
"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase__							=				{
    'configuration_megatron_bert': ['MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegatronBertConfig'],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__							=				[
						    'MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'MegatronBertForCausalLM',
						    'MegatronBertForMaskedLM',
						    'MegatronBertForMultipleChoice',
						    'MegatronBertForNextSentencePrediction',
						    'MegatronBertForPreTraining',
						    'MegatronBertForQuestionAnswering',
						    'MegatronBertForSequenceClassification',
						    'MegatronBertForTokenClassification',
						    'MegatronBertModel',
						    'MegatronBertPreTrainedModel',
						]

if TYPE_CHECKING:
						from .configuration_megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_megatron_bert import (
												    MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    MegatronBertForCausalLM,
												    MegatronBertForMaskedLM,
												    MegatronBertForMultipleChoice,
												    MegatronBertForNextSentencePrediction,
												    MegatronBertForPreTraining,
												    MegatronBertForQuestionAnswering,
												    MegatronBertForSequenceClassification,
												    MegatronBertForTokenClassification,
												    MegatronBertModel,
												    MegatronBertPreTrainedModel,
												)

else:
						import sys

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

"""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)