






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     _SCREAMING_SNAKE_CASE       :





		@staticmethod
		def 						_A (		*__lowerCamelCase				:					Tuple ,  **__lowerCamelCase				:					str	):
			pass

@is_pipeline_test
@require_vision
@require_torch
class     _SCREAMING_SNAKE_CASE       (			unittest.TestCase      ):
	snake_case__							:     Any     	=  MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING





	def 						_A (		self				:					List[Any] ,  __lowerCamelCase				:					Tuple ,  __lowerCamelCase				:					Union[str, Any] ,  __lowerCamelCase				:					Tuple	):
		UpperCamelCase     :Any          =	pipeline(
		    """zero-shot-object-detection""" ,  model="""hf-internal-testing/tiny-random-owlvit-object-detection"""	)

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





	def 						_A (		self				:					int ,  __lowerCamelCase				:					Tuple ,  __lowerCamelCase				:					Tuple	):
		UpperCamelCase     :Tuple          =	object_detector(examples[0] ,  threshold=0.0	)

		UpperCamelCase     :Optional[Any]          =	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				:					Dict	):
		pass





	@require_torch
	def 						_A (		self				:					List[str]	):
		UpperCamelCase     :Tuple          =	pipeline(
		    """zero-shot-object-detection""" ,  model="""hf-internal-testing/tiny-random-owlvit-object-detection"""	)

		UpperCamelCase     :Tuple          =	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""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
		        {"""score""": 0.7218, """label""": """remote""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
		        {"""score""": 0.7184, """label""": """couch""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
		        {"""score""": 0.6748, """label""": """remote""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
		        {"""score""": 0.6656, """label""": """cat""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
		        {"""score""": 0.6614, """label""": """couch""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
		        {"""score""": 0.6456, """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""": 0.6419, """label""": """cat""", """box""": {"""xmin""": 494, """ymin""": 105, """xmax""": 521, """ymax""": 127}},
		    ] ,  )

		UpperCamelCase     :Any          =	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""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
		            {"""score""": 0.7218, """label""": """remote""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
		            {"""score""": 0.7184, """label""": """couch""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
		            {"""score""": 0.6748, """label""": """remote""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
		            {"""score""": 0.6656, """label""": """cat""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
		            {"""score""": 0.6614, """label""": """couch""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
		            {"""score""": 0.6456, """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""": 0.6419, """label""": """cat""", """box""": {"""xmin""": 494, """ymin""": 105, """xmax""": 521, """ymax""": 127}},
		        ]
		    ] ,  )





	@require_torch
	@slow
	def 						_A (		self				:					Optional[Any]	):
		UpperCamelCase     :Optional[int]          =	pipeline("""zero-shot-object-detection"""	)

		UpperCamelCase     :Union[str, Any]          =	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""": 324, """ymin""": 20, """xmax""": 640, """ymax""": 373}},
		        {"""score""": 0.277, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 72, """xmax""": 177, """ymax""": 115}},
		        {"""score""": 0.2537, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 55, """xmax""": 315, """ymax""": 472}},
		        {"""score""": 0.1474, """label""": """remote""", """box""": {"""xmin""": 335, """ymin""": 74, """xmax""": 371, """ymax""": 187}},
		        {"""score""": 0.1208, """label""": """couch""", """box""": {"""xmin""": 4, """ymin""": 0, """xmax""": 642, """ymax""": 476}},
		    ] ,  )

		UpperCamelCase     :List[str]          =	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""": 324, """ymin""": 20, """xmax""": 640, """ymax""": 373}},
		            {"""score""": 0.277, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 72, """xmax""": 177, """ymax""": 115}},
		            {"""score""": 0.2537, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 55, """xmax""": 315, """ymax""": 472}},
		            {"""score""": 0.1474, """label""": """remote""", """box""": {"""xmin""": 335, """ymin""": 74, """xmax""": 371, """ymax""": 187}},
		            {"""score""": 0.1208, """label""": """couch""", """box""": {"""xmin""": 4, """ymin""": 0, """xmax""": 642, """ymax""": 476}},
		        ],
		        [
		            {"""score""": 0.2868, """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""": 0.2537, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 55, """xmax""": 315, """ymax""": 472}},
		            {"""score""": 0.1474, """label""": """remote""", """box""": {"""xmin""": 335, """ymin""": 74, """xmax""": 371, """ymax""": 187}},
		            {"""score""": 0.1208, """label""": """couch""", """box""": {"""xmin""": 4, """ymin""": 0, """xmax""": 642, """ymax""": 476}},
		        ],
		    ] ,  )





	@require_tf
	@unittest.skip("""Zero Shot Object Detection not implemented in TF"""	)
	def 						_A (		self				:					List[Any]	):
		pass





	@require_torch
	@slow
	def 						_A (		self				:					str	):
		UpperCamelCase     :Dict          =	0.2
		UpperCamelCase     :Optional[Any]          =	pipeline("""zero-shot-object-detection"""	)

		UpperCamelCase     :Optional[Any]          =	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""": 324, """ymin""": 20, """xmax""": 640, """ymax""": 373}},
		        {"""score""": 0.277, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 72, """xmax""": 177, """ymax""": 115}},
		        {"""score""": 0.2537, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 55, """xmax""": 315, """ymax""": 472}},
		    ] ,  )





	@require_torch
	@slow
	def 						_A (		self				:					Optional[int]	):
		UpperCamelCase     :int          =	2
		UpperCamelCase     :List[str]          =	pipeline("""zero-shot-object-detection"""	)

		UpperCamelCase     :Union[str, Any]          =	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""": 324, """ymin""": 20, """xmax""": 640, """ymax""": 373}},
		        {"""score""": 0.277, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 72, """xmax""": 177, """ymax""": 115}},
		    ] ,  )



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase							:  Optional[int]   	=						{"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase							:  Any   	=						[
						    """WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """WavLMForAudioFrameClassification""",
						    """WavLMForCTC""",
						    """WavLMForSequenceClassification""",
						    """WavLMForXVector""",
						    """WavLMModel""",
						    """WavLMPreTrainedModel""",
						]

if TYPE_CHECKING:
						from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_wavlm import (
												    WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
												    WavLMForAudioFrameClassification,
												    WavLMForCTC,
												    WavLMForSequenceClassification,
												    WavLMForXVector,
												    WavLMModel,
												    WavLMPreTrainedModel,
												)

else:
						import sys

						lowerCAmelCase							:  Union[str, Any]   	=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






