



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 							lowerCamelCase_:





								'''simple docstring'''



								@staticmethod
								def 			snake_case__      (    *lowerCamelCase__				,       **lowerCamelCase__   ):
												pass


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





					'''simple docstring'''



					lowercase__   :       Optional[Any]										= MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__				,       lowerCamelCase__   ):
									_lowerCamelCase        =				pipeline(
									    '''zero-shot-object-detection'''				,       model='''hf-internal-testing/tiny-random-owlvit-object-detection'''   )

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

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__   ):
									_lowerCamelCase        =				object_detector(examples[0]				,       threshold=0.0   )

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

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

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

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

									self.assertEqual(
									    nested_simplify(UpperCamelCase_				,       decimals=4   )				,       [
									        {'''score''': 0.7_2_3_5, '''label''': '''cat''', '''box''': {'''xmin''': 2_0_4, '''ymin''': 1_6_7, '''xmax''': 2_3_2, '''ymax''': 1_9_0}},
									        {'''score''': 0.7_2_1_8, '''label''': '''remote''', '''box''': {'''xmin''': 2_0_4, '''ymin''': 1_6_7, '''xmax''': 2_3_2, '''ymax''': 1_9_0}},
									        {'''score''': 0.7_1_8_4, '''label''': '''couch''', '''box''': {'''xmin''': 2_0_4, '''ymin''': 1_6_7, '''xmax''': 2_3_2, '''ymax''': 1_9_0}},
									        {'''score''': 0.6_7_4_8, '''label''': '''remote''', '''box''': {'''xmin''': 5_7_1, '''ymin''': 8_3, '''xmax''': 5_9_8, '''ymax''': 1_0_3}},
									        {'''score''': 0.6_6_5_6, '''label''': '''cat''', '''box''': {'''xmin''': 5_7_1, '''ymin''': 8_3, '''xmax''': 5_9_8, '''ymax''': 1_0_3}},
									        {'''score''': 0.6_6_1_4, '''label''': '''couch''', '''box''': {'''xmin''': 5_7_1, '''ymin''': 8_3, '''xmax''': 5_9_8, '''ymax''': 1_0_3}},
									        {'''score''': 0.6_4_5_6, '''label''': '''remote''', '''box''': {'''xmin''': 4_9_4, '''ymin''': 1_0_5, '''xmax''': 5_2_1, '''ymax''': 1_2_7}},
									        {'''score''': 0.6_4_2, '''label''': '''remote''', '''box''': {'''xmin''': 6_7, '''ymin''': 2_7_4, '''xmax''': 9_3, '''ymax''': 2_9_7}},
									        {'''score''': 0.6_4_1_9, '''label''': '''cat''', '''box''': {'''xmin''': 4_9_4, '''ymin''': 1_0_5, '''xmax''': 5_2_1, '''ymax''': 1_2_7}},
									    ]				,       )

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

									self.assertEqual(
									    nested_simplify(UpperCamelCase_				,       decimals=4   )				,       [
									        [
									            {'''score''': 0.7_2_3_5, '''label''': '''cat''', '''box''': {'''xmin''': 2_0_4, '''ymin''': 1_6_7, '''xmax''': 2_3_2, '''ymax''': 1_9_0}},
									            {'''score''': 0.7_2_1_8, '''label''': '''remote''', '''box''': {'''xmin''': 2_0_4, '''ymin''': 1_6_7, '''xmax''': 2_3_2, '''ymax''': 1_9_0}},
									            {'''score''': 0.7_1_8_4, '''label''': '''couch''', '''box''': {'''xmin''': 2_0_4, '''ymin''': 1_6_7, '''xmax''': 2_3_2, '''ymax''': 1_9_0}},
									            {'''score''': 0.6_7_4_8, '''label''': '''remote''', '''box''': {'''xmin''': 5_7_1, '''ymin''': 8_3, '''xmax''': 5_9_8, '''ymax''': 1_0_3}},
									            {'''score''': 0.6_6_5_6, '''label''': '''cat''', '''box''': {'''xmin''': 5_7_1, '''ymin''': 8_3, '''xmax''': 5_9_8, '''ymax''': 1_0_3}},
									            {'''score''': 0.6_6_1_4, '''label''': '''couch''', '''box''': {'''xmin''': 5_7_1, '''ymin''': 8_3, '''xmax''': 5_9_8, '''ymax''': 1_0_3}},
									            {'''score''': 0.6_4_5_6, '''label''': '''remote''', '''box''': {'''xmin''': 4_9_4, '''ymin''': 1_0_5, '''xmax''': 5_2_1, '''ymax''': 1_2_7}},
									            {'''score''': 0.6_4_2, '''label''': '''remote''', '''box''': {'''xmin''': 6_7, '''ymin''': 2_7_4, '''xmax''': 9_3, '''ymax''': 2_9_7}},
									            {'''score''': 0.6_4_1_9, '''label''': '''cat''', '''box''': {'''xmin''': 4_9_4, '''ymin''': 1_0_5, '''xmax''': 5_2_1, '''ymax''': 1_2_7}},
									        ]
									    ]				,       )

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

									_lowerCamelCase        =				object_detector(
									    '''http://images.cocodataset.org/val2017/000000039769.jpg'''				,       candidate_labels=['''cat''', '''remote''', '''couch''']				,       )
									self.assertEqual(
									    nested_simplify(UpperCamelCase_				,       decimals=4   )				,       [
									        {'''score''': 0.2_8_6_8, '''label''': '''cat''', '''box''': {'''xmin''': 3_2_4, '''ymin''': 2_0, '''xmax''': 6_4_0, '''ymax''': 3_7_3}},
									        {'''score''': 0.2_7_7, '''label''': '''remote''', '''box''': {'''xmin''': 4_0, '''ymin''': 7_2, '''xmax''': 1_7_7, '''ymax''': 1_1_5}},
									        {'''score''': 0.2_5_3_7, '''label''': '''cat''', '''box''': {'''xmin''': 1, '''ymin''': 5_5, '''xmax''': 3_1_5, '''ymax''': 4_7_2}},
									        {'''score''': 0.1_4_7_4, '''label''': '''remote''', '''box''': {'''xmin''': 3_3_5, '''ymin''': 7_4, '''xmax''': 3_7_1, '''ymax''': 1_8_7}},
									        {'''score''': 0.1_2_0_8, '''label''': '''couch''', '''box''': {'''xmin''': 4, '''ymin''': 0, '''xmax''': 6_4_2, '''ymax''': 4_7_6}},
									    ]				,       )

									_lowerCamelCase        =				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(UpperCamelCase_				,       decimals=4   )				,       [
									        [
									            {'''score''': 0.2_8_6_8, '''label''': '''cat''', '''box''': {'''xmin''': 3_2_4, '''ymin''': 2_0, '''xmax''': 6_4_0, '''ymax''': 3_7_3}},
									            {'''score''': 0.2_7_7, '''label''': '''remote''', '''box''': {'''xmin''': 4_0, '''ymin''': 7_2, '''xmax''': 1_7_7, '''ymax''': 1_1_5}},
									            {'''score''': 0.2_5_3_7, '''label''': '''cat''', '''box''': {'''xmin''': 1, '''ymin''': 5_5, '''xmax''': 3_1_5, '''ymax''': 4_7_2}},
									            {'''score''': 0.1_4_7_4, '''label''': '''remote''', '''box''': {'''xmin''': 3_3_5, '''ymin''': 7_4, '''xmax''': 3_7_1, '''ymax''': 1_8_7}},
									            {'''score''': 0.1_2_0_8, '''label''': '''couch''', '''box''': {'''xmin''': 4, '''ymin''': 0, '''xmax''': 6_4_2, '''ymax''': 4_7_6}},
									        ],
									        [
									            {'''score''': 0.2_8_6_8, '''label''': '''cat''', '''box''': {'''xmin''': 3_2_4, '''ymin''': 2_0, '''xmax''': 6_4_0, '''ymax''': 3_7_3}},
									            {'''score''': 0.2_7_7, '''label''': '''remote''', '''box''': {'''xmin''': 4_0, '''ymin''': 7_2, '''xmax''': 1_7_7, '''ymax''': 1_1_5}},
									            {'''score''': 0.2_5_3_7, '''label''': '''cat''', '''box''': {'''xmin''': 1, '''ymin''': 5_5, '''xmax''': 3_1_5, '''ymax''': 4_7_2}},
									            {'''score''': 0.1_4_7_4, '''label''': '''remote''', '''box''': {'''xmin''': 3_3_5, '''ymin''': 7_4, '''xmax''': 3_7_1, '''ymax''': 1_8_7}},
									            {'''score''': 0.1_2_0_8, '''label''': '''couch''', '''box''': {'''xmin''': 4, '''ymin''': 0, '''xmax''': 6_4_2, '''ymax''': 4_7_6}},
									        ],
									    ]				,       )

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

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

									_lowerCamelCase        =				object_detector(
									    '''http://images.cocodataset.org/val2017/000000039769.jpg'''				,       candidate_labels=['''cat''', '''remote''', '''couch''']				,       threshold=UpperCamelCase_				,       )
									self.assertEqual(
									    nested_simplify(UpperCamelCase_				,       decimals=4   )				,       [
									        {'''score''': 0.2_8_6_8, '''label''': '''cat''', '''box''': {'''xmin''': 3_2_4, '''ymin''': 2_0, '''xmax''': 6_4_0, '''ymax''': 3_7_3}},
									        {'''score''': 0.2_7_7, '''label''': '''remote''', '''box''': {'''xmin''': 4_0, '''ymin''': 7_2, '''xmax''': 1_7_7, '''ymax''': 1_1_5}},
									        {'''score''': 0.2_5_3_7, '''label''': '''cat''', '''box''': {'''xmin''': 1, '''ymin''': 5_5, '''xmax''': 3_1_5, '''ymax''': 4_7_2}},
									    ]				,       )





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

									_lowerCamelCase        =				object_detector(
									    '''http://images.cocodataset.org/val2017/000000039769.jpg'''				,       candidate_labels=['''cat''', '''remote''', '''couch''']				,       top_k=UpperCamelCase_				,       )
									self.assertEqual(
									    nested_simplify(UpperCamelCase_				,       decimals=4   )				,       [
									        {'''score''': 0.2_8_6_8, '''label''': '''cat''', '''box''': {'''xmin''': 3_2_4, '''ymin''': 2_0, '''xmax''': 6_4_0, '''ymax''': 3_7_3}},
									        {'''score''': 0.2_7_7, '''label''': '''remote''', '''box''': {'''xmin''': 4_0, '''ymin''': 7_2, '''xmax''': 1_7_7, '''ymax''': 1_1_5}},
									    ]				,       )





"""simple docstring"""
def        lowerCAmelCase_(   lowercase_     :							str						,   lowercase_     :							str							)	->       bool:
				_lowerCamelCase        =				len(lowercase_							)
				_lowerCamelCase        =				len(lowercase_							)
				_lowerCamelCase        =				[[False for _ in range(m + 1							)] for _ in range(n + 1							)]
				_lowerCamelCase        =				True
				for i in range(lowercase_							):
								for j in range(m + 1							):
												if dp[i][j]:
																if j < m and a[i].upper() == b[j]:
																				_lowerCamelCase        =				True
																if a[i].islower():
																				_lowerCamelCase        =				True
				return dp[n][m]


if __name__ == "__main__":
			import doctest

			doctest.testmod()
