

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 UpperCamelCase			(			*snake_case__ :      int							,    **snake_case__ :      str    ):

           """simple docstring"""






           pass




@is_pipeline_test
@require_vision
@require_torch
class      UpperCamelCase (     unittest.TestCase   ):
    __UpperCamelCase         =MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING

    def UpperCamelCase			(			self :      List[str]							,    snake_case__ :      Union[str, Any]							,    snake_case__ :      Any							,    snake_case__ :      Optional[Any]    ):

     """simple docstring"""






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

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

    def UpperCamelCase			(			self :      List[Any]							,    snake_case__ :      str							,    snake_case__ :      str    ):

     """simple docstring"""






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

     SCREAMING_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 UpperCamelCase			(			self :      Union[str, Any]    ):

     """simple docstring"""






     pass

    @require_torch
    def UpperCamelCase			(			self :      str    ):

     """simple docstring"""






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

     SCREAMING_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': 0.7_235, 'label': 'cat', 'box': {'xmin': 2_0_4, 'ymin': 1_6_7, 'xmax': 2_3_2, 'ymax': 1_9_0}},
             {'score': 0.7_218, 'label': 'remote', 'box': {'xmin': 2_0_4, 'ymin': 1_6_7, 'xmax': 2_3_2, 'ymax': 1_9_0}},
             {'score': 0.7_184, 'label': 'couch', 'box': {'xmin': 2_0_4, 'ymin': 1_6_7, 'xmax': 2_3_2, 'ymax': 1_9_0}},
             {'score': 0.6_748, 'label': 'remote', 'box': {'xmin': 5_7_1, 'ymin': 8_3, 'xmax': 5_9_8, 'ymax': 1_0_3}},
             {'score': 0.6_656, 'label': 'cat', 'box': {'xmin': 5_7_1, 'ymin': 8_3, 'xmax': 5_9_8, 'ymax': 1_0_3}},
             {'score': 0.6_614, 'label': 'couch', 'box': {'xmin': 5_7_1, 'ymin': 8_3, 'xmax': 5_9_8, 'ymax': 1_0_3}},
             {'score': 0.6_456, 'label': 'remote', 'box': {'xmin': 4_9_4, 'ymin': 1_0_5, 'xmax': 5_2_1, 'ymax': 1_2_7}},
             {'score': 0.642, 'label': 'remote', 'box': {'xmin': 6_7, 'ymin': 2_7_4, 'xmax': 9_3, 'ymax': 2_9_7}},
             {'score': 0.6_419, 'label': 'cat', 'box': {'xmin': 4_9_4, 'ymin': 1_0_5, 'xmax': 5_2_1, 'ymax': 1_2_7}},
         ]							,    )

     SCREAMING_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': 0.7_235, 'label': 'cat', 'box': {'xmin': 2_0_4, 'ymin': 1_6_7, 'xmax': 2_3_2, 'ymax': 1_9_0}},
                 {'score': 0.7_218, 'label': 'remote', 'box': {'xmin': 2_0_4, 'ymin': 1_6_7, 'xmax': 2_3_2, 'ymax': 1_9_0}},
                 {'score': 0.7_184, 'label': 'couch', 'box': {'xmin': 2_0_4, 'ymin': 1_6_7, 'xmax': 2_3_2, 'ymax': 1_9_0}},
                 {'score': 0.6_748, 'label': 'remote', 'box': {'xmin': 5_7_1, 'ymin': 8_3, 'xmax': 5_9_8, 'ymax': 1_0_3}},
                 {'score': 0.6_656, 'label': 'cat', 'box': {'xmin': 5_7_1, 'ymin': 8_3, 'xmax': 5_9_8, 'ymax': 1_0_3}},
                 {'score': 0.6_614, 'label': 'couch', 'box': {'xmin': 5_7_1, 'ymin': 8_3, 'xmax': 5_9_8, 'ymax': 1_0_3}},
                 {'score': 0.6_456, 'label': 'remote', 'box': {'xmin': 4_9_4, 'ymin': 1_0_5, 'xmax': 5_2_1, 'ymax': 1_2_7}},
                 {'score': 0.642, 'label': 'remote', 'box': {'xmin': 6_7, 'ymin': 2_7_4, 'xmax': 9_3, 'ymax': 2_9_7}},
                 {'score': 0.6_419, 'label': 'cat', 'box': {'xmin': 4_9_4, 'ymin': 1_0_5, 'xmax': 5_2_1, 'ymax': 1_2_7}},
             ]
         ]							,    )

    @require_torch
    @slow
    def UpperCamelCase			(			self :      Union[str, Any]    ):

     """simple docstring"""






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

     SCREAMING_SNAKE_CASE								=			object_detector(
         'http://images.cocodataset.org/val2017/000000039769.jpg'							,    candidate_labels=['cat', 'remote', 'couch']							,    )
     self.assertEqual(
         nested_simplify(lowerCamelCase__							,    decimals=4    )							,    [
             {'score': 0.2_868, 'label': 'cat', 'box': {'xmin': 3_2_4, 'ymin': 2_0, 'xmax': 6_4_0, 'ymax': 3_7_3}},
             {'score': 0.277, 'label': 'remote', 'box': {'xmin': 4_0, 'ymin': 7_2, 'xmax': 1_7_7, 'ymax': 1_1_5}},
             {'score': 0.2_537, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 5_5, 'xmax': 3_1_5, 'ymax': 4_7_2}},
             {'score': 0.1_474, 'label': 'remote', 'box': {'xmin': 3_3_5, 'ymin': 7_4, 'xmax': 3_7_1, 'ymax': 1_8_7}},
             {'score': 0.1_208, 'label': 'couch', 'box': {'xmin': 4, 'ymin': 0, 'xmax': 6_4_2, 'ymax': 4_7_6}},
         ]							,    )

     SCREAMING_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': 0.2_868, 'label': 'cat', 'box': {'xmin': 3_2_4, 'ymin': 2_0, 'xmax': 6_4_0, 'ymax': 3_7_3}},
                 {'score': 0.277, 'label': 'remote', 'box': {'xmin': 4_0, 'ymin': 7_2, 'xmax': 1_7_7, 'ymax': 1_1_5}},
                 {'score': 0.2_537, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 5_5, 'xmax': 3_1_5, 'ymax': 4_7_2}},
                 {'score': 0.1_474, 'label': 'remote', 'box': {'xmin': 3_3_5, 'ymin': 7_4, 'xmax': 3_7_1, 'ymax': 1_8_7}},
                 {'score': 0.1_208, 'label': 'couch', 'box': {'xmin': 4, 'ymin': 0, 'xmax': 6_4_2, 'ymax': 4_7_6}},
             ],
             [
                 {'score': 0.2_868, 'label': 'cat', 'box': {'xmin': 3_2_4, 'ymin': 2_0, 'xmax': 6_4_0, 'ymax': 3_7_3}},
                 {'score': 0.277, 'label': 'remote', 'box': {'xmin': 4_0, 'ymin': 7_2, 'xmax': 1_7_7, 'ymax': 1_1_5}},
                 {'score': 0.2_537, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 5_5, 'xmax': 3_1_5, 'ymax': 4_7_2}},
                 {'score': 0.1_474, 'label': 'remote', 'box': {'xmin': 3_3_5, 'ymin': 7_4, 'xmax': 3_7_1, 'ymax': 1_8_7}},
                 {'score': 0.1_208, '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 UpperCamelCase			(			self :      Tuple    ):

     """simple docstring"""






     pass

    @require_torch
    @slow
    def UpperCamelCase			(			self :      Optional[int]    ):

     """simple docstring"""






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

     SCREAMING_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': 0.2_868, 'label': 'cat', 'box': {'xmin': 3_2_4, 'ymin': 2_0, 'xmax': 6_4_0, 'ymax': 3_7_3}},
             {'score': 0.277, 'label': 'remote', 'box': {'xmin': 4_0, 'ymin': 7_2, 'xmax': 1_7_7, 'ymax': 1_1_5}},
             {'score': 0.2_537, 'label': 'cat', 'box': {'xmin': 1, 'ymin': 5_5, 'xmax': 3_1_5, 'ymax': 4_7_2}},
         ]							,    )




    @require_torch
    @slow
    def UpperCamelCase			(			self :      Any    ):

     """simple docstring"""






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

     SCREAMING_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': 0.2_868, 'label': 'cat', 'box': {'xmin': 3_2_4, 'ymin': 2_0, 'xmax': 6_4_0, 'ymax': 3_7_3}},
             {'score': 0.277, 'label': 'remote', 'box': {'xmin': 4_0, 'ymin': 7_2, 'xmax': 1_7_7, 'ymax': 1_1_5}},
         ]							,    )




from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
      if not (is_transformers_available() and is_torch_available()):
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      from ...utils.dummy_torch_and_transformers_objects import (
          ImageTextPipelineOutput,
          UniDiffuserPipeline,
      )
else:
      from .modeling_text_decoder import UniDiffuserTextDecoder
      from .modeling_uvit import UniDiffuserModel, UTransformeraDModel
      from .pipeline_unidiffuser import ImageTextPipelineOutput, UniDiffuserPipeline

