Paint over an area on an image

Question

I have been working with image processing not as long as I would like). I find an object in the image and draw an outline around it. How can I make this mask be white on the inside and black on the outside?

Python code

 import cv2 as cv
 from matplotlib import pyplot as plt
 import numpy as np

MIN_MATCH_COUNT = 20
img1 = cv.imread('horalka2.jpg',0) # queryImage
img2 = cv.imread('Obr4.jpg',0) # sourceImage
# Initiate SIFT detector
sift = cv.SIFT_create()
# find the keypoints and descriptors with SIFT
kp1, des1 = sift.detectAndCompute(img1,None)
kp2, des2 = sift.detectAndCompute(img2,None)
FLANN_INDEX_KDTREE = 1
index_params = dict(algorithm = FLANN_INDEX_KDTREE, trees = 5)
search_params = dict(checks = 50)
flann = cv.FlannBasedMatcher(index_params, search_params)
matches = flann.knnMatch(des1,des2,k=2)
# bf = cv.BFMatcher()
# matches = bf.knnMatch(des1,des2,k=2)

# store all the good matches as per Lowe's ratio test.
good = []
for m,n in matches:
    if m.distance < 0.4*n.distance:
    good.append(m)
    if len(good)>MIN_MATCH_COUNT:
        src_pts = np.float32([ kp1[m.queryIdx].pt for m in good ]).reshape(-1,1,2)
        dst_pts = np.float32([ kp2[m.trainIdx].pt for m in good ]).reshape(-1,1,2)
        M, mask = cv.findHomography(src_pts, dst_pts, cv.RANSAC,5.0)
        matchesMask = mask.ravel().tolist()
        h,w = img1.shape
        pts = np.float32([ [0,0],[0,h-1],[w-1,h-1],[w-1,0] ]).reshape(-1,1,2)
        dst = cv.perspectiveTransform(pts,M)
        img2 = cv.polylines(img2,[np.int32(dst)],True,255,2, cv.LINE_AA)
    else:
        print( "Not enough matches are found - {}/{}".format(len(good), MIN_MATCH_COUNT) 
)
matchesMask = None
draw_params = dict(matchColor = (0,255,0), # draw matches in green color
singlePointColor = None,
matchesMask = matchesMask, # draw only inliers
flags = 2)
img3 = cv.drawMatches(img1,kp1,img2,kp2,good,None,**draw_params)
plt.imshow(img3, 'gray'),plt.show()    

Answer 1

My solution to this problem looks like this: Maybe someone will help:)

edged = cv.Canny(img2, 30, 200)
    contours, hierarchy = cv.findContours(edged, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_NONE)

for c in contours:
    cv.drawContours(img2,[c], 0, (255,255,255), -1)
kernel = cv.getStructuringElement(cv.MORPH_RECT, (20,20))
opening = cv.morphologyEx(img2, cv.MORPH_OPEN, kernel, iterations=2)
opening[opening != 255] = 0

cv.imshow('Contours', opening)
cv.waitKey(0)