"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__lowerCAmelCase    :							Union[str, Any]													=						logging.get_logger(__name__)

__lowerCAmelCase    :							Optional[Any]													=						{
    "google/mobilenet_v2_1.4_224": "https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json",
    "google/mobilenet_v2_1.0_224": "https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json",
    "google/mobilenet_v2_0.75_160": "https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json",
    "google/mobilenet_v2_0.35_96": "https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json",
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}

class       a_      (     __UpperCamelCase			):
					UpperCamelCase_ :	List[Any]			=    "mobilenet_v2"




					def __init__(	self						:     Optional[Any]  ,						snake_case__						:     Union[str, Any]=3  ,						snake_case__						:     Tuple=224  ,						snake_case__						:     str=1.0  ,						snake_case__						:     Any=8  ,						snake_case__						:     Dict=8  ,						snake_case__						:     Any=6  ,						snake_case__						:     str=32  ,						snake_case__						:     str=True  ,						snake_case__						:     List[str]=True  ,						snake_case__						:     List[str]="relu6"  ,						snake_case__						:     Tuple=True  ,						snake_case__						:     List[str]=0.8  ,						snake_case__						:     int=0.02  ,						snake_case__						:     Any=0.001  ,						snake_case__						:     Dict=255  ,						**snake_case__						:     str  ,						):
							super().__init__(**snake_case__     )

							if depth_multiplier <= 0:
									raise ValueError("""depth_multiplier must be greater than zero."""     )

							lowerCAmelCase__        =   num_channels
							lowerCAmelCase__        =   image_size
							lowerCAmelCase__        =   depth_multiplier
							lowerCAmelCase__        =   depth_divisible_by
							lowerCAmelCase__        =   min_depth
							lowerCAmelCase__        =   expand_ratio
							lowerCAmelCase__        =   output_stride
							lowerCAmelCase__        =   first_layer_is_expansion
							lowerCAmelCase__        =   finegrained_output
							lowerCAmelCase__        =   hidden_act
							lowerCAmelCase__        =   tf_padding
							lowerCAmelCase__        =   classifier_dropout_prob
							lowerCAmelCase__        =   initializer_range
							lowerCAmelCase__        =   layer_norm_eps
							lowerCAmelCase__        =   semantic_loss_ignore_index

class       a_      (     __UpperCamelCase			):
					UpperCamelCase_ :	Tuple			=    version.parse("1.11"			)




					@property
					def 						_SCREAMING_SNAKE_CASE						(	self						:     Optional[int]     ):
							return OrderedDict([("""pixel_values""", {0: """batch"""})]     )




					@property
					def 						_SCREAMING_SNAKE_CASE						(	self						:     int     ):
							if self.task == "image-classification":
									return OrderedDict([("""logits""", {0: """batch"""})]     )
							else:
									return OrderedDict([("""last_hidden_state""", {0: """batch"""}), ("""pooler_output""", {0: """batch"""})]     )




					@property
					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[Any]     ):
							return 1E-4





"""simple docstring"""




import copy
import os

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

class       a_      :




					def __init__(	self						:     Optional[int]     ):
							lowerCAmelCase__        =   """"""
							lowerCAmelCase__        =   """"""
							lowerCAmelCase__        =   []
							lowerCAmelCase__        =   0
							lowerCAmelCase__        =   256
							lowerCAmelCase__        =   0
							lowerCAmelCase__        =   0
							lowerCAmelCase__        =   0
							lowerCAmelCase__        =   0




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[Any]  ,						snake_case__						:     Union[str, Any]     ):
							lowerCAmelCase__        =   cva.imread(snake_case__  ,						0     )
							lowerCAmelCase__        =   copy.deepcopy(self.img     )
							lowerCAmelCase__   ,					lowerCAmelCase__   ,					lowerCAmelCase__        =   plt.hist(self.img.ravel()  ,						256  ,						[0, 256]  ,						label="""x"""     )
							lowerCAmelCase__        =   np.sum(snake_case__     )
							for i in range(len(snake_case__     )     ):
									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(snake_case__     )
									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[Any]     ):
							plt.hist(self.img.ravel()  ,						256  ,						[0, 256]     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Optional[Any]     ):
							cva.imshow("""Output-Image"""  ,						self.img     )
							cva.imshow("""Input-Image"""  ,						self.original_image     )
							cva.waitKey(5000     )
							cva.destroyAllWindows()


if __name__ == "__main__":
			__lowerCAmelCase    :							Dict													=						os.path.join(os.path.basename(__file__), "image_data/input.jpg")
			__lowerCAmelCase    :							Optional[int]													=						ConstantStretch()
			stretcher.stretch(file_path)
			stretcher.plot_histogram()
			stretcher.show_image()




