






from collections import deque

from .hash_table import HashTable

class     _SCREAMING_SNAKE_CASE       (			_a      ):





	def __init__(		self				:					Union[str, Any] ,  *__lowerCamelCase				:					Dict ,  **__lowerCamelCase				:					str	):
		super().__init__(*__lowerCamelCase ,  **__lowerCamelCase	)





	def 						_A (		self				:					Optional[int] ,  __lowerCamelCase				:					Union[str, Any] ,  __lowerCamelCase				:					Union[str, Any]	):
		UpperCamelCase     :List[Any]          =	deque([]	) if self.values[key] is None else self.values[key]
		self.values[key].appendleft(__lowerCamelCase	)
		UpperCamelCase     :List[str]          =	self.values[key]





	def 						_A (		self				:					List[Any]	):
		return (
		    sum(self.charge_factor - len(__lowerCamelCase	) for slot in self.values	)
		    / self.size_table
		    * self.charge_factor
		)





	def 						_A (		self				:					Tuple ,  __lowerCamelCase				:					Dict ,  __lowerCamelCase				:					Dict=None	):
		if not (
		    len(self.values[key]	) == self.charge_factor and self.values.count(__lowerCamelCase	) == 0
		):
			return key
		return super()._collision_resolution(__lowerCamelCase ,  __lowerCamelCase	)








import cva
import numpy as np
class     a    :



      """simple docstring"""


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

        if k in (0.04, 0.06):
          __UpperCAmelCase							:	int           =  k
          __UpperCAmelCase							:	List[str]           =  window_size
        else:
          raise ValueError("""invalid k value"""					)
      def __str__(      self					:			Union[str, Any]					)							->      str:
        return str(self.k					)




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

            __UpperCAmelCase							:	int           =  (wxx * wyy) - (wxy**2)
            __UpperCAmelCase							:	Any           =  wxx + wyy
            __UpperCAmelCase							:	Optional[Any]           =  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)		,      255					)
        return color_img, corner_list


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


