
from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class 					lowercase__(							UpperCAmelCase				):



	"""simple docstring"""




	def __init__(			self    :     Any			,				SCREAMING_SNAKE_CASE_    :     pyspark.sql.DataFrame			,				SCREAMING_SNAKE_CASE_    :     Optional[NamedSplit] = None			,				SCREAMING_SNAKE_CASE_    :     Optional[Features] = None			,				SCREAMING_SNAKE_CASE_    :     bool = True			,				SCREAMING_SNAKE_CASE_    :     str = None			,				SCREAMING_SNAKE_CASE_    :     bool = False			,				SCREAMING_SNAKE_CASE_    :     str = None			,				SCREAMING_SNAKE_CASE_    :     bool = True			,				SCREAMING_SNAKE_CASE_    :     str = "arrow"			,				**SCREAMING_SNAKE_CASE_    :     str			,				)			->	Optional[int]:
					super().__init__(
					    split=SCREAMING_SNAKE_CASE_			,				features=SCREAMING_SNAKE_CASE_			,				cache_dir=SCREAMING_SNAKE_CASE_			,				keep_in_memory=SCREAMING_SNAKE_CASE_			,				streaming=SCREAMING_SNAKE_CASE_			,				**SCREAMING_SNAKE_CASE_			,				)
					lowercase_	    =   load_from_cache_file
					lowercase_	    =   file_format
					lowercase_	    =   Spark(
					    df=SCREAMING_SNAKE_CASE_			,				features=SCREAMING_SNAKE_CASE_			,				cache_dir=SCREAMING_SNAKE_CASE_			,				working_dir=SCREAMING_SNAKE_CASE_			,				**SCREAMING_SNAKE_CASE_			,				)




	def 		_lowercase    (			self    :     int			)			->	Optional[Any]:
					if self.streaming:
									return self.builder.as_streaming_dataset(split=self.split			)
					lowercase_	    =   None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
					self.builder.download_and_prepare(
					    download_mode=SCREAMING_SNAKE_CASE_			,				file_format=self._file_format			,				)
					return self.builder.as_dataset(split=self.split			)









from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros







def     UpperCAmelCase_		(					snake_case__    ,			snake_case__					)	->     Dict:



				"""simple docstring"""





				lowerCAmelCase__		  =  k_size // 2
				lowerCAmelCase__  ,   lowerCAmelCase__		  =  mgrid[0 - center : k_size - center, 0 - center : k_size - center]
				lowerCAmelCase__		  =  1 / (2 * pi * sigma) * exp(-(square(snake_case__					) + square(snake_case__					)) / (2 * square(snake_case__					))					)
				return g







def     UpperCAmelCase_		(					snake_case__    ,			snake_case__    ,			snake_case__					)	->     str:



				"""simple docstring"""





				lowerCAmelCase__  ,   lowerCAmelCase__		  =  image.shape[0], image.shape[1]
				# dst image height and width
				lowerCAmelCase__		  =  height - k_size + 1
				lowerCAmelCase__		  =  width - k_size + 1

				# im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
				lowerCAmelCase__		  =  zeros((dst_height * dst_width, k_size * k_size)					)
				lowerCAmelCase__		  =  0
				for i, j in product(range(snake_case__					)    ,			range(snake_case__					)					):
								lowerCAmelCase__		  =  ravel(image[i : i + k_size, j : j + k_size]					)
								lowerCAmelCase__		  =  window
								row += 1

				#  turn the kernel into shape(k*k, 1)
				lowerCAmelCase__		  =  gen_gaussian_kernel(snake_case__    ,			snake_case__					)
				lowerCAmelCase__		  =  ravel(snake_case__					)

				# reshape and get the dst image
				lowerCAmelCase__		  =  dot(snake_case__    ,			snake_case__					).reshape(snake_case__    ,			snake_case__					).astype(snake_case__					)

				return dst


if __name__ == "__main__":
	# read original image
	_lowerCAmelCase	:   List[str]    =   imread(R"../image_data/lena.jpg")
	# turn image in gray scale value
	_lowerCAmelCase	:   Optional[Any]    =   cvtColor(img, COLOR_BGR2GRAY)

	# get values with two different mask size
	_lowerCAmelCase	:   Optional[int]    =   gaussian_filter(gray, 3, sigma=1)
	_lowerCAmelCase	:   Tuple    =   gaussian_filter(gray, 5, sigma=0.8)

	# show result images
	imshow("gaussian filter with 3x3 mask", gaussianaxa)
	imshow("gaussian filter with 5x5 mask", gaussianaxa)
	waitKey()
