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test.py

+import bayesian_adapted_gmm_for_background_extraction as bayes
+import cv2
+
+# test one: successfully create a backgroundsubtractor
+
+koeBayes=bayes.BackgroundSubtractorBayes(0.61,10,3)
+
+# test two: successfully create a freimi: 
+cap = cv2.VideoCapture('test_video_1.mp4')
+ret, frame = cap.read(88)
+koeFreimi=bayes.freimi(8,frame)
+
+# test three: successfully create a mask for entire set of frames of the test video
+
+while(cap.isOpened() and frame_idx < cap.get(cv2.CAP_PROP_FRAME_COUNT) - 1):
+        ret, frame = cap.read()
+
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        #g2= BackgroundSubtractorBayes.apply(gray,0.7)
+        #g3=AltSub.apply(gray)
+        #g4=koeBayes.core.apply(gray)
+        g5=koeBayes.apply(gray,int(cap.get(cv2.CAP_PROP_POS_FRAMES)))
+