





from ...configuration_utils import PretrainedConfig
from ...utils import logging


_snake_case    :       Dict		       =    logging.get_logger(__name__)

_snake_case    :       Dict		       =    {
    'caidas/swin2sr-classicalsr-x2-64': (
        'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json'
    ),
}



class 							_UpperCAmelCase       (       _UpperCamelCase       ):

  """simple docstring"""


  a_              =					"""swin2sr"""

  a_              =					{
      """hidden_size""": """embed_dim""",
      """num_attention_heads""": """num_heads""",
      """num_hidden_layers""": """num_layers""",
  }






  def __init__(							self					:						Any   ,    lowerCAmelCase_					:						List[str]=6_4   ,    lowerCAmelCase_					:						str=1   ,    lowerCAmelCase_					:						int=3   ,    lowerCAmelCase_					:						Optional[Any]=1_8_0   ,    lowerCAmelCase_					:						Union[str, Any]=[6, 6, 6, 6, 6, 6]   ,    lowerCAmelCase_					:						int=[6, 6, 6, 6, 6, 6]   ,    lowerCAmelCase_					:						Optional[int]=8   ,    lowerCAmelCase_					:						List[str]=2.0   ,    lowerCAmelCase_					:						Tuple=True   ,    lowerCAmelCase_					:						Union[str, Any]=0.0   ,    lowerCAmelCase_					:						Dict=0.0   ,    lowerCAmelCase_					:						List[str]=0.1   ,    lowerCAmelCase_					:						int="gelu"   ,    lowerCAmelCase_					:						List[Any]=False   ,    lowerCAmelCase_					:						List[Any]=0.02   ,    lowerCAmelCase_					:						List[Any]=1e-5   ,    lowerCAmelCase_					:						Optional[Any]=2   ,    lowerCAmelCase_					:						Union[str, Any]=1.0   ,    lowerCAmelCase_					:						List[Any]="1conv"   ,    lowerCAmelCase_					:						Optional[Any]="pixelshuffle"   ,    **lowerCAmelCase_					:						Dict   ,    )				->		str:
     super().__init__(**lowerCAmelCase_	)

     __lowerCAmelCase				      =      image_size
     __lowerCAmelCase				      =      patch_size
     __lowerCAmelCase				      =      num_channels
     __lowerCAmelCase				      =      embed_dim
     __lowerCAmelCase				      =      depths
     __lowerCAmelCase				      =      len(lowerCAmelCase_	)
     __lowerCAmelCase				      =      num_heads
     __lowerCAmelCase				      =      window_size
     __lowerCAmelCase				      =      mlp_ratio
     __lowerCAmelCase				      =      qkv_bias
     __lowerCAmelCase				      =      hidden_dropout_prob
     __lowerCAmelCase				      =      attention_probs_dropout_prob
     __lowerCAmelCase				      =      drop_path_rate
     __lowerCAmelCase				      =      hidden_act
     __lowerCAmelCase				      =      use_absolute_embeddings
     __lowerCAmelCase				      =      layer_norm_eps
     __lowerCAmelCase				      =      initializer_range
     __lowerCAmelCase				      =      upscale
     __lowerCAmelCase				      =      img_range
     __lowerCAmelCase				      =      resi_connection
     __lowerCAmelCase				      =      upsampler






from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros







def     UpperCAmelCase_		(					snake_case__    ,			snake_case__					)	->     Dict:



				"""simple docstring"""





				lowerCAmelCase__		  =  k_size // 2
				lowerCAmelCase__  ,   lowerCAmelCase__		  =  mgrid[0 - center : k_size - center, 0 - center : k_size - center]
				lowerCAmelCase__		  =  1 / (2 * pi * sigma) * exp(-(square(snake_case__					) + square(snake_case__					)) / (2 * square(snake_case__					))					)
				return g







def     UpperCAmelCase_		(					snake_case__    ,			snake_case__    ,			snake_case__					)	->     str:



				"""simple docstring"""





				lowerCAmelCase__  ,   lowerCAmelCase__		  =  image.shape[0], image.shape[1]
				# dst image height and width
				lowerCAmelCase__		  =  height - k_size + 1
				lowerCAmelCase__		  =  width - k_size + 1

				# im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
				lowerCAmelCase__		  =  zeros((dst_height * dst_width, k_size * k_size)					)
				lowerCAmelCase__		  =  0
				for i, j in product(range(snake_case__					)    ,			range(snake_case__					)					):
								lowerCAmelCase__		  =  ravel(image[i : i + k_size, j : j + k_size]					)
								lowerCAmelCase__		  =  window
								row += 1

				#  turn the kernel into shape(k*k, 1)
				lowerCAmelCase__		  =  gen_gaussian_kernel(snake_case__    ,			snake_case__					)
				lowerCAmelCase__		  =  ravel(snake_case__					)

				# reshape and get the dst image
				lowerCAmelCase__		  =  dot(snake_case__    ,			snake_case__					).reshape(snake_case__    ,			snake_case__					).astype(snake_case__					)

				return dst


if __name__ == "__main__":
	# read original image
	_lowerCAmelCase	:   List[str]    =   imread(R"../image_data/lena.jpg")
	# turn image in gray scale value
	_lowerCAmelCase	:   Optional[Any]    =   cvtColor(img, COLOR_BGR2GRAY)

	# get values with two different mask size
	_lowerCAmelCase	:   Optional[int]    =   gaussian_filter(gray, 3, sigma=1)
	_lowerCAmelCase	:   Tuple    =   gaussian_filter(gray, 5, sigma=0.8)

	# show result images
	imshow("gaussian filter with 3x3 mask", gaussianaxa)
	imshow("gaussian filter with 5x5 mask", gaussianaxa)
	waitKey()
