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optical_flow_test.py

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+import numpy as np
+import cv2
+
+cap = cv2.VideoCapture(0)
+
+# params for ShiTomasi corner detection
+feature_params = dict( maxCorners = 100,
+                       qualityLevel = 0.3,
+                       minDistance = 7,
+                       blockSize = 7 )
+
+# Parameters for lucas kanade optical flow
+lk_params = dict( winSize  = (15,15),
+                  maxLevel = 2,
+                  criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03))
+
+# Create some random colors
+color = np.random.randint(0,255,(100,3))
+
+# Take first frame and find corners in it
+ret, old_frame = cap.read()
+old_gray = cv2.cvtColor(old_frame, cv2.COLOR_BGR2GRAY)
+p0 = cv2.goodFeaturesToTrack(old_gray, mask = None, **feature_params)
+
+# Create a mask image for drawing purposes
+mask = np.zeros_like(old_frame)
+
+counter = 0
+while(1):
+    ret,frame = cap.read()
+    frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+    # calculate optical flow
+    p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)
+
+    # Select good points
+    good_new = p1[st==1]
+    good_old = p0[st==1]
+
+    # draw the tracks
+    for i,(new,old) in enumerate(zip(good_new,good_old)):
+        a,b = new.ravel()
+        c,d = old.ravel()
+        mask = cv2.line(mask, (a,b),(c,d), color[i].tolist(), 2)
+        frame = cv2.circle(frame,(a,b),5,color[i].tolist(),-1)
+    img = cv2.add(frame,mask)
+
+    cv2.imshow('frame',img)
+    k = cv2.waitKey(30) & 0xff
+    if k == 27:
+        break
+
+    # Now update the previous frame and previous points
+    old_gray = frame_gray.copy()
+    p0 = good_new.reshape(-1,1,2)
+    counter += 1
+
+cv2.destroyAllWindows()
+cap.release()