What I need to do is fairly simple:
Just to see the 5 frames and the 5 corresponding fgmasks :
import numpy as np
import cv2
cap = cv2.VideoCapture('test.avi')
fgbg = cv2.BackgroundSubtractorMOG()
while(True):
# Capture frame-by-frame
ret, frame = cap.read()
fgmask = fgbg.apply(frame)
# Display the fgmask frame
cv2.imshow('fgmask',fgmask)
# Display original frame
cv2.imshow('img', frame)
k = cv2.waitKey(0) & 0xff
if k == 5:
break
cap.release()
cv2.destroyAllWindows()
Every frame gets opened and displayed correctly but the showed fgmask do not correspond to the showed original frame. Somewhere in the process, the order of the fgmasks gets mixed up.
The background does get subtracted correctly but I don't get the 5 expected fgmasks.
What am I missing ? I feel like this should be straightforward : the while loop runs over the 5 frames of the video and fgbg.apply apply the background subtraction function to each frame.
OpenCV version that I use is opencv-2.4.9-3
As bikz05 suggested, running average method worked pretty good on my 5 images sets. Thanks for the tip !
import cv2
import numpy as np
c = cv2.VideoCapture('test.avi')
_,f = c.read()
avg1 = np.float32(f)
avg2 = np.float32(f)
# loop over images and estimate background
for x in range(0,4):
_,f = c.read()
cv2.accumulateWeighted(f,avg1,1)
cv2.accumulateWeighted(f,avg2,0.01)
res1 = cv2.convertScaleAbs(avg1)
res2 = cv2.convertScaleAbs(avg2)
cv2.imshow('img',f)
cv2.imshow('avg1',res1)
cv2.imshow('avg2',res2)
k = cv2.waitKey(0) & 0xff
if k == 5:
break
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