
'''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       ( *lowerCAmelCase_					,     **lowerCAmelCase_						):





													"""simple docstring"""






													pass


@is_pipeline_test
@require_vision
@require_torch
class 		__UpperCAmelCase   (      unittest.TestCase		):
							__lowercase   	= MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING


							def 				lowerCamelCase       ( self					,     lowerCAmelCase_					,     lowerCAmelCase_					,     lowerCAmelCase_						):





								"""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					,     lowerCAmelCase_					,     lowerCAmelCase_						):





								"""simple docstring"""






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

								_snake_case     		=	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 				lowerCamelCase       ( self						):





								"""simple docstring"""






								pass


							@require_torch
							def 				lowerCamelCase       ( self						):





								"""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(lowerCAmelCase_					,     decimals=4						)					,     [
								        {'score': 0.7235, 'label': 'cat', 'box': {'xmin': 2_04, 'ymin': 1_67, 'xmax': 2_32, 'ymax': 1_90}},
								        {'score': 0.7218, 'label': 'remote', 'box': {'xmin': 2_04, 'ymin': 1_67, 'xmax': 2_32, 'ymax': 1_90}},
								        {'score': 0.7184, 'label': 'couch', 'box': {'xmin': 2_04, 'ymin': 1_67, 'xmax': 2_32, 'ymax': 1_90}},
								        {'score': 0.6748, 'label': 'remote', 'box': {'xmin': 5_71, 'ymin': 83, 'xmax': 5_98, 'ymax': 1_03}},
								        {'score': 0.6656, 'label': 'cat', 'box': {'xmin': 5_71, 'ymin': 83, 'xmax': 5_98, 'ymax': 1_03}},
								        {'score': 0.6614, 'label': 'couch', 'box': {'xmin': 5_71, 'ymin': 83, 'xmax': 5_98, 'ymax': 1_03}},
								        {'score': 0.6456, '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': 0.6419, 'label': 'cat', 'box': {'xmin': 4_94, 'ymin': 1_05, 'xmax': 5_21, 'ymax': 1_27}},
								    ]					,     )

								_snake_case     		=	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': 0.7235, 'label': 'cat', 'box': {'xmin': 2_04, 'ymin': 1_67, 'xmax': 2_32, 'ymax': 1_90}},
								            {'score': 0.7218, 'label': 'remote', 'box': {'xmin': 2_04, 'ymin': 1_67, 'xmax': 2_32, 'ymax': 1_90}},
								            {'score': 0.7184, 'label': 'couch', 'box': {'xmin': 2_04, 'ymin': 1_67, 'xmax': 2_32, 'ymax': 1_90}},
								            {'score': 0.6748, 'label': 'remote', 'box': {'xmin': 5_71, 'ymin': 83, 'xmax': 5_98, 'ymax': 1_03}},
								            {'score': 0.6656, 'label': 'cat', 'box': {'xmin': 5_71, 'ymin': 83, 'xmax': 5_98, 'ymax': 1_03}},
								            {'score': 0.6614, 'label': 'couch', 'box': {'xmin': 5_71, 'ymin': 83, 'xmax': 5_98, 'ymax': 1_03}},
								            {'score': 0.6456, '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': 0.6419, 'label': 'cat', 'box': {'xmin': 4_94, 'ymin': 1_05, 'xmax': 5_21, 'ymax': 1_27}},
								        ]
								    ]					,     )


							@require_torch
							@slow
							def 				lowerCamelCase       ( self						):





								"""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(lowerCAmelCase_					,     decimals=4						)					,     [
								        {'score': 0.2868, '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': 0.2537, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 55, 'xmax': 3_15, 'ymax': 4_72}},
								        {'score': 0.1474, 'label': 'remote', 'box': {'xmin': 3_35, 'ymin': 74, 'xmax': 3_71, 'ymax': 1_87}},
								        {'score': 0.1208, 'label': 'couch', 'box': {'xmin': 4, 'ymin': 0, 'xmax': 6_42, 'ymax': 4_76}},
								    ]					,     )

								_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(lowerCAmelCase_					,     decimals=4						)					,     [
								        [
								            {'score': 0.2868, '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': 0.2537, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 55, 'xmax': 3_15, 'ymax': 4_72}},
								            {'score': 0.1474, 'label': 'remote', 'box': {'xmin': 3_35, 'ymin': 74, 'xmax': 3_71, 'ymax': 1_87}},
								            {'score': 0.1208, 'label': 'couch', 'box': {'xmin': 4, 'ymin': 0, 'xmax': 6_42, 'ymax': 4_76}},
								        ],
								        [
								            {'score': 0.2868, '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': 0.2537, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 55, 'xmax': 3_15, 'ymax': 4_72}},
								            {'score': 0.1474, 'label': 'remote', 'box': {'xmin': 3_35, 'ymin': 74, 'xmax': 3_71, 'ymax': 1_87}},
								            {'score': 0.1208, '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 				lowerCamelCase       ( self						):





								"""simple docstring"""






								pass


							@require_torch
							@slow
							def 				lowerCamelCase       ( self						):





								"""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=lowerCAmelCase_					,     )
								self.assertEqual(
								    nested_simplify(lowerCAmelCase_					,     decimals=4						)					,     [
								        {'score': 0.2868, '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': 0.2537, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 55, 'xmax': 3_15, 'ymax': 4_72}},
								    ]					,     )




							@require_torch
							@slow
							def 				lowerCamelCase       ( self						):





								"""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=lowerCAmelCase_					,     )
								self.assertEqual(
								    nested_simplify(lowerCAmelCase_					,     decimals=4						)					,     [
								        {'score': 0.2868, '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'''







lowercase					:							Tuple   =      {
    "a": "AAAAA",
    "b": "AAAAB",
    "c": "AAABA",
    "d": "AAABB",
    "e": "AABAA",
    "f": "AABAB",
    "g": "AABBA",
    "h": "AABBB",
    "i": "ABAAA",
    "j": "BBBAA",
    "k": "ABAAB",
    "l": "ABABA",
    "m": "ABABB",
    "n": "ABBAA",
    "o": "ABBAB",
    "p": "ABBBA",
    "q": "ABBBB",
    "r": "BAAAA",
    "s": "BAAAB",
    "t": "BAABA",
    "u": "BAABB",
    "v": "BBBAB",
    "w": "BABAA",
    "x": "BABAB",
    "y": "BABBA",
    "z": "BABBB",
    " ": " ",
}


lowercase					:							Union[str, Any]   =      {value: key for key, value in encode_dict.items()}







def        SCREAMING_SNAKE_CASE__			(     __A			) ->			str:
	_snake_case     		=	''
	for letter in word.lower():
		if letter.isalpha() or letter == " ":
			encoded += encode_dict[letter]
		else:
			raise Exception('encode() accepts only letters of the alphabet and spaces'			)
	return encoded







def        SCREAMING_SNAKE_CASE__			(     __A			) ->			str:
	if set(__A			) - {"A", "B", " "} != set():
		raise Exception('decode() accepts only \'A\', \'B\' and spaces'			)
	_snake_case     		=	''
	for word in coded.split():
		while len(__A			) != 0:
			decoded += decode_dict[word[:5]]
			_snake_case     		=	word[5:]
		decoded += " "
	return decoded.strip()


if __name__ == "__main__":
					from doctest import testmod

					testmod()

