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