

'''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

UpperCAmelCase							=					180

def 			__UpperCamelCase							(		lowercase__  :					Dict,   lowercase__  :					Union[str, Any]	):






     '''simple docstring'''





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

def 			__UpperCamelCase							(		lowercase__  :					Dict,   lowercase__  :					List[Any],   lowercase__  :					Any	):






     '''simple docstring'''





     __lowercase     						=np.zeros(lowercase__	)

     for row in range(1,   image_shape[0] - 1	):
          for col in range(1,   image_shape[1] - 1	):
               __lowercase     						=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     						=sobel_grad[row, col - 1]
                    __lowercase     						=sobel_grad[row, col + 1]
                    if sobel_grad[row, col] >= w and sobel_grad[row, col] >= e:
                         __lowercase     						=sobel_grad[row, col]

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

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

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

     return destination

def 			__UpperCamelCase							(		lowercase__  :					Optional[int],   lowercase__  :					List[str],   lowercase__  :					Dict,   lowercase__  :					Optional[int],   lowercase__  :					str,   lowercase__  :					Optional[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:
                    __lowercase     						=strong
               elif destination[row, col] <= threshold_low:
                    __lowercase     						=0
               else:
                    __lowercase     						=weak

def 			__UpperCamelCase							(		lowercase__  :					Optional[int],   lowercase__  :					Optional[int],   lowercase__  :					str,   lowercase__  :					List[str]	):






     '''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_55 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     						=strong
                    else:
                         __lowercase     						=0

def 			__UpperCamelCase							(		lowercase__  :					Union[str, Any],   lowercase__  :					Optional[Any]=15,   lowercase__  :					Optional[int]=30,   lowercase__  :					Dict=1_28,   lowercase__  :					List[str]=2_55	):






     '''simple docstring'''





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

     __lowercase     						=suppress_non_maximum(image.shape,   lowercase__,   lowercase__	)

     detect_high_low_threshold(
         image.shape,   lowercase__,   lowercase__,   lowercase__,   lowercase__,   lowercase__	)

     track_edge(image.shape,   lowercase__,   lowercase__,   lowercase__	)

     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)





'''simple docstring'''

from typing import TYPE_CHECKING

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


UpperCAmelCase							=					{
    '''configuration_videomae''': ['''VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VideoMAEConfig'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase							=					[
           '''VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''VideoMAEForPreTraining''',
           '''VideoMAEModel''',
           '''VideoMAEPreTrainedModel''',
           '''VideoMAEForVideoClassification''',
       ]

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase							=					['''VideoMAEFeatureExtractor''']
       UpperCAmelCase							=					['''VideoMAEImageProcessor''']

if TYPE_CHECKING:
       from .configuration_videomae import VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP, VideoMAEConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_videomae import (
                  VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST,
                  VideoMAEForPreTraining,
                  VideoMAEForVideoClassification,
                  VideoMAEModel,
                  VideoMAEPreTrainedModel,
              )

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_videomae import VideoMAEFeatureExtractor
              from .image_processing_videomae import VideoMAEImageProcessor

else:
       import sys

       UpperCAmelCase							=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


