



"""simple docstring"""

# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile

from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version


lowercase__					:						Tuple												=			get_logger(__name__)




class  _UpperCAmelCase :
 _lowerCAmelCase     :    Dict	      =	"""dummy_data"""
 _lowerCAmelCase     :    Union[str, Any]	      =	"""datasets"""
 _lowerCAmelCase     :    Dict	      =	False

 def __init__(  self	: int						,  lowercase_	: str						,  lowercase_	: str						,  lowercase_	: Union[Version, str]						,  lowercase_	: Optional[str] = None						,  lowercase_	: bool = False						,  lowercase_	: bool = True						,  lowercase_	: Optional[List[Callable]] = None						,  ):
     snake_case_				:  List[str]       =			0
     snake_case_				:  int       =			dataset_name
     snake_case_				:  str       =			cache_dir
     snake_case_				:  str       =			use_local_dummy_data
     snake_case_				:  Union[str, Any]       =			config
     # download_callbacks take a single url as input
     snake_case_				:  List[Callable]       =			download_callbacks or []
     # if False, it doesn't load existing files and it returns the paths of the dummy files relative
     # to the dummy_data zip file root
     snake_case_				:  Union[str, Any]       =			load_existing_dummy_data

     # TODO(PVP, QL) might need to make this more general
     snake_case_				:  Dict       =			str(lowercase_       )
     # to be downloaded
     snake_case_				:  List[Any]       =			None
     snake_case_				:  Union[str, Any]       =			None

 @property
 def 		_snake_case      (  self	: List[Any]       ):
     if self._dummy_file is None:
         snake_case_				:  List[str]       =			self.download_dummy_data()
     return self._dummy_file

 @property
 def 		_snake_case      (  self	: Tuple       ):
     if self.config is not None:
         # structure is dummy / config_name / version_name
         return os.path.join('''dummy'''						,  self.config.name						,  self.version_name       )
     # structure is dummy / version_name
     return os.path.join('''dummy'''						,  self.version_name       )

 @property
 def 		_snake_case      (  self	: int       ):
     return os.path.join(self.dummy_data_folder						,  '''dummy_data.zip'''       )

 def 		_snake_case      (  self	: Dict       ):
     snake_case_				:  Union[str, Any]       =			(
         self.local_path_to_dummy_data if self.use_local_dummy_data is True else self.github_path_to_dummy_data
     )

     snake_case_				:  Union[str, Any]       =			cached_path(
         lowercase_						,  cache_dir=self.cache_dir						,  extract_compressed_file=lowercase_						,  force_extract=lowercase_       )

     return os.path.join(lowercase_						,  self.dummy_file_name       )

 @property
 def 		_snake_case      (  self	: List[Any]       ):
     return os.path.join(self.datasets_scripts_dir						,  self.dataset_name						,  self.dummy_zip_file       )

 @property
 def 		_snake_case      (  self	: int       ):
     if self._bucket_url is None:
         snake_case_				:  Any       =			hf_github_url(self.dataset_name						,  self.dummy_zip_file.replace(os.sep						,  '''/'''       )       )
     return self._bucket_url

 @property
 def 		_snake_case      (  self	: Any       ):
     # return full path if its a dir
     if os.path.isdir(self.dummy_file       ):
         return self.dummy_file
     # else cut off path to file -> example `xsum`.
     return "/".join(self.dummy_file.replace(os.sep						,  '''/'''       ).split('''/'''       )[:-1]       )

 def 		_snake_case      (  self	: int						,  lowercase_	: Any						,  *lowercase_	: Tuple       ):
     if self.load_existing_dummy_data:
         # dummy data is downloaded and tested
         snake_case_				:  int       =			self.dummy_file
     else:
         # dummy data cannot be downloaded and only the path to dummy file is returned
         snake_case_				:  Union[str, Any]       =			self.dummy_file_name

     # special case when data_url is a dict
     if isinstance(lowercase_						,  lowercase_       ):
         return self.create_dummy_data_dict(lowercase_						,  lowercase_       )
     elif isinstance(lowercase_						,  (list, tuple)       ):
         return self.create_dummy_data_list(lowercase_						,  lowercase_       )
     else:
         return self.create_dummy_data_single(lowercase_						,  lowercase_       )

 def 		_snake_case      (  self	: List[Any]						,  lowercase_	: List[Any]						,  *lowercase_	: List[Any]       ):
     return self.download_and_extract(lowercase_       )

 def 		_snake_case      (  self	: List[Any]						,  lowercase_	: Tuple						,  lowercase_	: Any       ):
     return self.download_and_extract(lowercase_       )

 def 		_snake_case      (  self	: str						,  lowercase_	: Any						,  *lowercase_	: str						,  **lowercase_	: List[Any]       ):
     return path

 def 		_snake_case      (  self	: int       ):
     return {}

 def 		_snake_case      (  self	: Tuple						,  lowercase_	: Dict						,  lowercase_	: Any       ):
     snake_case_				:  Optional[Any]       =			{}
     for key, single_urls in data_url.items():
         for download_callback in self.download_callbacks:
             if isinstance(lowercase_						,  lowercase_       ):
                 for single_url in single_urls:
                     download_callback(lowercase_       )
             else:
                 snake_case_				:  Dict       =			single_urls
                 download_callback(lowercase_       )
            # we force the name of each key to be the last file / folder name of the url path
            # if the url has arguments, we need to encode them with urllib.parse.quote_plus
         if isinstance(lowercase_						,  lowercase_       ):
             snake_case_				:  Any       =			[os.path.join(lowercase_						,  urllib.parse.quote_plus(Path(lowercase_       ).name       )       ) for x in single_urls]
         else:
             snake_case_				:  List[Any]       =			single_urls
             snake_case_				:  List[str]       =			os.path.join(lowercase_						,  urllib.parse.quote_plus(Path(lowercase_       ).name       )       )
         snake_case_				:  Union[str, Any]       =			value

     # make sure that values are unique
     if all(isinstance(lowercase_						,  lowercase_       ) for i in dummy_data_dict.values()       ) and len(set(dummy_data_dict.values()       )       ) < len(
         dummy_data_dict.values()       ):
         # append key to value to make its name unique
         snake_case_				:  Union[str, Any]       =			{key: value + key for key, value in dummy_data_dict.items()}

     return dummy_data_dict

 def 		_snake_case      (  self	: int						,  lowercase_	: List[Any]						,  lowercase_	: List[Any]       ):
     snake_case_				:  Tuple       =			[]
     # trick: if there are many shards named like `data.txt-000001-of-00300`, only use the first one
     snake_case_				:  Optional[int]       =			all(bool(re.findall('''[0-9]{3,}-of-[0-9]{3,}'''						,  lowercase_       )       ) for url in data_url       )
     snake_case_				:  int       =			all(
         url.startswith('''https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed'''       ) for url in data_url       )
     if data_url and (is_tf_records or is_pubmed_records):
         snake_case_				:  Optional[Any]       =			[data_url[0]] * len(lowercase_       )
     for single_url in data_url:
         for download_callback in self.download_callbacks:
             download_callback(lowercase_       )
         # we force the name of each key to be the last file / folder name of the url path
         # if the url has arguments, we need to encode them with urllib.parse.quote_plus
         snake_case_				:  Optional[Any]       =			os.path.join(lowercase_						,  urllib.parse.quote_plus(single_url.split('''/'''       )[-1]       )       )
         dummy_data_list.append(lowercase_       )
     return dummy_data_list

 def 		_snake_case      (  self	: Optional[Any]						,  lowercase_	: int						,  lowercase_	: Optional[int]       ):
     for download_callback in self.download_callbacks:
         download_callback(lowercase_       )
     # we force the name of each key to be the last file / folder name of the url path
     # if the url has arguments, we need to encode them with urllib.parse.quote_plus
     snake_case_				:  List[Any]       =			os.path.join(lowercase_						,  urllib.parse.quote_plus(data_url.split('''/'''       )[-1]       )       )
     if os.path.exists(lowercase_       ) or not self.load_existing_dummy_data:
         return value
     else:
         # Backward compatibility, maybe deprecate at one point.
         # For many datasets with single url calls to dl_manager.download_and_extract,
         # the dummy_data.zip file is actually the zipped downloaded file
         # while now we expected the dummy_data.zip file to be a directory containing
         # the downloaded file.
         return path_to_dummy_data

 def 		_snake_case      (  self	: Optional[int]       ):
     pass

 def 		_snake_case      (  self	: Any       ):
     pass

 def 		_snake_case      (  self	: Dict						,  lowercase_	: Tuple       ):
     def _iter_archive_members(lowercase_	: str       ):
         # this preserves the order of the members inside the ZIP archive
         snake_case_				:  Optional[Any]       =			Path(self.dummy_file       ).parent
         snake_case_				:  List[str]       =			path.relative_to(lowercase_       )
         with ZipFile(self.local_path_to_dummy_data       ) as zip_file:
             snake_case_				:  Union[str, Any]       =			zip_file.namelist()
         for member in members:
             if member.startswith(relative_path.as_posix()       ):
                 yield dummy_parent_path.joinpath(lowercase_       )

     snake_case_				:  Dict       =			Path(lowercase_       )
     snake_case_				:  Optional[Any]       =			_iter_archive_members(lowercase_       ) if self.use_local_dummy_data else path.rglob('''*'''       )
     for file_path in file_paths:
         if file_path.is_file() and not file_path.name.startswith(('''.''', '''__''')       ):
             yield file_path.relative_to(lowercase_       ).as_posix(), file_path.open('''rb'''       )






 def 		_snake_case      (  self	: Tuple						,  lowercase_	: int       ):
     if not isinstance(lowercase_						,  lowercase_       ):
         snake_case_				:  List[str]       =			[paths]
     for path in paths:
         if os.path.isfile(lowercase_       ):
             if os.path.basename(lowercase_       ).startswith(('''.''', '''__''')       ):
                 return
             yield path
         else:
             for dirpath, dirnames, filenames in os.walk(lowercase_       ):
                 if os.path.basename(lowercase_       ).startswith(('''.''', '''__''')       ):
                     continue
                 dirnames.sort()
                 for filename in sorted(lowercase_       ):
                     if filename.startswith(('''.''', '''__''')       ):
                         continue
                     yield os.path.join(lowercase_						,  lowercase_       )










"""simple docstring"""

import math
import sys

import cva
import numpy as np




def __lowercase    (							_a	,    _a					):
    # For applying gaussian function for each element in matrix.
    snake_case_				:  Dict       =			math.sqrt(_a					)
    snake_case_				:  Tuple       =			1 / (sigma * math.sqrt(2 * math.pi					))
    return cons * np.exp(-((img / sigma) ** 2) * 0.5					)




def __lowercase    (							_a	,    _a	,    _a	,    _a					):
    snake_case_				:  Optional[int]       =			kernel_size // 2
    return img[x - half : x + half + 1, y - half : y + half + 1]




def __lowercase    (							_a	,    _a					):
    # Creates a gaussian kernel of given dimension.
    snake_case_				:  Union[str, Any]       =			np.zeros((kernel_size, kernel_size)					)
    for i in range(0	,    _a					):
        for j in range(0	,    _a					):
            snake_case_				:  Union[str, Any]       =			math.sqrt(
                abs(i - kernel_size // 2					) ** 2 + abs(j - kernel_size // 2					) ** 2					)
    return vec_gaussian(_a	,    _a					)




def __lowercase    (							_a	,    _a	,    _a	,    _a	,    ):
    snake_case_				:  int       =			np.zeros(img.shape					)
    snake_case_				:  str       =			get_gauss_kernel(_a	,    _a					)
    snake_case_,			snake_case_				:  Any       =			img.shape
    for i in range(kernel_size // 2	,    size_x - kernel_size // 2					):
        for j in range(kernel_size // 2	,    size_y - kernel_size // 2					):
            snake_case_				:  List[Any]       =			get_slice(_a	,    _a	,    _a	,    _a					)
            snake_case_				:  Union[str, Any]       =			img_s - img_s[kernel_size // 2, kernel_size // 2]
            snake_case_				:  Optional[Any]       =			vec_gaussian(_a	,    _a					)
            snake_case_				:  Dict       =			np.multiply(_a	,    _a					)
            snake_case_				:  Dict       =			np.multiply(_a	,    _a					)
            snake_case_				:  List[Any]       =			np.sum(_a					) / np.sum(_a					)
            snake_case_				:  Dict       =			val
    return imga




def __lowercase    (							_a					):
    snake_case_				:  Optional[int]       =			args[1] if args[1:] else '''../image_data/lena.jpg'''
    snake_case_				:  int       =			float(args[2]					) if args[2:] else 1.0
    snake_case_				:  Dict       =			float(args[3]					) if args[3:] else 1.0
    if args[4:]:
        snake_case_				:  Optional[Any]       =			int(args[4]					)
        snake_case_				:  Union[str, Any]       =			kernel_size + abs(kernel_size % 2 - 1					)
    else:
        snake_case_				:  Union[str, Any]       =			5
    return filename, spatial_variance, intensity_variance, kernel_size


if __name__ == "__main__":
     lowercase__					,lowercase__					,lowercase__					,lowercase__					:						Tuple												=			parse_args(sys.argv)
     lowercase__					:						str												=			cva.imread(filename, 0)
     cva.imshow('''input image''', img)

     lowercase__					:						Tuple												=			img / 2_55
     lowercase__					:						Optional[int]												=			out.astype('''float32''')
     lowercase__					:						Union[str, Any]												=			bilateral_filter(out, spatial_variance, intensity_variance, kernel_size)
     lowercase__					:						List[str]												=			out * 2_55
     lowercase__					:						List[str]												=			np.uinta(out)
     cva.imshow('''output image''', out)
     cva.waitKey(0)
     cva.destroyAllWindows()





