def AugmentImage(img):
#The following does not utilize the global variables and was made before
#the optimisation for live augmentation.
I1 = cv2.imread("pattern.png")
I2 = img
I1Gray = cv2.cvtColor(I1,cv2.COLOR_RGB2GRAY)
I2Gray = cv2.cvtColor(img,cv2.COLOR_RGB2GRAY)
I1Corners = getCornerCoords(I1Gray)
I2Corners = getCornerCoords(I2Gray)
H = estimateHomography(I1Corners, I2Corners)
K, dist_coefs = calibrate.loadMatrixes()
box = cube_points((0,0,0),0.3)
#This is K * [I | O]
cam1 = Camera(hstack((K,dot(K,array([[0],[0],[-1]])) )) )
# compute second camera matrix from cam1.
cam2 = Camera(dot(H,cam1.P))
#isolates the [Rotation | translation] (extrinsic parameters)
A = dot(linalg.inv(K),cam2.P[:,:3])
#estimate z axis from cross product.
A = array([A[:,0],A[:,1],np.cross(A[:,0],A[:,1],axis=0)]).T
#add K again
cam2.P[:,:3] = np.dot(K,A[0])
# project with the second camera
box_cam2 = np.array(cam2.project(toHomogenious(box)))
figure()
imshow(I2)
plot(box_cam2[0,:],box_cam2[1,:],linewidth=3)
show()
__author__ = 'Roed, Ghurt, Stoffi'
import calibrationExample as calibrate
import numpy as np
from SIGBToolsForSecond import *
import cv2
import cv
global K, dist_coefs, I1, I1Corners, box, cam1
I1 = cv2.imread("pattern.png")
I1Gray = cv2.cvtColor(I1,cv2.COLOR_RGB2GRAY)
K, dist_coefs = calibrate.loadMatrixes()
def cube_points(c,wid):
""" Creates a list of points for plotting a cube with plot. (the first 5 points are
the bottom square, some sides repeated). """
p = []
#bottom
p.append([c[0]-wid,c[1]-wid,c[2]-wid])
p.append([c[0]-wid,c[1]+wid,c[2]-wid])
p.append([c[0]+wid,c[1]+wid,c[2]-wid])
p.append([c[0]+wid,c[1]-wid,c[2]-wid])
p.append([c[0]-wid,c[1]-wid,c[2]-wid])
#top
p.append([c[0]-wid,c[1]-wid,c[2]+wid])
p.append([c[0]-wid,c[1]+wid,c[2]+wid])
p.append([c[0]+wid,c[1]+wid,c[2]+wid])
p.append([c[0]+wid,c[1]-wid,c[2]+wid])
p.append([c[0]-wid,c[1]-wid,c[2]+wid])
