Add segmentation and object tracking python tests

modules/python/test/test_grabcut.py

@@ -0,0 +1,67 @@
+#!/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 == None:
+            self.assertEqual(0, 1, '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 == None:
+            mask_prob = mask.copy()
+            cv2.imwrite(self.extraTestDataPath + '/cv/grabcut/mask_probpy.png', mask_prob)
+        if exp_mask1 == 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 == 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)