


'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__A :  List[Any]    							=				{
    "configuration_roc_bert": ["ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoCBertConfig"],
    "tokenization_roc_bert": ["RoCBertTokenizer"],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  pass

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A :  Union[str, Any]    							=				[
      "ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST",
      "RoCBertForCausalLM",
      "RoCBertForMaskedLM",
      "RoCBertForMultipleChoice",
      "RoCBertForPreTraining",
      "RoCBertForQuestionAnswering",
      "RoCBertForSequenceClassification",
      "RoCBertForTokenClassification",
      "RoCBertLayer",
      "RoCBertModel",
      "RoCBertPreTrainedModel",
      "load_tf_weights_in_roc_bert",
  ]

if TYPE_CHECKING:
  from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
  from .tokenization_roc_bert import RoCBertTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    raise OptionalDependencyNotAvailable()

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_roc_bert import (
        ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        RoCBertForCausalLM,
        RoCBertForMaskedLM,
        RoCBertForMultipleChoice,
        RoCBertForPreTraining,
        RoCBertForQuestionAnswering,
        RoCBertForSequenceClassification,
        RoCBertForTokenClassification,
        RoCBertLayer,
        RoCBertModel,
        RoCBertPreTrainedModel,
        load_tf_weights_in_roc_bert,
    )


else:
  import sys

  __A :  int    							=				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)







'''simple docstring'''






from pathlib import Path

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







def     UpperCamelCase_      (   A__ :       np.ndarray							,   A__ :       np.ndarray							,   A__ :       np.ndarray							,   A__ :       int							,   A__ :       int ):
  '''simple docstring'''





  lowerCAmelCase_      :				List[Any]      =       cva.getAffineTransform(A__							,   A__ )
  return cva.warpAffine(A__							,   A__							,   (rows, cols) )


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

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

  # add all rotated images in a list
  __A :  Optional[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 :  Dict    							=				plt.figure(1)
  __A :  Optional[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()



