
'''simple docstring'''

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import array, dot, pad, ravel, uinta, zeros


def 		_UpperCAmelCase			(					_lowerCamelCase  :    List[Any]					, _lowerCamelCase  :    Tuple						)      ->  Any:
  _lowerCAmelCase    :					Dict							=   image.shape
  _lowerCAmelCase    :					Optional[int]							=   cols - block_size[1] + 1
  _lowerCAmelCase    :					Tuple							=   rows - block_size[0] + 1
  _lowerCAmelCase    :					str							=   zeros((dst_height * dst_width, block_size[1] * block_size[0])						)
  _lowerCAmelCase    :					Optional[int]							=   0
  for i in range(0					, _lowerCamelCase						):
    for j in range(0					, _lowerCamelCase						):
      _lowerCAmelCase    :					Optional[int]							=   ravel(image[i : i + block_size[0], j : j + block_size[1]]						)
      _lowerCAmelCase    :					Optional[Any]							=   window
      row += 1

  return image_array


def 		_UpperCAmelCase			(					_lowerCamelCase  :    Optional[Any]					, _lowerCamelCase  :    Optional[int]						)      ->  int:
  _lowerCAmelCase    :					Optional[int]							=   image.shape[0], image.shape[1]
  _lowerCAmelCase    :					Any							=   filter_kernel.shape[0]
  _lowerCAmelCase    :					Tuple							=   k_size // 2
  # Pads image with the edge values of array.
  _lowerCAmelCase    :					Optional[int]							=   pad(_lowerCamelCase					, _lowerCamelCase					, mode="""edge"""						)

  # im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
  _lowerCAmelCase    :					Any							=   imacol(_lowerCamelCase					, (k_size, k_size)						)

  #  turn the kernel into shape(k*k, 1)
  _lowerCAmelCase    :					Tuple							=   ravel(_lowerCamelCase						)
  # reshape and get the dst image
  _lowerCAmelCase    :					str							=   dot(_lowerCamelCase					, _lowerCamelCase						).reshape(_lowerCamelCase					, _lowerCamelCase						)
  return dst


if __name__ == "__main__":
     # read original image
     UpperCamelCase_            =    imread(r"""../image_data/lena.jpg""")
     # turn image in gray scale value
     UpperCamelCase_            =    cvtColor(img, COLOR_BGR2GRAY)
     # Laplace operator
     UpperCamelCase_            =    array([[0, 1, 0], [1, -4, 1], [0, 1, 0]])
     UpperCamelCase_            =    img_convolve(gray, Laplace_kernel).astype(uinta)
     imshow("""Laplacian""", out)
     waitKey(0)


'''simple docstring'''

import platform
from argparse import ArgumentParser

import huggingface_hub
import pandas
import pyarrow

from datasets import __version__ as version
from datasets.commands import BaseDatasetsCLICommand


def 		_UpperCAmelCase			(					_lowerCamelCase  :    List[Any]						)      ->  Optional[Any]:
  return EnvironmentCommand()



class 					a_					(_a      ):




       @staticmethod
       def 							__UpperCamelCase    (       snake_case_					):
         _lowerCAmelCase    :					Optional[Any]							=   parser.add_parser("""env"""				,				help="""Print relevant system environment info."""					)
         download_parser.set_defaults(func=snake_case_					)




       def 							__UpperCamelCase    (       self					):
         _lowerCAmelCase    :					Optional[Any]							=   {
             """`datasets` version""": version,
             """Platform""": platform.platform(),
             """Python version""": platform.python_version(),
             """Huggingface_hub version""": huggingface_hub.__version__,
             """PyArrow version""": pyarrow.__version__,
             """Pandas version""": pandas.__version__,
         }

         print("""\nCopy-and-paste the text below in your GitHub issue.\n"""					)
         print(self.format_dict(snake_case_					)					)

         return info







       @staticmethod
       def 							__UpperCamelCase    (       snake_case_					):
         return "\n".join([f'- {prop}: {val}' for prop, val in d.items()]					) + "\n"


