mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
67 lines
2.4 KiB
67 lines
2.4 KiB
9 years ago
|
#!/usr/bin/env python
|
||
|
|
'''
|
||
|
|
===============================================================================
|
||
|
|
Interactive Image Segmentation using GrabCut algorithm.
|
||
|
|
===============================================================================
|
||
|
|
'''
|
||
|
|
|
||
|
|
# Python 2/3 compatibility
|
||
|
|
from __future__ import print_function
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
import cv2
|
||
|
|
import sys
|
||
|
|
|
||
|
|
from tests_common import NewOpenCVTests
|
||
|
|
|
||
|
|
class grabcut_test(NewOpenCVTests):
|
||
|
|
|
||
|
|
def verify(self, mask, exp):
|
||
|
|
|
||
|
|
maxDiffRatio = 0.02
|
||
|
|
expArea = np.count_nonzero(exp)
|
||
|
|
nonIntersectArea = np.count_nonzero(mask != exp)
|
||
|
|
curRatio = float(nonIntersectArea) / expArea
|
||
|
|
return curRatio < maxDiffRatio
|
||
|
|
|
||
|
|
def scaleMask(self, mask):
|
||
|
|
|
||
|
|
return np.where((mask==cv2.GC_FGD) + (mask==cv2.GC_PR_FGD),255,0).astype('uint8')
|
||
|
|
|
||
|
|
def test_grabcut(self):
|
||
|
|
|
||
|
|
img = self.get_sample('cv/shared/airplane.png')
|
||
|
|
mask_prob = self.get_sample("cv/grabcut/mask_probpy.png", 0)
|
||
|
|
exp_mask1 = self.get_sample("cv/grabcut/exp_mask1py.png", 0)
|
||
|
|
exp_mask2 = self.get_sample("cv/grabcut/exp_mask2py.png", 0)
|
||
|
|
|
||
|
|
if img is None:
|
||
|
|
self.assertTrue(False, 'Missing test data')
|
||
|
|
|
||
|
|
rect = (24, 126, 459, 168)
|
||
|
|
mask = np.zeros(img.shape[:2], dtype = np.uint8)
|
||
|
|
bgdModel = np.zeros((1,65),np.float64)
|
||
|
|
fgdModel = np.zeros((1,65),np.float64)
|
||
|
|
cv2.grabCut(img, mask, rect, bgdModel, fgdModel, 0, cv2.GC_INIT_WITH_RECT)
|
||
|
|
cv2.grabCut(img, mask, rect, bgdModel, fgdModel, 2, cv2.GC_EVAL)
|
||
|
|
|
||
|
|
if mask_prob is None:
|
||
|
|
mask_prob = mask.copy()
|
||
|
|
cv2.imwrite(self.extraTestDataPath + '/cv/grabcut/mask_probpy.png', mask_prob)
|
||
|
|
if exp_mask1 is None:
|
||
|
|
exp_mask1 = self.scaleMask(mask)
|
||
|
|
cv2.imwrite(self.extraTestDataPath + '/cv/grabcut/exp_mask1py.png', exp_mask1)
|
||
|
|
|
||
|
|
self.assertEqual(self.verify(self.scaleMask(mask), exp_mask1), True)
|
||
|
|
|
||
|
|
mask = mask_prob
|
||
|
|
bgdModel = np.zeros((1,65),np.float64)
|
||
|
|
fgdModel = np.zeros((1,65),np.float64)
|
||
|
|
cv2.grabCut(img, mask, rect, bgdModel, fgdModel, 0, cv2.GC_INIT_WITH_MASK)
|
||
|
|
cv2.grabCut(img, mask, rect, bgdModel, fgdModel, 1, cv2.GC_EVAL)
|
||
|
|
|
||
|
|
if exp_mask2 is None:
|
||
|
|
exp_mask2 = self.scaleMask(mask)
|
||
|
|
cv2.imwrite(self.extraTestDataPath + '/cv/grabcut/exp_mask2py.png', exp_mask2)
|
||
|
|
|
||
|
|
self.assertEqual(self.verify(self.scaleMask(mask), exp_mask2), True)
|