


import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey

from digital_image_processing.filters.convolve import img_convolve
def       UpperCamelCase__     (  SCREAMING_SNAKE_CASE__						):
 __lowerCamelCase		:							int							=						np.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]]						)
 __lowerCamelCase		:							Tuple							=						np.array([[1, 2, 1], [0, 0, 0], [-1, -2, -1]]						)

 __lowerCamelCase		:							List[Any]							=						np.abs(img_convolve(_UpperCAmelCase			,       _UpperCAmelCase						)						)
 __lowerCamelCase		:							int							=						np.abs(img_convolve(_UpperCAmelCase			,       _UpperCAmelCase						)						)
 # modify the pix within [0, 255]
 __lowerCamelCase		:							Optional[int]							=						dst_x * 255 / np.max(_UpperCAmelCase						)
 __lowerCamelCase		:							Tuple							=						dst_y * 255 / np.max(_UpperCAmelCase						)

 __lowerCamelCase		:							Union[str, Any]							=						np.sqrt((np.square(_UpperCAmelCase						)) + (np.square(_UpperCAmelCase						))						)
 __lowerCamelCase		:							Union[str, Any]							=						dst_xy * 255 / np.max(_UpperCAmelCase						)
 __lowerCamelCase		:							List[Any]							=						dst_xy.astype(np.uinta						)

 __lowerCamelCase		:							List[Any]							=						np.arctana(_UpperCAmelCase			,       _UpperCAmelCase						)
 return dst, theta


if __name__ == "__main__":
       # read original image
       lowercase_           =	imread('../image_data/lena.jpg')
       # turn image in gray scale value
       lowercase_           =	cvtColor(img, COLOR_BGR2GRAY)

       lowercase_           =	sobel_filter(gray)

       # show result images
       imshow('sobel filter', sobel_grad)
       imshow('sobel theta', sobel_theta)
       waitKey(0)








"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__UpperCamelCase			:		List[Any]		    =   {'''configuration_yoso''': ['''YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''YosoConfig''']}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase			:		Dict		    =   [
           '''YOSO_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''YosoForMaskedLM''',
           '''YosoForMultipleChoice''',
           '''YosoForQuestionAnswering''',
           '''YosoForSequenceClassification''',
           '''YosoForTokenClassification''',
           '''YosoLayer''',
           '''YosoModel''',
           '''YosoPreTrainedModel''',
       ]


if TYPE_CHECKING:
       from .configuration_yoso import YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP, YosoConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_yoso import (
                  YOSO_PRETRAINED_MODEL_ARCHIVE_LIST,
                  YosoForMaskedLM,
                  YosoForMultipleChoice,
                  YosoForQuestionAnswering,
                  YosoForSequenceClassification,
                  YosoForTokenClassification,
                  YosoLayer,
                  YosoModel,
                  YosoPreTrainedModel,
              )


else:
       import sys

       __UpperCamelCase			:		Any		    =   _LazyModule(__name__, globals()['''__file__'''], _import_structure)





