
'''simple docstring'''

import copy
import os

import cva
import numpy as np
from matplotlib import pyplot as plt






class  A  :





	def __init__(       self      :							Optional[Any]				):


				"""simple docstring"""

				lowerCAmelCase__										=				""
				lowerCAmelCase__										=				""
				lowerCAmelCase__										=				[]
				lowerCAmelCase__										=				0
				lowerCAmelCase__										=				256
				lowerCAmelCase__										=				0
				lowerCAmelCase__										=				0
				lowerCAmelCase__										=				0
				lowerCAmelCase__										=				0





	def 				__SCREAMING_SNAKE_CASE	(       self      :							str   ,				__magic_name__      :							Any				):


				"""simple docstring"""

				lowerCAmelCase__										=				cva.imread(__magic_name__   ,				0				)
				lowerCAmelCase__										=				copy.deepcopy(self.img				)
				lowerCAmelCase__						,lowerCAmelCase__						,lowerCAmelCase__										=				plt.hist(self.img.ravel()   ,				256   ,				[0, 256]   ,				label="x"				)
				lowerCAmelCase__										=				np.sum(__magic_name__				)
				for i in range(len(__magic_name__				)				):
							lowerCAmelCase__										=				x[i] / self.k
							self.sk += prk
							lowerCAmelCase__										=				(self.L - 1) * self.sk
							if self.rem != 0:
										lowerCAmelCase__										=				int(last % last				)
							lowerCAmelCase__										=				int(last + 1 if self.rem >= 0.5 else last				)
							self.last_list.append(__magic_name__				)
							lowerCAmelCase__										=				int(np.ma.count(self.img				) / self.img[1].size				)
							lowerCAmelCase__										=				self.img[1].size
				for i in range(self.number_of_cols				):
							for j in range(self.number_of_rows				):
										lowerCAmelCase__										=				self.img[j][i]
										if num != self.last_list[num]:
													lowerCAmelCase__										=				self.last_list[num]
				cva.imwrite("output_data/output.jpg"   ,				self.img				)





	def 				__SCREAMING_SNAKE_CASE	(       self      :							Optional[int]				):


				"""simple docstring"""

				plt.hist(self.img.ravel()   ,				256   ,				[0, 256]				)







	def 				__SCREAMING_SNAKE_CASE	(       self      :							int				):


				"""simple docstring"""

				cva.imshow("Output-Image"   ,				self.img				)
				cva.imshow("Input-Image"   ,				self.original_image				)
				cva.waitKey(5000				)
				cva.destroyAllWindows()


if __name__ == "__main__":
		UpperCAmelCase__ :			Any											=		os.path.join(os.path.basename(__file__), "image_data/input.jpg")
		UpperCAmelCase__ :			str											=		ConstantStretch()
		stretcher.stretch(file_path)
		stretcher.plot_histogram()
		stretcher.show_image()










"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


A_						:    str				=      {'configuration_unispeech': ['UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP', 'UniSpeechConfig']}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_						:    Optional[int]				=      [
							    'UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'UniSpeechForCTC',
							    'UniSpeechForPreTraining',
							    'UniSpeechForSequenceClassification',
							    'UniSpeechModel',
							    'UniSpeechPreTrainedModel',
							]

if TYPE_CHECKING:
							from .configuration_unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_unispeech import (
														    UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST,
														    UniSpeechForCTC,
														    UniSpeechForPreTraining,
														    UniSpeechForSequenceClassification,
														    UniSpeechModel,
														    UniSpeechPreTrainedModel,
														)

else:
							import sys

							A_						:    int				=      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





