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import cv2
import math
import numpy
from math import sin,cos
cap = cv2.VideoCapture("../vid.mp4")
feature_params = dict( maxCorners = 100,
qualityLevel = 0.3,
minDistance = 20,
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))
ret,oldframe=cap.read()
oldgray=cv2.cvtColor(oldframe,cv2.COLOR_BGR2GRAY)
total_angle=0.
total_x=0
total_y=0
while(cap.isOpened()):
ret, frame = cap.read()
gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
p0 = cv2.goodFeaturesToTrack(oldgray, mask = None, **feature_params)
# calculate optical flow
p1, st, err = cv2.calcOpticalFlowPyrLK(oldgray, gray, p0, None, **lk_params)
# Select good points
good_new = p1[st==1]
good_old = p0[st==1]
for i in p0:
x,y=i.ravel()
cv2.line(frame, (x,y),(x,y), (0,0,255),5)
one=[]
two=[]
for i,(new,old) in enumerate(zip(good_new, good_old)):
x1,y1=new.ravel()
x2,y2=old.ravel()
cv2.line(frame, (x1,y1),(x2,y2), (0,255,0),5)
one=one+[(x1,y1)]
two=two+[(x2,y2)]
mat = cv2.estimateRigidTransform(gray,oldgray,False)
angle = math.atan2(mat[0,1],mat[0,0])
stretch = int((math.sqrt(mat[0,1]**2+mat[0,0]**2)-1)*100)
print angle/3.141592654*180,'deg\t',stretch,"%\t", mat[0,2],'\t',mat[1,2]
height, width, bpp = frame.shape
frame2=frame.copy()
mat2=cv2.getRotationMatrix2D((width/2,height/2), total_angle/3.141593654*180, 1.)
print mat2.__repr__()
total_angle=total_angle+angle
# mat2=numpy.array([[cos(total_angle), sin(total_angle), total_x], [-sin(total_angle),cos(total_angle),total_y]])
frame2= cv2.warpAffine(frame2, mat2, (width,height) )
cv2.imshow('frame', frame)
cv2.imshow('frame2', frame2)
oldframe=frame
oldgray=gray
if cv2.waitKey(20) & 0xFF == ord("q"):
break
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