


import cva
import numpy as np

class   A__ :







    """simple docstring"""

    def __init__(	self      , __snake_case      , __snake_case   ):

         if k in (0.04, 0.06):
              snake_case					=    k
              snake_case					=    window_size
         else:
              raise ValueError('''invalid k value'''   )
    def __str__(	self   ):
         return str(self.k   )




    def 		a_      (	self      , __snake_case   ):
         snake_case					=    cva.imread(__lowerCamelCase      , 0   )
         snake_case					=    img.shape
         snake_case					=    []
         snake_case					=    img.copy()
         snake_case					=    cva.cvtColor(__lowerCamelCase      , cva.COLOR_GRAY2RGB   )
         snake_case					=    np.gradient(__lowerCamelCase   )
         snake_case					=    dx**2
         snake_case					=    dy**2
         snake_case					=    dx * dy
         snake_case					=    0.04
         snake_case					=    self.window_size // 2
         for y in range(__lowerCamelCase      , h - offset   ):
              for x in range(__lowerCamelCase      , w - offset   ):
                   snake_case					=    ixx[
                       y - offset : y + offset + 1, x - offset : x + offset + 1
                   ].sum()
                   snake_case					=    iyy[
                       y - offset : y + offset + 1, x - offset : x + offset + 1
                   ].sum()
                   snake_case					=    ixy[
                       y - offset : y + offset + 1, x - offset : x + offset + 1
                   ].sum()

                   snake_case					=    (wxx * wyy) - (wxy**2)
                   snake_case					=    wxx + wyy
                   snake_case					=    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_5_5   )
         return color_img, corner_list


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








import warnings

from ...utils import logging
from .image_processing_beit import BeitImageProcessor


_SCREAMING_SNAKE_CASE      :			List[str]      				=   logging.get_logger(__name__)

class   A__ (   snake_case__     ):







    """simple docstring"""

    def __init__(	self      , *__snake_case      , **__snake_case   ):
         warnings.warn(
             '''The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
             ''' use BeitImageProcessor instead.'''      , __snake_case      , )
         super().__init__(*__snake_case      , **__snake_case   )




