






'''simple docstring'''
from pathlib import Path

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





def        _a(     UpperCamelCase__ :  List[Any],		UpperCamelCase__ :  Dict,		UpperCamelCase__ :  List[Any],		UpperCamelCase__ :  Optional[int],		UpperCamelCase__ :  Tuple							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__   : Union[str, Any]													=cva.getAffineTransform(lowerCAmelCase_,		lowerCAmelCase_							)
      return cva.warpAffine(lowerCAmelCase_,		lowerCAmelCase_,		(rows, cols)							)


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

  # set different points to rotate image
  a_ 		=       np.array([[5_0, 5_0], [2_0_0, 5_0], [5_0, 2_0_0]], np.floataa)
  a_ 		=       np.array([[1_0, 1_0_0], [2_0_0, 5_0], [1_0_0, 2_5_0]], np.floataa)
  a_ 		=       np.array([[5_0, 5_0], [1_5_0, 5_0], [1_2_0, 2_0_0]], np.floataa)
  a_ 		=       np.array([[1_0, 1_0_0], [8_0, 5_0], [1_8_0, 2_5_0]], np.floataa)

  # add all rotated images in a list
  a_ 		=       [
      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_ 		=       plt.figure(1)
  a_ 		=       ['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()




'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCAmelCase									=   {
    '''configuration_bigbird_pegasus''': [
        '''BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BigBirdPegasusConfig''',
        '''BigBirdPegasusOnnxConfig''',
    ],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase									=   [
							    '''BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''BigBirdPegasusForCausalLM''',
							    '''BigBirdPegasusForConditionalGeneration''',
							    '''BigBirdPegasusForQuestionAnswering''',
							    '''BigBirdPegasusForSequenceClassification''',
							    '''BigBirdPegasusModel''',
							    '''BigBirdPegasusPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_bigbird_pegasus import (
							    BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    BigBirdPegasusConfig,
							    BigBirdPegasusOnnxConfig,
							)

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_bigbird_pegasus import (
														    BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BigBirdPegasusForCausalLM,
														    BigBirdPegasusForConditionalGeneration,
														    BigBirdPegasusForQuestionAnswering,
														    BigBirdPegasusForSequenceClassification,
														    BigBirdPegasusModel,
														    BigBirdPegasusPreTrainedModel,
														)


else:
							import sys

							__lowerCAmelCase									=   _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




