






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


a		:       str			     = {"configuration_vit_mae": ["VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTMAEConfig"]}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a		:       int			     = [
           "VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST",
           "ViTMAEForPreTraining",
           "ViTMAELayer",
           "ViTMAEModel",
           "ViTMAEPreTrainedModel",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a		:       str			     = [
           "TFViTMAEForPreTraining",
           "TFViTMAEModel",
           "TFViTMAEPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_vit_mae import VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMAEConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_vit_mae import (
                  VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST,
                  ViTMAEForPreTraining,
                  ViTMAELayer,
                  ViTMAEModel,
                  ViTMAEPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_vit_mae import TFViTMAEForPreTraining, TFViTMAEModel, TFViTMAEPreTrainedModel


else:
       import sys

       a		:       int			     = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










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)


