


import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image

from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_processing.dithering import burkes as bs
from digital_image_processing.edge_detection import canny
from digital_image_processing.filters import convolve as conv
from digital_image_processing.filters import gaussian_filter as gg
from digital_image_processing.filters import local_binary_pattern as lbp
from digital_image_processing.filters import median_filter as med
from digital_image_processing.filters import sobel_filter as sob
from digital_image_processing.resize import resize as rs

__lowerCamelCase        =     imread(R'''digital_image_processing/image_data/lena_small.jpg''')
__lowerCamelCase        =     cvtColor(img, COLOR_BGR2GRAY)



def  _a			(						):
     a_    :     List[Any]										=    cn.convert_to_negative(__UpperCamelCase )
     # assert negative_img array for at least one True
     assert negative_img.any()



def  _a			(						):
     with Image.open("""digital_image_processing/image_data/lena_small.jpg""" ) as img:
          # Work around assertion for response
          assert str(cc.change_contrast(__UpperCamelCase  ,  1_1_0 ) ).startswith(
              """<PIL.Image.Image image mode=RGB size=100x100 at""" )



def  _a			(						):
     a_    :     int										=    canny.gen_gaussian_kernel(9  ,  sigma=1.4 )
     # Assert ambiguous array
     assert resp.all()



def  _a			(						):
     a_    :     Any										=    imread("""digital_image_processing/image_data/lena_small.jpg"""  ,  0 )
     # assert ambiguous array for all == True
     assert canny_img.all()
     a_    :     str										=    canny.canny(__UpperCamelCase )
     # assert canny array for at least one True
     assert canny_array.any()



def  _a			(						):
     assert gg.gaussian_filter(__UpperCamelCase  ,  5  ,  sigma=0.9 ).all()



def  _a			(						):
     # laplace diagonals
     a_    :     int										=    array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]] )
     a_    :     List[str]										=    conv.img_convolve(__UpperCamelCase  ,  __UpperCamelCase ).astype(__UpperCamelCase )
     assert res.any()



def  _a			(						):
     assert med.median_filter(__UpperCamelCase  ,  3 ).any()



def  _a			(						):
     a_			,			a_    :     List[str]										=    sob.sobel_filter(__UpperCamelCase )
     assert grad.any() and theta.any()



def  _a			(						):
     a_    :     str										=    sp.make_sepia(__UpperCamelCase  ,  2_0 )
     assert sepia.all()



def  _a			(						__UpperCamelCase = "digital_image_processing/image_data/lena_small.jpg" ):
     a_    :     List[Any]										=    bs.Burkes(imread(__UpperCamelCase  ,  1 )  ,  1_2_0 )
     burkes.process()
     assert burkes.output_img.any()



def  _a			(						__UpperCamelCase = "digital_image_processing/image_data/lena_small.jpg"  ,  ):
     a_    :     Optional[Any]										=    rs.NearestNeighbour(imread(__UpperCamelCase  ,  1 )  ,  4_0_0  ,  2_0_0 )
     nn.process()
     assert nn.output.any()



def  _a			(						):
     a_    :     List[str]										=    """digital_image_processing/image_data/lena.jpg"""

     # Reading the image and converting it to grayscale.
     a_    :     Optional[int]										=    imread(__UpperCamelCase  ,  0 )

     # Test for get_neighbors_pixel function() return not None
     a_    :     Tuple										=    0
     a_    :     Union[str, Any]										=    0
     a_    :     Tuple										=    image[x_coordinate][y_coordinate]

     a_    :     Optional[int]										=    lbp.get_neighbors_pixel(
         __UpperCamelCase  ,  __UpperCamelCase  ,  __UpperCamelCase  ,  __UpperCamelCase )

     assert neighbors_pixels is not None

     # Test for local_binary_pattern function()
     # Create a numpy array as the same height and width of read image
     a_    :     int										=    np.zeros((image.shape[0], image.shape[1]) )

     # Iterating through the image and calculating the local binary pattern value
     # for each pixel.
     for i in range(0  ,  image.shape[0] ):
          for j in range(0  ,  image.shape[1] ):
               a_    :     Tuple										=    lbp.local_binary_value(__UpperCamelCase  ,  __UpperCamelCase  ,  __UpperCamelCase )

     assert lbp_image.any()







from datetime import datetime as dt
import os

from github import Github


__lowerCamelCase        =     [
    '''good first issue''',
    '''good second issue''',
    '''good difficult issue''',
    '''feature request''',
    '''new model''',
    '''wip''',
]



def  _a			(						):
     a_    :     List[str]										=    Github(os.environ["""GITHUB_TOKEN"""] )
     a_    :     str										=    g.get_repo("""huggingface/transformers""" )
     a_    :     List[str]										=    repo.get_issues(state="""open""" )

     for issue in open_issues:
          a_    :     Optional[Any]										=    sorted([comment for comment in issue.get_comments()]  ,  key=lambda __UpperCamelCase : i.created_at  ,  reverse=__UpperCamelCase )
          a_    :     List[Any]										=    comments[0] if len(__UpperCamelCase ) > 0 else None
          if (
              last_comment is not None
              and last_comment.user.login == "github-actions[bot]"
              and (dt.utcnow() - issue.updated_at).days > 7
              and (dt.utcnow() - issue.created_at).days >= 3_0
              and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels() )
          ):
               # print(f"Would close issue {issue.number} since it has been 7 days of inactivity since bot mention.")
               issue.edit(state="""closed""" )
          elif (
              (dt.utcnow() - issue.updated_at).days > 2_3
              and (dt.utcnow() - issue.created_at).days >= 3_0
              and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels() )
          ):
               # print(f"Would add stale comment to {issue.number}")
               issue.create_comment(
                   """This issue has been automatically marked as stale because it has not had """
                   """recent activity. If you think this still needs to be addressed """
                   """please comment on this thread.\n\nPlease note that issues that do not follow the """
                   """[contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) """
                   """are likely to be ignored.""" )


if __name__ == "__main__":
       main()



