




import cva
import numpy as np



class       a					:

     '''simple docstring'''





     def __init__(     self       :      List[str] ,   __snake_case       :      float ,   __snake_case       :      int    ):

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




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

                 UpperCAmelCase_										=					(wxx * wyy) - (wxy**2)
                 UpperCAmelCase_										=					wxx + wyy
                 UpperCAmelCase_										=					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__":
 _lowerCamelCase      			=						HarrisCorner(0.04, 3)
 _lowerCamelCase			,					_lowerCamelCase      			=						edge_detect.detect('path_to_image')
 cva.imwrite('detect.png', color_img)











from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowerCamelCase      			=						logging.get_logger(__name__)

_lowerCamelCase      			=						{
    'facebook/data2vec-text-base': 'https://huggingface.co/data2vec/resolve/main/config.json',
}



class       a					(       _A      ):

     '''simple docstring'''





     lowerCAmelCase    :	Optional[Any]       		=  'data2vec-text'
     def __init__(     self       :      Optional[Any] ,   __snake_case       :      Optional[int]=3_05_22 ,   __snake_case       :      List[str]=7_68 ,   __snake_case       :      Tuple=12 ,   __snake_case       :      int=12 ,   __snake_case       :      Union[str, Any]=30_72 ,   __snake_case       :      List[Any]="gelu" ,   __snake_case       :      Any=0.1 ,   __snake_case       :      Union[str, Any]=0.1 ,   __snake_case       :      Tuple=5_12 ,   __snake_case       :      str=2 ,   __snake_case       :      str=0.02 ,   __snake_case       :      List[Any]=1E-12 ,   __snake_case       :      Any=1 ,   __snake_case       :      List[Any]=0 ,   __snake_case       :      Dict=2 ,   __snake_case       :      Any="absolute" ,   __snake_case       :      Union[str, Any]=True ,   __snake_case       :      Any=None ,   **__snake_case       :      List[Any] ,   ):
         super().__init__(pad_token_id=__snake_case ,   bos_token_id=__snake_case ,   eos_token_id=__snake_case ,   **__snake_case    )

         UpperCAmelCase_										=					vocab_size
         UpperCAmelCase_										=					hidden_size
         UpperCAmelCase_										=					num_hidden_layers
         UpperCAmelCase_										=					num_attention_heads
         UpperCAmelCase_										=					hidden_act
         UpperCAmelCase_										=					intermediate_size
         UpperCAmelCase_										=					hidden_dropout_prob
         UpperCAmelCase_										=					attention_probs_dropout_prob
         UpperCAmelCase_										=					max_position_embeddings
         UpperCAmelCase_										=					type_vocab_size
         UpperCAmelCase_										=					initializer_range
         UpperCAmelCase_										=					layer_norm_eps
         UpperCAmelCase_										=					position_embedding_type
         UpperCAmelCase_										=					use_cache
         UpperCAmelCase_										=					classifier_dropout



class       a					(       _A      ):

     '''simple docstring'''





     @property
     def   lowerCamelCase_       (     self       :      str    ):
         if self.task == "multiple-choice":
             UpperCAmelCase_										=					{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
         else:
             UpperCAmelCase_										=					{0: '''batch''', 1: '''sequence'''}
         return OrderedDict(
             [
                 ('''input_ids''', dynamic_axis),
                 ('''attention_mask''', dynamic_axis),
             ]    )





