





"""simple docstring"""


import cva
import numpy as np

from digital_image_processing.filters.convolve import img_convolve
from digital_image_processing.filters.sobel_filter import sobel_filter

a__   :       Dict   						=			1_8_0





def 							a__     (					_UpperCAmelCase		,       _UpperCAmelCase		)      ->					Tuple:

 '''simple docstring'''






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





def 							a__     (					_UpperCAmelCase		,       _UpperCAmelCase		,       _UpperCAmelCase		)      ->					Optional[int]:

 '''simple docstring'''






 snake_case__      							=			np.zeros(snake_case__		)

 for row in range(1		,       image_shape[0] - 1		):
  for col in range(1		,       image_shape[1] - 1		):
   snake_case__      							=			gradient_direction[row, col]

   if (
       0 <= direction < PI / 8
       or 1_5 * PI / 8 <= direction <= 2 * PI
       or 7 * PI / 8 <= direction <= 9 * PI / 8
   ):
    snake_case__      							=			sobel_grad[row, col - 1]
    snake_case__      							=			sobel_grad[row, col + 1]
    if sobel_grad[row, col] >= w and sobel_grad[row, col] >= e:
     snake_case__      							=			sobel_grad[row, col]

   elif (
       PI / 8 <= direction < 3 * PI / 8
       or 9 * PI / 8 <= direction < 1_1 * PI / 8
   ):
    snake_case__      							=			sobel_grad[row + 1, col - 1]
    snake_case__      							=			sobel_grad[row - 1, col + 1]
    if sobel_grad[row, col] >= sw and sobel_grad[row, col] >= ne:
     snake_case__      							=			sobel_grad[row, col]

   elif (
       3 * PI / 8 <= direction < 5 * PI / 8
       or 1_1 * PI / 8 <= direction < 1_3 * PI / 8
   ):
    snake_case__      							=			sobel_grad[row - 1, col]
    snake_case__      							=			sobel_grad[row + 1, col]
    if sobel_grad[row, col] >= n and sobel_grad[row, col] >= s:
     snake_case__      							=			sobel_grad[row, col]

   elif (
       5 * PI / 8 <= direction < 7 * PI / 8
       or 1_3 * PI / 8 <= direction < 1_5 * PI / 8
   ):
    snake_case__      							=			sobel_grad[row - 1, col - 1]
    snake_case__      							=			sobel_grad[row + 1, col + 1]
    if sobel_grad[row, col] >= nw and sobel_grad[row, col] >= se:
     snake_case__      							=			sobel_grad[row, col]

 return destination





def 							a__     (					_UpperCAmelCase		,       _UpperCAmelCase		,       _UpperCAmelCase		,       _UpperCAmelCase		,       _UpperCAmelCase		,       _UpperCAmelCase		)      ->					List[Any]:

 '''simple docstring'''






 for row in range(1		,       image_shape[0] - 1		):
  for col in range(1		,       image_shape[1] - 1		):
   if destination[row, col] >= threshold_high:
    snake_case__      							=			strong
   elif destination[row, col] <= threshold_low:
    snake_case__      							=			0
   else:
    snake_case__      							=			weak





def 							a__     (					_UpperCAmelCase		,       _UpperCAmelCase		,       _UpperCAmelCase		,       _UpperCAmelCase		)      ->					List[Any]:

 '''simple docstring'''






 for row in range(1		,       image_shape[0]		):
  for col in range(1		,       image_shape[1]		):
   if destination[row, col] == weak:
    if 2_5_5 in (
        destination[row, col + 1],
        destination[row, col - 1],
        destination[row - 1, col],
        destination[row + 1, col],
        destination[row - 1, col - 1],
        destination[row + 1, col - 1],
        destination[row - 1, col + 1],
        destination[row + 1, col + 1],
    ):
     snake_case__      							=			strong
    else:
     snake_case__      							=			0





def 							a__     (					_UpperCAmelCase		,       _UpperCAmelCase=1_5		,       _UpperCAmelCase=3_0		,       _UpperCAmelCase=1_2_8		,       _UpperCAmelCase=2_5_5		)      ->					Union[str, Any]:

 '''simple docstring'''






 snake_case__      							=			img_convolve(snake_case__		,       gen_gaussian_kernel(9		,       sigma=1.4		)		)
 # get the gradient and degree by sobel_filter
 snake_case__							,				snake_case__      							=			sobel_filter(snake_case__		)
 snake_case__      							=			PI + np.radadeg(snake_case__		)

 snake_case__      							=			suppress_non_maximum(image.shape		,       snake_case__		,       snake_case__		)

 detect_high_low_threshold(
     image.shape		,       snake_case__		,       snake_case__		,       snake_case__		,       snake_case__		,       snake_case__		)

 track_edge(image.shape		,       snake_case__		,       snake_case__		,       snake_case__		)

 return destination


if __name__ == "__main__":
   # read original image in gray mode
   a__   :       str   						=			cva.imread(r"""../image_data/lena.jpg""", 0)
   # canny edge detection
   a__   :       Dict   						=			canny(lena)
   cva.imshow("""canny""", canny_destination)
   cva.waitKey(0)








"""simple docstring"""


import copy
from typing import Dict

from ...generation.configuration_utils import GenerationConfig
from ...utils import logging


a__   :       str   						=			logging.get_logger(__name__)



class        lowercase_			(       __lowerCAmelCase							):
       snake_case__			:							Dict										=       """semantic"""

       def __init__(     self				,   __SCREAMING_SNAKE_CASE=1_0000				,   __SCREAMING_SNAKE_CASE=True				,   __SCREAMING_SNAKE_CASE=768				,   __SCREAMING_SNAKE_CASE=False				,   __SCREAMING_SNAKE_CASE=False				,   __SCREAMING_SNAKE_CASE=False				,   __SCREAMING_SNAKE_CASE=False				,   __SCREAMING_SNAKE_CASE=0.7				,   __SCREAMING_SNAKE_CASE=True				,   __SCREAMING_SNAKE_CASE=1_0048				,   __SCREAMING_SNAKE_CASE=12_9595				,   __SCREAMING_SNAKE_CASE=12_9599				,   __SCREAMING_SNAKE_CASE=1_0000				,   __SCREAMING_SNAKE_CASE=256				,   __SCREAMING_SNAKE_CASE=49.9				,   **__SCREAMING_SNAKE_CASE				,   ):






        '''simple docstring'''

        super().__init__(
            temperature=__SCREAMING_SNAKE_CASE				,   do_sample=__SCREAMING_SNAKE_CASE				,   eos_token_id=__SCREAMING_SNAKE_CASE				,   renormalize_logits=__SCREAMING_SNAKE_CASE				,   max_new_tokens=__SCREAMING_SNAKE_CASE				,   output_scores=__SCREAMING_SNAKE_CASE				,   return_dict_in_generate=__SCREAMING_SNAKE_CASE				,   output_hidden_states=__SCREAMING_SNAKE_CASE				,   output_attentions=__SCREAMING_SNAKE_CASE				,   **__SCREAMING_SNAKE_CASE				,   )

        snake_case__      							=			text_encoding_offset
        snake_case__      							=			text_pad_token
        snake_case__      							=			eos_token_id
        snake_case__      							=			semantic_infer_token
        snake_case__      							=			semantic_vocab_size
        snake_case__      							=			max_input_semantic_length
        snake_case__      							=			semantic_rate_hz



class        lowercase_			(       __lowerCAmelCase							):
       snake_case__			:							Union[str, Any]										=       """coarse_acoustics"""

       def __init__(     self				,   __SCREAMING_SNAKE_CASE=True				,   __SCREAMING_SNAKE_CASE=False				,   __SCREAMING_SNAKE_CASE=False				,   __SCREAMING_SNAKE_CASE=False				,   __SCREAMING_SNAKE_CASE=False				,   __SCREAMING_SNAKE_CASE=0.7				,   __SCREAMING_SNAKE_CASE=True				,   __SCREAMING_SNAKE_CASE=1_2048				,   __SCREAMING_SNAKE_CASE=75				,   __SCREAMING_SNAKE_CASE=2				,   __SCREAMING_SNAKE_CASE=1_2050				,   __SCREAMING_SNAKE_CASE=256				,   __SCREAMING_SNAKE_CASE = 630				,   __SCREAMING_SNAKE_CASE = 60				,   **__SCREAMING_SNAKE_CASE				,   ):






        '''simple docstring'''

        super().__init__(
            temperature=__SCREAMING_SNAKE_CASE				,   do_sample=__SCREAMING_SNAKE_CASE				,   renormalize_logits=__SCREAMING_SNAKE_CASE				,   output_scores=__SCREAMING_SNAKE_CASE				,   return_dict_in_generate=__SCREAMING_SNAKE_CASE				,   output_hidden_states=__SCREAMING_SNAKE_CASE				,   output_attentions=__SCREAMING_SNAKE_CASE				,   **__SCREAMING_SNAKE_CASE				,   )

        snake_case__      							=			coarse_semantic_pad_token
        snake_case__      							=			coarse_rate_hz
        snake_case__      							=			n_coarse_codebooks
        snake_case__      							=			coarse_infer_token
        snake_case__      							=			max_coarse_input_length
        snake_case__      							=			max_coarse_history
        snake_case__      							=			sliding_window_len



class        lowercase_			(       __lowerCAmelCase							):
       snake_case__			:							Union[str, Any]										=       """fine_acoustics"""

       def __init__(     self				,   __SCREAMING_SNAKE_CASE=0.5				,   __SCREAMING_SNAKE_CASE=512				,   __SCREAMING_SNAKE_CASE=1024				,   __SCREAMING_SNAKE_CASE=8				,   **__SCREAMING_SNAKE_CASE				,   ):






        '''simple docstring'''

        super().__init__(temperature=__SCREAMING_SNAKE_CASE       )

        snake_case__      							=			max_fine_history_length
        snake_case__      							=			max_fine_input_length
        snake_case__      							=			n_fine_codebooks



class        lowercase_			(       __lowerCAmelCase							):
       snake_case__			:							List[str]										=       """bark"""
       snake_case__			:							Dict										=       True

       def __init__(     self				,   __SCREAMING_SNAKE_CASE = None				,   __SCREAMING_SNAKE_CASE = None				,   __SCREAMING_SNAKE_CASE = None				,   __SCREAMING_SNAKE_CASE=2_4000				,   __SCREAMING_SNAKE_CASE=1024				,   **__SCREAMING_SNAKE_CASE				,   ):






        '''simple docstring'''

        if semantic_config is None:
         snake_case__      							=			{}
         logger.info("semantic_config is None. initializing the semantic model with default values."       )

        if coarse_acoustics_config is None:
         snake_case__      							=			{}
         logger.info("coarse_acoustics_config is None. initializing the coarse model with default values."       )

        if fine_acoustics_config is None:
         snake_case__      							=			{}
         logger.info("fine_acoustics_config is None. initializing the fine model with default values."       )

        snake_case__      							=			BarkSemanticGenerationConfig(**__SCREAMING_SNAKE_CASE       )
        snake_case__      							=			BarkCoarseGenerationConfig(**__SCREAMING_SNAKE_CASE       )
        snake_case__      							=			BarkFineGenerationConfig(**__SCREAMING_SNAKE_CASE       )

        snake_case__      							=			sample_rate
        snake_case__      							=			codebook_size

       @classmethod
       def 						_SCREAMING_SNAKE_CASE(     cls				,   __SCREAMING_SNAKE_CASE				,   __SCREAMING_SNAKE_CASE				,   __SCREAMING_SNAKE_CASE				,   **__SCREAMING_SNAKE_CASE				,   ):






        '''simple docstring'''

        return cls(
            semantic_config=semantic_config.to_dict()				,   coarse_acoustics_config=coarse_acoustics_config.to_dict()				,   fine_acoustics_config=fine_acoustics_config.to_dict()				,   **__SCREAMING_SNAKE_CASE				,   )

       def 						_SCREAMING_SNAKE_CASE(     self       ):






        '''simple docstring'''

        snake_case__      							=			copy.deepcopy(self.__dict__       )

        snake_case__      							=			self.semantic_config.to_dict()
        snake_case__      							=			self.coarse_acoustics_config.to_dict()
        snake_case__      							=			self.fine_acoustics_config.to_dict()

        snake_case__      							=			self.__class__.model_type
        return output

