Sunday, March 11, 2018

Python 3.6.4 : Testing OpenCV default GrabCut algorithm.

The main goal for me was to test the new install of python 3.6.4 and python modules with Windows operating system version 8.1.
For this tutorial I chose these python modules: cv2, numpy and matplotlib .
I have tested the GrabCut algorithm article from here.
The article comes with a python script that includes the modules I tested in this programming language.
They tell us:
User inputs the rectangle. Everything outside this rectangle will be taken as sure background (That is the reason it is mentioned before that your rectangle should include all the objects). Everything inside rectangle is unknown. Similarly any user input specifying foreground and background are considered as hard-labelling which means they won't change in the process.
From my point of view, it is not a very successful algorithm to crop off the background, but is working well.
import numpy as np
import cv2
from matplotlib import pyplot as plt

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

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

rect = (57,58,476,741)
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]

plt.imshow(img),plt.colorbar(),plt.show()
The intersection areas are eliminated exactly as in the documentation.
See my first test on an image taken from the internet.

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