Getting Rid of Lines in OpenCV-Python - python-3.x

Question

Like I converted my original input to HSV color space image & applied the INRANGE function and found the green & blue lines & now i want to get rid of them and I want the image to look like in output....how shall i now get rid of the lines & replace them by the background color??
Code Snippet:
import cv2 as cv
import numpy as np
img= cv.imread('C:\input.png',1)
hsv=cv.cvtColor(img,cv.COLOR_BGR2HSV)
lower_green = np.array([30,70,20])
upper_green = np.array([70,255,255])
lower_blue = np.array([95, 110, 20])
upper_blue = np.array([135, 255, 255])
mask = cv.inRange(hsv, lower_green , upper_blue)
res = cv.bitwise_and(img,img, mask= mask)
cv.imwrite("out2.jpg", res)

Answer 1

Here is a quick and dirty solution.
Create a mask from manually threshold image containing the lines (mask 1)
Also create a binary inverted image of this mask (mask 2)
Mask the image of the shirt with mask 1
Inpaint the image above using mask 2
The solution definitely can be improved by performing morphological operations on the mask to remove the lines. Share your thoughts as well

Answer 2

By doing something like #jeru-luke said, the result will be like this:
import cv2 as cv
import numpy as np
img = cv.imread('z12.png', 1)
hsv = cv.cvtColor(img, cv.COLOR_BGR2HSV)
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
lower_green = np.array([30, 70, 20])
upper_green = np.array([70, 255, 255])
lower_blue = np.array([95, 110, 20])
upper_blue = np.array([135, 255, 255])
mask = cv.inRange(hsv, lower_green, upper_blue)
mask = cv.bitwise_not(mask)
bk = np.full(img.shape, 255, dtype=np.uint8) # white bk
fg_masked = cv.bitwise_and(img, img, mask=mask)
# get masked background, mask must be inverted
mask = cv.bitwise_not(mask)
bk_masked = cv.bitwise_and(bk, bk, mask=mask)
# combine masked foreground and masked background
final = cv.bitwise_or(fg_masked, bk_masked)
cv.imwrite('out_put.png', final)
cv.imshow('final', final), cv.waitKey(0)

Answer 3

import cv2 as cv
import numpy as np
img= cv.imread(r'input.png',1)
hsv=cv.cvtColor(img,cv.COLOR_BGR2HSV)
h,s,v = cv.split(hsv)
th, threshed = cv.threshold(s, 100, 255, cv.THRESH_OTSU|cv.THRESH_BINARY) #black background
mask_w = cv.bitwise_not(threshed) #white background
fg_masked = cv.bitwise_and(v, v, mask=mask_w) #masking the image of shirt with mask_w
dst = cv.inpaint(fg_masked,threshed,3, cv.INPAINT_NS) #inpainting
#Dilation & Erosion.
kernel = np.ones((4, 4),np.uint8)
dilation = cv.dilate(dst,kernel,iterations = 2)
erosion = cv.erode(dilation, kernel, iterations=1)
dilation2= cv.dilate(erosion,kernel,iterations = 1)
dilation3= cv.dilate(dilation2,kernel,iterations = 1)
erosion_final = cv.erode(dilation3, kernel, iterations=3)
cv.imwrite("output_2 [improved].png", erosion_final)