'''simple docstring'''

import cva
import numpy as np



class 			UpperCAmelCase  :





       '''simple docstring'''



       def __init__(						self	,   __lowerCAmelCase	,   __lowerCAmelCase )  ->  str:






        if k in (0.0_4, 0.0_6):
         lowercase__				:    Union[str, Any]  =					k
         lowercase__				:    str  =					window_size
        else:
         raise ValueError('''invalid k value''' )

       def __str__(						self )  ->  List[Any]:
        return str(self.k )


       def _lowerCAmelCase(						self	,   __lowerCAmelCase )  ->  List[str]:
        lowercase__				:    Dict  =					cva.imread(_A	,   0 )
        lowercase__				:    int  =					img.shape
        lowercase__				:    list[list[int]]  =					[]
        lowercase__				:    Optional[Any]  =					img.copy()
        lowercase__				:    Optional[Any]  =					cva.cvtColor(_A	,   cva.COLOR_GRAY2RGB )
        lowercase__				:    List[Any]  =					np.gradient(_A )
        lowercase__				:    str  =					dx**2
        lowercase__				:    Optional[Any]  =					dy**2
        lowercase__				:    Optional[Any]  =					dx * dy
        lowercase__				:    Optional[Any]  =					0.0_4
        lowercase__				:    str  =					self.window_size // 2
        for y in range(_A	,   h - offset ):
         for x in range(_A	,   w - offset ):
          lowercase__				:    Union[str, Any]  =					ixx[
              y - offset : y + offset + 1, x - offset : x + offset + 1
          ].sum()
          lowercase__				:    int  =					iyy[
              y - offset : y + offset + 1, x - offset : x + offset + 1
          ].sum()
          lowercase__				:    Optional[int]  =					ixy[
              y - offset : y + offset + 1, x - offset : x + offset + 1
          ].sum()

          lowercase__				:    int  =					(wxx * wyy) - (wxy**2)
          lowercase__				:    Optional[int]  =					wxx + wyy
          lowercase__				:    List[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: Optional[int]          =   HarrisCorner(0.04, 3)
  __a: List[Any]          =   edge_detect.detect("""path_to_image""")
  cva.imwrite("""detect.png""", color_img)


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowerCamelCase					:	Union[str, Any]       =  {
    '''configuration_chinese_clip''': [
        '''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ChineseCLIPConfig''',
        '''ChineseCLIPOnnxConfig''',
        '''ChineseCLIPTextConfig''',
        '''ChineseCLIPVisionConfig''',
    ],
    '''processing_chinese_clip''': ['''ChineseCLIPProcessor'''],
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCamelCase					:	Any       =  ['''ChineseCLIPFeatureExtractor''']
		__lowerCamelCase					:	Optional[int]       =  ['''ChineseCLIPImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCamelCase					:	int       =  [
		    '''CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''ChineseCLIPModel''',
		    '''ChineseCLIPPreTrainedModel''',
		    '''ChineseCLIPTextModel''',
		    '''ChineseCLIPVisionModel''',
		]

if TYPE_CHECKING:
		from .configuration_chinese_clip import (
		    CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    ChineseCLIPConfig,
		    ChineseCLIPOnnxConfig,
		    ChineseCLIPTextConfig,
		    ChineseCLIPVisionConfig,
		)
		from .processing_chinese_clip import ChineseCLIPProcessor

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_chinese_clip import ChineseCLIPFeatureExtractor, ChineseCLIPImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_chinese_clip import (
				    CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ChineseCLIPModel,
				    ChineseCLIPPreTrainedModel,
				    ChineseCLIPTextModel,
				    ChineseCLIPVisionModel,
				)

else:
		import sys

		__lowerCamelCase					:	Any       =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
