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optical_flow.py

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+import numpy as np
+import cv2
+import time
+
+help_message = '''
+USAGE: optical_flow.py [<video_source>]
+Keys:
+ 1 - toggle HSV flow visualization
+ 2 - toggle glitch
+'''
+count = 0
+def draw_flow(img, flow, step=16):
+    h, w = img.shape[:2]
+    y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1)
+    fx, fy = flow[y,x].T
+    lines = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2)
+    lines = np.int32(lines + 0.5)
+    vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
+
+    cv2.polylines(vis, lines, 0, (0, 255, 0))
+    for (x1, y1), (x2, y2) in lines:      
+	cv2.circle(vis, (x1, y1), 1, (0, 255, 0), -1)
+    return vis
+
+def draw_hsv(flow):
+    h, w = flow.shape[:2]
+    fx, fy = flow[:,:,0], flow[:,:,1]
+    ang = np.arctan2(fy, fx) + np.pi
+    v = np.sqrt(fx*fx+fy*fy)
+    hsv = np.zeros((h, w, 3), np.uint8)
+    hsv[...,0] = ang*(180/np.pi/2)
+    hsv[...,1] = 255
+    hsv[...,2] = np.minimum(v*4, 255)
+    bgr = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
+    return bgr
+
+def warp_flow(img, flow):
+    h, w = flow.shape[:2]
+    flow = -flow
+    flow[:,:,0] += np.arange(w)
+    flow[:,:,1] += np.arange(h)[:,np.newaxis]
+    res = cv2.remap(img, flow, None, cv2.INTER_LINEAR)
+    return res
+
+if __name__ == '__main__':
+    import sys
+    print help_message
+    try: fn = sys.argv[1]
+    except: fn = 0
+
+    cam = cv2.VideoCapture(fn)
+    ret, prev = cam.read()
+
+    prevgray = cv2.cvtColor(prev, cv2.COLOR_BGR2GRAY)
+    show_hsv = True
+    show_glitch = False
+    cur_glitch = prev.copy()
+
+    while True:
+        ret, img = cam.read()
+	vis = img.copy()
+	gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+	flow = cv2.calcOpticalFlowFarneback(prevgray, gray, 0.5, 5, 15, 3, 5, 1.1, cv2.OPTFLOW_FARNEBACK_GAUSSIAN)
+	prevgray = gray
+	cv2.imshow('flow', draw_flow(gray, flow))
+	if show_hsv:
+	    gray1 = cv2.cvtColor(draw_hsv(flow), cv2.COLOR_BGR2GRAY)
+	    thresh = cv2.threshold(gray1, 25, 255, cv2.THRESH_BINARY)[1]
+	    thresh = cv2.dilate(thresh, None, iterations=2)
+	    (cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
+
+		# loop over the contours
+	    for c in cnts:
+		# if the contour is too small, ignore it
+	    	(x, y, w, h) = cv2.boundingRect(c)
+		if w > 100 and h > 100 and w < 900 and h < 680:
+			cv2.rectangle(vis, (x, y), (x + w, y + h), (0, 255, 0), 4)
+			cv2.putText(vis,str(time.time()), (x,y), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,0,255),1)
+
+	    cv2.imshow('Image', vis)
+	if show_glitch:
+	    cur_glitch = warp_flow(cur_glitch, flow)
+	    cv2.imshow('glitch', cur_glitch)
+	ch = 0xFF & cv2.waitKey(5)
+	if ch == 27:
+	    break
+	if ch == ord('1'):
+	    show_hsv = not show_hsv
+	    print 'HSV flow visualization is', ['off', 'on'][show_hsv]
+	if ch == ord('2'):
+	    show_glitch = not show_glitch
+	    if show_glitch:
+	        cur_glitch = img.copy()
+	    print 'glitch is', ['off', 'on'][show_glitch]
+
+    cv2.destroyAllWindows()