


import copy
import os

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






class        __snake_case	:







    """simple docstring"""



    def __init__(       self   :  Any		)       ->  Union[str, Any]:
      lowerCAmelCase_      :				Any      =       """"""
      lowerCAmelCase_      :				Any      =       """"""
      lowerCAmelCase_      :				Dict      =       []
      lowerCAmelCase_      :				List[str]      =       0
      lowerCAmelCase_      :				int      =       2_56
      lowerCAmelCase_      :				int      =       0
      lowerCAmelCase_      :				Optional[Any]      =       0
      lowerCAmelCase_      :				Optional[Any]      =       0
      lowerCAmelCase_      :				Dict      =       0

    def __lowercase       (       self   :  int   ,						lowerCamelCase   :  str		)       ->  int:
      lowerCAmelCase_      :				Tuple      =       cva.imread(__A   ,						0		)
      lowerCAmelCase_      :				Any      =       copy.deepcopy(self.img		)
      lowerCAmelCase_,							lowerCAmelCase_,							lowerCAmelCase_      :				Any      =       plt.hist(self.img.ravel()   ,						2_56   ,						[0, 2_56]   ,						label="""x"""		)
      lowerCAmelCase_      :				List[str]      =       np.sum(__A		)
      for i in range(len(__A		)		):
        lowerCAmelCase_      :				str      =       x[i] / self.k
        self.sk += prk
        lowerCAmelCase_      :				Union[str, Any]      =       (self.L - 1) * self.sk
        if self.rem != 0:
          lowerCAmelCase_      :				List[str]      =       int(last % last		)
        lowerCAmelCase_      :				int      =       int(last + 1 if self.rem >= 0.5 else last		)
        self.last_list.append(__A		)
        lowerCAmelCase_      :				Optional[Any]      =       int(np.ma.count(self.img		) / self.img[1].size		)
        lowerCAmelCase_      :				List[str]      =       self.img[1].size
      for i in range(self.number_of_cols		):
        for j in range(self.number_of_rows		):
          lowerCAmelCase_      :				Optional[int]      =       self.img[j][i]
          if num != self.last_list[num]:
            lowerCAmelCase_      :				Union[str, Any]      =       self.last_list[num]
      cva.imwrite("""output_data/output.jpg"""   ,						self.img		)

    def __lowercase       (       self   :  Optional[Any]		)       ->  Optional[int]:
      plt.hist(self.img.ravel()   ,						2_56   ,						[0, 2_56]		)





    def __lowercase       (       self   :  str		)       ->  Any:
      cva.imshow("""Output-Image"""   ,						self.img		)
      cva.imshow("""Input-Image"""   ,						self.original_image		)
      cva.waitKey(50_00		)
      cva.destroyAllWindows()


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







'''simple docstring'''






from pathlib import Path

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







def     UpperCamelCase_      (   A__ :       np.ndarray							,   A__ :       np.ndarray							,   A__ :       np.ndarray							,   A__ :       int							,   A__ :       int ):
  '''simple docstring'''





  lowerCAmelCase_      :				List[Any]      =       cva.getAffineTransform(A__							,   A__ )
  return cva.warpAffine(A__							,   A__							,   (rows, cols) )


if __name__ == "__main__":
  # read original image
  __A :  Dict    							=				cva.imread(
      str(Path(__file__).resolve().parent.parent / "image_data" / "lena.jpg")
  )
  # turn image in gray scale value
  __A :  List[Any]    							=				cva.cvtColor(image, cva.COLOR_BGR2GRAY)
  # get image shape
  __A							,			__A :  Dict    							=				gray_img.shape

  # set different points to rotate image
  __A :  List[str]    							=				np.array([[50, 50], [200, 50], [50, 200]], np.floataa)
  __A :  Tuple    							=				np.array([[10, 100], [200, 50], [100, 250]], np.floataa)
  __A :  List[Any]    							=				np.array([[50, 50], [150, 50], [120, 200]], np.floataa)
  __A :  Optional[Any]    							=				np.array([[10, 100], [80, 50], [180, 250]], np.floataa)

  # add all rotated images in a list
  __A :  Optional[Any]    							=				[
      gray_img,
      get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
      get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
      get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
  ]

  # plot different image rotations
  __A :  Dict    							=				plt.figure(1)
  __A :  Optional[Any]    							=				["Original", "Rotation 1", "Rotation 2", "Rotation 3"]
  for i, image in enumerate(images):
    plt.subplot(2, 2, i + 1), plt.imshow(image, "gray")
    plt.title(titles[i])
    plt.axis("off")
    plt.subplots_adjust(left=0.0, bottom=0.0_5, right=1.0, top=0.9_5)
  plt.show()



