Open Source Computer Vision Library https://opencv.org/
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#!/usr/bin/python
from opencv.cv import *
from opencv.highgui import *
import sys
import time
from math import cos,sin
CLOCKS_PER_SEC = 1.0
MHI_DURATION = 1
MAX_TIME_DELTA = 0.5
MIN_TIME_DELTA = 0.05
N = 4
buf = range(10)
last = 0
mhi = None # MHI
orient = None # orientation
mask = None # valid orientation mask
segmask = None # motion segmentation map
storage = None # temporary storage
def update_mhi( img, dst, diff_threshold ):
global last
global mhi
global storage
global mask
global orient
global segmask
timestamp = time.clock()/CLOCKS_PER_SEC # get current time in seconds
size = cvSize(img.width,img.height) # get current frame size
idx1 = last
if not mhi or mhi.width != size.width or mhi.height != size.height:
for i in range( N ):
buf[i] = cvCreateImage( size, IPL_DEPTH_8U, 1 )
cvZero( buf[i] )
mhi = cvCreateImage( size, IPL_DEPTH_32F, 1 )
cvZero( mhi ) # clear MHI at the beginning
orient = cvCreateImage( size, IPL_DEPTH_32F, 1 )
segmask = cvCreateImage( size, IPL_DEPTH_32F, 1 )
mask = cvCreateImage( size, IPL_DEPTH_8U, 1 )
cvCvtColor( img, buf[last], CV_BGR2GRAY ) # convert frame to grayscale
idx2 = (last + 1) % N # index of (last - (N-1))th frame
last = idx2
silh = buf[idx2]
cvAbsDiff( buf[idx1], buf[idx2], silh ) # get difference between frames
cvThreshold( silh, silh, diff_threshold, 1, CV_THRESH_BINARY ) # and threshold it
cvUpdateMotionHistory( silh, mhi, timestamp, MHI_DURATION ) # update MHI
cvCvtScale( mhi, mask, 255./MHI_DURATION,
(MHI_DURATION - timestamp)*255./MHI_DURATION )
cvZero( dst )
cvMerge( mask, None, None, None, dst )
cvCalcMotionGradient( mhi, mask, orient, MAX_TIME_DELTA, MIN_TIME_DELTA, 3 )
if( not storage ):
storage = cvCreateMemStorage(0)
else:
cvClearMemStorage(storage)
seq = cvSegmentMotion( mhi, segmask, storage, timestamp, MAX_TIME_DELTA )
for i in range(-1, seq.total):
if( i < 0 ): # case of the whole image
comp_rect = cvRect( 0, 0, size.width, size.height )
color = CV_RGB(255,255,255)
magnitude = 100.
else: # i-th motion component
comp_rect = seq[i].rect
if( comp_rect.width + comp_rect.height < 100 ): # reject very small components
continue
color = CV_RGB(255,0,0)
magnitude = 30.
silh_roi = cvGetSubRect(silh, comp_rect)
mhi_roi = cvGetSubRect( mhi, comp_rect )
orient_roi = cvGetSubRect( orient, comp_rect )
mask_roi = cvGetSubRect( mask, comp_rect )
angle = cvCalcGlobalOrientation( orient_roi, mask_roi, mhi_roi, timestamp, MHI_DURATION)
angle = 360.0 - angle # adjust for images with top-left origin
count = cvNorm( silh_roi, None, CV_L1, None ) # calculate number of points within silhouette ROI
if( count < comp_rect.width * comp_rect.height * 0.05 ):
continue
center = cvPoint( (comp_rect.x + comp_rect.width/2),
(comp_rect.y + comp_rect.height/2) )
cvCircle( dst, center, cvRound(magnitude*1.2), color, 3, CV_AA, 0 )
cvLine( dst, center, cvPoint( cvRound( center.x + magnitude*cos(angle*CV_PI/180)),
cvRound( center.y - magnitude*sin(angle*CV_PI/180))), color, 3, CV_AA, 0 )
if __name__ == "__main__":
motion = 0
capture = 0
if len(sys.argv)==1:
capture = cvCreateCameraCapture( 0 )
elif len(sys.argv)==2 and sys.argv[1].isdigit():
capture = cvCreateCameraCapture( int(sys.argv[1]) )
elif len(sys.argv)==2:
capture = cvCreateFileCapture( sys.argv[1] )
if not capture:
print "Could not initialize capturing..."
sys.exit(-1)
cvNamedWindow( "Motion", 1 )
while True:
image = cvQueryFrame( capture )
if( image ):
if( not motion ):
motion = cvCreateImage( cvSize(image.width,image.height), 8, 3 )
cvZero( motion )
#motion.origin = image.origin
update_mhi( image, motion, 30 )
cvShowImage( "Motion", motion )
if( cvWaitKey(10) != -1 ):
break
else:
break
cvDestroyWindow( "Motion" )