
"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


lowerCAmelCase__							=				logging.get_logger(__name__)

lowerCAmelCase__							=				{
    'microsoft/swin-tiny-patch4-window7-224': (
        'https://huggingface.co/microsoft/swin-tiny-patch4-window7-224/resolve/main/config.json'
    ),
    # See all Swin models at https://huggingface.co/models?filter=swin
}





class  snake_case     (							__lowercase       ,			__lowercase   ):
							UpperCAmelCase__						     =      '''swin'''

							UpperCAmelCase__						     =      {
							    '''num_attention_heads''': '''num_heads''',
							    '''num_hidden_layers''': '''num_layers''',
							}

							def __init__(self       ,       SCREAMING_SNAKE_CASE_=2_24       ,       SCREAMING_SNAKE_CASE_=4       ,       SCREAMING_SNAKE_CASE_=3       ,       SCREAMING_SNAKE_CASE_=96       ,       SCREAMING_SNAKE_CASE_=[2, 2, 6, 2]       ,       SCREAMING_SNAKE_CASE_=[3, 6, 12, 24]       ,       SCREAMING_SNAKE_CASE_=7       ,       SCREAMING_SNAKE_CASE_=4.0       ,       SCREAMING_SNAKE_CASE_=True       ,       SCREAMING_SNAKE_CASE_=0.0       ,       SCREAMING_SNAKE_CASE_=0.0       ,       SCREAMING_SNAKE_CASE_=0.1       ,       SCREAMING_SNAKE_CASE_="gelu"       ,       SCREAMING_SNAKE_CASE_=False       ,       SCREAMING_SNAKE_CASE_=0.02       ,       SCREAMING_SNAKE_CASE_=1e-5       ,       SCREAMING_SNAKE_CASE_=32       ,       SCREAMING_SNAKE_CASE_=None       ,       SCREAMING_SNAKE_CASE_=None       ,       **SCREAMING_SNAKE_CASE_       ,       ):

									"""simple docstring"""







									super().__init__(**SCREAMING_SNAKE_CASE_    )

									SCREAMING_SNAKE_CASE_						 = image_size
									SCREAMING_SNAKE_CASE_						 = patch_size
									SCREAMING_SNAKE_CASE_						 = num_channels
									SCREAMING_SNAKE_CASE_						 = embed_dim
									SCREAMING_SNAKE_CASE_						 = depths
									SCREAMING_SNAKE_CASE_						 = len(SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = num_heads
									SCREAMING_SNAKE_CASE_						 = window_size
									SCREAMING_SNAKE_CASE_						 = mlp_ratio
									SCREAMING_SNAKE_CASE_						 = qkv_bias
									SCREAMING_SNAKE_CASE_						 = hidden_dropout_prob
									SCREAMING_SNAKE_CASE_						 = attention_probs_dropout_prob
									SCREAMING_SNAKE_CASE_						 = drop_path_rate
									SCREAMING_SNAKE_CASE_						 = hidden_act
									SCREAMING_SNAKE_CASE_						 = use_absolute_embeddings
									SCREAMING_SNAKE_CASE_						 = layer_norm_eps
									SCREAMING_SNAKE_CASE_						 = initializer_range
									SCREAMING_SNAKE_CASE_						 = encoder_stride
									# we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
									# this indicates the channel dimension after the last stage of the model
									SCREAMING_SNAKE_CASE_						 = int(embed_dim * 2 ** (len(SCREAMING_SNAKE_CASE_    ) - 1)    )
									SCREAMING_SNAKE_CASE_						 = ['''stem'''] + [f'stage{idx}' for idx in range(1       ,       len(SCREAMING_SNAKE_CASE_    ) + 1    )]
									SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_						 = get_aligned_output_features_output_indices(
									    out_features=SCREAMING_SNAKE_CASE_       ,       out_indices=SCREAMING_SNAKE_CASE_       ,       stage_names=self.stage_names    )





class  snake_case     (							__lowercase   ):
							UpperCAmelCase__						     =      version.parse('''1.11'''   )

							@property
							def _lowercase					(self    ):

									"""simple docstring"""







									return OrderedDict(
									    [
									        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
									    ]    )







							@property
							def _lowercase					(self    ):

									"""simple docstring"""







									return 1e-4

"""simple docstring"""




import cva
import numpy as np





class  snake_case     :

							def __init__(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									if k in (0.04, 0.06):
											SCREAMING_SNAKE_CASE_						 = k
											SCREAMING_SNAKE_CASE_						 = window_size
									else:
											raise ValueError('''invalid k value'''    )

							def __str__(self    ):

									"""simple docstring"""







									return str(self.k    )







							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = cva.imread(SCREAMING_SNAKE_CASE_       ,       0    )
									SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_						 = img.shape
									SCREAMING_SNAKE_CASE_						 = []
									SCREAMING_SNAKE_CASE_						 = img.copy()
									SCREAMING_SNAKE_CASE_						 = cva.cvtColor(SCREAMING_SNAKE_CASE_       ,       cva.COLOR_GRAY2RGB    )
									SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_						 = np.gradient(SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = dx**2
									SCREAMING_SNAKE_CASE_						 = dy**2
									SCREAMING_SNAKE_CASE_						 = dx * dy
									SCREAMING_SNAKE_CASE_						 = 0.04
									SCREAMING_SNAKE_CASE_						 = self.window_size // 2
									for y in range(SCREAMING_SNAKE_CASE_       ,       h - offset    ):
											for x in range(SCREAMING_SNAKE_CASE_       ,       w - offset    ):
													SCREAMING_SNAKE_CASE_						 = ixx[
													    y - offset : y + offset + 1, x - offset : x + offset + 1
													].sum()
													SCREAMING_SNAKE_CASE_						 = iyy[
													    y - offset : y + offset + 1, x - offset : x + offset + 1
													].sum()
													SCREAMING_SNAKE_CASE_						 = ixy[
													    y - offset : y + offset + 1, x - offset : x + offset + 1
													].sum()

													SCREAMING_SNAKE_CASE_						 = (wxx * wyy) - (wxy**2)
													SCREAMING_SNAKE_CASE_						 = wxx + wyy
													SCREAMING_SNAKE_CASE_						 = det - k * (trace**2)
													# Can change the value
													if r > 0.5:
															corner_list.append([x, y, r]    )
															color_img.itemset((y, x, 0)       ,       0    )
															color_img.itemset((y, x, 1)       ,       0    )
															color_img.itemset((y, x, 2)       ,       2_55    )
									return color_img, corner_list


if __name__ == "__main__":
						lowerCAmelCase__							=				HarrisCorner(0.04, 3)
						lowerCAmelCase__,  lowerCAmelCase__							=				edge_detect.detect('path_to_image')
						cva.imwrite('detect.png', color_img)