






'''simple docstring'''





from pathlib import PurePosixPath
from typing import Optional

import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo

from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class 				lowercase       (							UpperCamelCase_      ):


    '''simple docstring'''

    lowerCAmelCase__      				=							""""""
    lowerCAmelCase__      				=							"""hf-legacy"""  # "hf://"" is reserved for hffs

    def __init__(					self     :     str				,     __lowerCamelCase     :     Optional[int] = None				,     __lowerCamelCase     :     Tuple = None				,     **__lowerCamelCase     :     List[Any]				,     )							->							int:

     '''simple docstring'''




     super().__init__(self				,     **_a     )
     lowerCamelCase__  =     repo_info
     lowerCamelCase__  =     token
     lowerCamelCase__  =     None

    def    a__				(					self     :     str     )							->							Optional[int]:

     '''simple docstring'''




     if self.dir_cache is None:
      lowerCamelCase__  =     {}
      for hf_file in self.repo_info.siblings:
       # TODO(QL): add sizes
       lowerCamelCase__  =     {
           """name""": hf_file.rfilename,
           """size""": None,
           """type""": """file""",
       }
       self.dir_cache.update(
           {
               str(_a     ): {"name": str(_a     ), "size": None, "type": "directory"}
               for d in list(PurePosixPath(hf_file.rfilename     ).parents     )[:-1]
           }     )

    def    a__				(					self     :     Union[str, Any]				,     __lowerCamelCase     :     Tuple				,     __lowerCamelCase     :     List[str] = "rb"				,     **__lowerCamelCase     :     Optional[int]				,     )							->							Dict:

     '''simple docstring'''




     if not isinstance(self.repo_info				,     _a     ):
      raise NotImplementedError(f'''Open is only implemented for dataset repositories, but got {self.repo_info}'''     )
     lowerCamelCase__  =     hf_hub_url(self.repo_info.id				,     _a				,     revision=self.repo_info.sha     )
     return fsspec.open(
         _a				,     mode=_a				,     headers=get_authentication_headers_for_url(_a				,     use_auth_token=self.token     )				,     client_kwargs={"trust_env": True}				,     ).open()

    def    a__				(					self     :     Tuple				,     __lowerCamelCase     :     Dict				,     **__lowerCamelCase     :     List[str]     )							->							List[str]:

     '''simple docstring'''




     self._get_dirs()
     lowerCamelCase__  =     self._strip_protocol(_a     )
     if path in self.dir_cache:
      return self.dir_cache[path]
     else:
      raise FileNotFoundError(_a     )




    def    a__				(					self     :     Optional[Any]				,     __lowerCamelCase     :     Any				,     __lowerCamelCase     :     Any=False				,     **__lowerCamelCase     :     Union[str, Any]     )							->							Optional[int]:

     '''simple docstring'''




     self._get_dirs()
     lowerCamelCase__  =     PurePosixPath(path.strip("/"     )     )
     lowerCamelCase__  =     {}
     for p, f in self.dir_cache.items():
      lowerCamelCase__  =     PurePosixPath(p.strip("/"     )     )
      lowerCamelCase__  =     p.parent
      if root == path:
       lowerCamelCase__  =     f
     lowerCamelCase__  =     list(paths.values()     )
     if detail:
      return out
     else:
      return sorted(f["name"] for f in out     )









'''simple docstring'''





from pathlib import Path

import cva
import numpy as np
from matplotlib import pyplot as plt






def    lowerCamelCase_     (    lowercase__				,     lowercase__				,     lowercase__				,     lowercase__				,     lowercase__):
 lowerCamelCase__  =     cva.getAffineTransform(lowercase__				,     lowercase__)
 return cva.warpAffine(lowercase__				,     lowercase__				,     (rows, cols))


if __name__ == "__main__":
 # read original image
 __A							:							Any  							=		cva.imread(
     str(Path(__file__).resolve().parent.parent / """image_data""" / """lena.jpg""")
 )
 # turn image in gray scale value
 __A							:							int  							=		cva.cvtColor(image, cva.COLOR_BGR2GRAY)
 # get image shape
 __A							,			__A							:							Dict  							=		gray_img.shape

 # set different points to rotate image
 __A							:							int  							=		np.array([[50, 50], [2_00, 50], [50, 2_00]], np.floataa)
 __A							:							Any  							=		np.array([[10, 1_00], [2_00, 50], [1_00, 2_50]], np.floataa)
 __A							:							str  							=		np.array([[50, 50], [1_50, 50], [1_20, 2_00]], np.floataa)
 __A							:							Optional[int]  							=		np.array([[10, 1_00], [80, 50], [1_80, 2_50]], np.floataa)

 # add all rotated images in a list
 __A							:							List[Any]  							=		[
     gray_img,
     get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
     get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
     get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
 ]

 # plot different image rotations
 __A							:							int  							=		plt.figure(1)
 __A							:							int  							=		["""Original""", """Rotation 1""", """Rotation 2""", """Rotation 3"""]
 for i, image in enumerate(images):
  plt.subplot(2, 2, i + 1), plt.imshow(image, """gray""")
  plt.title(titles[i])
  plt.axis("""off""")
  plt.subplots_adjust(left=0.0, bottom=0.05, right=1.0, top=0.95)
 plt.show()

