Optic flow: Lucas-Kanade algorithm

In [1]:
import numpy as np
import cv2
#from numpy import *
In [2]:
cap = cv2.VideoCapture('648aa10.avi')
length = int(cap.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT))
width  = int(cap.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
height = int(cap.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT))
fps    = cap.get(cv2.cv.CV_CAP_PROP_FPS)
ii=1
In [3]:
length
Out[3]:
251
In [4]:
# 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)

while(ii<length):
    ii+=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()
        cv2.line(mask, (a,b),(c,d), color[i].tolist(), 2)
        cv2.circle(frame,(a,b),5,color[i].tolist(),-1)
    img = cv2.add(frame,mask)

    #note cv2.waitKey() must be used with  cv2.imshow to show the image
    # the & 0xFF is required for 64-bit machines
    cv2.imshow('frame',img)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
    
    # Now update the previous frame and previous points
    old_gray = frame_gray.copy()
    p0 = good_new.reshape(-1,1,2)

cv2.imwrite('trackwindmill.png',img)
cv2.destroyAllWindows()
cap.release()
In [5]:
 
Out[5]:
True
In [ ]: