
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__   :





														@staticmethod
														def 			a__ ( *_UpperCAmelCase  :   List[str]     , **_UpperCAmelCase  :   Dict				)						->		str:



																		"""simple docstring"""


																		pass
@is_pipeline_test
@require_vision
@require_torch
class 	A__   (						unittest.TestCase				):
							lowerCAmelCase__		:						str    			=							MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING





							def 			a__ ( self  :   List[Any]     , _UpperCAmelCase  :   Union[str, Any]     , _UpperCAmelCase  :   Union[str, Any]     , _UpperCAmelCase  :   List[str]				)						->		str:



											"""simple docstring"""


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

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





							def 			a__ ( self  :   str     , _UpperCAmelCase  :   List[str]     , _UpperCAmelCase  :   Any				)						->		Optional[int]:



											"""simple docstring"""


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

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





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



											"""simple docstring"""


											pass





							@require_torch
							def 			a__ ( self  :   Optional[int]				)						->		Dict:



											"""simple docstring"""


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

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

											self.assertEqual(
											    nested_simplify(lowerCamelCase__     , decimals=4				)     , [
											        {'score': 0.7_235, 'label': 'cat', 'box': {'xmin': 2_04, 'ymin': 1_67, 'xmax': 2_32, 'ymax': 1_90}},
											        {'score': 0.7_218, 'label': 'remote', 'box': {'xmin': 2_04, 'ymin': 1_67, 'xmax': 2_32, 'ymax': 1_90}},
											        {'score': 0.7_184, 'label': 'couch', 'box': {'xmin': 2_04, 'ymin': 1_67, 'xmax': 2_32, 'ymax': 1_90}},
											        {'score': 0.6_748, 'label': 'remote', 'box': {'xmin': 5_71, 'ymin': 83, 'xmax': 5_98, 'ymax': 1_03}},
											        {'score': 0.6_656, 'label': 'cat', 'box': {'xmin': 5_71, 'ymin': 83, 'xmax': 5_98, 'ymax': 1_03}},
											        {'score': 0.6_614, 'label': 'couch', 'box': {'xmin': 5_71, 'ymin': 83, 'xmax': 5_98, 'ymax': 1_03}},
											        {'score': 0.6_456, 'label': 'remote', 'box': {'xmin': 4_94, 'ymin': 1_05, 'xmax': 5_21, 'ymax': 1_27}},
											        {'score': 0.642, 'label': 'remote', 'box': {'xmin': 67, 'ymin': 2_74, 'xmax': 93, 'ymax': 2_97}},
											        {'score': 0.6_419, 'label': 'cat', 'box': {'xmin': 4_94, 'ymin': 1_05, 'xmax': 5_21, 'ymax': 1_27}},
											    ]     , )

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

											self.assertEqual(
											    nested_simplify(lowerCamelCase__     , decimals=4				)     , [
											        [
											            {'score': 0.7_235, 'label': 'cat', 'box': {'xmin': 2_04, 'ymin': 1_67, 'xmax': 2_32, 'ymax': 1_90}},
											            {'score': 0.7_218, 'label': 'remote', 'box': {'xmin': 2_04, 'ymin': 1_67, 'xmax': 2_32, 'ymax': 1_90}},
											            {'score': 0.7_184, 'label': 'couch', 'box': {'xmin': 2_04, 'ymin': 1_67, 'xmax': 2_32, 'ymax': 1_90}},
											            {'score': 0.6_748, 'label': 'remote', 'box': {'xmin': 5_71, 'ymin': 83, 'xmax': 5_98, 'ymax': 1_03}},
											            {'score': 0.6_656, 'label': 'cat', 'box': {'xmin': 5_71, 'ymin': 83, 'xmax': 5_98, 'ymax': 1_03}},
											            {'score': 0.6_614, 'label': 'couch', 'box': {'xmin': 5_71, 'ymin': 83, 'xmax': 5_98, 'ymax': 1_03}},
											            {'score': 0.6_456, 'label': 'remote', 'box': {'xmin': 4_94, 'ymin': 1_05, 'xmax': 5_21, 'ymax': 1_27}},
											            {'score': 0.642, 'label': 'remote', 'box': {'xmin': 67, 'ymin': 2_74, 'xmax': 93, 'ymax': 2_97}},
											            {'score': 0.6_419, 'label': 'cat', 'box': {'xmin': 4_94, 'ymin': 1_05, 'xmax': 5_21, 'ymax': 1_27}},
											        ]
											    ]     , )





							@require_torch
							@slow
							def 			a__ ( self  :   int				)						->		List[Any]:



											"""simple docstring"""


											__lowercase								=					pipeline('zero-shot-object-detection'				)

											__lowercase								=					object_detector(
											    'http://images.cocodataset.org/val2017/000000039769.jpg'     , candidate_labels=['cat', 'remote', 'couch']     , )
											self.assertEqual(
											    nested_simplify(lowerCamelCase__     , decimals=4				)     , [
											        {'score': 0.2_868, 'label': 'cat', 'box': {'xmin': 3_24, 'ymin': 20, 'xmax': 6_40, 'ymax': 3_73}},
											        {'score': 0.277, 'label': 'remote', 'box': {'xmin': 40, 'ymin': 72, 'xmax': 1_77, 'ymax': 1_15}},
											        {'score': 0.2_537, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 55, 'xmax': 3_15, 'ymax': 4_72}},
											        {'score': 0.1_474, 'label': 'remote', 'box': {'xmin': 3_35, 'ymin': 74, 'xmax': 3_71, 'ymax': 1_87}},
											        {'score': 0.1_208, 'label': 'couch', 'box': {'xmin': 4, 'ymin': 0, 'xmax': 6_42, 'ymax': 4_76}},
											    ]     , )

											__lowercase								=					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(lowerCamelCase__     , decimals=4				)     , [
											        [
											            {'score': 0.2_868, 'label': 'cat', 'box': {'xmin': 3_24, 'ymin': 20, 'xmax': 6_40, 'ymax': 3_73}},
											            {'score': 0.277, 'label': 'remote', 'box': {'xmin': 40, 'ymin': 72, 'xmax': 1_77, 'ymax': 1_15}},
											            {'score': 0.2_537, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 55, 'xmax': 3_15, 'ymax': 4_72}},
											            {'score': 0.1_474, 'label': 'remote', 'box': {'xmin': 3_35, 'ymin': 74, 'xmax': 3_71, 'ymax': 1_87}},
											            {'score': 0.1_208, 'label': 'couch', 'box': {'xmin': 4, 'ymin': 0, 'xmax': 6_42, 'ymax': 4_76}},
											        ],
											        [
											            {'score': 0.2_868, 'label': 'cat', 'box': {'xmin': 3_24, 'ymin': 20, 'xmax': 6_40, 'ymax': 3_73}},
											            {'score': 0.277, 'label': 'remote', 'box': {'xmin': 40, 'ymin': 72, 'xmax': 1_77, 'ymax': 1_15}},
											            {'score': 0.2_537, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 55, 'xmax': 3_15, 'ymax': 4_72}},
											            {'score': 0.1_474, 'label': 'remote', 'box': {'xmin': 3_35, 'ymin': 74, 'xmax': 3_71, 'ymax': 1_87}},
											            {'score': 0.1_208, 'label': 'couch', 'box': {'xmin': 4, 'ymin': 0, 'xmax': 6_42, 'ymax': 4_76}},
											        ],
											    ]     , )





							@require_tf
							@unittest.skip('Zero Shot Object Detection not implemented in TF'				)
							def 			a__ ( self  :   Tuple				)						->		Dict:



											"""simple docstring"""


											pass





							@require_torch
							@slow
							def 			a__ ( self  :   int				)						->		int:



											"""simple docstring"""


											__lowercase								=					0.2
											__lowercase								=					pipeline('zero-shot-object-detection'				)

											__lowercase								=					object_detector(
											    'http://images.cocodataset.org/val2017/000000039769.jpg'     , candidate_labels=['cat', 'remote', 'couch']     , threshold=lowerCamelCase__     , )
											self.assertEqual(
											    nested_simplify(lowerCamelCase__     , decimals=4				)     , [
											        {'score': 0.2_868, 'label': 'cat', 'box': {'xmin': 3_24, 'ymin': 20, 'xmax': 6_40, 'ymax': 3_73}},
											        {'score': 0.277, 'label': 'remote', 'box': {'xmin': 40, 'ymin': 72, 'xmax': 1_77, 'ymax': 1_15}},
											        {'score': 0.2_537, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 55, 'xmax': 3_15, 'ymax': 4_72}},
											    ]     , )





							@require_torch
							@slow
							def 			a__ ( self  :   Optional[int]				)						->		str:



											"""simple docstring"""


											__lowercase								=					2
											__lowercase								=					pipeline('zero-shot-object-detection'				)

											__lowercase								=					object_detector(
											    'http://images.cocodataset.org/val2017/000000039769.jpg'     , candidate_labels=['cat', 'remote', 'couch']     , top_k=lowerCamelCase__     , )
											self.assertEqual(
											    nested_simplify(lowerCamelCase__     , decimals=4				)     , [
											        {'score': 0.2_868, 'label': 'cat', 'box': {'xmin': 3_24, 'ymin': 20, 'xmax': 6_40, 'ymax': 3_73}},
											        {'score': 0.277, 'label': 'remote', 'box': {'xmin': 40, 'ymin': 72, 'xmax': 1_77, 'ymax': 1_15}},
											    ]     , )









'''simple docstring'''


import warnings

from diffusers import StableDiffusionImgaImgPipeline  # noqa F401


warnings.warn(
    'The `image_to_image.py` script is outdated. Please use directly `from diffusers import'
    ' StableDiffusionImg2ImgPipeline` instead.'
)



