





'''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 UpperCAmelCase				:



        @staticmethod
        def        __lowerCamelCase    (	*__A  ,      **__A       ):
         pass






@is_pipeline_test
@require_vision
@require_torch
class UpperCAmelCase				(		unittest.TestCase				):
    _A			:      List[str]     =							MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING



    def        __lowerCamelCase    (	self  ,      __A  ,      __A  ,      __A       ):
     __UpperCAmelCase       = pipeline(
         'zero-shot-object-detection'  ,      model='hf-internal-testing/tiny-random-owlvit-object-detection'       )

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



    def        __lowerCamelCase    (	self  ,      __A  ,      __A       ):
     __UpperCAmelCase       = object_detector(examples[0]  ,      threshold=0.0       )

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



    @require_tf
    @unittest.skip('Zero Shot Object Detection not implemented in TF'       )
    def        __lowerCamelCase    (	self       ):
     pass



    @require_torch
    def        __lowerCamelCase    (	self       ):
     __UpperCAmelCase       = pipeline(
         'zero-shot-object-detection'  ,      model='hf-internal-testing/tiny-random-owlvit-object-detection'       )

     __UpperCAmelCase       = object_detector(
         './tests/fixtures/tests_samples/COCO/000000039769.png'  ,      candidate_labels=['cat', 'remote', 'couch']  ,      threshold=0.6_4  ,      )

     self.assertEqual(
         nested_simplify(_snake_case  ,      decimals=4       )  ,      [
             {'score': 0.7_2_3_5, 'label': 'cat', 'box': {'xmin': 204, 'ymin': 167, 'xmax': 232, 'ymax': 190}},
             {'score': 0.7_2_1_8, 'label': 'remote', 'box': {'xmin': 204, 'ymin': 167, 'xmax': 232, 'ymax': 190}},
             {'score': 0.7_1_8_4, 'label': 'couch', 'box': {'xmin': 204, 'ymin': 167, 'xmax': 232, 'ymax': 190}},
             {'score': 0.6_7_4_8, 'label': 'remote', 'box': {'xmin': 571, 'ymin': 83, 'xmax': 598, 'ymax': 103}},
             {'score': 0.6_6_5_6, 'label': 'cat', 'box': {'xmin': 571, 'ymin': 83, 'xmax': 598, 'ymax': 103}},
             {'score': 0.6_6_1_4, 'label': 'couch', 'box': {'xmin': 571, 'ymin': 83, 'xmax': 598, 'ymax': 103}},
             {'score': 0.6_4_5_6, 'label': 'remote', 'box': {'xmin': 494, 'ymin': 105, 'xmax': 521, 'ymax': 127}},
             {'score': 0.6_4_2, 'label': 'remote', 'box': {'xmin': 67, 'ymin': 274, 'xmax': 93, 'ymax': 297}},
             {'score': 0.6_4_1_9, 'label': 'cat', 'box': {'xmin': 494, 'ymin': 105, 'xmax': 521, 'ymax': 127}},
         ]  ,      )

     __UpperCAmelCase       = object_detector(
         [
             {
                 'image': './tests/fixtures/tests_samples/COCO/000000039769.png',
                 'candidate_labels': ['cat', 'remote', 'couch'],
             }
         ]  ,      threshold=0.6_4  ,      )

     self.assertEqual(
         nested_simplify(_snake_case  ,      decimals=4       )  ,      [
             [
                 {'score': 0.7_2_3_5, 'label': 'cat', 'box': {'xmin': 204, 'ymin': 167, 'xmax': 232, 'ymax': 190}},
                 {'score': 0.7_2_1_8, 'label': 'remote', 'box': {'xmin': 204, 'ymin': 167, 'xmax': 232, 'ymax': 190}},
                 {'score': 0.7_1_8_4, 'label': 'couch', 'box': {'xmin': 204, 'ymin': 167, 'xmax': 232, 'ymax': 190}},
                 {'score': 0.6_7_4_8, 'label': 'remote', 'box': {'xmin': 571, 'ymin': 83, 'xmax': 598, 'ymax': 103}},
                 {'score': 0.6_6_5_6, 'label': 'cat', 'box': {'xmin': 571, 'ymin': 83, 'xmax': 598, 'ymax': 103}},
                 {'score': 0.6_6_1_4, 'label': 'couch', 'box': {'xmin': 571, 'ymin': 83, 'xmax': 598, 'ymax': 103}},
                 {'score': 0.6_4_5_6, 'label': 'remote', 'box': {'xmin': 494, 'ymin': 105, 'xmax': 521, 'ymax': 127}},
                 {'score': 0.6_4_2, 'label': 'remote', 'box': {'xmin': 67, 'ymin': 274, 'xmax': 93, 'ymax': 297}},
                 {'score': 0.6_4_1_9, 'label': 'cat', 'box': {'xmin': 494, 'ymin': 105, 'xmax': 521, 'ymax': 127}},
             ]
         ]  ,      )



    @require_torch
    @slow
    def        __lowerCamelCase    (	self       ):
     __UpperCAmelCase       = pipeline('zero-shot-object-detection'       )

     __UpperCAmelCase       = object_detector(
         'http://images.cocodataset.org/val2017/000000039769.jpg'  ,      candidate_labels=['cat', 'remote', 'couch']  ,      )
     self.assertEqual(
         nested_simplify(_snake_case  ,      decimals=4       )  ,      [
             {'score': 0.2_8_6_8, 'label': 'cat', 'box': {'xmin': 324, 'ymin': 20, 'xmax': 640, 'ymax': 373}},
             {'score': 0.2_7_7, 'label': 'remote', 'box': {'xmin': 40, 'ymin': 72, 'xmax': 177, 'ymax': 115}},
             {'score': 0.2_5_3_7, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 55, 'xmax': 315, 'ymax': 472}},
             {'score': 0.1_4_7_4, 'label': 'remote', 'box': {'xmin': 335, 'ymin': 74, 'xmax': 371, 'ymax': 187}},
             {'score': 0.1_2_0_8, 'label': 'couch', 'box': {'xmin': 4, 'ymin': 0, 'xmax': 642, 'ymax': 476}},
         ]  ,      )

     __UpperCAmelCase       = 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(_snake_case  ,      decimals=4       )  ,      [
             [
                 {'score': 0.2_8_6_8, 'label': 'cat', 'box': {'xmin': 324, 'ymin': 20, 'xmax': 640, 'ymax': 373}},
                 {'score': 0.2_7_7, 'label': 'remote', 'box': {'xmin': 40, 'ymin': 72, 'xmax': 177, 'ymax': 115}},
                 {'score': 0.2_5_3_7, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 55, 'xmax': 315, 'ymax': 472}},
                 {'score': 0.1_4_7_4, 'label': 'remote', 'box': {'xmin': 335, 'ymin': 74, 'xmax': 371, 'ymax': 187}},
                 {'score': 0.1_2_0_8, 'label': 'couch', 'box': {'xmin': 4, 'ymin': 0, 'xmax': 642, 'ymax': 476}},
             ],
             [
                 {'score': 0.2_8_6_8, 'label': 'cat', 'box': {'xmin': 324, 'ymin': 20, 'xmax': 640, 'ymax': 373}},
                 {'score': 0.2_7_7, 'label': 'remote', 'box': {'xmin': 40, 'ymin': 72, 'xmax': 177, 'ymax': 115}},
                 {'score': 0.2_5_3_7, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 55, 'xmax': 315, 'ymax': 472}},
                 {'score': 0.1_4_7_4, 'label': 'remote', 'box': {'xmin': 335, 'ymin': 74, 'xmax': 371, 'ymax': 187}},
                 {'score': 0.1_2_0_8, '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       ):
     pass



    @require_torch
    @slow
    def        __lowerCamelCase    (	self       ):
     __UpperCAmelCase       = 0.2
     __UpperCAmelCase       = pipeline('zero-shot-object-detection'       )

     __UpperCAmelCase       = object_detector(
         'http://images.cocodataset.org/val2017/000000039769.jpg'  ,      candidate_labels=['cat', 'remote', 'couch']  ,      threshold=_snake_case  ,      )
     self.assertEqual(
         nested_simplify(_snake_case  ,      decimals=4       )  ,      [
             {'score': 0.2_8_6_8, 'label': 'cat', 'box': {'xmin': 324, 'ymin': 20, 'xmax': 640, 'ymax': 373}},
             {'score': 0.2_7_7, 'label': 'remote', 'box': {'xmin': 40, 'ymin': 72, 'xmax': 177, 'ymax': 115}},
             {'score': 0.2_5_3_7, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 55, 'xmax': 315, 'ymax': 472}},
         ]  ,      )




    @require_torch
    @slow
    def        __lowerCamelCase    (	self       ):
     __UpperCAmelCase       = 2
     __UpperCAmelCase       = pipeline('zero-shot-object-detection'       )

     __UpperCAmelCase       = object_detector(
         'http://images.cocodataset.org/val2017/000000039769.jpg'  ,      candidate_labels=['cat', 'remote', 'couch']  ,      top_k=_snake_case  ,      )
     self.assertEqual(
         nested_simplify(_snake_case  ,      decimals=4       )  ,      [
             {'score': 0.2_8_6_8, 'label': 'cat', 'box': {'xmin': 324, 'ymin': 20, 'xmax': 640, 'ymax': 373}},
             {'score': 0.2_7_7, 'label': 'remote', 'box': {'xmin': 40, 'ymin': 72, 'xmax': 177, 'ymax': 115}},
         ]  ,      )










from __future__ import annotations


def A    (							__UpperCamelCase = 4       )    ->   list[list[int]]:
			A__	  =     abs(__UpperCamelCase       ) or 4
			return [[1 + x + y * row_size for x in range(__UpperCamelCase       )] for y in range(__UpperCamelCase       )]


def A    (							__UpperCamelCase       )    ->   list[list[int]]:
			return reverse_row(transpose(__UpperCamelCase       )       )
			# OR.. transpose(reverse_column(matrix))


def A    (							__UpperCamelCase       )    ->   list[list[int]]:
			return reverse_row(reverse_column(__UpperCamelCase       )       )
			# OR.. reverse_column(reverse_row(matrix))


def A    (							__UpperCamelCase       )    ->   list[list[int]]:
			return reverse_column(transpose(__UpperCamelCase       )       )
			# OR.. transpose(reverse_row(matrix))


def A    (							__UpperCamelCase       )    ->   list[list[int]]:
			A__	  =     [list(__UpperCamelCase       ) for x in zip(*__UpperCamelCase       )]
			return matrix


def A    (							__UpperCamelCase       )    ->   list[list[int]]:
			A__	  =     matrix[::-1]
			return matrix


def A    (							__UpperCamelCase       )    ->   list[list[int]]:
			A__	  =     [x[::-1] for x in matrix]
			return matrix


def A    (							__UpperCamelCase       )    ->   None:
			for i in matrix:
						print(*__UpperCamelCase       )


if __name__ == "__main__":
							SCREAMING_SNAKE_CASE__   			=   make_matrix()
							print('''\norigin:\n''')
							print_matrix(matrix)
							print('''\nrotate 90 counterclockwise:\n''')
							print_matrix(rotate_aa(matrix))

							SCREAMING_SNAKE_CASE__   			=   make_matrix()
							print('''\norigin:\n''')
							print_matrix(matrix)
							print('''\nrotate 180:\n''')
							print_matrix(rotate_aaa(matrix))

							SCREAMING_SNAKE_CASE__   			=   make_matrix()
							print('''\norigin:\n''')
							print_matrix(matrix)
							print('''\nrotate 270 counterclockwise:\n''')
							print_matrix(rotate_aaa(matrix))




