





'''simple docstring'''






# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import doctest
import sys
import warnings
from os.path import abspath, dirname, join

import _pytest

from transformers.testing_utils import HfDoctestModule, HfDocTestParser


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
__lowerCamelCase						: Union[str, Any]		=   abspath(join(dirname(__file__), 'src'))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action='ignore', category=FutureWarning)


def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  config.addinivalue_line(
      '''markers'''  ,      '''is_pt_tf_cross_test: mark test to run only when PT and TF interactions are tested'''   )
  config.addinivalue_line(
      '''markers'''  ,      '''is_pt_flax_cross_test: mark test to run only when PT and FLAX interactions are tested'''   )
  config.addinivalue_line('''markers'''  ,      '''is_pipeline_test: mark test to run only when pipelines are tested'''   )
  config.addinivalue_line('''markers'''  ,      '''is_staging_test: mark test to run only in the staging environment'''   )
  config.addinivalue_line('''markers'''  ,      '''accelerate_tests: mark test that require accelerate'''   )
  config.addinivalue_line('''markers'''  ,      '''tool_tests: mark the tool tests that are run on their specific schedule'''   )


def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  from transformers.testing_utils import pytest_addoption_shared

  pytest_addoption_shared(__SCREAMING_SNAKE_CASE   )


def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  from transformers.testing_utils import pytest_terminal_summary_main

  _UpperCamelCase       			=terminalreporter.config.getoption('''--make-reports'''   )
  if make_reports:
    pytest_terminal_summary_main(__SCREAMING_SNAKE_CASE  ,      id=__SCREAMING_SNAKE_CASE   )


def 					_a   (__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  if exitstatus == 5:
    _UpperCamelCase       			=0


# Doctest custom flag to ignore output.
__lowerCamelCase						: Tuple		=   doctest.register_optionflag('IGNORE_RESULT')

__lowerCamelCase						: Union[str, Any]		=   doctest.OutputChecker







class 		UpperCAmelCase   (				lowercase_):


  """simple docstring"""







  def   UpperCamelCase__      (				self    :					Dict							,	UpperCamelCase__    :					List[str]							,	UpperCamelCase__    :					Union[str, Any]							,	UpperCamelCase__    :					Optional[int]  )     ->						str:
    if IGNORE_RESULT & optionflags:
      return True
    return OutputChecker.check_output(self							,	UpperCamelCase__							,	UpperCamelCase__							,	UpperCamelCase__  )




__lowerCamelCase						: Any		=   CustomOutputChecker
__lowerCamelCase						: Optional[Any]		=   HfDoctestModule
__lowerCamelCase						: int		=   HfDocTestParser













'''simple docstring'''






from pathlib import Path

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


def 					_a   (__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  _UpperCamelCase       			=cva.getAffineTransform(__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   )
  return cva.warpAffine(__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      (rows, cols)   )


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

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

      # add all rotated images in a list
      __lowerCamelCase						: int		=   [
          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
      __lowerCamelCase						: Optional[Any]		=   plt.figure(1)
      __lowerCamelCase						: Tuple		=   ['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()






