





'''simple docstring'''






from __future__ import annotations




class  _A :

		def __init__(   self					:   Optional[int]  ,      __magic_name__					:   list[list[int]]			)					->    str:


					"""simple docstring"""

					__snake_case					:      str							      =     TypeError(
					    """Matrices must be formed from a list of zero or more lists containing at """
					    """least one and the same number of values, each of which must be of type """
					    """int or float."""			)
					if len(__magic_name__			) != 0:
								__snake_case					:      List[str]							      =     len(rows[0]			)
								if cols == 0:
											raise error
								for row in rows:
											if len(__magic_name__			) != cols:
														raise error
											for value in row:
														if not isinstance(__magic_name__  ,      (int, float)			):
																	raise error
								__snake_case					:      Any							      =     rows
					else:
								__snake_case					:      List[Any]							      =     []

		def 	lowercase__     (   self					:   int			)					->    list[list[int]]:


					"""simple docstring"""

					return [[row[i] for row in self.rows] for i in range(len(self.rows[0]			)			)]

		@property
		def 	lowercase__     (   self					:   Union[str, Any]			)					->    int:


					"""simple docstring"""

					return len(self.rows			)

		@property
		def 	lowercase__     (   self					:   Any			)					->    int:


					"""simple docstring"""

					return len(self.rows[0]			)

		@property
		def 	lowercase__     (   self					:   str			)					->    tuple[int, int]:


					"""simple docstring"""

					return (self.num_rows, self.num_columns)

		@property
		def 	lowercase__     (   self					:   Optional[int]			)					->    bool:


					"""simple docstring"""

					return self.order[0] == self.order[1]

		def 	lowercase__     (   self					:   List[str]			)					->    Matrix:


					"""simple docstring"""

					__snake_case					:      List[str]							      =     [
					    [0 if column_num != row_num else 1 for column_num in range(self.num_rows			)]
					    for row_num in range(self.num_rows			)
					]
					return Matrix(__magic_name__			)

		def 	lowercase__     (   self					:   str			)					->    int:


					"""simple docstring"""

					if not self.is_square:
								return 0
					if self.order == (0, 0):
								return 1
					if self.order == (1, 1):
								return int(self.rows[0][0]			)
					if self.order == (2, 2):
								return int(
								    (self.rows[0][0] * self.rows[1][1])
								    - (self.rows[0][1] * self.rows[1][0])			)
					else:
								return sum(
								    self.rows[0][column] * self.cofactors().rows[0][column]
								    for column in range(self.num_columns			)			)

		def 	lowercase__     (   self					:   Any			)					->    bool:


					"""simple docstring"""

					return bool(self.determinant()			)

		def 	lowercase__     (   self					:   str  ,      __magic_name__					:   int  ,      __magic_name__					:   int			)					->    int:


					"""simple docstring"""

					__snake_case					:      Optional[int]							      =     [
					    [
					        self.rows[other_row][other_column]
					        for other_column in range(self.num_columns			)
					        if other_column != column
					    ]
					    for other_row in range(self.num_rows			)
					    if other_row != row
					]
					return Matrix(__magic_name__			).determinant()

		def 	lowercase__     (   self					:   Optional[int]  ,      __magic_name__					:   int  ,      __magic_name__					:   int			)					->    int:


					"""simple docstring"""

					if (row + column) % 2 == 0:
								return self.get_minor(__magic_name__  ,      __magic_name__			)
					return -1 * self.get_minor(__magic_name__  ,      __magic_name__			)

		def 	lowercase__     (   self					:   int			)					->    Matrix:


					"""simple docstring"""

					return Matrix(
					    [
					        [self.get_minor(__magic_name__  ,      __magic_name__			) for column in range(self.num_columns			)]
					        for row in range(self.num_rows			)
					    ]			)

		def 	lowercase__     (   self					:   str			)					->    Matrix:


					"""simple docstring"""

					return Matrix(
					    [
					        [
					            self.minors().rows[row][column]
					            if (row + column) % 2 == 0
					            else self.minors().rows[row][column] * -1
					            for column in range(self.minors().num_columns			)
					        ]
					        for row in range(self.minors().num_rows			)
					    ]			)

		def 	lowercase__     (   self					:   List[str]			)					->    Matrix:


					"""simple docstring"""

					__snake_case					:      List[str]							      =     [
					    [self.cofactors().rows[column][row] for column in range(self.num_columns			)]
					    for row in range(self.num_rows			)
					]
					return Matrix(__magic_name__			)

		def 	lowercase__     (   self					:   Any			)					->    Matrix:


					"""simple docstring"""

					__snake_case					:      List[Any]							      =     self.determinant()
					if not determinant:
								raise TypeError("""Only matrices with a non-zero determinant have an inverse"""			)
					return self.adjugate() * (1 / determinant)

		def __repr__(   self					:   Optional[int]			)					->    str:


					"""simple docstring"""

					return str(self.rows			)

		def __str__(   self					:   Optional[Any]			)					->    str:


					"""simple docstring"""

					if self.num_rows == 0:
								return "[]"
					if self.num_rows == 1:
								return "[[" + ". ".join(str(self.rows[0]			)			) + "]]"
					return (
					    "["
					    + "\n ".join(
					        [
					            """[""" + """. """.join([str(__magic_name__			) for value in row]			) + """.]"""
					            for row in self.rows
					        ]			)
					    + "]"
					)

		def 	lowercase__     (   self					:   Union[str, Any]  ,      __magic_name__					:   list[int]  ,      __magic_name__					:   int | None = None			)					->    None:


					"""simple docstring"""

					__snake_case					:      Tuple							      =     TypeError("""Row must be a list containing all ints and/or floats"""			)
					if not isinstance(__magic_name__  ,      __magic_name__			):
								raise type_error
					for value in row:
								if not isinstance(__magic_name__  ,      (int, float)			):
											raise type_error
					if len(__magic_name__			) != self.num_columns:
								raise ValueError(
								    """Row must be equal in length to the other rows in the matrix"""			)
					if position is None:
								self.rows.append(__magic_name__			)
					else:
								__snake_case					:      Optional[Any]							      =     self.rows[0:position] + [row] + self.rows[position:]

		def 	lowercase__     (   self					:   List[Any]  ,      __magic_name__					:   list[int]  ,      __magic_name__					:   int | None = None			)					->    None:


					"""simple docstring"""

					__snake_case					:      Tuple							      =     TypeError(
					    """Column must be a list containing all ints and/or floats"""			)
					if not isinstance(__magic_name__  ,      __magic_name__			):
								raise type_error
					for value in column:
								if not isinstance(__magic_name__  ,      (int, float)			):
											raise type_error
					if len(__magic_name__			) != self.num_rows:
								raise ValueError(
								    """Column must be equal in length to the other columns in the matrix"""			)
					if position is None:
								__snake_case					:      str							      =     [self.rows[i] + [column[i]] for i in range(self.num_rows			)]
					else:
								__snake_case					:      List[Any]							      =     [
								    self.rows[i][0:position] + [column[i]] + self.rows[i][position:]
								    for i in range(self.num_rows			)
								]

		def __eq__(   self					:   Tuple  ,      __magic_name__					:   object			)					->    bool:


					"""simple docstring"""

					if not isinstance(__magic_name__  ,      __magic_name__			):
								return NotImplemented
					return self.rows == other.rows

		def __ne__(   self					:   List[Any]  ,      __magic_name__					:   object			)					->    bool:


					"""simple docstring"""

					return not self == other

		def __neg__(   self					:   Dict			)					->    Matrix:


					"""simple docstring"""

					return self * -1

		def __add__(   self					:   List[Any]  ,      __magic_name__					:   Matrix			)					->    Matrix:


					"""simple docstring"""

					if self.order != other.order:
								raise ValueError("""Addition requires matrices of the same order"""			)
					return Matrix(
					    [
					        [self.rows[i][j] + other.rows[i][j] for j in range(self.num_columns			)]
					        for i in range(self.num_rows			)
					    ]			)

		def __sub__(   self					:   Optional[Any]  ,      __magic_name__					:   Matrix			)					->    Matrix:


					"""simple docstring"""

					if self.order != other.order:
								raise ValueError("""Subtraction requires matrices of the same order"""			)
					return Matrix(
					    [
					        [self.rows[i][j] - other.rows[i][j] for j in range(self.num_columns			)]
					        for i in range(self.num_rows			)
					    ]			)

		def __mul__(   self					:   Union[str, Any]  ,      __magic_name__					:   Matrix | int | float			)					->    Matrix:


					"""simple docstring"""

					if isinstance(__magic_name__  ,      (int, float)			):
								return Matrix(
								    [[int(element * other			) for element in row] for row in self.rows]			)
					elif isinstance(__magic_name__  ,      __magic_name__			):
								if self.num_columns != other.num_rows:
											raise ValueError(
											    """The number of columns in the first matrix must """
											    """be equal to the number of rows in the second"""			)
								return Matrix(
								    [
								        [Matrix.dot_product(__magic_name__  ,      __magic_name__			) for column in other.columns()]
								        for row in self.rows
								    ]			)
					else:
								raise TypeError(
								    """A Matrix can only be multiplied by an int, float, or another matrix"""			)

		def __pow__(   self					:   Tuple  ,      __magic_name__					:   int			)					->    Matrix:


					"""simple docstring"""

					if not isinstance(__magic_name__  ,      __magic_name__			):
								raise TypeError("""A Matrix can only be raised to the power of an int"""			)
					if not self.is_square:
								raise ValueError("""Only square matrices can be raised to a power"""			)
					if other == 0:
								return self.identity()
					if other < 0:
								if self.is_invertable():
											return self.inverse() ** (-other)
								raise ValueError(
								    """Only invertable matrices can be raised to a negative power"""			)
					__snake_case					:      int							      =     self
					for _ in range(other - 1			):
								result *= self
					return result

		@classmethod
		def 	lowercase__     (   cls					:   Dict  ,      __magic_name__					:   list[int]  ,      __magic_name__					:   list[int]			)					->    int:


					"""simple docstring"""

					return sum(row[i] * column[i] for i in range(len(__magic_name__			)			)			)


if __name__ == "__main__":
	import doctest

	doctest.testmod()









'''simple docstring'''






import cva
import numpy as np




class  _A :

		def __init__(   self					:   Any  ,      __magic_name__					:   float  ,      __magic_name__					:   int			)					->    Optional[int]:


					"""simple docstring"""

					if k in (0.04, 0.06):
								__snake_case					:      List[str]							      =     k
								__snake_case					:      int							      =     window_size
					else:
								raise ValueError("""invalid k value"""			)

		def __str__(   self					:   Union[str, Any]			)					->    str:


					"""simple docstring"""

					return str(self.k			)

		def 	lowercase__     (   self					:   Dict  ,      __magic_name__					:   str			)					->    tuple[cva.Mat, list[list[int]]]:


					"""simple docstring"""

					__snake_case					:      Dict							      =     cva.imread(__magic_name__  ,      0			)
					__snake_case      ,     __snake_case					:      List[str]							      =     img.shape
					__snake_case					:      list[list[int]]							      =     []
					__snake_case					:      str							      =     img.copy()
					__snake_case					:      Tuple							      =     cva.cvtColor(__magic_name__  ,      cva.COLOR_GRAY2RGB			)
					__snake_case      ,     __snake_case					:      List[Any]							      =     np.gradient(__magic_name__			)
					__snake_case					:      Optional[Any]							      =     dx**2
					__snake_case					:      Tuple							      =     dy**2
					__snake_case					:      List[Any]							      =     dx * dy
					__snake_case					:      List[Any]							      =     0.04
					__snake_case					:      Tuple							      =     self.window_size // 2
					for y in range(__magic_name__  ,      h - offset			):
								for x in range(__magic_name__  ,      w - offset			):
											__snake_case					:      Dict							      =     ixx[
											    y - offset : y + offset + 1, x - offset : x + offset + 1
											].sum()
											__snake_case					:      Optional[int]							      =     iyy[
											    y - offset : y + offset + 1, x - offset : x + offset + 1
											].sum()
											__snake_case					:      str							      =     ixy[
											    y - offset : y + offset + 1, x - offset : x + offset + 1
											].sum()

											__snake_case					:      List[str]							      =     (wxx * wyy) - (wxy**2)
											__snake_case					:      Dict							      =     wxx + wyy
											__snake_case					:      List[str]							      =     det - k * (trace**2)
											# Can change the value
											if r > 0.5:
														corner_list.append([x, y, r]			)
														color_img.itemset((y, x, 0)  ,      0			)
														color_img.itemset((y, x, 1)  ,      0			)
														color_img.itemset((y, x, 2)  ,      2_55			)
					return color_img, corner_list


if __name__ == "__main__":
	__UpperCamelCase					    =	HarrisCorner(0.04, 3)
	__UpperCamelCase    ,		__UpperCamelCase					    =	edge_detect.detect("path_to_image")
	cva.imwrite("detect.png", color_img)


