





'''simple docstring'''






import glob
import os
import random
from string import ascii_lowercase, digits

import cva
__UpperCamelCase					    =	""
__UpperCamelCase					    =	""
__UpperCamelCase					    =	""
__UpperCamelCase					    =	1  # (0 is vertical, 1 is horizontal)







def 					_a						(       ) ->				None:



			"""simple docstring"""


			__snake_case      ,     __snake_case					:      Optional[int]							      =     get_dataset(_lowerCamelCase    ,	_lowerCamelCase )
			print("""Processing...""" )
			__snake_case      ,     __snake_case      ,     __snake_case					:      Union[str, Any]							      =     update_image_and_anno(_lowerCamelCase    ,	_lowerCamelCase    ,	_lowerCamelCase )

			for index, image in enumerate(_lowerCamelCase ):
						# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
						__snake_case					:      Tuple							      =     random_chars(32 )
						__snake_case					:      Tuple							      =     paths[index].split(os.sep )[-1].rsplit("""."""    ,	1 )[0]
						__snake_case					:      List[Any]							      =     F'''{OUTPUT_DIR}/{file_name}_FLIP_{letter_code}'''
						cva.imwrite(F'''/{file_root}.jpg'''    ,	_lowerCamelCase    ,	[cva.IMWRITE_JPEG_QUALITY, 85] )
						print(F'''Success {index+1}/{len(_lowerCamelCase )} with {file_name}''' )
						__snake_case					:      str							      =     []
						for anno in new_annos[index]:
									__snake_case					:      Union[str, Any]							      =     F'''{anno[0]} {anno[1]} {anno[2]} {anno[3]} {anno[4]}'''
									annos_list.append(_lowerCamelCase )
						with open(F'''/{file_root}.txt'''    ,	"""w""" ) as outfile:
									outfile.write("""\n""".join(line for line in annos_list ) )







def 					_a						(       _lowerCamelCase    ,	_lowerCamelCase ) ->				tuple[list, list]:



			"""simple docstring"""


			__snake_case					:      int							      =     []
			__snake_case					:      int							      =     []
			for label_file in glob.glob(os.path.join(_lowerCamelCase    ,	"""*.txt""" ) ):
						__snake_case					:      str							      =     label_file.split(os.sep )[-1].rsplit("""."""    ,	1 )[0]
						with open(_lowerCamelCase ) as in_file:
									__snake_case					:      List[Any]							      =     in_file.readlines()
						__snake_case					:      Tuple							      =     os.path.join(_lowerCamelCase    ,	F'''{label_name}.jpg''' )

						__snake_case					:      Tuple							      =     []
						for obj_list in obj_lists:
									__snake_case					:      Union[str, Any]							      =     obj_list.rstrip("""\n""" ).split(""" """ )
									boxes.append(
									    [
									        int(obj[0] ),
									        float(obj[1] ),
									        float(obj[2] ),
									        float(obj[3] ),
									        float(obj[4] ),
									    ] )
						if not boxes:
									continue
						img_paths.append(_lowerCamelCase )
						labels.append(_lowerCamelCase )
			return img_paths, labels







def 					_a						(       _lowerCamelCase    ,	_lowerCamelCase    ,	_lowerCamelCase = 1 ) ->				tuple[list, list, list]:



			"""simple docstring"""


			__snake_case					:      Tuple							      =     []
			__snake_case					:      Optional[Any]							      =     []
			__snake_case					:      List[Any]							      =     []
			for idx in range(len(_lowerCamelCase ) ):
						__snake_case					:      str							      =     []
						__snake_case					:      List[Any]							      =     img_list[idx]
						path_list.append(_lowerCamelCase )
						__snake_case					:      Optional[Any]							      =     anno_list[idx]
						__snake_case					:      int							      =     cva.imread(_lowerCamelCase )
						if flip_type == 1:
									__snake_case					:      List[Any]							      =     cva.flip(_lowerCamelCase    ,	_lowerCamelCase )
									for bbox in img_annos:
												__snake_case					:      int							      =     1 - bbox[1]
												new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]] )
						elif flip_type == 0:
									__snake_case					:      Any							      =     cva.flip(_lowerCamelCase    ,	_lowerCamelCase )
									for bbox in img_annos:
												__snake_case					:      List[str]							      =     1 - bbox[2]
												new_annos.append([bbox[0], bbox[1], y_center_new, bbox[3], bbox[4]] )
						new_annos_lists.append(_lowerCamelCase )
						new_imgs_list.append(_lowerCamelCase )
			return new_imgs_list, new_annos_lists, path_list







def 					_a						(       _lowerCamelCase = 32 ) ->				str:



			"""simple docstring"""


			assert number_char > 1, "The number of character should greater than 1"
			__snake_case					:      List[str]							      =     ascii_lowercase + digits
			return "".join(random.choice(_lowerCamelCase ) for _ in range(_lowerCamelCase ) )


if __name__ == "__main__":
	main()
	print("DONE ✅")



"""simple docstring"""


import heapq






def      __UpperCAmelCase       (      lowercase		):







  """simple docstring"""
  _UpperCAmelCase    			=   []

  # for each node and his adjacency list add them and the rank of the node to queue
  # using heapq module the queue will be filled like a Priority Queue
  # heapq works with a min priority queue, so I used -1*len(v) to build it
  for key, value in graph.items():
    # O(log(n))
    heapq.heappush(lowercase ,[-1 * len(lowercase		), (key, value)]		)

  # chosen_vertices = set of chosen vertices
  _UpperCAmelCase    			=   set()

  # while queue isn't empty and there are still edges
  #   (queue[0][0] is the rank of the node with max rank)
  while queue and queue[0][0] != 0:
    # extract vertex with max rank from queue and add it to chosen_vertices
    _UpperCAmelCase    			=   heapq.heappop(lowercase		)[1][0]
    chosen_vertices.add(lowercase		)

    # Remove all arcs adjacent to argmax
    for elem in queue:
      # if v haven't adjacent node, skip
      if elem[0] == 0:
        continue
      # if argmax is reachable from elem
      # remove argmax from elem's adjacent list and update his rank
      if argmax in elem[1][1]:
        _UpperCAmelCase    			=   elem[1][1].index(lowercase		)
        del elem[1][1][index]
        elem[0] += 1
        # re-order the queue
    heapq.heapify(lowercase		)
  return chosen_vertices


if __name__ == "__main__":
    import doctest

    doctest.testmod()

    UpperCAmelCase__			=    {0: [1, 3], 1: [0, 3], 2: [0, 3, 4], 3: [0, 1, 2], 4: [2, 3]}
    print(F'''Minimum vertex cover:\n{greedy_min_vertex_cover(graph)}''')
