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

UpperCamelCase													=		180

def     lowercase_       (    _lowerCamelCase							: List[Any]	,			_lowerCamelCase							: Optional[Any]):
    lowercase__				:     List[str]					      =       k_size // 2
    lowercase__      ,     lowercase__				:     Optional[int]					      =       np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
    lowercase__				:     List[str]					      =       (
        1
        / (2 * np.pi * sigma)
        * np.exp(-(np.square(_lowerCamelCase) + np.square(_lowerCamelCase)) / (2 * np.square(_lowerCamelCase)))
    )
    return g

def     lowercase_       (    _lowerCamelCase							: str	,			_lowerCamelCase							: Optional[int]	,			_lowerCamelCase							: Dict):
    lowercase__				:     List[Any]					      =       np.zeros(_lowerCamelCase)

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

            if (
                0 <= direction < PI / 8
                or 15 * PI / 8 <= direction <= 2 * PI
                or 7 * PI / 8 <= direction <= 9 * PI / 8
            ):
                lowercase__				:     Union[str, Any]					      =       sobel_grad[row, col - 1]
                lowercase__				:     List[Any]					      =       sobel_grad[row, col + 1]
                if sobel_grad[row, col] >= w and sobel_grad[row, col] >= e:
                    lowercase__				:     Dict					      =       sobel_grad[row, col]

            elif (
                PI / 8 <= direction < 3 * PI / 8
                or 9 * PI / 8 <= direction < 11 * PI / 8
            ):
                lowercase__				:     List[str]					      =       sobel_grad[row + 1, col - 1]
                lowercase__				:     List[str]					      =       sobel_grad[row - 1, col + 1]
                if sobel_grad[row, col] >= sw and sobel_grad[row, col] >= ne:
                    lowercase__				:     Union[str, Any]					      =       sobel_grad[row, col]

            elif (
                3 * PI / 8 <= direction < 5 * PI / 8
                or 11 * PI / 8 <= direction < 13 * PI / 8
            ):
                lowercase__				:     Tuple					      =       sobel_grad[row - 1, col]
                lowercase__				:     Tuple					      =       sobel_grad[row + 1, col]
                if sobel_grad[row, col] >= n and sobel_grad[row, col] >= s:
                    lowercase__				:     Union[str, Any]					      =       sobel_grad[row, col]

            elif (
                5 * PI / 8 <= direction < 7 * PI / 8
                or 13 * PI / 8 <= direction < 15 * PI / 8
            ):
                lowercase__				:     Tuple					      =       sobel_grad[row - 1, col - 1]
                lowercase__				:     Any					      =       sobel_grad[row + 1, col + 1]
                if sobel_grad[row, col] >= nw and sobel_grad[row, col] >= se:
                    lowercase__				:     int					      =       sobel_grad[row, col]

    return destination

def     lowercase_       (    _lowerCamelCase							: str	,			_lowerCamelCase							: Union[str, Any]	,			_lowerCamelCase							: Optional[Any]	,			_lowerCamelCase							: str	,			_lowerCamelCase							: int	,			_lowerCamelCase							: Tuple):







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

def     lowercase_       (    _lowerCamelCase							: str	,			_lowerCamelCase							: Any	,			_lowerCamelCase							: List[Any]	,			_lowerCamelCase							: Dict):







    for row in range(1	,			image_shape[0]):
        for col in range(1	,			image_shape[1]):
            if destination[row, col] == weak:
                if 255 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],
                ):
                    lowercase__				:     Optional[Any]					      =       strong
                else:
                    lowercase__				:     Optional[int]					      =       0

def     lowercase_       (    _lowerCamelCase							: Any	,			_lowerCamelCase							: List[str]=15	,			_lowerCamelCase							: Union[str, Any]=30	,			_lowerCamelCase							: Tuple=128	,			_lowerCamelCase							: List[Any]=255):
    lowercase__				:     int					      =       img_convolve(_lowerCamelCase	,			gen_gaussian_kernel(9	,			sigma=1.4))
    # get the gradient and degree by sobel_filter
    lowercase__      ,     lowercase__				:     List[str]					      =       sobel_filter(_lowerCamelCase)
    lowercase__				:     Union[str, Any]					      =       PI + np.radadeg(_lowerCamelCase)

    lowercase__				:     Tuple					      =       suppress_non_maximum(image.shape	,			_lowerCamelCase	,			_lowerCamelCase)

    detect_high_low_threshold(
        image.shape	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase)

    track_edge(image.shape	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase)

    return destination


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




import unittest

from datasets import load_dataset

from transformers import load_tool

from .test_tools_common import ToolTesterMixin



class 						snake_case_ (	unittest.TestCase						,__A ):






   def    __UpperCamelCase  (   self       :  Optional[int]						)      ->		List[Any]:
       lowercase__				:     List[Any]					      =       load_tool("document-question-answering"						)
       self.tool.setup()
       lowercase__				:     Optional[int]					      =       load_tool("document-question-answering"			,		remote=lowercase_						)






   def    __UpperCamelCase  (   self       :  int						)      ->		Optional[int]:
       lowercase__				:     List[Any]					      =       load_dataset("hf-internal-testing/example-documents"			,		split="test"						)
       lowercase__				:     List[Any]					      =       dataset[0]["image"]

       lowercase__				:     int					      =       self.tool(lowercase_			,		"When is the coffee break?"						)
       self.assertEqual(lowercase_			,		"11-14 to 11:39 a.m."						)






   def    __UpperCamelCase  (   self       :  Optional[Any]						)      ->		List[Any]:
       lowercase__				:     str					      =       load_dataset("hf-internal-testing/example-documents"			,		split="test"						)
       lowercase__				:     str					      =       dataset[0]["image"]

       lowercase__				:     List[str]					      =       self.remote_tool(lowercase_			,		"When is the coffee break?"						)
       self.assertEqual(lowercase_			,		"11-14 to 11:39 a.m."						)






   def    __UpperCamelCase  (   self       :  List[Any]						)      ->		Dict:
       lowercase__				:     List[str]					      =       load_dataset("hf-internal-testing/example-documents"			,		split="test"						)
       lowercase__				:     List[str]					      =       dataset[0]["image"]

       self.tool(document=lowercase_			,		question="When is the coffee break?"						)







   def    __UpperCamelCase  (   self       :  str						)      ->		Optional[Any]:
       lowercase__				:     Optional[Any]					      =       load_dataset("hf-internal-testing/example-documents"			,		split="test"						)
       lowercase__				:     int					      =       dataset[0]["image"]

       lowercase__				:     Tuple					      =       self.remote_tool(document=lowercase_			,		question="When is the coffee break?"						)
       self.assertEqual(lowercase_			,		"11-14 to 11:39 a.m."						)



