





"""simple docstring"""


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

import cva
import numpy as np

# Parrameters
lowerCamelCase__						= (720, 1280)  # Height, Width
lowerCamelCase__						= (0.4, 0.6)  # if height or width lower than this scale, drop it.
lowerCamelCase__						= 1 / 100
lowerCamelCase__						= ""
lowerCamelCase__						= ""
lowerCamelCase__						= ""
lowerCamelCase__						= 250




def        lowercase__     (       )       ->		None:




      """simple docstring"""

      _UpperCamelCase,	_UpperCamelCase   :						Optional[Any]    =							get_dataset(lowercase_		,lowercase_      )
      for index in range(lowercase_      ):
            _UpperCamelCase   :						int    =							random.sample(range(len(lowercase_      )      )		,4      )
            _UpperCamelCase,	_UpperCamelCase,	_UpperCamelCase   :						Tuple    =							update_image_and_anno(
                lowercase_		,lowercase_		,lowercase_		,lowercase_		,lowercase_		,filter_scale=lowercase_		,)

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




def        lowercase__     (       lowercase_		,lowercase_      )       ->		tuple[list, list]:




      """simple docstring"""

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

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

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




def        lowercase__     (       lowercase_		,lowercase_		,lowercase_		,lowercase_		,lowercase_		,lowercase_ = 0.0		,)       ->		tuple[list, list, str]:




      """simple docstring"""

      _UpperCamelCase   :						Optional[Any]    =							np.zeros([output_size[0], output_size[1], 3]		,dtype=np.uinta      )
      _UpperCamelCase   :						Optional[Any]    =							scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
      _UpperCamelCase   :						str    =							scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
      _UpperCamelCase   :						int    =							int(scale_x * output_size[1]      )
      _UpperCamelCase   :						Tuple    =							int(scale_y * output_size[0]      )

      _UpperCamelCase   :						Union[str, Any]    =							[]
      _UpperCamelCase   :						Any    =							[]
      for i, index in enumerate(lowercase_      ):
            _UpperCamelCase   :						str    =							all_img_list[index]
            path_list.append(lowercase_      )
            _UpperCamelCase   :						Any    =							all_annos[index]
            _UpperCamelCase   :						Tuple    =							cva.imread(lowercase_      )
            if i == 0:  # top-left
                  _UpperCamelCase   :						str    =							cva.resize(lowercase_		,(divid_point_x, divid_point_y)      )
                  _UpperCamelCase   :						str    =							img
                  for bbox in img_annos:
                        _UpperCamelCase   :						Optional[Any]    =							bbox[1] * scale_x
                        _UpperCamelCase   :						Union[str, Any]    =							bbox[2] * scale_y
                        _UpperCamelCase   :						Any    =							bbox[3] * scale_x
                        _UpperCamelCase   :						List[Any]    =							bbox[4] * scale_y
                        new_anno.append([bbox[0], xmin, ymin, xmax, ymax]      )
            elif i == 1:  # top-right
                  _UpperCamelCase   :						List[Any]    =							cva.resize(lowercase_		,(output_size[1] - divid_point_x, divid_point_y)      )
                  _UpperCamelCase   :						Union[str, Any]    =							img
                  for bbox in img_annos:
                        _UpperCamelCase   :						Any    =							scale_x + bbox[1] * (1 - scale_x)
                        _UpperCamelCase   :						Optional[Any]    =							bbox[2] * scale_y
                        _UpperCamelCase   :						List[str]    =							scale_x + bbox[3] * (1 - scale_x)
                        _UpperCamelCase   :						Union[str, Any]    =							bbox[4] * scale_y
                        new_anno.append([bbox[0], xmin, ymin, xmax, ymax]      )
            elif i == 2:  # bottom-left
                  _UpperCamelCase   :						Union[str, Any]    =							cva.resize(lowercase_		,(divid_point_x, output_size[0] - divid_point_y)      )
                  _UpperCamelCase   :						Optional[Any]    =							img
                  for bbox in img_annos:
                        _UpperCamelCase   :						Dict    =							bbox[1] * scale_x
                        _UpperCamelCase   :						int    =							scale_y + bbox[2] * (1 - scale_y)
                        _UpperCamelCase   :						str    =							bbox[3] * scale_x
                        _UpperCamelCase   :						int    =							scale_y + bbox[4] * (1 - scale_y)
                        new_anno.append([bbox[0], xmin, ymin, xmax, ymax]      )
            else:  # bottom-right
                  _UpperCamelCase   :						List[str]    =							cva.resize(
                      lowercase_		,(output_size[1] - divid_point_x, output_size[0] - divid_point_y)      )
                  _UpperCamelCase   :						Tuple    =							img
                  for bbox in img_annos:
                        _UpperCamelCase   :						Dict    =							scale_x + bbox[1] * (1 - scale_x)
                        _UpperCamelCase   :						List[str]    =							scale_y + bbox[2] * (1 - scale_y)
                        _UpperCamelCase   :						Optional[int]    =							scale_x + bbox[3] * (1 - scale_x)
                        _UpperCamelCase   :						List[Any]    =							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   :						Dict    =							[
                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        lowercase__     (       lowercase_      )       ->		str:




      """simple docstring"""

      assert number_char > 1, "The number of character should greater than 1"
      _UpperCamelCase   :						Optional[int]    =							ascii_lowercase + digits
      return "".join(random.choice(lowercase_      ) for _ in range(lowercase_      )      )


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







"""simple docstring"""


import re




def        lowercase__     (       lowercase_      )       ->		bool:




      """simple docstring"""

      _UpperCamelCase   :						List[Any]    =							re.compile(
          r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$"      )

      return bool(re.search(lowercase_		,lowercase_      )      )


if __name__ == "__main__":
  lowerCamelCase__						= "0094702343221"

  print(is_sri_lankan_phone_number(phone))
