




# Copyright 2022 The HuggingFace Team and The OpenBMB Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCamelCase__			:       Union[str, Any]         =							{
    'configuration_cpmant': ['CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CpmAntConfig'],
    'tokenization_cpmant': ['CpmAntTokenizer'],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__			:       Optional[int]         =							[
       'CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'CpmAntForCausalLM',
       'CpmAntModel',
       'CpmAntPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_cpmant import CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP, CpmAntConfig
   from .tokenization_cpmant import CpmAntTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_cpmant import (
          CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST,
          CpmAntForCausalLM,
          CpmAntModel,
          CpmAntPreTrainedModel,
      )


else:
   import sys

   lowerCamelCase__			:       List[Any]         =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





import cva
import numpy as np





class 	lowerCamelCase_							:


 '''simple docstring'''







 def __init__(							self  :		Optional[Any]    ,    _lowerCAmelCase  :		float    ,    _lowerCAmelCase  :		int						):

       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  :		Tuple						):
       return str(self.k						)




 def 				lowerCAmelCase_  (							self  :		int    ,    _lowerCAmelCase  :		str						):
       SCREAMING_SNAKE_CASE_     						=      cva.imread(_lowerCAmelCase    ,    0						)
       SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      img.shape
       SCREAMING_SNAKE_CASE_     						=      []
       SCREAMING_SNAKE_CASE_     						=      img.copy()
       SCREAMING_SNAKE_CASE_     						=      cva.cvtColor(_lowerCAmelCase    ,    cva.COLOR_GRAY2RGB						)
       SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      np.gradient(_lowerCAmelCase						)
       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(_lowerCAmelCase    ,    h - offset						):
             for x in range(_lowerCAmelCase    ,    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)    ,    255						)
       return color_img, corner_list


if __name__ == "__main__":
   lowerCamelCase__			:       Optional[int]         =							HarrisCorner(0.04, 3)
   lowerCamelCase__    ,							lowerCamelCase__			:       str         =							edge_detect.detect('path_to_image')
   cva.imwrite('detect.png', color_img)