



import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey





class 		UpperCAmelCase    :





   def __init__(						self							,  _lowerCAmelCase							,  _lowerCAmelCase      ):
         _lowerCAmelCase			      =	0
         # max greyscale value for #FFFFFF
         _lowerCAmelCase			      =	int(self.get_greyscale(255							,  255							,  255      )      )

         if not self.min_threshold < threshold < self.max_threshold:
               _lowerCAmelCase			      =	F'''Factor value should be from 0 to {self.max_threshold}'''
               raise ValueError(_lowerCAmelCase      )

         _lowerCAmelCase			      =	input_img
         _lowerCAmelCase			      =	threshold
         _lowerCAmelCase      , _lowerCAmelCase			      =	self.input_img.shape[1], self.input_img.shape[0]

         # error table size (+4 columns and +1 row) greater than input image because of
         # lack of if statements
         _lowerCAmelCase			      =	[
             [0 for _ in range(self.height + 4      )] for __ in range(self.width + 1      )
         ]
         _lowerCAmelCase			      =	np.ones((self.width, self.height, 3)							,  np.uinta      ) * 255





   @classmethod
   def 						__lowerCAmelCase				(						cls							,  _lowerCAmelCase							,  _lowerCAmelCase							,  _lowerCAmelCase      ):
         return 0.114 * blue + 0.587 * green + 0.2_126 * red





   def 						__lowerCAmelCase				(						self      ):
         for y in range(self.height      ):
               for x in range(self.width      ):
                     _lowerCAmelCase			      =	int(self.get_greyscale(*self.input_img[y][x]      )      )
                     if self.threshold > greyscale + self.error_table[y][x]:
                           _lowerCAmelCase			      =	(0, 0, 0)
                           _lowerCAmelCase			      =	greyscale + self.error_table[x][y]
                     else:
                           _lowerCAmelCase			      =	(255, 255, 255)
                           _lowerCAmelCase			      =	greyscale + self.error_table[x][y] - 255
                     self.error_table[y][x + 1] += int(8 / 32 * current_error      )
                     self.error_table[y][x + 2] += int(4 / 32 * current_error      )
                     self.error_table[y + 1][x] += int(8 / 32 * current_error      )
                     self.error_table[y + 1][x + 1] += int(4 / 32 * current_error      )
                     self.error_table[y + 1][x + 2] += int(2 / 32 * current_error      )
                     self.error_table[y + 1][x - 1] += int(4 / 32 * current_error      )
                     self.error_table[y + 1][x - 2] += int(2 / 32 * current_error      )


if __name__ == "__main__":
    # create Burke's instances with original images in greyscale
    UpperCAmelCase_          =				[
        Burkes(imread("image_data/lena.jpg", 1), threshold)
        for threshold in (1, 1_2_6, 1_3_0, 1_4_0)
    ]

    for burkes in burkes_instances:
        burkes.process()

    for burkes in burkes_instances:
        imshow(
            F"""Original image with dithering threshold: {burkes.threshold}""",
            burkes.output_img,
        )

    waitKey(0)
    destroyAllWindows()




import copy

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


UpperCAmelCase_          =				logging.get_logger(__name__)

UpperCAmelCase_          =				{
    "facebook/sam-vit-huge": "https://huggingface.co/facebook/sam-vit-huge/resolve/main/config.json",
    "facebook/sam-vit-large": "https://huggingface.co/facebook/sam-vit-large/resolve/main/config.json",
    "facebook/sam-vit-base": "https://huggingface.co/facebook/sam-vit-base/resolve/main/config.json",
}





class 		UpperCAmelCase    (    snake_case_					):





   def __init__(						self							,  _lowerCAmelCase=256							,  _lowerCAmelCase=1_024							,  _lowerCAmelCase=16							,  _lowerCAmelCase=16							,  _lowerCAmelCase=4							,  _lowerCAmelCase="gelu"							,  _lowerCAmelCase=1E-6							,  **_lowerCAmelCase							,  ):
         super().__init__(**_lowerCAmelCase      )
         _lowerCAmelCase			      =	hidden_size
         _lowerCAmelCase			      =	image_size
         _lowerCAmelCase			      =	patch_size
         _lowerCAmelCase			      =	image_size // patch_size
         _lowerCAmelCase			      =	mask_input_channels
         _lowerCAmelCase			      =	num_point_embeddings
         _lowerCAmelCase			      =	hidden_act
         _lowerCAmelCase			      =	layer_norm_eps






class 		UpperCAmelCase    (    snake_case_					):





   def __init__(						self							,  _lowerCAmelCase=256							,  _lowerCAmelCase="relu"							,  _lowerCAmelCase=2_048							,  _lowerCAmelCase=2							,  _lowerCAmelCase=8							,  _lowerCAmelCase=2							,  _lowerCAmelCase=3							,  _lowerCAmelCase=3							,  _lowerCAmelCase=256							,  _lowerCAmelCase=1E-6							,  **_lowerCAmelCase							,  ):
         super().__init__(**_lowerCAmelCase      )
         _lowerCAmelCase			      =	hidden_size
         _lowerCAmelCase			      =	hidden_act
         _lowerCAmelCase			      =	mlp_dim
         _lowerCAmelCase			      =	num_hidden_layers
         _lowerCAmelCase			      =	num_attention_heads
         _lowerCAmelCase			      =	attention_downsample_rate
         _lowerCAmelCase			      =	num_multimask_outputs
         _lowerCAmelCase			      =	iou_head_depth
         _lowerCAmelCase			      =	iou_head_hidden_dim
         _lowerCAmelCase			      =	layer_norm_eps






class 		UpperCAmelCase    (    snake_case_					):





   def __init__(						self							,  _lowerCAmelCase=768							,  _lowerCAmelCase=256							,  _lowerCAmelCase=12							,  _lowerCAmelCase=12							,  _lowerCAmelCase=3							,  _lowerCAmelCase=1_024							,  _lowerCAmelCase=16							,  _lowerCAmelCase="gelu"							,  _lowerCAmelCase=1E-06							,  _lowerCAmelCase=0.0							,  _lowerCAmelCase=1E-10							,  _lowerCAmelCase=True							,  _lowerCAmelCase=4.0							,  _lowerCAmelCase=True							,  _lowerCAmelCase=True							,  _lowerCAmelCase=14							,  _lowerCAmelCase=[2, 5, 8, 11]							,  _lowerCAmelCase=128							,  _lowerCAmelCase=None							,  **_lowerCAmelCase							,  ):
         super().__init__(**_lowerCAmelCase      )

         _lowerCAmelCase			      =	hidden_size
         _lowerCAmelCase			      =	output_channels
         _lowerCAmelCase			      =	num_hidden_layers
         _lowerCAmelCase			      =	num_attention_heads
         _lowerCAmelCase			      =	num_channels
         _lowerCAmelCase			      =	image_size
         _lowerCAmelCase			      =	patch_size
         _lowerCAmelCase			      =	hidden_act
         _lowerCAmelCase			      =	layer_norm_eps
         _lowerCAmelCase			      =	attention_dropout
         _lowerCAmelCase			      =	initializer_range
         _lowerCAmelCase			      =	qkv_bias
         _lowerCAmelCase			      =	mlp_ratio
         _lowerCAmelCase			      =	use_abs_pos
         _lowerCAmelCase			      =	use_rel_pos
         _lowerCAmelCase			      =	window_size
         _lowerCAmelCase			      =	global_attn_indexes
         _lowerCAmelCase			      =	num_pos_feats
         _lowerCAmelCase			      =	int(hidden_size * mlp_ratio      ) if mlp_dim is None else mlp_dim






class 		UpperCAmelCase    (    snake_case_					):
   SCREAMING_SNAKE_CASE__					      =  '''sam'''
   SCREAMING_SNAKE_CASE__					      =  True





   def __init__(						self							,  _lowerCAmelCase=None							,  _lowerCAmelCase=None							,  _lowerCAmelCase=None							,  _lowerCAmelCase=0.02							,  **_lowerCAmelCase							,  ):
         super().__init__(**_lowerCAmelCase      )
         _lowerCAmelCase			      =	vision_config if vision_config is not None else {}
         _lowerCAmelCase			      =	prompt_encoder_config if prompt_encoder_config is not None else {}
         _lowerCAmelCase			      =	mask_decoder_config if mask_decoder_config is not None else {}

         if isinstance(_lowerCAmelCase							,  _lowerCAmelCase      ):
               _lowerCAmelCase			      =	vision_config.to_dict()
         if isinstance(_lowerCAmelCase							,  _lowerCAmelCase      ):
               _lowerCAmelCase			      =	prompt_encoder_config.to_dict()
         if isinstance(_lowerCAmelCase							,  _lowerCAmelCase      ):
               _lowerCAmelCase			      =	mask_decoder_config.to_dict()

         _lowerCAmelCase			      =	SamVisionConfig(**_lowerCAmelCase      )
         _lowerCAmelCase			      =	SamPromptEncoderConfig(**_lowerCAmelCase      )
         _lowerCAmelCase			      =	SamMaskDecoderConfig(**_lowerCAmelCase      )
         _lowerCAmelCase			      =	initializer_range





   def 						__lowerCAmelCase				(						self      ):
         _lowerCAmelCase			      =	copy.deepcopy(self.__dict__      )
         _lowerCAmelCase			      =	self.vision_config.to_dict()
         _lowerCAmelCase			      =	self.prompt_encoder_config.to_dict()
         _lowerCAmelCase			      =	self.mask_decoder_config.to_dict()
         _lowerCAmelCase			      =	self.__class__.model_type
         return output