mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
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110 lines
3.9 KiB
110 lines
3.9 KiB
#!/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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