





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

from digital_image_processing.filters.convolve import img_convolve





def   _lowercase       (    _UpperCAmelCase					)    ->	Dict:
				lowerCamelCase									=np.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]]					)
				lowerCamelCase									=np.array([[1, 2, 1], [0, 0, 0], [-1, -2, -1]]					)

				lowerCamelCase									=np.abs(img_convolve(_UpperCAmelCase      ,   _UpperCAmelCase					)					)
				lowerCamelCase									=np.abs(img_convolve(_UpperCAmelCase      ,   _UpperCAmelCase					)					)
				# modify the pix within [0, 255]
				lowerCamelCase									=dst_x * 2_55 / np.max(_UpperCAmelCase					)
				lowerCamelCase									=dst_y * 2_55 / np.max(_UpperCAmelCase					)

				lowerCamelCase									=np.sqrt((np.square(_UpperCAmelCase					)) + (np.square(_UpperCAmelCase					))					)
				lowerCamelCase									=dst_xy * 2_55 / np.max(_UpperCAmelCase					)
				lowerCamelCase									=dst_xy.astype(np.uinta					)

				lowerCamelCase									=np.arctana(_UpperCAmelCase      ,   _UpperCAmelCase					)
				return dst, theta


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

							UpperCAmelCase__					,UpperCAmelCase__    :      Any       					=sobel_filter(gray)

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












from typing import TYPE_CHECKING

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


UpperCAmelCase__    :      Optional[Any]       					={
    '''configuration_donut_swin''': ['''DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DonutSwinConfig'''],
    '''processing_donut''': ['''DonutProcessor'''],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__    :      Any       					=[
							    '''DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''DonutSwinModel''',
							    '''DonutSwinPreTrainedModel''',
							]

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__    :      Tuple       					=['''DonutFeatureExtractor''']
							UpperCAmelCase__    :      List[str]       					=['''DonutImageProcessor''']


if TYPE_CHECKING:
							from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
							from .processing_donut import DonutProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_donut_swin import (
														    DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DonutSwinModel,
														    DonutSwinPreTrainedModel,
														)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_donut import DonutFeatureExtractor
														from .image_processing_donut import DonutImageProcessor

else:
							import sys

							UpperCAmelCase__    :      int       					=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





