




import numpy as np  # noqa: E402

from ...configuration_utils import ConfigMixin, register_to_config
from ...schedulers.scheduling_utils import SchedulerMixin


try:
     import librosa  # noqa: E402

     _UpperCAmelCase						:    Union[str, Any]      =  True
     _UpperCAmelCase						:    Optional[int]      =  ""
except Exception as e:
     _UpperCAmelCase						:    Optional[int]      =  False
     _UpperCAmelCase						:    Dict      =  (
         f'''Cannot import librosa because {e}. Make sure to correctly install librosa to be able to install it.'''
     )


from PIL import Image  # noqa: E402




class  __lowerCAmelCase							(				lowerCAmelCase   ,			lowerCAmelCase):
       _a			       =    '''mel_config.json'''






       @register_to_config
       def __init__( self:       Optional[int]							,       _lowerCAmelCase:       int = 2_56							,       _lowerCAmelCase:       int = 2_56							,       _lowerCAmelCase:       int = 2_20_50							,       _lowerCAmelCase:       int = 20_48							,       _lowerCAmelCase:       int = 5_12							,       _lowerCAmelCase:       int = 80							,       _lowerCAmelCase:       int = 32							,       ):
         lowercase     :Any   						=    hop_length
         lowercase     :List[str]   						=    sample_rate
         lowercase     :List[Any]   						=    n_fft
         lowercase     :List[Any]   						=    top_db
         lowercase     :Any   						=    n_iter
         self.set_resolution(_lowerCAmelCase							,       _lowerCAmelCase					)
         lowercase     :List[Any]   						=    None

         if not _librosa_can_be_imported:
           raise ValueError(_import_error					)






       def        SCREAMING_SNAKE_CASE     ( self:       List[str]							,       _lowerCAmelCase:       int							,       _lowerCAmelCase:       int					):
         lowercase     :List[str]   						=    x_res
         lowercase     :Optional[Any]   						=    y_res
         lowercase     :Tuple   						=    self.y_res
         lowercase     :List[str]   						=    self.x_res * self.hop_length - 1






       def        SCREAMING_SNAKE_CASE     ( self:       str							,       _lowerCAmelCase:       str = None							,       _lowerCAmelCase:       np.ndarray = None					):
         if audio_file is not None:
           lowercase						,     lowercase     :str   						=    librosa.load(_lowerCAmelCase							,       mono=_lowerCAmelCase							,       sr=self.sr					)
         else:
           lowercase     :int   						=    raw_audio

         # Pad with silence if necessary.
         if len(self.audio					) < self.x_res * self.hop_length:
           lowercase     :Dict   						=    np.concatenate([self.audio, np.zeros((self.x_res * self.hop_length - len(self.audio					),)					)]					)






       def        SCREAMING_SNAKE_CASE     ( self:       Tuple					):
         return len(self.audio					) // self.slice_size






       def        SCREAMING_SNAKE_CASE     ( self:       List[str]							,       _lowerCAmelCase:       int = 0					):
         return self.audio[self.slice_size * slice : self.slice_size * (slice + 1)]






       def        SCREAMING_SNAKE_CASE     ( self:       Optional[Any]					):
         return self.sr






       def        SCREAMING_SNAKE_CASE     ( self:       List[str]							,       _lowerCAmelCase:       int					):
         lowercase     :int   						=    librosa.feature.melspectrogram(
             y=self.get_audio_slice(_lowerCAmelCase					)							,       sr=self.sr							,       n_fft=self.n_fft							,       hop_length=self.hop_length							,       n_mels=self.n_mels					)
         lowercase     :Optional[int]   						=    librosa.power_to_db(_lowerCAmelCase							,       ref=np.max							,       top_db=self.top_db					)
         lowercase     :List[str]   						=    (((log_S + self.top_db) * 2_55 / self.top_db).clip(0							,       2_55					) + 0.5).astype(np.uinta					)
         lowercase     :Any   						=    Image.fromarray(_lowerCAmelCase					)
         return image






       def        SCREAMING_SNAKE_CASE     ( self:       List[str]							,       _lowerCAmelCase:       Image.Image					):
         lowercase     :Optional[Any]   						=    np.frombuffer(image.tobytes()							,       dtype="uint8"					).reshape((image.height, image.width)					)
         lowercase     :str   						=    bytedata.astype("float"					) * self.top_db / 2_55 - self.top_db
         lowercase     :List[str]   						=    librosa.db_to_power(_lowerCAmelCase					)
         lowercase     :str   						=    librosa.feature.inverse.mel_to_audio(
             _lowerCAmelCase							,       sr=self.sr							,       n_fft=self.n_fft							,       hop_length=self.hop_length							,       n_iter=self.n_iter					)
         return audio









import unittest
from pathlib import Path

from transformers import is_vision_available, load_tool
from transformers.testing_utils import get_tests_dir

from .test_tools_common import ToolTesterMixin


if is_vision_available():
     from PIL import Image




class  __lowerCAmelCase							(				unittest.TestCase   ,			lowerCAmelCase):






       def        SCREAMING_SNAKE_CASE     ( self:       Dict					):
         lowercase     :Any   						=    load_tool("image-segmentation"					)
         self.tool.setup()
         lowercase     :int   						=    load_tool("image-segmentation"							,       remote=_lowerCAmelCase					)






       def        SCREAMING_SNAKE_CASE     ( self:       str					):
         lowercase     :Any   						=    Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"					)					) / "000000039769.png"					)
         lowercase     :Dict   						=    self.tool(_lowerCAmelCase							,       "cat"					)
         self.assertTrue(isinstance(_lowerCAmelCase							,       Image.Image					)					)






       def        SCREAMING_SNAKE_CASE     ( self:       Union[str, Any]					):
         lowercase     :Dict   						=    Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"					)					) / "000000039769.png"					)
         lowercase     :List[Any]   						=    self.remote_tool(_lowerCAmelCase							,       "cat"					)
         self.assertTrue(isinstance(_lowerCAmelCase							,       Image.Image					)					)






       def        SCREAMING_SNAKE_CASE     ( self:       List[Any]					):
         lowercase     :Optional[Any]   						=    Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"					)					) / "000000039769.png"					)
         lowercase     :Dict   						=    self.tool(image=_lowerCAmelCase							,       label="cat"					)
         self.assertTrue(isinstance(_lowerCAmelCase							,       Image.Image					)					)






       def        SCREAMING_SNAKE_CASE     ( self:       Tuple					):
         lowercase     :int   						=    Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"					)					) / "000000039769.png"					)
         lowercase     :List[str]   						=    self.remote_tool(image=_lowerCAmelCase							,       label="cat"					)
         self.assertTrue(isinstance(_lowerCAmelCase							,       Image.Image					)					)



