using PyPlot
using NtToolBox
# using Autoreload
# arequire("NtToolBox")

# include("NtToolBox/src/ndgrid.jl")
n = 200
(Y, X) = meshgrid(collect(1:n), collect(1:n));

r = n/3.;

c = [r, r] .+ 10;

phi1 = sqrt((X .- c[1]).^2 + (Y .- c[2]).^2) - r;

include("NtSolutions/segmentation_3_snakes_levelset/exo1.jl");

## Insert your code here.

figure(figsize = (10,5))

subplot(1,2,1)
NtToolBox.plot_levelset(phi1)

subplot(1,2,2)
NtToolBox.plot_levelset(phi2)

include("NtSolutions/segmentation_3_snakes_levelset/exo2.jl")

## Insert your code here.

Tmax = 200;

tau = .5;

niter = Int(Tmax/tau);

phi = copy(phi0);

g0 = NtToolBox.Grad(phi, "sym", 2);

d = max(eps().*ones(n, n), sqrt(sum(g0.^2, 3)));

g = g0./cat(3, d[:, :], d[:, :]);

K = - d.*NtToolBox.Div(g[:, :, 1], g[:, :, 2], "sym", 2);

phi = phi - tau.*K;

include("NtSolutions/segmentation_3_snakes_levelset/exo3.jl")

## Insert your code here.

phi = phi0.^3;

include("NtToolBox/src/perform_fast_marching.jl")
include("NtToolBox/src/perform_redistancing.jl")

phi1 = perform_redistancing(phi0);

figure(figsize = (10, 5))

subplot(1, 2, 1)
plot_levelset(phi)
title("Before redistancing")

subplot(1, 2, 2)
plot_levelset(phi1)
title("After redistancing")

show()

n = 200;

f0 = NtToolBox.rescale(NtToolBox.load_image("NtToolBox/src/data/cortex.png", n));

g = NtToolBox.Grad(f0, "sym", 2)
d0 = sqrt(sum(g.^2, 3));

a = 5;

d = NtToolBox.perform_blurring(d0[:, :, 1], [a], "per");

epsilon = 1e-1;

W = 1./(epsilon + d)
W = NtToolBox.rescale(-d, 0.1, 1);

figure(figsize = (10, 5))
NtToolBox.imageplot(f0, "Image to segment", [1, 2, 1])
NtToolBox.imageplot(W, "Weight", [1, 2, 2])

include("NtSolutions/segmentation_3_snakes_levelset/exo4.jl");

## Insert your code here.

figure(figsize = (5, 5))
NtToolBox.plot_levelset(phi0, 0, f0)

tau = .4;

Tmax = 1500
niter = Int(Tmax/tau);

phi = copy(phi0);

gW = NtToolBox.Grad(W, "sym", 2);

include("NtSolutions/segmentation_3_snakes_levelset/exo5.jl");

## Insert your code here.

phi = phi - tau*G;

phi = perform_redistancing(phi[:, :]);

# run -i nt_solutions/segmentation_3_snakes_levelset/exo6

include("NtSolutions/segmentation_3_snakes_levelset/exo6.jl")

# figure(figsize = (10, 10))
# phi = copy(phi0)
# k = 0
# gW = NtToolBox.Grad(W, "sym", 2)

# for i in 1 : niter
#     gD = NtToolBox.Grad(phi, "sym", 2)
#     d = max(eps().*ones(n, n), sqrt(sum(g0.^2, 3)))
#     g = gD./cat(3, d[:, :], d[:, :])
#     G = W.*(d.*NtToolBox.Div(g[:, :, 1], g[:, :, 2], "sym", 2)) + sum(gW.*gD, 3)
#     phi = (phi + tau.*G)[:, :]
#     if i % 30 == 0
#         phi = NtToolBox.perform_redistancing(phi)
#     end
#     if i % Base.div(niter, 4.) == 0
#         k = k + 1
#         subplot(2, 2, k)
#         NtToolBox.plot_levelset(phi, 0, f0)
#     end
# end




## Insert your code here.

include("NtSolutions/segmentation_3_snakes_levelset/exo7.jl")

## Insert your code here.

lambd = 2;

c1 = .7
c2 = 0;

tau = .5;

Tmax = 100
niter = Int(Tmax/ tau);

phi = copy(phi0);

include("NtSolutions/segmentation_3_snakes_levelset/exo8.jl");

## Insert your code here.

phi = phi + tau*G;

include("NtSolutions/segmentation_3_snakes_levelset/exo9.jl")

## Insert your code here.
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