OpenCV 光流Optical Flow示例

import cv2
import numpy as np
video_file = 'slow_traffic_small.mp4'
cap = cv2.VideoCapture(video_file)
# 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 purpose
mask = np.zeros_like(old_frame)
while True:
    ret, frame = cap.read()
    if ret:
        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
        if p1 is not None:
            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, (int(a), int(b)), (int(c), int(d)), color[i].tolist(), 2)
            frame = cv2.circle(frame, (int(a), int(b)), 5, color[i].tolist(), -1)
        img = cv2.add(frame,mask)
        cv2.imshow('frame',img)
        k = cv2.waitKey(30) & 0xff
        if k == 27:
            cv2.destroyAllWindows()
            break
        # Now update the previous frame and previous points
        old_gray = frame_gray.copy()
        p0 = good_new.reshape(-1,1,2)
    else:
        cv2.destroyAllWindows()
        break

import cv2
import numpy as np
cap = cv2.VideoCapture("vtest.avi")
ret, frame1 = cap.read()
frame1_gray = cv2.cvtColor(frame1, cv2.COLOR_BGR2GRAY)
hsv = np.zeros_like(frame1)
hsv[...,1] = 255
while(1):
    ret, frame2 = cap.read()
    if ret:
        frame2_gray = cv2.cvtColor(frame2, cv2.COLOR_BGR2GRAY)
        flow = cv2.calcOpticalFlowFarneback(frame1_gray, frame2_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
        mag, ang = cv2.cartToPolar(flow[...,0], flow[...,1])
        hsv[...,0] = ang*180/np.pi/2
        hsv[...,2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_MINMAX)
        bgr = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
        cv2.imshow('frame2', bgr)
        k = cv2.waitKey(30) & 0xff
        if k == 27:
        	cv2.destroyAllWindows()
            break
        elif k == ord('s'):
            cv2.imwrite('opticalfb.png',frame2)
            cv2.imwrite('opticalhsv.png',bgr)
        frame1_gray = frame2_gray
    else:
        cv2.destroyAllWindows()
        break