CODEWITHSUNDEEP
pythonimageopencvimage-processing
VICTOR
VICTOR

Reputation: 1942

OpenCV grabcut() background color and Contour in Python

I am using Python and OpenCV. I am now using grabcut() to crop out the object I want. Here is my code:

img = cv2.imread('test.jpg')
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
mask = np.zeros(img.shape[:2], np.uint8)

bgdModel = np.zeros((1, 65), np.float64)
fgdModel = np.zeros((1, 65), np.float64)

rect = (2,2,630,930)
cv2.grabCut(img,mask,rect,bgdModel,fgdModel,5,cv2.GC_INIT_WITH_RECT)

mask2 = np.where((mask==2)|(mask==0), 0,1).astype('uint8')
img = img*mask2[:,:, np.newaxis]

enter image description here enter image description here

Afterwards, I try to find out the contour.

I have tried to find the contour by the code below:

imgray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
ret,thresh = cv2.threshold(imgray,127,255,0)
im2, contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)

And it returns a contours array with length 48. When I draw this out: enter image description here

First question is how can I get the contour (array) of this grab cut?

enter image description here Second question: as you can see, the background color is black. How can I change the background color to white?

Thank you.

Upvotes: 4

Views: 9930

Answers (2)

Tombery
Tombery

Reputation: 351

At first, you need to get the background. To this must be subtracted from the original image with the mask image. And then change the black background to white (or any color). And then back to add with the image of the mask.

import numpy as np
import cv2

cv2.namedWindow(‘image’, cv2.WINDOW_NORMAL)

#Load the Image
imgo = cv2.imread(‘input.jpg’)
height, width = imgo.shape[:2]

#Create a mask holder
mask = np.zeros(imgo.shape[:2],np.uint8)

#Grab Cut the object
bgdModel = np.zeros((1,65),np.float64)
fgdModel = np.zeros((1,65),np.float64)

#Hard Coding the Rect… The object must lie within this rect.
rect = (10,10,width-30,height-30)
cv2.grabCut(imgo,mask,rect,bgdModel,fgdModel,5,cv2.GC_INIT_WITH_RECT)
mask = np.where((mask==2)|(mask==0),0,1).astype(‘uint8’)
img1 = imgo*mask[:,:,np.newaxis]

#Get the background
background = imgo – img1

#Change all pixels in the background that are not black to white
background[np.where((background > [0,0,0]).all(axis = 2))] =[255,255,255]

#Add the background and the image
final = background + img1

#To be done – Smoothening the edges….

cv2.imshow(‘image’, final )

k = cv2.waitKey(0)

if k==27:
cv2.destroyAllWindows()

Information taken from the site https://nxtify.wordpress.com/2015/02/24/image-background-removal-using-opencv-in-python/

Upvotes: 11

Sambasivarao. K
Sambasivarao. K

Reputation: 29

If you want a single contour like boundary, you can go for edge detection on the output of grabcut and morphology dilation on the edge image to get as a proper connected contour and can get the array of pixels of the boundary.

For making the background white, All the pixels outside your bounding box can be default made to white. The black pixels inside your bounding box, you can compare with the original image corresponding gray level, if it is black, you can keep it, otherwise make it to white. Because if the original pixel is not black, but made black by grabcut, then it is considered as background. If black pixel is there in foreground, the grabcut never makes it to black (ideal case).

Upvotes: -1

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