


'''simple docstring'''






import unittest

from diffusers.pipelines.pipeline_utils import is_safetensors_compatible






class        __snake_case	(       unittest.TestCase):







    """simple docstring"""



    def __lowercase       (       self   :  Tuple		)       ->  Dict:
      lowerCAmelCase_      :				str      =       [
          """safety_checker/pytorch_model.bin""",
          """safety_checker/model.safetensors""",
          """vae/diffusion_pytorch_model.bin""",
          """vae/diffusion_pytorch_model.safetensors""",
          """text_encoder/pytorch_model.bin""",
          """text_encoder/model.safetensors""",
          """unet/diffusion_pytorch_model.bin""",
          """unet/diffusion_pytorch_model.safetensors""",
      ]
      self.assertTrue(is_safetensors_compatible(lowerCamelCase		)		)

    def __lowercase       (       self   :  List[Any]		)       ->  int:
      lowerCAmelCase_      :				Tuple      =       [
          """unet/diffusion_pytorch_model.bin""",
          """unet/diffusion_pytorch_model.safetensors""",
      ]
      self.assertTrue(is_safetensors_compatible(lowerCamelCase		)		)

    def __lowercase       (       self   :  Optional[int]		)       ->  Optional[Any]:
      lowerCAmelCase_      :				int      =       [
          """safety_checker/pytorch_model.bin""",
          """safety_checker/model.safetensors""",
          """vae/diffusion_pytorch_model.bin""",
          """vae/diffusion_pytorch_model.safetensors""",
          """text_encoder/pytorch_model.bin""",
          """text_encoder/model.safetensors""",
          """unet/diffusion_pytorch_model.bin""",
          # Removed: 'unet/diffusion_pytorch_model.safetensors',
      ]
      self.assertFalse(is_safetensors_compatible(lowerCamelCase		)		)

    def __lowercase       (       self   :  int		)       ->  List[Any]:
      lowerCAmelCase_      :				Dict      =       [
          """text_encoder/pytorch_model.bin""",
          """text_encoder/model.safetensors""",
      ]
      self.assertTrue(is_safetensors_compatible(lowerCamelCase		)		)

    def __lowercase       (       self   :  str		)       ->  List[str]:
      lowerCAmelCase_      :				Union[str, Any]      =       [
          """safety_checker/pytorch_model.bin""",
          """safety_checker/model.safetensors""",
          """vae/diffusion_pytorch_model.bin""",
          """vae/diffusion_pytorch_model.safetensors""",
          """text_encoder/pytorch_model.bin""",
          # Removed: 'text_encoder/model.safetensors',
          """unet/diffusion_pytorch_model.bin""",
          """unet/diffusion_pytorch_model.safetensors""",
      ]
      self.assertFalse(is_safetensors_compatible(lowerCamelCase		)		)

    def __lowercase       (       self   :  List[Any]		)       ->  Tuple:
      lowerCAmelCase_      :				Union[str, Any]      =       [
          """safety_checker/pytorch_model.fp16.bin""",
          """safety_checker/model.fp16.safetensors""",
          """vae/diffusion_pytorch_model.fp16.bin""",
          """vae/diffusion_pytorch_model.fp16.safetensors""",
          """text_encoder/pytorch_model.fp16.bin""",
          """text_encoder/model.fp16.safetensors""",
          """unet/diffusion_pytorch_model.fp16.bin""",
          """unet/diffusion_pytorch_model.fp16.safetensors""",
      ]
      lowerCAmelCase_      :				Union[str, Any]      =       """fp16"""
      self.assertTrue(is_safetensors_compatible(lowerCamelCase   ,						variant=lowerCamelCase		)		)

    def __lowercase       (       self   :  Optional[Any]		)       ->  List[str]:
      lowerCAmelCase_      :				str      =       [
          """unet/diffusion_pytorch_model.fp16.bin""",
          """unet/diffusion_pytorch_model.fp16.safetensors""",
      ]
      lowerCAmelCase_      :				Optional[int]      =       """fp16"""
      self.assertTrue(is_safetensors_compatible(lowerCamelCase   ,						variant=lowerCamelCase		)		)

    def __lowercase       (       self   :  Tuple		)       ->  Optional[Any]:
      # pass variant but use the non-variant filenames
      lowerCAmelCase_      :				Dict      =       [
          """unet/diffusion_pytorch_model.bin""",
          """unet/diffusion_pytorch_model.safetensors""",
      ]
      lowerCAmelCase_      :				str      =       """fp16"""
      self.assertTrue(is_safetensors_compatible(lowerCamelCase   ,						variant=lowerCamelCase		)		)

    def __lowercase       (       self   :  Optional[int]		)       ->  List[str]:
      lowerCAmelCase_      :				str      =       [
          """safety_checker/pytorch_model.fp16.bin""",
          """safety_checker/model.fp16.safetensors""",
          """vae/diffusion_pytorch_model.fp16.bin""",
          """vae/diffusion_pytorch_model.fp16.safetensors""",
          """text_encoder/pytorch_model.fp16.bin""",
          """text_encoder/model.fp16.safetensors""",
          """unet/diffusion_pytorch_model.fp16.bin""",
          # Removed: 'unet/diffusion_pytorch_model.fp16.safetensors',
      ]
      lowerCAmelCase_      :				List[str]      =       """fp16"""
      self.assertFalse(is_safetensors_compatible(lowerCamelCase   ,						variant=lowerCamelCase		)		)

    def __lowercase       (       self   :  Union[str, Any]		)       ->  Optional[int]:
      lowerCAmelCase_      :				str      =       [
          """text_encoder/pytorch_model.fp16.bin""",
          """text_encoder/model.fp16.safetensors""",
      ]
      lowerCAmelCase_      :				Optional[Any]      =       """fp16"""
      self.assertTrue(is_safetensors_compatible(lowerCamelCase   ,						variant=lowerCamelCase		)		)

    def __lowercase       (       self   :  List[Any]		)       ->  List[Any]:
      # pass variant but use the non-variant filenames
      lowerCAmelCase_      :				Dict      =       [
          """text_encoder/pytorch_model.bin""",
          """text_encoder/model.safetensors""",
      ]
      lowerCAmelCase_      :				Any      =       """fp16"""
      self.assertTrue(is_safetensors_compatible(lowerCamelCase   ,						variant=lowerCamelCase		)		)





    def __lowercase       (       self   :  Dict		)       ->  Any:
      lowerCAmelCase_      :				Optional[int]      =       [
          """safety_checker/pytorch_model.fp16.bin""",
          """safety_checker/model.fp16.safetensors""",
          """vae/diffusion_pytorch_model.fp16.bin""",
          """vae/diffusion_pytorch_model.fp16.safetensors""",
          """text_encoder/pytorch_model.fp16.bin""",
          # 'text_encoder/model.fp16.safetensors',
          """unet/diffusion_pytorch_model.fp16.bin""",
          """unet/diffusion_pytorch_model.fp16.safetensors""",
      ]
      lowerCAmelCase_      :				int      =       """fp16"""
      self.assertFalse(is_safetensors_compatible(lowerCamelCase   ,						variant=lowerCamelCase		)		)







'''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()



