






"""simple docstring"""





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

import cva
import numpy as np

# Parrameters
A__					: Tuple=	(7_20, 12_80)  # Height, Width
A__					: Tuple=	(0.4, 0.6)  # if height or width lower than this scale, drop it.
A__					: str=	1 / 1_00
A__					: int=	""""""
A__					: List[str]=	""""""
A__					: Optional[int]=	""""""
A__					: str=	2_50







def   lowerCAmelCase_( )					->	None:
    """simple docstring"""

    UpperCamelCase__       ,						UpperCamelCase__         =    get_dataset(SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE					)
    for index in range(SCREAMING_SNAKE_CASE					):
        UpperCamelCase__         =    random.sample(range(len(SCREAMING_SNAKE_CASE					)					) ,	4					)
        UpperCamelCase__       ,						UpperCamelCase__       ,						UpperCamelCase__         =    update_image_and_anno(
            SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE ,	filter_scale=SCREAMING_SNAKE_CASE ,	)

        # Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
        UpperCamelCase__         =    random_chars(32					)
        UpperCamelCase__         =    path.split(os.sep					)[-1].rsplit('.' ,	1					)[0]
        UpperCamelCase__         =    F'{OUTPUT_DIR}/{file_name}_MOSAIC_{letter_code}'
        cva.imwrite(F'{file_root}.jpg' ,	SCREAMING_SNAKE_CASE ,	[cva.IMWRITE_JPEG_QUALITY, 85]					)
        print(F'Succeeded {index+1}/{NUMBER_IMAGES} with {file_name}'					)
        UpperCamelCase__         =    []
        for anno in new_annos:
            UpperCamelCase__         =    anno[3] - anno[1]
            UpperCamelCase__         =    anno[4] - anno[2]
            UpperCamelCase__         =    anno[1] + width / 2
            UpperCamelCase__         =    anno[2] + height / 2
            UpperCamelCase__         =    F'{anno[0]} {x_center} {y_center} {width} {height}'
            annos_list.append(SCREAMING_SNAKE_CASE					)
        with open(F'{file_root}.txt' ,	'w'					) as outfile:
            outfile.write('\n'.join(line for line in annos_list					)					)







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE					)					->	tuple[list, list]:
    """simple docstring"""

    UpperCamelCase__         =    []
    UpperCamelCase__         =    []
    for label_file in glob.glob(os.path.join(SCREAMING_SNAKE_CASE ,	'*.txt'					)					):
        UpperCamelCase__         =    label_file.split(os.sep					)[-1].rsplit('.' ,	1					)[0]
        with open(SCREAMING_SNAKE_CASE					) as in_file:
            UpperCamelCase__         =    in_file.readlines()
        UpperCamelCase__         =    os.path.join(SCREAMING_SNAKE_CASE ,	F'{label_name}.jpg'					)

        UpperCamelCase__         =    []
        for obj_list in obj_lists:
            UpperCamelCase__         =    obj_list.rstrip('\n'					).split(' '					)
            UpperCamelCase__         =    float(obj[1]					) - float(obj[3]					) / 2
            UpperCamelCase__         =    float(obj[2]					) - float(obj[4]					) / 2
            UpperCamelCase__         =    float(obj[1]					) + float(obj[3]					) / 2
            UpperCamelCase__         =    float(obj[2]					) + float(obj[4]					) / 2

            boxes.append([int(obj[0]					), xmin, ymin, xmax, ymax]					)
        if not boxes:
            continue
        img_paths.append(SCREAMING_SNAKE_CASE					)
        labels.append(SCREAMING_SNAKE_CASE					)
    return img_paths, labels







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE = 0.0 ,	)					->	tuple[list, list, str]:
    """simple docstring"""

    UpperCamelCase__         =    np.zeros([output_size[0], output_size[1], 3] ,	dtype=np.uinta					)
    UpperCamelCase__         =    scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
    UpperCamelCase__         =    scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
    UpperCamelCase__         =    int(scale_x * output_size[1]					)
    UpperCamelCase__         =    int(scale_y * output_size[0]					)

    UpperCamelCase__         =    []
    UpperCamelCase__         =    []
    for i, index in enumerate(SCREAMING_SNAKE_CASE					):
        UpperCamelCase__         =    all_img_list[index]
        path_list.append(SCREAMING_SNAKE_CASE					)
        UpperCamelCase__         =    all_annos[index]
        UpperCamelCase__         =    cva.imread(SCREAMING_SNAKE_CASE					)
        if i == 0:  # top-left
            UpperCamelCase__         =    cva.resize(SCREAMING_SNAKE_CASE ,	(divid_point_x, divid_point_y)					)
            UpperCamelCase__         =    img
            for bbox in img_annos:
                UpperCamelCase__         =    bbox[1] * scale_x
                UpperCamelCase__         =    bbox[2] * scale_y
                UpperCamelCase__         =    bbox[3] * scale_x
                UpperCamelCase__         =    bbox[4] * scale_y
                new_anno.append([bbox[0], xmin, ymin, xmax, ymax]					)
        elif i == 1:  # top-right
            UpperCamelCase__         =    cva.resize(SCREAMING_SNAKE_CASE ,	(output_size[1] - divid_point_x, divid_point_y)					)
            UpperCamelCase__         =    img
            for bbox in img_annos:
                UpperCamelCase__         =    scale_x + bbox[1] * (1 - scale_x)
                UpperCamelCase__         =    bbox[2] * scale_y
                UpperCamelCase__         =    scale_x + bbox[3] * (1 - scale_x)
                UpperCamelCase__         =    bbox[4] * scale_y
                new_anno.append([bbox[0], xmin, ymin, xmax, ymax]					)
        elif i == 2:  # bottom-left
            UpperCamelCase__         =    cva.resize(SCREAMING_SNAKE_CASE ,	(divid_point_x, output_size[0] - divid_point_y)					)
            UpperCamelCase__         =    img
            for bbox in img_annos:
                UpperCamelCase__         =    bbox[1] * scale_x
                UpperCamelCase__         =    scale_y + bbox[2] * (1 - scale_y)
                UpperCamelCase__         =    bbox[3] * scale_x
                UpperCamelCase__         =    scale_y + bbox[4] * (1 - scale_y)
                new_anno.append([bbox[0], xmin, ymin, xmax, ymax]					)
        else:  # bottom-right
            UpperCamelCase__         =    cva.resize(
                SCREAMING_SNAKE_CASE ,	(output_size[1] - divid_point_x, output_size[0] - divid_point_y)					)
            UpperCamelCase__         =    img
            for bbox in img_annos:
                UpperCamelCase__         =    scale_x + bbox[1] * (1 - scale_x)
                UpperCamelCase__         =    scale_y + bbox[2] * (1 - scale_y)
                UpperCamelCase__         =    scale_x + bbox[3] * (1 - scale_x)
                UpperCamelCase__         =    scale_y + bbox[4] * (1 - scale_y)
                new_anno.append([bbox[0], xmin, ymin, xmax, ymax]					)

    # Remove bounding box small than scale of filter
    if filter_scale > 0:
        UpperCamelCase__         =    [
            anno
            for anno in new_anno
            if filter_scale < (anno[3] - anno[1]) and filter_scale < (anno[4] - anno[2])
        ]

    return output_img, new_anno, path_list[0]







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	str:
    """simple docstring"""

    assert number_char > 1, "The number of character should greater than 1"
    UpperCamelCase__         =    ascii_lowercase + digits
    return "".join(random.choice(SCREAMING_SNAKE_CASE					) for _ in range(SCREAMING_SNAKE_CASE					)					)


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












"""simple docstring"""





from __future__ import annotations

from typing import Generic, TypeVar

A__					: Any=	TypeVar("""T""")
class    __lowerCamelCase    (  Generic[T]  ):

   def __init__(					self ,				snake_case_      )		->       None:
       UpperCamelCase__         =    data
       UpperCamelCase__         =    self
       UpperCamelCase__         =    0







class    __lowerCamelCase    (  Generic[T]  ):

   def __init__(					self      )		->       None:
       # map from node name to the node object
       UpperCamelCase__         =    {}

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       None:
       # create a new set with x as its member
       UpperCamelCase__         =    DisjointSetTreeNode(snake_case_      )

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       DisjointSetTreeNode[T]:
       # find the set x belongs to (with path-compression)
       UpperCamelCase__         =    self.map[data]
       if elem_ref != elem_ref.parent:
           UpperCamelCase__         =    self.find_set(elem_ref.parent.data      )
       return elem_ref.parent

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_ ,				snake_case_      )		->       None:
       # helper function for union operation
       if nodea.rank > nodea.rank:
           UpperCamelCase__         =    nodea
       else:
           UpperCamelCase__         =    nodea
           if nodea.rank == nodea.rank:
               nodea.rank += 1







   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_ ,				snake_case_      )		->       None:
       # merge 2 disjoint sets
       self.link(self.find_set(snake_case_      ) ,				self.find_set(snake_case_      )      )







class    __lowerCamelCase    (  Generic[T]  ):

   def __init__(					self      )		->       None:
       # connections: map from the node to the neighbouring nodes (with weights)
       UpperCamelCase__         =    {}

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       None:
       # add a node ONLY if its not present in the graph
       if node not in self.connections:
           UpperCamelCase__         =    {}

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_ ,				snake_case_ ,				snake_case_      )		->       None:
       # add an edge with the given weight
       self.add_node(snake_case_      )
       self.add_node(snake_case_      )
       UpperCamelCase__         =    weight
       UpperCamelCase__         =    weight







   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       GraphUndirectedWeighted[T]:
       UpperCamelCase__         =    []
       UpperCamelCase__         =    set()
       for start in self.connections:
           for end in self.connections[start]:
               if (start, end) not in seen:
                   seen.add((end, start)      )
                   edges.append((start, end, self.connections[start][end])      )
       edges.sort(key=lambda snake_case_      : x[2]      )

       # creating the disjoint set
       UpperCamelCase__         =    DisjointSetTree[T]()
       for node in self.connections:
           disjoint_set.make_set(snake_case_      )

       # MST generation
       UpperCamelCase__         =    0
       UpperCamelCase__         =    0
       UpperCamelCase__         =    GraphUndirectedWeighted[T]()
       while num_edges < len(self.connections      ) - 1:
           UpperCamelCase__       ,						UpperCamelCase__       ,						UpperCamelCase__         =    edges[index]
           index += 1
           UpperCamelCase__         =    disjoint_set.find_set(snake_case_      )
           UpperCamelCase__         =    disjoint_set.find_set(snake_case_      )
           if parent_u != parent_v:
               num_edges += 1
               graph.add_edge(snake_case_ ,				snake_case_ ,				snake_case_      )
               disjoint_set.union(snake_case_ ,				snake_case_      )
       return graph




