import cv2
import numpy

#read an image
I_origin = cv2.imread("C:/Users/student/Downloads/flag_green.jpg",1)

#converting into the hsv space

I_hsv = cv2.cvtColor(I_origin,cv2.COLOR_RGB2HSV)
h,s,v = cv2.split(I_hsv)

#creating mask
H1 = h >= 30
H2 = h <= 80
mask = numpy.bitwise_and(H1,H2)
inverse_mask = numpy.logical_not(mask)
mask = numpy.asarray(mask,dtype=numpy.uint8)
inverse_mask = numpy.asarray(inverse_mask,dtype=numpy.uint8)

#creating both of sharped and unsharped versions
value = 11
sigma_value = 1.5
sharped = cv2.GaussianBlur(I_origin, (value, value),sigma_value)
unsharped = cv2.addWeighted(I_origin, 3.5, sharped, -2.5, 0)

#masking both of object and background regions correctly
area_object = numpy.zeros(I_origin.shape,dtype=numpy.uint8)
background_object = numpy.zeros(I_origin.shape,dtype=numpy.uint8)

for i in range(0,3):
    area_object[:,:,i] = unsharped[:,:,i]*mask
    background_object[:,:,i] = sharped[:,:,i]*inverse_mask

result = area_object + background_object
cv2.imshow("result",result)
cv2.waitKey()