text: import cv2
  import numpy as np
  import copy
  import sys
  
  path=sys.path[0]+'/' 
  img_input=cv2.imread(path+"original_imgs/point.jpg",0)
  filter_kernel=np.array([[-1,-1,-1],[-1,8,-1],[-1,-1,-1]])
  size_img_input=img_input.shape
  kernel_size=filter_kernel.shape
  decenter=int((kernel_size[1]-1)/2)
  new_img=np.zeros(img_input.shape)
  for i in range(0,size_img_input[0]):
          for j in range(0,size_img_input[1]):
              H=np.zeros((kernel_size[0],kernel_size[1])).astype('int')
              G=np.zeros((kernel_size[0],kernel_size[1])).astype('int')
              for n in range(-decenter,decenter+1):
                  for m in range(-decenter,decenter+1):
                      if i+n in range(0,size_img_input[0]) and j+m in range(0,size_img_input[1]):
                          H[decenter+n,decenter+m]=img_input[i+n,j+m]
                      else:
                          H[decenter+n,decenter+m]=0
              for x in range(-decenter,decenter+1):
                  for y in range(-decenter,decenter+1):
                      G[decenter+x,decenter+y]=H[decenter+x,decenter+y]*filter_kernel[decenter+x,decenter+y]
              new_img[i,j]=sum(sum(G))
      
  #img_new_adjusted=new_img.clip(0, 255)
  #img_new=np.rint(img_new_adjusted).astype('uint8')
  
  
  #cv2.imshow('img_mask',img_new)
  