"""
from __future__ import annotations

from collections.abc import Iterator





class        __A       :





							'''simple docstring'''

							def __init__(			self							: Any						,    UpperCAmelCase_							: int    )   ->None:



														"""simple docstring"""



														snake_case_          =						value
														snake_case_          =						None
														snake_case_          =						None





class        __A       :





							'''simple docstring'''

							def __init__(			self							: List[Any]						,    UpperCAmelCase_							: Node    )   ->None:



														"""simple docstring"""



														snake_case_          =						tree



							def 						lowerCAmelCase    (			self							: List[str]						,    UpperCAmelCase_							: Node | None    )   ->int:



														"""simple docstring"""



														if node is None:
																					return 0
														return node.value + (
														    self.depth_first_search(node.left    ) + self.depth_first_search(node.right    )
														)



							def __iter__(			self							: str    )   ->Iterator[int]:



														"""simple docstring"""



														yield self.depth_first_search(self.tree    )


if __name__ == "__main__":
				import doctest

				doctest.testmod()



