


import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand


def 			UpperCAmelCase_				(      UpperCAmelCase__  ):
					return EnvironmentCommand()







class        UpperCamelCase__   (	__magic_name__   ):

					@staticmethod
					def   UpperCAmelCase__       (     UpperCamelCase__       :   ArgumentParser       ):






										'''simple docstring'''






										lowercase_  							=			parser.add_parser("""env"""       )
										download_parser.set_defaults(func=UpperCamelCase__       )

					def   UpperCAmelCase__       (     self       :   Optional[Any]       ):






										'''simple docstring'''






										lowercase_  							=			huggingface_hub.__version__

										lowercase_  							=			"""not installed"""
										lowercase_  							=			"""NA"""
										if is_torch_available():
															import torch

															lowercase_  							=			torch.__version__
															lowercase_  							=			torch.cuda.is_available()

										lowercase_  							=			"""not installed"""
										if is_transformers_available():
															import transformers

															lowercase_  							=			transformers.__version__

										lowercase_  							=			"""not installed"""
										if is_accelerate_available():
															import accelerate

															lowercase_  							=			accelerate.__version__

										lowercase_  							=			"""not installed"""
										if is_xformers_available():
															import xformers

															lowercase_  							=			xformers.__version__

										lowercase_  							=			{
										    """`diffusers` version""": version,
										    """Platform""": platform.platform(),
										    """Python version""": platform.python_version(),
										    """PyTorch version (GPU?)""": F'''{pt_version} ({pt_cuda_available})''',
										    """Huggingface_hub version""": hub_version,
										    """Transformers version""": transformers_version,
										    """Accelerate version""": accelerate_version,
										    """xFormers version""": xformers_version,
										    """Using GPU in script?""": """<fill in>""",
										    """Using distributed or parallel set-up in script?""": """<fill in>""",
										}

										print("""\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n"""       )
										print(self.format_dict(UpperCamelCase__       )       )

										return info







					@staticmethod
					def   UpperCAmelCase__       (     UpperCamelCase__       :   Tuple       ):






										'''simple docstring'''






										return "\n".join([F'''- {prop}: {val}''' for prop, val in d.items()]       ) + "\n"






import cva
import numpy as np







class        UpperCamelCase__   :

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






										'''simple docstring'''






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

					def __str__(     self       :   Optional[int]       ):






										'''simple docstring'''






										return str(self.k       )







					def   UpperCAmelCase__       (     self       :   Optional[Any]							,					UpperCamelCase__       :   str       ):






										'''simple docstring'''






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

																				lowercase_  							=			(wxx * wyy) - (wxy**2)
																				lowercase_  							=			wxx + wyy
																				lowercase_  							=			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					  =     HarrisCorner(0.04, 3)
							a  ,					a					  =     edge_detect.detect('path_to_image')
							cva.imwrite('detect.png', color_img)


