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   snake_case_       :






         @staticmethod
         def       __UpperCamelCase     (      *lowercase_				:     int	,						**lowercase_				:     Optional[int]  )					->						Dict:
             pass



@is_pipeline_test
@require_vision
@require_torch
class   snake_case_       (		unittest.TestCase       ):
   __A	:		Optional[Any]         =				MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING






   def       __UpperCamelCase     (      self				:     Any	,						lowercase_				:     Tuple	,						lowercase_				:     List[str]	,						lowercase_				:     Dict  )					->						Union[str, Any]:
       lowercase__ :   Dict    					=				pipeline(
           "zero-shot-object-detection"	,						model="hf-internal-testing/tiny-random-owlvit-object-detection"  )

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






   def       __UpperCamelCase     (      self				:     Optional[Any]	,						lowercase_				:     Dict	,						lowercase_				:     Optional[Any]  )					->						Optional[Any]:
       lowercase__ :   List[str]    					=				object_detector(examples[0]	,						threshold=0.0  )

       lowercase__ :   Optional[int]    					=				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				:     Optional[Any]  )					->						Optional[Any]:
       pass






   @require_torch
   def       __UpperCamelCase     (      self				:     List[Any]  )					->						Optional[Any]:
       lowercase__ :   Union[str, Any]    					=				pipeline(
           "zero-shot-object-detection"	,						model="hf-internal-testing/tiny-random-owlvit-object-detection"  )

       lowercase__ :   Dict    					=				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": 0.72_35, "label": "cat", "box": {"xmin": 2_04, "ymin": 1_67, "xmax": 2_32, "ymax": 1_90}},
               {"score": 0.72_18, "label": "remote", "box": {"xmin": 2_04, "ymin": 1_67, "xmax": 2_32, "ymax": 1_90}},
               {"score": 0.71_84, "label": "couch", "box": {"xmin": 2_04, "ymin": 1_67, "xmax": 2_32, "ymax": 1_90}},
               {"score": 0.67_48, "label": "remote", "box": {"xmin": 5_71, "ymin": 83, "xmax": 5_98, "ymax": 1_03}},
               {"score": 0.66_56, "label": "cat", "box": {"xmin": 5_71, "ymin": 83, "xmax": 5_98, "ymax": 1_03}},
               {"score": 0.66_14, "label": "couch", "box": {"xmin": 5_71, "ymin": 83, "xmax": 5_98, "ymax": 1_03}},
               {"score": 0.64_56, "label": "remote", "box": {"xmin": 4_94, "ymin": 1_05, "xmax": 5_21, "ymax": 1_27}},
               {"score": 0.6_42, "label": "remote", "box": {"xmin": 67, "ymin": 2_74, "xmax": 93, "ymax": 2_97}},
               {"score": 0.64_19, "label": "cat", "box": {"xmin": 4_94, "ymin": 1_05, "xmax": 5_21, "ymax": 1_27}},
           ]	,						)

       lowercase__ :   Union[str, 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": 0.72_35, "label": "cat", "box": {"xmin": 2_04, "ymin": 1_67, "xmax": 2_32, "ymax": 1_90}},
                   {"score": 0.72_18, "label": "remote", "box": {"xmin": 2_04, "ymin": 1_67, "xmax": 2_32, "ymax": 1_90}},
                   {"score": 0.71_84, "label": "couch", "box": {"xmin": 2_04, "ymin": 1_67, "xmax": 2_32, "ymax": 1_90}},
                   {"score": 0.67_48, "label": "remote", "box": {"xmin": 5_71, "ymin": 83, "xmax": 5_98, "ymax": 1_03}},
                   {"score": 0.66_56, "label": "cat", "box": {"xmin": 5_71, "ymin": 83, "xmax": 5_98, "ymax": 1_03}},
                   {"score": 0.66_14, "label": "couch", "box": {"xmin": 5_71, "ymin": 83, "xmax": 5_98, "ymax": 1_03}},
                   {"score": 0.64_56, "label": "remote", "box": {"xmin": 4_94, "ymin": 1_05, "xmax": 5_21, "ymax": 1_27}},
                   {"score": 0.6_42, "label": "remote", "box": {"xmin": 67, "ymin": 2_74, "xmax": 93, "ymax": 2_97}},
                   {"score": 0.64_19, "label": "cat", "box": {"xmin": 4_94, "ymin": 1_05, "xmax": 5_21, "ymax": 1_27}},
               ]
           ]	,						)






   @require_torch
   @slow
   def       __UpperCamelCase     (      self				:     List[Any]  )					->						Dict:
       lowercase__ :   Any    					=				pipeline("zero-shot-object-detection"  )

       lowercase__ :   Any    					=				object_detector(
           "http://images.cocodataset.org/val2017/000000039769.jpg"	,						candidate_labels=["cat", "remote", "couch"]	,						)
       self.assertEqual(
           nested_simplify(__lowerCamelCase	,						decimals=4  )	,						[
               {"score": 0.28_68, "label": "cat", "box": {"xmin": 3_24, "ymin": 20, "xmax": 6_40, "ymax": 3_73}},
               {"score": 0.2_77, "label": "remote", "box": {"xmin": 40, "ymin": 72, "xmax": 1_77, "ymax": 1_15}},
               {"score": 0.25_37, "label": "cat", "box": {"xmin": 1, "ymin": 55, "xmax": 3_15, "ymax": 4_72}},
               {"score": 0.14_74, "label": "remote", "box": {"xmin": 3_35, "ymin": 74, "xmax": 3_71, "ymax": 1_87}},
               {"score": 0.12_08, "label": "couch", "box": {"xmin": 4, "ymin": 0, "xmax": 6_42, "ymax": 4_76}},
           ]	,						)

       lowercase__ :   Optional[Any]    					=				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": 0.28_68, "label": "cat", "box": {"xmin": 3_24, "ymin": 20, "xmax": 6_40, "ymax": 3_73}},
                   {"score": 0.2_77, "label": "remote", "box": {"xmin": 40, "ymin": 72, "xmax": 1_77, "ymax": 1_15}},
                   {"score": 0.25_37, "label": "cat", "box": {"xmin": 1, "ymin": 55, "xmax": 3_15, "ymax": 4_72}},
                   {"score": 0.14_74, "label": "remote", "box": {"xmin": 3_35, "ymin": 74, "xmax": 3_71, "ymax": 1_87}},
                   {"score": 0.12_08, "label": "couch", "box": {"xmin": 4, "ymin": 0, "xmax": 6_42, "ymax": 4_76}},
               ],
               [
                   {"score": 0.28_68, "label": "cat", "box": {"xmin": 3_24, "ymin": 20, "xmax": 6_40, "ymax": 3_73}},
                   {"score": 0.2_77, "label": "remote", "box": {"xmin": 40, "ymin": 72, "xmax": 1_77, "ymax": 1_15}},
                   {"score": 0.25_37, "label": "cat", "box": {"xmin": 1, "ymin": 55, "xmax": 3_15, "ymax": 4_72}},
                   {"score": 0.14_74, "label": "remote", "box": {"xmin": 3_35, "ymin": 74, "xmax": 3_71, "ymax": 1_87}},
                   {"score": 0.12_08, "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       __UpperCamelCase     (      self				:     List[str]  )					->						Tuple:
       pass






   @require_torch
   @slow
   def       __UpperCamelCase     (      self				:     Any  )					->						Tuple:
       lowercase__ :   str    					=				0.2
       lowercase__ :   Optional[Any]    					=				pipeline("zero-shot-object-detection"  )

       lowercase__ :   Tuple    					=				object_detector(
           "http://images.cocodataset.org/val2017/000000039769.jpg"	,						candidate_labels=["cat", "remote", "couch"]	,						threshold=__lowerCamelCase	,						)
       self.assertEqual(
           nested_simplify(__lowerCamelCase	,						decimals=4  )	,						[
               {"score": 0.28_68, "label": "cat", "box": {"xmin": 3_24, "ymin": 20, "xmax": 6_40, "ymax": 3_73}},
               {"score": 0.2_77, "label": "remote", "box": {"xmin": 40, "ymin": 72, "xmax": 1_77, "ymax": 1_15}},
               {"score": 0.25_37, "label": "cat", "box": {"xmin": 1, "ymin": 55, "xmax": 3_15, "ymax": 4_72}},
           ]	,						)







   @require_torch
   @slow
   def       __UpperCamelCase     (      self				:     str  )					->						Any:
       lowercase__ :   Any    					=				2
       lowercase__ :   List[Any]    					=				pipeline("zero-shot-object-detection"  )

       lowercase__ :   str    					=				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": 0.28_68, "label": "cat", "box": {"xmin": 3_24, "ymin": 20, "xmax": 6_40, "ymax": 3_73}},
               {"score": 0.2_77, "label": "remote", "box": {"xmin": 40, "ymin": 72, "xmax": 1_77, "ymax": 1_15}},
           ]	,						)









import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


__lowerCAmelCase		:				List[Any]       			=		logging.get_logger(__name__)




class     snake_case__							(_UpperCamelCase   ):
				"""simple docstring"""



				def __init__(      self				:     Union[str, Any]					,      *__lowerCamelCase				:     Optional[Any]					,      **__lowerCamelCase				:     Dict							)					->     None:
							warnings.warn(
							    "The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
							    " use DonutImageProcessor instead."					,      __lowerCamelCase					,      )
							super().__init__(*__lowerCamelCase					,      **__lowerCamelCase							)






