


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

import cva
import numpy as np

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



def       _lowerCAmelCase    (				)->None:
   '''simple docstring'''






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

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



def       _lowerCAmelCase    (				lowerCAmelCase_				:str		,    lowerCAmelCase_				:str				)->tuple[list, list]:
   '''simple docstring'''






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

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

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



def       _lowerCAmelCase    (				lowerCAmelCase_				:list		,    lowerCAmelCase_				:list		,    lowerCAmelCase_				:list[int]		,    lowerCAmelCase_				:tuple[int, int]		,    lowerCAmelCase_				:tuple[float, float]		,    lowerCAmelCase_				:float = 0.0		,    )->tuple[list, list, str]:
   '''simple docstring'''






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

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






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


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








'''simple docstring'''



from collections import namedtuple

import requests
from lxml import html  # type: ignore

A__						:   Tuple				=    namedtuple("""covid_data""", """cases deaths recovered""")



def      UpperCAmelCase__   (      UpperCAmelCase_       :							str = "https://www.worldometers.info/coronavirus/"				)	->						covid_data:
     __lowerCamelCase  :      Union[str, Any]														=						'//div[@class = "maincounter-number"]/span/text()'
     return covid_data(*html.fromstring(requests.get(UpperCAmelCase_				).content				).xpath(UpperCAmelCase_				)				)


A__						:   str				=    """Total COVID-19 cases in the world: {}
Total deaths due to COVID-19 in the world: {}
Total COVID-19 patients recovered in the world: {}"""

print(fmt.format(*covid_stats()))






