






import numpy as np
import torch
from imwatermark import WatermarkEncoder


# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__UpperCamelCase   :   List[str]      =    0B10_11_00_11_11_10_11_00_10_01_00_00_01_11_10_11_10_11_00_01_10_01_11_10
# bin(x)[2:] gives bits of x as str, use int to convert them to 0/1
__UpperCamelCase   :   List[Any]      =    [int(bit) for bit in bin(WATERMARK_MESSAGE)[2:]]


class 							__UpperCamelCase     :







	def __init__(	self   :				int      )		->			List[Any]:
		"""simple docstring"""







		__lowercase   							=	WATERMARK_BITS
		__lowercase   							=	WatermarkEncoder()

		self.encoder.set_watermark("""bits"""							,					self.watermark      )







	def 			_a (	self   :				List[Any]							,					_lowerCAmelCase   :				torch.FloatTensor      )		->			Union[str, Any]:
		"""simple docstring"""







		if images.shape[-1] < 256:
			return images

		__lowercase   							=	(255 * (images / 2 + 0.5)).cpu().permute(0							,					2							,					3							,					1      ).float().numpy()

		__lowercase   							=	[self.encoder.encode(_lowerCAmelCase							,					"""dwtDct"""      ) for image in images]

		__lowercase   							=	torch.from_numpy(np.array(_lowerCAmelCase      )      ).permute(0							,					3							,					1							,					2      )

		__lowercase   							=	torch.clamp(2 * (images / 255 - 0.5)							,					min=-1.0							,					max=1.0      )
		return images




from PIL import Image







def 						lowerCamelCase__      ( __A    :Image		):


       """simple docstring"""




       __snake_case	,    __snake_case       	=							image.size
       __snake_case       	=							0
       __snake_case       	=							image.load()
       for i in range(__A		):
              for j in range(__A		):
                     __snake_case       	=							pixels[j, i]
                     mean += pixel
       mean //= width * height

       for j in range(__A		):
              for i in range(__A		):
                     __snake_case       	=							2_5_5 if pixels[i, j] > mean else 0
       return image


if __name__ == "__main__":
    UpperCamelCase__		 =     mean_threshold(Image.open('''path_to_image''').convert('''L'''))
    image.save('''output_image_path''')

