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import cv2
import math
import numpy
from math import sin,cos
cap = cv2.VideoCapture("../vid.mp4")
writer = cv2.VideoWriter("../outvid.avi",cv2.cv.CV_FOURCC(*'MP42'),25,(1600,600),1)
###### CONFIG ######
feature_params = dict( maxCorners = 100,
qualityLevel = 0.3,
minDistance = 20,
blockSize = 7 )
scale_factor=0.5
scr_width=1600
scr_height=600
# 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))
###### INITALISATION ######
ret,oldframe=cap.read()
oldgray=cv2.cvtColor(oldframe,cv2.COLOR_BGR2GRAY)
height, width, bpp = oldframe.shape
mask = numpy.ones((height,width, 1), numpy.uint8) * 255
screencontent = numpy.zeros((scr_height, scr_width,3), numpy.uint8)
total_angle=0.
total_x=1500
total_y=-300
while(cap.isOpened()):
ret, frame = cap.read()
gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
# calculate movement, rotation and stretch. (we will ignore the stretch factor.)
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)
# calculate shift_x and _y is if one would rotate-and-stretch around the center of the image, not the topleft corner
shift_x = mat[0,2] - width/2 + ( mat[0,0]*width/2 + mat[0,1]*height/2 )
shift_y = mat[1,2] - height/2 + ( mat[1,0]*width/2 + mat[1,1]*height/2 )
# accumulate values
total_x = total_x + shift_x
total_y = total_y + shift_y
total_angle=total_angle+angle
print angle/3.141592654*180,'deg\t',stretch,"%\t", shift_x,'\t',shift_y
# rotate and move current frame into a global context
mat2=cv2.getRotationMatrix2D((width/2,height/2), total_angle/3.141593654*180, scale_factor)
mat2[0,2] = mat2[0,2]+total_x*scale_factor
mat2[1,2] = mat2[1,2]+total_y*scale_factor
frame2= cv2.warpAffine(frame, mat2, (scr_width,scr_height) )
mask2 = cv2.warpAffine(mask, mat2, (scr_width,scr_height) )
ret, mask2 = cv2.threshold(mask2, 254, 255, cv2.THRESH_BINARY)
mask3 = cv2.erode(mask2, numpy.ones((20,200),numpy.uint8)) # strip off the potentially-badlooking edges. left/right borders are darkened, strip them off
mask4 = cv2.erode(mask2, numpy.ones((1,1),numpy.uint8))
screencontent = cv2.bitwise_and(screencontent,screencontent, mask=cv2.bitwise_not(mask3)) # blank out
screencontent = cv2.add(screencontent, cv2.bitwise_and(frame2,frame2,mask=mask3)) # and redraw
screencontent2=screencontent.copy()
screencontent2=cv2.bitwise_and(screencontent2,screencontent2, mask=cv2.bitwise_not(mask4))
screencontent2=cv2.add(screencontent2, cv2.bitwise_and(frame2,frame2,mask=mask4))
cv2.imshow('frame', frame)
cv2.imshow('screencontent', screencontent)
cv2.imshow('screencontent2', screencontent2)
writer.write(screencontent2)
oldframe=frame
oldgray=gray
key = cv2.waitKey(1) & 0xFF
if key == ord("q"):
break
if key == ord("r"):
total_angle=0.
total_x=700
total_y=-200
screencontent = numpy.zeros((scr_height, scr_width,3), numpy.uint8)
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