
'''simple docstring'''



from typing import List, Union

import numpy as np

from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
						from PIL import Image

						from ..image_utils import load_image

if is_torch_available():
						import torch

						from ..models.auto.modeling_auto import MODEL_FOR_DEPTH_ESTIMATION_MAPPING

lowercase_    =		logging.get_logger(__name__)




@add_end_docstrings(__SCREAMING_SNAKE_CASE			)
class   UpperCAmelCase_					(		__SCREAMING_SNAKE_CASE			):






						'''simple docstring'''






						def __init__( self   ,       *_lowercase   ,       **_lowercase				):

												"""simple docstring"""



												super().__init__(*_snake_case   ,       **_snake_case				)
												requires_backends(self   ,       """vision"""				)
												self.check_model_type(_snake_case				)




						def __call__( self   ,       _lowercase   ,       **_lowercase				):

												"""simple docstring"""



												return super().__call__(_snake_case   ,       **_snake_case				)




						def  _lowercase     ( self   ,       **_lowercase				):

												"""simple docstring"""



												return {}, {}, {}




						def  _lowercase     ( self   ,       _lowercase				):

												"""simple docstring"""



												_lowerCAmelCase  						=			load_image(_snake_case				)
												_lowerCAmelCase  						=			image.size
												_lowerCAmelCase  						=			self.image_processor(images=_snake_case   ,       return_tensors=self.framework				)
												return model_inputs




						def  _lowercase     ( self   ,       _lowercase				):

												"""simple docstring"""



												_lowerCAmelCase  						=			self.model(**_snake_case				)
												return model_outputs




						def  _lowercase     ( self   ,       _lowercase				):

												"""simple docstring"""



												_lowerCAmelCase  						=			model_outputs.predicted_depth
												_lowerCAmelCase  						=			torch.nn.functional.interpolate(
												    predicted_depth.unsqueeze(1				)   ,       size=self.image_size[::-1]   ,       mode="""bicubic"""   ,       align_corners=_snake_case				)
												_lowerCAmelCase  						=			prediction.squeeze().cpu().numpy()
												_lowerCAmelCase  						=			(output * 255 / np.max(_snake_case				)).astype("""uint8"""				)
												_lowerCAmelCase  						=			Image.fromarray(_snake_case				)
												_lowerCAmelCase  						=			{}
												_lowerCAmelCase  						=			predicted_depth
												_lowerCAmelCase  						=			depth
												return output_dict


'''simple docstring'''



def A				(__lowerCamelCase				:list[int]			,     __lowerCamelCase				:list[int]		):

						# Check if the input is valid
						if not len(__lowerCamelCase		) == len(__lowerCamelCase		) == 3:
												raise ValueError("""Please enter a valid equation."""		)
						if equationa[0] == equationa[1] == equationa[0] == equationa[1] == 0:
												raise ValueError("""Both a & b of two equations can't be zero."""		)

						# Extract the coefficients
						_lowerCAmelCase						,   _lowerCAmelCase						,   _lowerCAmelCase  						=			equationa
						_lowerCAmelCase						,   _lowerCAmelCase						,   _lowerCAmelCase  						=			equationa

						# Calculate the determinants of the matrices
						_lowerCAmelCase  						=			aa * ba - aa * ba
						_lowerCAmelCase  						=			ca * ba - ca * ba
						_lowerCAmelCase  						=			aa * ca - aa * ca

						# Check if the system of linear equations has a solution (using Cramer's rule)
						if determinant == 0:
												if determinant_x == determinant_y == 0:
																		raise ValueError("""Infinite solutions. (Consistent system)"""		)
												else:
																		raise ValueError("""No solution. (Inconsistent system)"""		)
						else:
												if determinant_x == determinant_y == 0:
																		# Trivial solution (Inconsistent system)
																		return (0.0, 0.0)
												else:
																		_lowerCAmelCase  						=			determinant_x / determinant
																		_lowerCAmelCase  						=			determinant_y / determinant
																		# Non-Trivial Solution (Consistent system)
																		return (x, y)
