


import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment







@require_huggingface_suite
class        snake_case_   (unittest.TestCase      ):
					def  lowerCamelCase__(      self   :Optional[Any]      )					->    Dict:
												a__             =     inspect.getfile(accelerate.test_utils      )
												a__             =     os.path.sep.join(
												    mod_file.split(os.path.sep      )[:-1] + ['scripts', 'external_deps', 'test_metrics.py']      )

												from accelerate.test_utils.scripts.external_deps import test_metrics  # noqa: F401

												a__             =     test_metrics
					@require_cpu
					def  lowerCamelCase__(      self   :Union[str, Any]      )					->    Dict:
												debug_launcher(self.test_metrics.main			,num_processes=1      )
					@require_cpu
					def  lowerCamelCase__(      self   :List[Any]      )					->    int:
												debug_launcher(self.test_metrics.main      )
					@require_single_gpu
					def  lowerCamelCase__(      self   :Any      )					->    Dict:
												self.test_metrics.main()



					@require_multi_gpu
					def  lowerCamelCase__(      self   :Tuple      )					->    str:
												print(F'Found {torch.cuda.device_count()} devices.'      )
												a__             =     ['torchrun', F'--nproc_per_node={torch.cuda.device_count()}', self.test_file_path]
												with patch_environment(omp_num_threads=1      ):
																			execute_subprocess_async(_A			,env=os.environ.copy()      )











import cva
import numpy as np

class 	A_       :
	def __init__(    self							,					_A							,					_A		):






				'''simple docstring'''







				if k in (0.04, 0.06):
							UpperCAmelCase   		=				k
							UpperCAmelCase   		=				window_size
				else:
							raise ValueError('''invalid k value'''		)
	def __str__(    self		):






				'''simple docstring'''







				return str(self.k		)







	def      _lowercase				(    self							,					_A		):






				'''simple docstring'''







				UpperCAmelCase   		=				cva.imread(_A							,					0		)
				UpperCAmelCase		,			UpperCAmelCase   		=				img.shape
				UpperCAmelCase   		=				[]
				UpperCAmelCase   		=				img.copy()
				UpperCAmelCase   		=				cva.cvtColor(_A							,					cva.COLOR_GRAY2RGB		)
				UpperCAmelCase		,			UpperCAmelCase   		=				np.gradient(_A		)
				UpperCAmelCase   		=				dx**2
				UpperCAmelCase   		=				dy**2
				UpperCAmelCase   		=				dx * dy
				UpperCAmelCase   		=				0.04
				UpperCAmelCase   		=				self.window_size // 2
				for y in range(_A							,					h - offset		):
							for x in range(_A							,					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_5_5		)
				return color_img, corner_list


if __name__ == "__main__":
				__A				:    Tuple       =   HarrisCorner(0.04, 3)
				__A    , __A				:    List[Any]       =   edge_detect.detect("path_to_image")
				cva.imwrite("detect.png", color_img)



