
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(lowerCAmelCase__       )
class     __UpperCamelCase (							lowerCAmelCase__       ):






     """simple docstring"""







     def __init__(				self							:							str     ,						*_A							:							Dict     ,						**_A							:							Tuple ):







       """simple docstring"""




       super().__init__(*_A     ,						**_A )
       requires_backends(self     ,						'''vision''' )
       self.check_model_type(_A )



     def __call__(				self							:							Dict     ,						_A							:							Union[str, List[str], "Image.Image", List["Image.Image"]]     ,						**_A							:							int ):







       """simple docstring"""




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



     def  UpperCAmelCase__							(				self							:							Optional[Any]     ,						**_A							:							List[Any] ):







       """simple docstring"""




       return {}, {}, {}



     def  UpperCAmelCase__							(				self							:							Optional[int]     ,						_A							:							Optional[int] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		load_image(_A )
       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		image.size
       __SCREAMING_SNAKE_CASE      :	Any					=		self.image_processor(images=_A     ,						return_tensors=self.framework )
       return model_inputs



     def  UpperCAmelCase__							(				self							:							Any     ,						_A							:							Optional[Any] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Any					=		self.model(**_A )
       return model_outputs




     def  UpperCAmelCase__							(				self							:							Any     ,						_A							:							Optional[Any] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	int					=		model_outputs.predicted_depth
       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		torch.nn.functional.interpolate(
           predicted_depth.unsqueeze(1 )     ,						size=self.image_size[::-1]     ,						mode='''bicubic'''     ,						align_corners=_A )
       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		prediction.squeeze().cpu().numpy()
       __SCREAMING_SNAKE_CASE      :	Any					=		(output * 255 / np.max(_A )).astype('''uint8''' )
       __SCREAMING_SNAKE_CASE      :	str					=		Image.fromarray(_A )
       __SCREAMING_SNAKE_CASE      :	str					=		{}
       __SCREAMING_SNAKE_CASE      :	Tuple					=		predicted_depth
       __SCREAMING_SNAKE_CASE      :	str					=		depth
       return output_dict






'''simple docstring'''





from __future__ import annotations

from typing import Any

class   _a							:






     def __init__(					self   ,_SCREAMING_SNAKE_CASE       )				->     None:
          _snake_case				= num_of_nodes
          _snake_case				= []
          _snake_case				= {}






     def 							_lowercase      (					self   ,_SCREAMING_SNAKE_CASE   ,_SCREAMING_SNAKE_CASE   ,_SCREAMING_SNAKE_CASE       )				->     None:
          self.m_edges.append([u_node, v_node, weight]       )






     def 							_lowercase      (					self   ,_SCREAMING_SNAKE_CASE       )				->     int:

          if self.m_component[u_node] == u_node:
               return u_node
          return self.find_component(self.m_component[u_node]       )






     def 							_lowercase      (					self   ,_SCREAMING_SNAKE_CASE       )				->     None:

          if self.m_component[u_node] != u_node:
               for k in self.m_component:
                    _snake_case				= self.find_component(_SCREAMING_SNAKE_CASE       )






     def 							_lowercase      (					self   ,_SCREAMING_SNAKE_CASE   ,_SCREAMING_SNAKE_CASE   ,_SCREAMING_SNAKE_CASE       )				->     None:

          if component_size[u_node] <= component_size[v_node]:
               _snake_case				= v_node
               component_size[v_node] += component_size[u_node]
               self.set_component(_SCREAMING_SNAKE_CASE       )

          elif component_size[u_node] >= component_size[v_node]:
               _snake_case				= self.find_component(_SCREAMING_SNAKE_CASE       )
               component_size[u_node] += component_size[v_node]
               self.set_component(_SCREAMING_SNAKE_CASE       )






     def 							_lowercase      (					self       )				->     None:
          _snake_case				= []
          _snake_case				= 0

          _snake_case				= [-1] * self.m_num_of_nodes

          # A list of components (initialized to all of the nodes)
          for node in range(self.m_num_of_nodes       ):
               self.m_component.update({node: node}       )
               component_size.append(1       )

          _snake_case				= self.m_num_of_nodes

          while num_of_components > 1:
               for edge in self.m_edges:
                    _snake_case				,   _snake_case				,   _snake_case				= edge

                    _snake_case				= self.m_component[u]
                    _snake_case				= self.m_component[v]

                    if u_component != v_component:

                         for component in (u_component, v_component):
                              if (
                                  minimum_weight_edge[component] == -1
                                  or minimum_weight_edge[component][2] > w
                              ):
                                   _snake_case				= [u, v, w]

               for edge in minimum_weight_edge:
                    if isinstance(_SCREAMING_SNAKE_CASE   ,_SCREAMING_SNAKE_CASE       ):
                         _snake_case				,   _snake_case				,   _snake_case				= edge

                         _snake_case				= self.m_component[u]
                         _snake_case				= self.m_component[v]

                         if u_component != v_component:
                              mst_weight += w
                              self.union(_SCREAMING_SNAKE_CASE   ,_SCREAMING_SNAKE_CASE   ,_SCREAMING_SNAKE_CASE       )
                              print(f"""Added edge [{u} - {v}]\nAdded weight: {w}\n"""       )
                              num_of_components -= 1

               _snake_case				= [-1] * self.m_num_of_nodes
          print(f"""The total weight of the minimal spanning tree is: {mst_weight}"""       )







def       __a      (  )		->					None:

     """simple docstring"""






if __name__ == "__main__":
   import doctest

   doctest.testmod()


