

'''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 	A_			:






      '''simple docstring'''



      @staticmethod
      def        UpperCAmelCase_	(		*lowercase_			:					Any					,      **lowercase_			:					List[str]	)						->     str:
       pass




def 				UpperCamelCase(					UpperCAmelCase_     ):
 UpperCAmelCase	:     Optional[int]						 =			hashlib.mda(image.tobytes()     )
 return m.hexdigest()[:10]




def 				UpperCamelCase(					UpperCAmelCase_     ):
 UpperCAmelCase	:     Any						 =			np.array(UpperCAmelCase_     )
 UpperCAmelCase	:     Optional[Any]						 =			npimg.shape
 return {"hash": hashimage(UpperCAmelCase_     ), "shape": shape}




@is_pipeline_test
@require_vision
@require_torch
class 	A_			(    unittest.TestCase							):






     '''simple docstring'''



     UpperCAmelCase_						:     Any  		=  dict(
         (list(MODEL_FOR_MASK_GENERATION_MAPPING.items()							) if MODEL_FOR_MASK_GENERATION_MAPPING else [])							)
     UpperCAmelCase_						:     Optional[Any]  		=  dict(
         (list(TF_MODEL_FOR_MASK_GENERATION_MAPPING.items()							) if TF_MODEL_FOR_MASK_GENERATION_MAPPING else [])							)


     def        UpperCAmelCase_	(		self			:					Optional[Any]					,      lowercase_			:					Any					,      lowercase_			:					str					,      lowercase_			:					Optional[int]	)						->     Union[str, Any]:
      UpperCAmelCase	:     int						 =			MaskGenerationPipeline(model=lowercase_					,      image_processor=lowercase_	)
      return image_segmenter, [
          "./tests/fixtures/tests_samples/COCO/000000039769.png",
          "./tests/fixtures/tests_samples/COCO/000000039769.png",
      ]


     def        UpperCAmelCase_	(		self			:					str					,      lowercase_			:					Optional[Any]					,      lowercase_			:					Dict	)						->     str:
      pass


     @require_tf
     @unittest.skip('Image segmentation not implemented in TF'	)
     def        UpperCAmelCase_	(		self			:					List[str]	)						->     Union[str, Any]:
      pass


     @slow
     @require_torch
     def        UpperCAmelCase_	(		self			:					int	)						->     Tuple:
      UpperCAmelCase	:     List[str]						 =			pipeline('mask-generation'					,      model='facebook/sam-vit-huge'	)

      UpperCAmelCase	:     Dict						 =			image_segmenter('http://images.cocodataset.org/val2017/000000039769.jpg'					,      points_per_batch=256	)

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

      # fmt: off
      self.assertEqual(
          nested_simplify(lowercase_					,      decimals=4	)					,      [
              {'mask': {'hash': '115ad19f5f', 'shape': (480, 640)}, 'scores': 1.0444},
              {'mask': {'hash': '6affa964c6', 'shape': (480, 640)}, 'scores': 1.021},
              {'mask': {'hash': 'dfe28a0388', 'shape': (480, 640)}, 'scores': 1.0167},
              {'mask': {'hash': 'c0a5f4a318', 'shape': (480, 640)}, 'scores': 1.0132},
              {'mask': {'hash': 'fe8065c197', 'shape': (480, 640)}, 'scores': 1.0053},
              {'mask': {'hash': 'e2d0b7a0b7', 'shape': (480, 640)}, 'scores': 0.9967},
              {'mask': {'hash': '453c7844bd', 'shape': (480, 640)}, 'scores': 0.993},
              {'mask': {'hash': '3d44f2926d', 'shape': (480, 640)}, 'scores': 0.9909},
              {'mask': {'hash': '64033ddc3f', 'shape': (480, 640)}, 'scores': 0.9879},
              {'mask': {'hash': '801064ff79', 'shape': (480, 640)}, 'scores': 0.9834},
              {'mask': {'hash': '6172f276ef', 'shape': (480, 640)}, 'scores': 0.9716},
              {'mask': {'hash': 'b49e60e084', 'shape': (480, 640)}, 'scores': 0.9612},
              {'mask': {'hash': 'a811e775fd', 'shape': (480, 640)}, 'scores': 0.9599},
              {'mask': {'hash': 'a6a8ebcf4b', 'shape': (480, 640)}, 'scores': 0.9552},
              {'mask': {'hash': '9d8257e080', 'shape': (480, 640)}, 'scores': 0.9532},
              {'mask': {'hash': '32de6454a8', 'shape': (480, 640)}, 'scores': 0.9516},
              {'mask': {'hash': 'af3d4af2c8', 'shape': (480, 640)}, 'scores': 0.9499},
              {'mask': {'hash': '3c6db475fb', 'shape': (480, 640)}, 'scores': 0.9483},
              {'mask': {'hash': 'c290813fb9', 'shape': (480, 640)}, 'scores': 0.9464},
              {'mask': {'hash': 'b6f0b8f606', 'shape': (480, 640)}, 'scores': 0.943},
              {'mask': {'hash': '92ce16bfdf', 'shape': (480, 640)}, 'scores': 0.943},
              {'mask': {'hash': 'c749b25868', 'shape': (480, 640)}, 'scores': 0.9408},
              {'mask': {'hash': 'efb6cab859', 'shape': (480, 640)}, 'scores': 0.9335},
              {'mask': {'hash': '1ff2eafb30', 'shape': (480, 640)}, 'scores': 0.9326},
              {'mask': {'hash': '788b798e24', 'shape': (480, 640)}, 'scores': 0.9262},
              {'mask': {'hash': 'abea804f0e', 'shape': (480, 640)}, 'scores': 0.8999},
              {'mask': {'hash': '7b9e8ddb73', 'shape': (480, 640)}, 'scores': 0.8986},
              {'mask': {'hash': 'cd24047c8a', 'shape': (480, 640)}, 'scores': 0.8984},
              {'mask': {'hash': '6943e6bcbd', 'shape': (480, 640)}, 'scores': 0.8873},
              {'mask': {'hash': 'b5f47c9191', 'shape': (480, 640)}, 'scores': 0.8871}
          ]					,      )
      # fmt: on




     @require_torch
     @slow
     def        UpperCAmelCase_	(		self			:					Optional[int]	)						->     int:
      UpperCAmelCase	:     Any						 =			'facebook/sam-vit-huge'
      UpperCAmelCase	:     int						 =			pipeline('mask-generation'					,      model=lowercase_	)

      UpperCAmelCase	:     str						 =			image_segmenter(
          'http://images.cocodataset.org/val2017/000000039769.jpg'					,      pred_iou_thresh=1					,      points_per_batch=256	)

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

      self.assertEqual(
          nested_simplify(lowercase_					,      decimals=4	)					,      [
              {'mask': {'hash': '115ad19f5f', 'shape': (480, 640)}, 'scores': 1.0444},
              {'mask': {'hash': '6affa964c6', 'shape': (480, 640)}, 'scores': 1.0210},
              {'mask': {'hash': 'dfe28a0388', 'shape': (480, 640)}, 'scores': 1.0167},
              {'mask': {'hash': 'c0a5f4a318', 'shape': (480, 640)}, 'scores': 1.0132},
              {'mask': {'hash': 'fe8065c197', 'shape': (480, 640)}, 'scores': 1.0053},
          ]					,      )







'''simple docstring'''

# Lint as: python3
import itertools
import os
import re


lowercase__         =      re.compile(r"([A-Z]+)([A-Z][a-z])")
lowercase__         =      re.compile(r"([a-z\d])([A-Z])")

lowercase__         =      re.compile(r"(?<!_)_(?!_)")
lowercase__         =      re.compile(r"(_{2,})")

lowercase__         =      r"^\w+(\.\w+)*$"

lowercase__         =      r"<>:/\|?*"




def 				UpperCamelCase(					UpperCAmelCase_     ):
 UpperCAmelCase	:     List[str]						 =			_uppercase_uppercase_re.sub(R'\1_\2'  ,	UpperCAmelCase_     )
 UpperCAmelCase	:     str						 =			_lowercase_uppercase_re.sub(R'\1_\2'  ,	UpperCAmelCase_     )
 return name.lower()




def 				UpperCamelCase(					UpperCAmelCase_     ):
 UpperCAmelCase	:     List[str]						 =			_single_underscore_re.split(UpperCAmelCase_     )
 UpperCAmelCase	:     Optional[Any]						 =			[_multiple_underscores_re.split(UpperCAmelCase_     ) for n in name]
 return "".join(n.capitalize() for n in itertools.chain.from_iterable(UpperCAmelCase_     ) if n != ''     )




def 				UpperCamelCase(					UpperCAmelCase_     ):
 if os.path.basename(UpperCAmelCase_     ) != name:
  raise ValueError(F"""Should be a dataset name, not a path: {name}"""     )
 return camelcase_to_snakecase(UpperCAmelCase_     )




def 				UpperCamelCase(					UpperCAmelCase_  ,	UpperCAmelCase_     ):
 if os.path.basename(UpperCAmelCase_     ) != name:
  raise ValueError(F"""Should be a dataset name, not a path: {name}"""     )
 if not re.match(_split_re  ,	UpperCAmelCase_     ):
  raise ValueError(F"""Split name should match '{_split_re}'' but got '{split}'."""     )
 return F"""{filename_prefix_for_name(UpperCAmelCase_     )}-{split}"""




def 				UpperCamelCase(					UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_=None     ):
 UpperCAmelCase	:     Dict						 =			filename_prefix_for_split(UpperCAmelCase_  ,	UpperCAmelCase_     )
 if filetype_suffix:
  prefix += F""".{filetype_suffix}"""
 UpperCAmelCase	:     Optional[int]						 =			os.path.join(UpperCAmelCase_  ,	UpperCAmelCase_     )
 return F"""{filepath}*"""




def 				UpperCamelCase(					UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_=None  ,	UpperCAmelCase_=None     ):
 UpperCAmelCase	:     Optional[int]						 =			filename_prefix_for_split(UpperCAmelCase_  ,	UpperCAmelCase_     )
 UpperCAmelCase	:     str						 =			os.path.join(UpperCAmelCase_  ,	UpperCAmelCase_     )

 if shard_lengths:
  UpperCAmelCase	:     List[str]						 =			len(UpperCAmelCase_     )
  UpperCAmelCase	:     List[str]						 =			[F"""{prefix}-{shard_id:05d}-of-{num_shards:05d}""" for shard_id in range(UpperCAmelCase_     )]
  if filetype_suffix:
   UpperCAmelCase	:     Dict						 =			[filename + F""".{filetype_suffix}""" for filename in filenames]
  return filenames
 else:
  UpperCAmelCase	:     Optional[Any]						 =			prefix
  if filetype_suffix:
   filename += F""".{filetype_suffix}"""
  return [filename]




