
from itertools import count
from math import asin, pi, sqrt



def        lowerCamelCase_  (   __UpperCamelCase     ):
				return (
				    (1 - 2 * point) * sqrt(point - point**2     ) + 2 * point + asin(sqrt(1 - point     )     )
				) / 4



def        lowerCamelCase_  (   __UpperCamelCase     ):
				A_       	=  (circles_number + 1 - sqrt(2 * circles_number     )) / (
				    2 * (circles_number**2 + 1)
				)
				A_       	=  circles_number * intersection_y

				A_       	=  intersection_x * intersection_y / 2
				A_       	=  circle_bottom_arc_integral(
				    1 / 2     ) - circle_bottom_arc_integral(__UpperCamelCase     )

				return triangle_area + concave_region_area



def        lowerCamelCase_  (   __UpperCamelCase = 1 / 10_00     ):
				A_       	=  (1 - pi / 4) / 4

				for n in count(1     ):
								if concave_triangle_area(__UpperCamelCase     ) / l_section_area < fraction:
												return n

				return -1


if __name__ == "__main__":
						print(f'''{solution() = }''')

from cva import destroyAllWindows, imread, imshow, waitKey



def        lowerCamelCase_  (   __UpperCamelCase ,						__UpperCamelCase     ):
				A_	,					A_       	=  img.shape[0], img.shape[1]

				def to_grayscale(__UpperCamelCase ,						__UpperCamelCase ,						__UpperCamelCase     ):
								return 0.2126 * red + 0.587 * green + 0.114 * blue

				def normalize(__UpperCamelCase     ):
								return min(__UpperCamelCase ,						2_55     )

				for i in range(__UpperCamelCase     ):
								for j in range(__UpperCamelCase     ):
												A_       	=  int(to_grayscale(*img[i][j]     )     )
												A_       	=  [
												    normalize(__UpperCamelCase     ),
												    normalize(greyscale + factor     ),
												    normalize(greyscale + 2 * factor     ),
												]

				return img


if __name__ == "__main__":
						# read original image
						SCREAMING_SNAKE_CASE   :		Optional[Any]					 =       {
						    percentage: imread("image_data/lena.jpg", 1) for percentage in (10, 20, 30, 40)
						}

						for percentage, img in images.items():
												make_sepia(img, percentage)

						for percentage, img in images.items():
												imshow(f'''Original image with sepia (factor: {percentage})''', img)

						waitKey(0)
						destroyAllWindows()