# open the video
cap = ocv.cvCreateFileCapture(invideofile)
# extract the number of frames
max_frames = ocv.cvGetCaptureProperty(cap,ocv.CV_CAP_PROP_FRAME_COUNT)
# interrogate the first frame to get the size
frame = ocv.cvQueryFrame(cap)
frame_size = ocv.cvGetSize(frame)
working = ocv.cvCreateImage(frame_size,ocv.IPL_DEPTH_32F,3)
accumulator = ocv.cvCreateImage(frame_size,ocv.IPL_DEPTH_32F,3)
background = ocv.cvCreateImage(frame_size,ocv.IPL_DEPTH_32F,3)
ones = ocv.cvCreateImage(frame_size,ocv.IPL_DEPTH_32F,3)
target = ocv.cvCloneImage(frame)
# Set divisor image all to one
ocv.cvSet(ones,ocv.cvScalar(1.0,1.0,1.0,0))
if show:
ocv.cvNamedWindow ('Track', ocv.CV_WINDOW_AUTOSIZE)
ocv.cvMoveWindow ('Track', 100, 100)
t = 1
n = 1
while True:
# check to see if we should stop
if max_frames:
if t > max_frames:
break
# capture the next frame
frame = ocv.cvQueryFrame(cap)
# Convert frame to grayscale
ocv.cvConvertImage(frame,gray)
# Convert grayscale to float
ocv.cvConvert(gray,grayfloat)
# Smooth - CRITICAL to remove codec artifacts
ocv.cvSmooth(grayfloat,grayfloat,ocv.CV_GAUSSIAN,3,3,0.5)
#ocv.cvSmooth(gray,gray,ocv.CV_MEDIAN)
# Subtract current frame from background model
ocv.cvAbsDiff(grayfloat, background, grayfloat);
# Normalise image
ocv.cvSet(ones,ocv.cvScalar(1.0,0,0,0),0)
minval = ocv.cvMinMaxLoc(grayfloat,True,False)
maxval = ocv.cvMinMaxLoc(grayfloat,False,True)
#print min,max
ocv.cvSubS(grayfloat,ocv.cvScalar(minval,0,0,0),grayfloat,0)
if ((maxval-minval)!=0): #Stop divide by zero
ocv.cvDiv(grayfloat,ones,grayfloat,1.0/(maxval-minval))
else:
cvZero(grayfloat)
ocv.cvScale(grayfloat,grayfloat,255.0) # Scale back to 0-255
# Convert back to int
ocv.cvConvert(grayfloat,gray)
#ocv.cvMerge(gray,gray,gray,0,output) # Show on output
#Find the "lightest" things in the image
