'''simple docstring'''

from pathlib import Path

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







def 	UpperCamelCase_		(   snake_case_			:			np.ndarray		,						snake_case_			:			np.ndarray		,						snake_case_			:			np.ndarray		,						snake_case_			:			int		,						snake_case_			:			int )   ->	Optional[int]:






 '''simple docstring'''

 __lowerCAmelCase											=		cva.getAffineTransform(snake_case__		,						snake_case__ )
 return cva.warpAffine(snake_case__		,						snake_case__		,						(rows, cols) )


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

 # set different points to rotate image
 _A     : List[str]    =							np.array([[50, 50], [200, 50], [50, 200]], np.floataa)
 _A     : Dict    =							np.array([[10, 100], [200, 50], [100, 250]], np.floataa)
 _A     : Optional[Any]    =							np.array([[50, 50], [150, 50], [120, 200]], np.floataa)
 _A     : Optional[int]    =							np.array([[10, 100], [80, 50], [180, 250]], np.floataa)

 # add all rotated images in a list
 _A     : 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     : str    =							plt.figure(1)
 _A     : List[Any]    =							['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=0.0_5, right=1.0, top=0.9_5)
 plt.show()










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE__					:     Optional[Any]       =     {'configuration_sew': ['SEW_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWConfig']}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE__					:     List[str]       =     [
     'SEW_PRETRAINED_MODEL_ARCHIVE_LIST',
     'SEWForCTC',
     'SEWForSequenceClassification',
     'SEWModel',
     'SEWPreTrainedModel',
 ]

if TYPE_CHECKING:
 from .configuration_sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_sew import (
      SEW_PRETRAINED_MODEL_ARCHIVE_LIST,
      SEWForCTC,
      SEWForSequenceClassification,
      SEWModel,
      SEWPreTrainedModel,
  )


else:
 import sys

 SCREAMING_SNAKE_CASE__					:     Tuple       =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





