
'''simple docstring'''



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

			__A          =    True
			__A          =    ""
except Exception as e:
			__A          =    False
			__A          =    (
			    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 			A							(       __UpperCAmelCase		,						__UpperCAmelCase				):
			lowerCamelCase							:							str       		=  """mel_config.json"""



			@register_to_config
			def __init__(					self       ,     lowerCamelCase__ = 256       ,     lowerCamelCase__ = 256       ,     lowerCamelCase__ = 22_050       ,     lowerCamelCase__ = 2_048       ,     lowerCamelCase__ = 512       ,     lowerCamelCase__ = 80       ,     lowerCamelCase__ = 32       ,     )			->		str:




									'''simple docstring'''



									lowercase__							 =       hop_length
									lowercase__							 =       sample_rate
									lowercase__							 =       n_fft
									lowercase__							 =       top_db
									lowercase__							 =       n_iter
									self.set_resolution(lowerCamelCase__       ,     lowerCamelCase__       )
									lowercase__							 =       None

									if not _librosa_can_be_imported:
															raise ValueError(_import_error       )



			def A__ (					self       ,     lowerCamelCase__       ,     lowerCamelCase__       )			->		Dict:




									'''simple docstring'''



									lowercase__							 =       x_res
									lowercase__							 =       y_res
									lowercase__							 =       self.y_res
									lowercase__							 =       self.x_res * self.hop_length - 1



			def A__ (					self       ,     lowerCamelCase__ = None       ,     lowerCamelCase__ = None       )			->		Optional[int]:




									'''simple docstring'''



									if audio_file is not None:
															lowercase__ ,						lowercase__							 =       librosa.load(lowerCamelCase__       ,     mono=lowerCamelCase__       ,     sr=self.sr       )
									else:
															lowercase__							 =       raw_audio

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



			def A__ (					self       )			->		int:




									'''simple docstring'''



									return len(self.audio       ) // self.slice_size



			def A__ (					self       ,     lowerCamelCase__ = 0       )			->		np.ndarray:




									'''simple docstring'''



									return self.audio[self.slice_size * slice : self.slice_size * (slice + 1)]



			def A__ (					self       )			->		int:




									'''simple docstring'''



									return self.sr



			def A__ (					self       ,     lowerCamelCase__       )			->		Image.Image:




									'''simple docstring'''



									lowercase__							 =       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__							 =       librosa.power_to_db(lowerCamelCase__       ,     ref=np.max       ,     top_db=self.top_db       )
									lowercase__							 =       (((log_S + self.top_db) * 255 / self.top_db).clip(0       ,     255       ) + 0.5).astype(np.uinta       )
									lowercase__							 =       Image.fromarray(lowerCamelCase__       )
									return image



			def A__ (					self       ,     lowerCamelCase__       )			->		np.ndarray:




									'''simple docstring'''



									lowercase__							 =       np.frombuffer(image.tobytes()       ,     dtype="""uint8"""       ).reshape((image.height, image.width)       )
									lowercase__							 =       bytedata.astype("""float"""       ) * self.top_db / 255 - self.top_db
									lowercase__							 =       librosa.db_to_power(lowerCamelCase__       )
									lowercase__							 =       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








'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__A          =    {"configuration_detr": ["DETR_PRETRAINED_CONFIG_ARCHIVE_MAP", "DetrConfig", "DetrOnnxConfig"]}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__A          =    ["DetrFeatureExtractor"]
				__A          =    ["DetrImageProcessor"]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__A          =    [
				    "DETR_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "DetrForObjectDetection",
				    "DetrForSegmentation",
				    "DetrModel",
				    "DetrPreTrainedModel",
				]


if TYPE_CHECKING:
				from .configuration_detr import DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DetrConfig, DetrOnnxConfig

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_detr import DetrFeatureExtractor
								from .image_processing_detr import DetrImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_detr import (
								    DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
								    DetrForObjectDetection,
								    DetrForSegmentation,
								    DetrModel,
								    DetrPreTrainedModel,
								)

else:
				import sys

				__A          =    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






