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Lab6.py
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Lab6.py
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# Optical Flow
import cv2
import numpy as np
import matplotlib.pyplot as plt
cap = cv2.VideoCapture("../videos/car1.mp4")
feature_params = dict(maxCorners = 100, qualityLevel = 0.3, minDistance = 7, blockSize = 7)
of_params = dict(winSize = (15,15), maxLevel = 2, criteria = (cv2.TermCriteria_EPS | cv2.TermCriteria_COUNT, 10, 0.03))
# Create some random colors
color = np.random.randint(0,255,(100,3))
ret, old_frame = cap.read()
old_gray = cv2.cvtColor(old_frame, cv2.COLOR_BGR2GRAY)
p0 = cv2.goodFeaturesToTrack(old_gray, mask=None, **feature_params)
mask = np.zeros_like(old_frame)
while(1):
ret,frame = cap.read()
new_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, new_gray, p0, None, **of_params)
good_new = p1[st==1]
good_old = p0[st==1]
for i, (new,old) in enumerate(zip(good_new, good_old)):
a,b = new.ravel()
c,d = old.ravel()
a = int(a)
b = int(b)
c = int(c)
d = int(d)
mask = cv2.line(mask, (a,b), (c,d), color[i].tolist(), 5)
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
old_gray = new_gray.copy()
p0 = good_new.reshape(-1,1,2)
cv2.destroyAllWindows()