



from typing import List

from ...configuration_utils import PretrainedConfig
from ...utils import logging


a__      :				int   	=			logging.get_logger(__name__)

a__      :				Optional[Any]   	=			{
    "snap-research/efficientformer-l1-300": (
        "https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json"
    ),
}



class       UpperCAmelCase__(							lowerCamelCase	):

   '''simple docstring'''




   A    :  List[str]       				=    "efficientformer"


   def __init__(						self  :			Any			,				lowerCAmelCase  :			List[int] = [3, 2, 6, 4]			,				lowerCAmelCase  :			List[int] = [48, 96, 2_24, 4_48]			,				lowerCAmelCase  :			List[bool] = [True, True, True, True]			,				lowerCAmelCase  :			int = 4_48			,				lowerCAmelCase  :			int = 32			,				lowerCAmelCase  :			int = 4			,				lowerCAmelCase  :			int = 7			,				lowerCAmelCase  :			int = 5			,				lowerCAmelCase  :			int = 8			,				lowerCAmelCase  :			int = 4			,				lowerCAmelCase  :			float = 0.0			,				lowerCAmelCase  :			int = 16			,				lowerCAmelCase  :			int = 3			,				lowerCAmelCase  :			int = 3			,				lowerCAmelCase  :			int = 3			,				lowerCAmelCase  :			int = 2			,				lowerCAmelCase  :			int = 1			,				lowerCAmelCase  :			float = 0.0			,				lowerCAmelCase  :			int = 1			,				lowerCAmelCase  :			bool = True			,				lowerCAmelCase  :			bool = True			,				lowerCAmelCase  :			float = 1E-5			,				lowerCAmelCase  :			str = "gelu"			,				lowerCAmelCase  :			float = 0.02			,				lowerCAmelCase  :			float = 1E-1_2			,				lowerCAmelCase  :			int = 2_24			,				lowerCAmelCase  :			float = 1E-0_5			,				**lowerCAmelCase  :			Union[str, Any]			,				)	->				None:




         """simple docstring"""

         super().__init__(**lowerCAmelCase)

         lowercase__     =  hidden_act
         lowercase__     =  hidden_dropout_prob
         lowercase__     =  hidden_sizes
         lowercase__     =  num_hidden_layers
         lowercase__     =  num_attention_heads
         lowercase__     =  initializer_range
         lowercase__     =  layer_norm_eps
         lowercase__     =  patch_size
         lowercase__     =  num_channels
         lowercase__     =  depths
         lowercase__     =  mlp_expansion_ratio
         lowercase__     =  downsamples
         lowercase__     =  dim
         lowercase__     =  key_dim
         lowercase__     =  attention_ratio
         lowercase__     =  resolution
         lowercase__     =  pool_size
         lowercase__     =  downsample_patch_size
         lowercase__     =  downsample_stride
         lowercase__     =  downsample_pad
         lowercase__     =  drop_path_rate
         lowercase__     =  num_metaad_blocks
         lowercase__     =  distillation
         lowercase__     =  use_layer_scale
         lowercase__     =  layer_scale_init_value
         lowercase__     =  image_size
         lowercase__     =  batch_norm_eps





import cva
import numpy as np



class       UpperCAmelCase__:

   '''simple docstring'''




   def __init__(						self  :			Union[str, Any]			,				lowerCAmelCase  :			float			,				lowerCAmelCase  :			int)	->				Dict:




         """simple docstring"""

         if k in (0.04, 0.06):
               lowercase__     =  k
               lowercase__     =  window_size
         else:
               raise ValueError('invalid k value')


   def __str__(						self  :			Tuple)	->				str:




         """simple docstring"""

         return str(self.k)



   def 			UpperCAmelCase		(						self  :			Union[str, Any]			,				lowerCAmelCase  :			str)	->				tuple[cva.Mat, list[list[int]]]:




         """simple docstring"""

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

                     lowercase__     =  (wxx * wyy) - (wxy**2)
                     lowercase__     =  wxx + wyy
                     lowercase__     =  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__":
       a__      :				Dict   	=			HarrisCorner(0.0_4, 3)
       a__	,		a__      :				Dict   	=			edge_detect.detect("path_to_image")
       cva.imwrite("detect.png", color_img)
