





'''simple docstring'''







import hashlib
import unittest
from typing import Dict

import numpy as np

from transformers import (
    MODEL_FOR_MASK_GENERATION_MAPPING,
    TF_MODEL_FOR_MASK_GENERATION_MAPPING,
    is_vision_available,
    pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_torch,
    require_vision,
    slow,
)


if is_vision_available():
   from PIL import Image
else:
   class 			_lowercase						:







        @staticmethod
        def     UpperCamelCase			( *A__    ,   **A__    ) ->	int:
         pass

def    __UpperCamelCase	(	a    : Image     ) ->str:
 snake_case				=			hashlib.mda(image.tobytes()     )
 return m.hexdigest()[:10]

def    __UpperCamelCase	(	a    : Image     ) ->Dict:
 snake_case				=			np.array(a     )
 snake_case				=			npimg.shape
 return {"hash": hashimage(a     ), "shape": shape}






@is_pipeline_test
@require_vision
@require_torch
class 			_lowercase						(       unittest.TestCase					):
     _UpperCAmelCase										=					dict(
         (list(MODEL_FOR_MASK_GENERATION_MAPPING.items()					) if MODEL_FOR_MASK_GENERATION_MAPPING else [])					)
     _UpperCAmelCase										=					dict(
         (list(TF_MODEL_FOR_MASK_GENERATION_MAPPING.items()					) if TF_MODEL_FOR_MASK_GENERATION_MAPPING else [])					)







     def     UpperCamelCase			( self    ,   A__    ,   A__    ,   A__    ) ->	int:
      snake_case				=			MaskGenerationPipeline(model=A__    ,   image_processor=A__    )
      return image_segmenter, [
          "./tests/fixtures/tests_samples/COCO/000000039769.png",
          "./tests/fixtures/tests_samples/COCO/000000039769.png",
      ]







     def     UpperCamelCase			( self    ,   A__    ,   A__    ) ->	Any:
      pass







     @require_tf
     @unittest.skip('''Image segmentation not implemented in TF'''    )
     def     UpperCamelCase			( self    ) ->	Dict:
      pass







     @slow
     @require_torch
     def     UpperCamelCase			( self    ) ->	int:
      snake_case				=			pipeline('''mask-generation'''    ,   model='''facebook/sam-vit-huge'''    )

      snake_case				=			image_segmenter('''http://images.cocodataset.org/val2017/000000039769.jpg'''    ,   points_per_batch=2_56    )

      # Shortening by hashing
      snake_case				=			[]
      for i, o in enumerate(outputs['''masks''']    ):
       new_outupt += [{"mask": mask_to_test_readable(A__    ), "scores": outputs["scores"][i]}]

      # fmt: off
      self.assertEqual(
          nested_simplify(A__    ,   decimals=4    )    ,   [
              {'''mask''': {'''hash''': '''115ad19f5f''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0_4_4_4},
              {'''mask''': {'''hash''': '''6affa964c6''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0_2_1},
              {'''mask''': {'''hash''': '''dfe28a0388''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0_1_6_7},
              {'''mask''': {'''hash''': '''c0a5f4a318''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0_1_3_2},
              {'''mask''': {'''hash''': '''fe8065c197''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0_0_5_3},
              {'''mask''': {'''hash''': '''e2d0b7a0b7''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_9_6_7},
              {'''mask''': {'''hash''': '''453c7844bd''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_9_3},
              {'''mask''': {'''hash''': '''3d44f2926d''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_9_0_9},
              {'''mask''': {'''hash''': '''64033ddc3f''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_8_7_9},
              {'''mask''': {'''hash''': '''801064ff79''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_8_3_4},
              {'''mask''': {'''hash''': '''6172f276ef''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_7_1_6},
              {'''mask''': {'''hash''': '''b49e60e084''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_6_1_2},
              {'''mask''': {'''hash''': '''a811e775fd''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_5_9_9},
              {'''mask''': {'''hash''': '''a6a8ebcf4b''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_5_5_2},
              {'''mask''': {'''hash''': '''9d8257e080''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_5_3_2},
              {'''mask''': {'''hash''': '''32de6454a8''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_5_1_6},
              {'''mask''': {'''hash''': '''af3d4af2c8''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_4_9_9},
              {'''mask''': {'''hash''': '''3c6db475fb''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_4_8_3},
              {'''mask''': {'''hash''': '''c290813fb9''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_4_6_4},
              {'''mask''': {'''hash''': '''b6f0b8f606''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_4_3},
              {'''mask''': {'''hash''': '''92ce16bfdf''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_4_3},
              {'''mask''': {'''hash''': '''c749b25868''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_4_0_8},
              {'''mask''': {'''hash''': '''efb6cab859''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_3_3_5},
              {'''mask''': {'''hash''': '''1ff2eafb30''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_3_2_6},
              {'''mask''': {'''hash''': '''788b798e24''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9_2_6_2},
              {'''mask''': {'''hash''': '''abea804f0e''', '''shape''': (4_80, 6_40)}, '''scores''': 0.8_9_9_9},
              {'''mask''': {'''hash''': '''7b9e8ddb73''', '''shape''': (4_80, 6_40)}, '''scores''': 0.8_9_8_6},
              {'''mask''': {'''hash''': '''cd24047c8a''', '''shape''': (4_80, 6_40)}, '''scores''': 0.8_9_8_4},
              {'''mask''': {'''hash''': '''6943e6bcbd''', '''shape''': (4_80, 6_40)}, '''scores''': 0.8_8_7_3},
              {'''mask''': {'''hash''': '''b5f47c9191''', '''shape''': (4_80, 6_40)}, '''scores''': 0.8_8_7_1}
          ]    ,   )
      # fmt: on







     @require_torch
     @slow
     def     UpperCamelCase			( self    ) ->	Dict:
      snake_case				=			'''facebook/sam-vit-huge'''
      snake_case				=			pipeline('''mask-generation'''    ,   model=A__    )

      snake_case				=			image_segmenter(
          '''http://images.cocodataset.org/val2017/000000039769.jpg'''    ,   pred_iou_thresh=1    ,   points_per_batch=2_56    )

      # Shortening by hashing
      snake_case				=			[]
      for i, o in enumerate(outputs['''masks''']    ):
       new_outupt += [{"mask": mask_to_test_readable(A__    ), "scores": outputs["scores"][i]}]

      self.assertEqual(
          nested_simplify(A__    ,   decimals=4    )    ,   [
              {'''mask''': {'''hash''': '''115ad19f5f''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0_4_4_4},
              {'''mask''': {'''hash''': '''6affa964c6''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0_2_1_0},
              {'''mask''': {'''hash''': '''dfe28a0388''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0_1_6_7},
              {'''mask''': {'''hash''': '''c0a5f4a318''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0_1_3_2},
              {'''mask''': {'''hash''': '''fe8065c197''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0_0_5_3},
          ]    ,   )








'''simple docstring'''







from ..utils import DummyObject, requires_backends
class 			_lowercase						(       metaclass=__a					):
     _UpperCAmelCase										=					['''transformers''', '''torch''', '''note_seq''']







     def __init__( self    ,   *A__    ,   **A__    ) ->	Union[str, Any]:
      requires_backends(self    ,   ['''transformers''', '''torch''', '''note_seq''']    )







     @classmethod
     def     UpperCamelCase			( cls    ,   *A__    ,   **A__    ) ->	Optional[Any]:
      requires_backends(cls    ,   ['''transformers''', '''torch''', '''note_seq''']    )







     @classmethod
     def     UpperCamelCase			( cls    ,   *A__    ,   **A__    ) ->	Any:
      requires_backends(cls    ,   ['''transformers''', '''torch''', '''note_seq''']    )

