



'''simple docstring'''



import cva
import numpy as np






class 					UpperCAmelCase__	:



					def __init__(    self			,				UpperCamelCase			,				UpperCamelCase     )     ->			Optional[int]:

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



					def __str__(    self     )     ->			str:
						return str(self.k     )



					def        UpperCAmelCase_ (    self			,				UpperCamelCase     )     ->			tuple[cva.Mat, list[list[int]]]:
						__lowerCAmelCase												=  cva.imread(UpperCamelCase			,				0     )
						__lowerCAmelCase							,       __lowerCAmelCase												=  img.shape
						__lowerCAmelCase												=  []
						__lowerCAmelCase												=  img.copy()
						__lowerCAmelCase												=  cva.cvtColor(UpperCamelCase			,				cva.COLOR_GRAY2RGB     )
						__lowerCAmelCase							,       __lowerCAmelCase												=  np.gradient(UpperCamelCase     )
						__lowerCAmelCase												=  dx**2
						__lowerCAmelCase												=  dy**2
						__lowerCAmelCase												=  dx * dy
						__lowerCAmelCase												=  0.04
						__lowerCAmelCase												=  self.window_size // 2
						for y in range(UpperCamelCase			,				h - offset     ):
							for x in range(UpperCamelCase			,				w - offset     ):
								__lowerCAmelCase												=  ixx[
								    y - offset : y + offset + 1, x - offset : x + offset + 1
								].sum()
								__lowerCAmelCase												=  iyy[
								    y - offset : y + offset + 1, x - offset : x + offset + 1
								].sum()
								__lowerCAmelCase												=  ixy[
								    y - offset : y + offset + 1, x - offset : x + offset + 1
								].sum()

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




'''simple docstring'''



import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union

import torch

from ..utils import BaseOutput


lowerCAmelCase	:		Optional[Any]				=   '''scheduler_config.json'''






class 					UpperCAmelCase__	(		UpperCamelCase__ ):
					a      :     str        =							1
					a      :     Optional[int]        =							2
					a      :     int        =							3
					a      :     Union[str, Any]        =							4
					a      :     int        =							5
					a      :     Optional[int]        =							6
					a      :     str        =							7
					a      :     List[Any]        =							8
					a      :     List[str]        =							9
					a      :     List[str]        =							1_0
					a      :     int        =							1_1
					a      :     Any        =							1_2
					a      :     Any        =							1_3
					a      :     Tuple        =							1_4






@dataclass
class 					UpperCAmelCase__	(		UpperCamelCase__ ):
					a      :     torch.FloatTensor






class 					UpperCAmelCase__	:
					a      :     Tuple        =							SCHEDULER_CONFIG_NAME
					a      :     Union[str, Any]        =							[]
					a      :     str        =							True



					@classmethod
					def        UpperCAmelCase_ (    cls			,				UpperCamelCase = None			,				UpperCamelCase = None			,				UpperCamelCase=False			,				**UpperCamelCase			,				)     ->			int:
						__lowerCAmelCase							,       __lowerCAmelCase							,       __lowerCAmelCase												=  cls.load_config(
						    pretrained_model_name_or_path=UpperCamelCase			,				subfolder=UpperCamelCase			,				return_unused_kwargs=UpperCamelCase			,				return_commit_hash=UpperCamelCase			,				**UpperCamelCase			,				)
						return cls.from_config(UpperCamelCase			,				return_unused_kwargs=UpperCamelCase			,				**UpperCamelCase     )



					def        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase = False			,				**UpperCamelCase     )     ->			Dict:
						self.save_config(save_directory=UpperCamelCase			,				push_to_hub=UpperCamelCase			,				**UpperCamelCase     )



					@property
					def        UpperCAmelCase_ (    self     )     ->			str:
						return self._get_compatibles()



					@classmethod
					def        UpperCAmelCase_ (    cls     )     ->			Tuple:
						__lowerCAmelCase												=  list(set([cls.__name__] + cls._compatibles     )     )
						__lowerCAmelCase												=  importlib.import_module(__name__.split("."     )[0]     )
						__lowerCAmelCase												=  [
						    getattr(UpperCamelCase			,				UpperCamelCase     ) for c in compatible_classes_str if hasattr(UpperCamelCase			,				UpperCamelCase     )
						]
						return compatible_classes