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https://github.com/opencv/opencv.git
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111 lines
4.0 KiB
Python
Executable File
111 lines
4.0 KiB
Python
Executable File
#!/usr/bin/python
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import urllib2
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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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import cv2.cv as cv
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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 = cv.GetSize(img) # get current frame size
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idx1 = last
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if not mhi or cv.GetSize(mhi) != size:
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for i in range(N):
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buf[i] = cv.CreateImage(size, cv.IPL_DEPTH_8U, 1)
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cv.Zero(buf[i])
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mhi = cv.CreateImage(size,cv. IPL_DEPTH_32F, 1)
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cv.Zero(mhi) # clear MHI at the beginning
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orient = cv.CreateImage(size,cv. IPL_DEPTH_32F, 1)
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segmask = cv.CreateImage(size,cv. IPL_DEPTH_32F, 1)
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mask = cv.CreateImage(size,cv. IPL_DEPTH_8U, 1)
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cv.CvtColor(img, buf[last], cv.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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cv.AbsDiff(buf[idx1], buf[idx2], silh) # get difference between frames
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cv.Threshold(silh, silh, diff_threshold, 1, cv.CV_THRESH_BINARY) # and threshold it
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cv.UpdateMotionHistory(silh, mhi, timestamp, MHI_DURATION) # update MHI
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cv.CvtScale(mhi, mask, 255./MHI_DURATION,
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(MHI_DURATION - timestamp)*255./MHI_DURATION)
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cv.Zero(dst)
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cv.Merge(mask, None, None, None, dst)
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cv.CalcMotionGradient(mhi, mask, orient, MAX_TIME_DELTA, MIN_TIME_DELTA, 3)
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if not storage:
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storage = cv.CreateMemStorage(0)
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seq = cv.SegmentMotion(mhi, segmask, storage, timestamp, MAX_TIME_DELTA)
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for (area, value, comp_rect) in seq:
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if comp_rect[2] + comp_rect[3] > 100: # reject very small components
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color = cv.CV_RGB(255, 0,0)
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silh_roi = cv.GetSubRect(silh, comp_rect)
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mhi_roi = cv.GetSubRect(mhi, comp_rect)
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orient_roi = cv.GetSubRect(orient, comp_rect)
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mask_roi = cv.GetSubRect(mask, comp_rect)
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angle = 360 - cv.CalcGlobalOrientation(orient_roi, mask_roi, mhi_roi, timestamp, MHI_DURATION)
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count = cv.Norm(silh_roi, None, cv.CV_L1, None) # calculate number of points within silhouette ROI
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if count < (comp_rect[2] * comp_rect[3] * 0.05):
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continue
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magnitude = 30.
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center = ((comp_rect[0] + comp_rect[2] / 2), (comp_rect[1] + comp_rect[3] / 2))
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cv.Circle(dst, center, cv.Round(magnitude*1.2), color, 3, cv.CV_AA, 0)
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cv.Line(dst,
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center,
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(cv.Round(center[0] + magnitude * cos(angle * cv.CV_PI / 180)),
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cv.Round(center[1] - magnitude * sin(angle * cv.CV_PI / 180))),
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color,
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3,
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cv.CV_AA,
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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 = cv.CreateCameraCapture(0)
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elif len(sys.argv)==2 and sys.argv[1].isdigit():
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capture = cv.CreateCameraCapture(int(sys.argv[1]))
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elif len(sys.argv)==2:
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capture = cv.CreateFileCapture(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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cv.NamedWindow("Motion", 1)
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while True:
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image = cv.QueryFrame(capture)
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if(image):
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if(not motion):
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motion = cv.CreateImage((image.width, image.height), 8, 3)
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cv.Zero(motion)
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#motion.origin = image.origin
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update_mhi(image, motion, 30)
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cv.ShowImage("Motion", motion)
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if(cv.WaitKey(10) != -1):
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break
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else:
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break
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cv.DestroyWindow("Motion")
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