




import copy
import re





class     SCREAMING_SNAKE_CASE__		:
     lowercase_ :      Optional[Any]				= "hp"
     lowercase_ :      Any				= {}
     lowercase_ :      Dict				= None
     @classmethod
     def        A__      (						cls	:		Tuple       ,						__lowerCamelCase	:		Tuple       ,						__lowerCamelCase	:		Dict						):



       """simple docstring"""
       lowerCAmelCase__										=      prefix
       lowerCAmelCase__										=      defaults
       cls.build_naming_info()
     @staticmethod
     def        A__      (						__lowerCamelCase	:		Tuple       ,						__lowerCamelCase	:		List[str]						):



       """simple docstring"""
       if len(__lowerCamelCase						) == 0:
         return ""
       lowerCAmelCase__										=      None
       if any(char.isdigit() for char in word						):
         raise Exception(F"""Parameters should not contain numbers: '{word}' contains a number"""						)
       if word in info["short_word"]:
         return info["short_word"][word]
       for prefix_len in range(1       ,						len(__lowerCamelCase						) + 1						):
         lowerCAmelCase__										=      word[:prefix_len]
         if prefix in info["reverse_short_word"]:
           continue
         else:
           lowerCAmelCase__										=      prefix
           break

       if short_word is None:
         # Paranoid fallback
         def int_to_alphabetic(__lowerCamelCase	:		Optional[int]						):
           lowerCAmelCase__										=      ''''''
           while integer != 0:
             lowerCAmelCase__										=      chr(ord('''A'''						) + integer % 10						) + s
             integer //= 10
           return s

         lowerCAmelCase__										=      0
         while True:
           lowerCAmelCase__										=      word + '''#''' + int_to_alphabetic(__lowerCamelCase						)
           if sword in info["reverse_short_word"]:
             continue
           else:
             lowerCAmelCase__										=      sword
             break

       lowerCAmelCase__										=      short_word
       lowerCAmelCase__										=      word
       return short_word
     @staticmethod
     def        A__      (						__lowerCamelCase	:		int       ,						__lowerCamelCase	:		Optional[int]						):



       """simple docstring"""
       lowerCAmelCase__										=      param_name.split('''_'''						)

       lowerCAmelCase__										=      [TrialShortNamer.shortname_for_word(__lowerCamelCase       ,						__lowerCamelCase						) for word in words]

       # We try to create a separatorless short name, but if there is a collision we have to fallback
       # to a separated short name
       lowerCAmelCase__										=      ['''''', '''_''']

       for separator in separators:
         lowerCAmelCase__										=      separator.join(__lowerCamelCase						)
         if shortname not in info["reverse_short_param"]:
           lowerCAmelCase__										=      shortname
           lowerCAmelCase__										=      param_name
           return shortname

       return param_name
     @staticmethod
     def        A__      (						__lowerCamelCase	:		List[Any]       ,						__lowerCamelCase	:		Optional[int]						):



       """simple docstring"""
       lowerCAmelCase__										=      TrialShortNamer.shortname_for_key(__lowerCamelCase       ,						__lowerCamelCase						)
       lowerCAmelCase__										=      short_name
       lowerCAmelCase__										=      param_name
     @classmethod
     def        A__      (						cls	:		Optional[int]						):



       """simple docstring"""
       if cls.NAMING_INFO is not None:
         return

       lowerCAmelCase__										=      {
           '''short_word''': {},
           '''reverse_short_word''': {},
           '''short_param''': {},
           '''reverse_short_param''': {},
       }

       lowerCAmelCase__										=      list(cls.DEFAULTS.keys()						)

       for k in field_keys:
         cls.add_new_param_name(__lowerCamelCase       ,						__lowerCamelCase						)

       lowerCAmelCase__										=      info
     @classmethod
     def        A__      (						cls	:		Dict       ,						__lowerCamelCase	:		List[str]						):



       """simple docstring"""
       cls.build_naming_info()
       assert cls.PREFIX is not None
       lowerCAmelCase__										=      [copy.copy(cls.PREFIX						)]

       for k, v in params.items():
         if k not in cls.DEFAULTS:
           raise Exception(F"""You should provide a default value for the param name {k} with value {v}"""						)
         if v == cls.DEFAULTS[k]:
           # The default value is not added to the name
           continue

         lowerCAmelCase__										=      cls.NAMING_INFO['''short_param'''][k]

         if isinstance(__lowerCamelCase       ,						__lowerCamelCase						):
           lowerCAmelCase__										=      1 if v else 0

         lowerCAmelCase__										=      '''''' if isinstance(__lowerCamelCase       ,						(int, float)						) else '''-'''
         lowerCAmelCase__										=      F"""{key}{sep}{v}"""
         name.append(__lowerCamelCase						)

       return "_".join(__lowerCamelCase						)



     @classmethod
     def        A__      (						cls	:		List[Any]       ,						__lowerCamelCase	:		Union[str, Any]						):



       """simple docstring"""
       lowerCAmelCase__										=      repr[len(cls.PREFIX						) + 1 :]
       if repr == "":
         lowerCAmelCase__										=      []
       else:
         lowerCAmelCase__										=      repr.split('''_'''						)

       lowerCAmelCase__										=      {}

       for value in values:
         if "-" in value:
           lowerCAmelCase__				,      lowerCAmelCase__										=      value.split('''-'''						)
         else:
           lowerCAmelCase__										=      re.sub('''[0-9.]'''       ,						''''''       ,						__lowerCamelCase						)
           lowerCAmelCase__										=      float(re.sub('''[^0-9.]'''       ,						''''''       ,						__lowerCamelCase						)						)

         lowerCAmelCase__										=      cls.NAMING_INFO['''reverse_short_param'''][p_k]

         lowerCAmelCase__										=      p_v

       for k in cls.DEFAULTS:
         if k not in parameters:
           lowerCAmelCase__										=      cls.DEFAULTS[k]

       return parameters







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     SCREAMING_SNAKE_CASE__		:
           @staticmethod
           def        A__      (						*__lowerCamelCase	:		List[str]       ,						**__lowerCamelCase	:		Optional[int]						):



             """simple docstring"""
             pass
def 		a_							( __lowerCAmelCase				):
  lowerCAmelCase__										=      hashlib.mda(image.tobytes()				)
  return m.hexdigest()[:10]
def 		a_							( __lowerCAmelCase				):
  lowerCAmelCase__										=      np.array(__lowerCAmelCase				)
  lowerCAmelCase__										=      npimg.shape
  return {"hash": hashimage(__lowerCAmelCase				), "shape": shape}





@is_pipeline_test
@require_vision
@require_torch
class     SCREAMING_SNAKE_CASE__		(unittest.TestCase			):
     lowercase_ :      Any				= dict(
         (list(MODEL_FOR_MASK_GENERATION_MAPPING.items()			) if MODEL_FOR_MASK_GENERATION_MAPPING else [])			)
     lowercase_ :      str				= dict(
         (list(TF_MODEL_FOR_MASK_GENERATION_MAPPING.items()			) if TF_MODEL_FOR_MASK_GENERATION_MAPPING else [])			)
     def        A__      (						self	:		int       ,						__lowerCamelCase	:		Union[str, Any]       ,						__lowerCamelCase	:		Dict       ,						__lowerCamelCase	:		int						):



       """simple docstring"""
       lowerCAmelCase__										=      MaskGenerationPipeline(model=__lowerCamelCase       ,						image_processor=__lowerCamelCase						)
       return image_segmenter, [
           "./tests/fixtures/tests_samples/COCO/000000039769.png",
           "./tests/fixtures/tests_samples/COCO/000000039769.png",
       ]
     def        A__      (						self	:		Optional[int]       ,						__lowerCamelCase	:		Dict       ,						__lowerCamelCase	:		Optional[int]						):



       """simple docstring"""
       pass
     @require_tf
     @unittest.skip('''Image segmentation not implemented in TF'''						)
     def        A__      (						self	:		Dict						):



       """simple docstring"""
       pass
     @slow
     @require_torch
     def        A__      (						self	:		Optional[int]						):



       """simple docstring"""
       lowerCAmelCase__										=      pipeline('''mask-generation'''       ,						model='''facebook/sam-vit-huge'''						)

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

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

       # fmt: off
       self.assertEqual(
           nested_simplify(__lowerCamelCase       ,						decimals=4						)       ,						[
               {'''mask''': {'''hash''': '''115ad19f5f''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0444},
               {'''mask''': {'''hash''': '''6affa964c6''', '''shape''': (4_80, 6_40)}, '''scores''': 1.021},
               {'''mask''': {'''hash''': '''dfe28a0388''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0167},
               {'''mask''': {'''hash''': '''c0a5f4a318''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0132},
               {'''mask''': {'''hash''': '''fe8065c197''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0053},
               {'''mask''': {'''hash''': '''e2d0b7a0b7''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9967},
               {'''mask''': {'''hash''': '''453c7844bd''', '''shape''': (4_80, 6_40)}, '''scores''': 0.993},
               {'''mask''': {'''hash''': '''3d44f2926d''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9909},
               {'''mask''': {'''hash''': '''64033ddc3f''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9879},
               {'''mask''': {'''hash''': '''801064ff79''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9834},
               {'''mask''': {'''hash''': '''6172f276ef''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9716},
               {'''mask''': {'''hash''': '''b49e60e084''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9612},
               {'''mask''': {'''hash''': '''a811e775fd''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9599},
               {'''mask''': {'''hash''': '''a6a8ebcf4b''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9552},
               {'''mask''': {'''hash''': '''9d8257e080''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9532},
               {'''mask''': {'''hash''': '''32de6454a8''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9516},
               {'''mask''': {'''hash''': '''af3d4af2c8''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9499},
               {'''mask''': {'''hash''': '''3c6db475fb''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9483},
               {'''mask''': {'''hash''': '''c290813fb9''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9464},
               {'''mask''': {'''hash''': '''b6f0b8f606''', '''shape''': (4_80, 6_40)}, '''scores''': 0.943},
               {'''mask''': {'''hash''': '''92ce16bfdf''', '''shape''': (4_80, 6_40)}, '''scores''': 0.943},
               {'''mask''': {'''hash''': '''c749b25868''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9408},
               {'''mask''': {'''hash''': '''efb6cab859''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9335},
               {'''mask''': {'''hash''': '''1ff2eafb30''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9326},
               {'''mask''': {'''hash''': '''788b798e24''', '''shape''': (4_80, 6_40)}, '''scores''': 0.9262},
               {'''mask''': {'''hash''': '''abea804f0e''', '''shape''': (4_80, 6_40)}, '''scores''': 0.8999},
               {'''mask''': {'''hash''': '''7b9e8ddb73''', '''shape''': (4_80, 6_40)}, '''scores''': 0.8986},
               {'''mask''': {'''hash''': '''cd24047c8a''', '''shape''': (4_80, 6_40)}, '''scores''': 0.8984},
               {'''mask''': {'''hash''': '''6943e6bcbd''', '''shape''': (4_80, 6_40)}, '''scores''': 0.8873},
               {'''mask''': {'''hash''': '''b5f47c9191''', '''shape''': (4_80, 6_40)}, '''scores''': 0.8871}
           ]       ,						)
       # fmt: on



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



       """simple docstring"""
       lowerCAmelCase__										=      '''facebook/sam-vit-huge'''
       lowerCAmelCase__										=      pipeline('''mask-generation'''       ,						model=__lowerCamelCase						)

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

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

       self.assertEqual(
           nested_simplify(__lowerCamelCase       ,						decimals=4						)       ,						[
               {'''mask''': {'''hash''': '''115ad19f5f''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0444},
               {'''mask''': {'''hash''': '''6affa964c6''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0210},
               {'''mask''': {'''hash''': '''dfe28a0388''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0167},
               {'''mask''': {'''hash''': '''c0a5f4a318''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0132},
               {'''mask''': {'''hash''': '''fe8065c197''', '''shape''': (4_80, 6_40)}, '''scores''': 1.0053},
           ]       ,						)

