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optictest.py
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optictest.py
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import numpy as np
import cv2
import pickle
DxyvUxy = []
cap = cv2.VideoCapture('slow_traffic_small.mp4')
# 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)
count = 1
while(1):
count += 1
if count == 150:
# with open('DxyvUxy.pkl','wb') as file:
# pickle.dump(DxyvUxy,file)
break
ret,frame = cap.read()
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
dx = cv2.Sobel(old_gray,cv2.CV_16S,1,0)
dy = cv2.Sobel(old_gray,cv2.CV_16S,0,1)
VI = frame_gray - old_gray
dx = cv2.resize(dx,(6400,3600))
dy = cv2.resize(dy,(6400,3600))
VI = cv2.resize(VI,(6400,3600))
# 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]
good_old_around = np.around(good_old*10).astype(np.int64)
for i in range(len(good_old)):
temp1 = []
if good_old_around[i][1] >= 3600:
good_old_around[i][1] = 3599
if good_old_around[i][0] >= 6400:
good_old_around[i][0] = 6399
x = dx[(good_old_around[i][1]),(good_old_around[i][0])]
y = dy[(good_old_around[i][1]),(good_old_around[i][0])]
vi = (VI[(good_old_around[i][1]),(good_old_around[i][0])])*4
ux = good_new[i][1] - good_old[i][1]
uy = good_new[i][0] - good_old[i][0]
temp1.append(x)
temp1.append(y)
temp1.append(vi)
temp1.append(ux)
temp1.append(uy)
DxyvUxy.append(temp1)
# 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('expected flow',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)
cv2.destroyAllWindows()
cap.release()