from utils import get_points_from_img,get_elements

from SC import SC

import cv2 as cv

from numpy import *

import sys

if __name__ == '__main__':

import sys

def make_graph(P1,P2,COST,LINES):

pylab.show()

a = SC(r_outer=2)

sampls = 30

imgs = get_elements('test.png')

points1,t1 = get_points_from_img('9M.png',simpleto=sampls)

P = a.compute(points1)

x1 = [p[0] for p in points1]

y1 = [400-p[1] for p in points1]

for i,img in enumerate(imgs):

cv.imshow('Preview - %s' % i,img)

cv.waitKey(0)

sys.exit()

for img in imgs:

cv.imshow('Preview2',img)

cv.waitKey(0)

points2,t2 = get_points_from_img(img,simpleto=sampls)

if points2:

Q = a.compute(points2)

x2 = [p[0] for p in points2]

y2 = [400-p[1] for p in points2]

COST,indexes = a.diff(Q,P)

# getting correspoding points arrays for interpolation

pp = []

qp = []

for i,k in indexes:

qp.append(points2[i])

pp.append(points1[k])

fx,fy,diff,affcost = a.interpolate(qp,pp)

x3 = [fx(p[0]) for p in points2]

y3 = [400-fy(p[1]) for p in points2]

LINES = []

for q1,p1 in indexes:

LINES.append([[points1[p1][0],400-points1[p1][1]],[points2[q1][0],400-points2[q1][1]]])

polarity_flag = 1

ori_weight = 0.1

costmat_shape = a.cost(Q,P)

theta_diff = kron(ones((1,sampls)),t1) - kron(ones((sampls,1)),t2.H)

if polarity_flag:

# use edge polarity

costmat_theta=0.5*(1-cos(theta_diff))

else:

# ignore edge polarity

costmat_theta=0.5*(1-cos(2*theta_diff))

print(costmat_shape.shape,costmat_theta.shape)

costmat=(1-ori_weight)*costmat_shape+ori_weight*costmat_theta;

a1=costmat.min(0)

a2=costmat.min(1)

sc_cost=max(mean(a1),mean(a2));

print("Shape cost: %s\nBending energy: %s\nAffine Cost: %s\n" % (sc_cost,diff,affcost))

TOTAL = 0.1*diff+sc_cost+0.3*affcost

print('TOTAL MATCH:',TOTAL)

make_graph((x1,y1),(x2,y2),TOTAL,LINES)

#make_graph((x1,y1),(x2,y2),COST,LINES)

#make_graph((x1,y1),(x3,y3),diff)