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

n = 256
name = "NtToolBox/src/data/hibiscus.png"
f = load_image(name, n, 1)
imageplot(f);

slex = 19:23
sely = 62:66
floor(255*f[19:24,62:66]);

sub = (l, k) -> l[collect(i for i in 1:length(l[:, 1]) if (i - 1 )%k == 0), collect(i for i in 1:length(l[1, :]) if (i - 1 )%k == 0)]

imageplot(sub(f, 4))

klist = [2, 4, 8, 16]
clf
for i in 1:length(klist)
    k = klist[i]
    imageplot( sub(f,k), string("1 ligne/ colonne sur ", string(k)), [2, 2, i])
end

quant = (l,q) -> (round(q*rescale(f, 1e-3, 1 - 1e-3) - 1/2) + 1/2)/q
imageplot(quant(f,4), "4 niveaux de gris")

qlist = [16, 4, 3, 2]
for i in 1:length(qlist)
    q = qlist[i]
    f1 = quant(f,q)
    f1[1] = 0
    f1[2] = 1
    imageplot(f1, string(string(q), " niveaux de gris"), [2, 2, i])
end

name = "NtToolBox/src/data/boat.png"
f = load_image(name, n)
sigma = .08
f = f + randn(n,n)*sigma
imageplot(clamP(f)) #We wrote clamP instead of clamp, because there is already a function clamp in module Base.

roll2d = (f, i, j) -> circshift(f, (i, j))
function filt_moy(f, k)
    n = size(f)[1]
    g = zeros(n, n)
    for i in -k:k
        for j in -k:k
            g = g + roll2d(f, i, j)
        end
    end
    return g/((2*k + 1)^2)
end
imageplot(clamP(f), "Image bruitée", [1, 2, 1])
imageplot(clamP(filt_moy(f, 1)), "Image moyennée", [1, 2, 2])

klist = [1, 2, 3, 4]
for i in 1:length(klist)
    k = klist[i]
    f1 = filt_moy(f, k)
    imageplot(clamP(f1), string("Moyenne de ", string((2*k+1)^2), " pixels"), [2, 2, i])
end

function filt_med(f, k)
    n = size(f)[1]
    g = zeros(n, n, (2*k+1)^2)
    s = 1
    for i in -k:k
        for j in -k:k
            g[:,:,s] = roll2d(f, i, j)
            s = s+1
        end
    end
    return median(g, 3)[:, :]
end
imageplot(clamP(filt_moy(f, 1)), "Moyenne de 9 nombres", [1, 2, 1])
imageplot(clamP(filt_med(f, 1)), "Médiane de 9 nombres", [1, 2, 2])

klist = [1, 2, 3, 4]
for i in 1:length(klist)
    k = klist[i]
    f1 = filt_med(f, k)
    imageplot(clamP(f1), string("Médiane de ", string((2*k + 1)^2), " pixels"), [2, 2, i])
end

n = 256
name = "NtToolBox/src/data/hibiscus.png"
f = load_image(name, n);

edge = f -> sqrt( (roll2d(f, +1, 0) - roll2d(f, -1, 0)).^2 + (roll2d(f, 0, +1) - roll2d(f, 0, -1)).^2 )

imageplot(f, "Image", [1, 2, 1])
imageplot(edge(f), L"Carte de $\ell$", [1, 2, 2])
On peut voir que dans l'image de droite, les contours des objets
ressortent en blanc, car ils correspondent aux grandes valeurs de $\ell$.
n = 256
name = "NtToolBox/src/data/hibiscus.png"
f = load_image(name, n, 0, 1);

f1 = copy(f)
f1[:,:, [2, 3]] = 0

f2 = copy(f)
f2[:,:, [1, 3]] = 0

f3 = copy(f)
f3[:,:, [1, 2]] = 0;

imageplot(f, "Image couleur", [2, 2, 1])
imageplot(f1, "Canal rouge", [2, 2, 2])
imageplot(f2, "Canal vert", [2, 2, 3])
imageplot(f3, "Canal bleu", [2, 2, 4])

imageplot(f, "Couleur", [1, 2, 1])
imageplot(sum(f, 3)[:, :], "Luminance", [1, 2, 2])

f1 = copy(f)
f1[:, :, [2,3]] = 1

f2 = copy(f)
f2[:, :, [1,3]] = 1

f3 = copy(f)
f3[:, :, [1,2]] = 1;

imageplot(f, "Image couleur", [2, 2, 1])
imageplot(f1, "Canal cyan", [2, 2, 2])
imageplot(f2, "Canal magenta", [2, 2, 3])
imageplot(f3, "Canal jaune", [2, 2, 4])

n = 256
name = "NtToolBox/src/data/hibiscus.png"
f = load_image(name, n);

imageplot(-f)

imageplot(f.^2, "Carré")

imageplot(sqrt(f), L"Remplacement de a par $\sqrt{a}$")

name = "NtToolBox/src/data/hibiscus.png"
f = load_image(name, n, 0, 1);

function repeat3(x, k)
    if (ndims(x) == 3) & (size(x)[3] == 3)
        x1 = Images.imresize( repeat(x[:, :, 1], inner = [1, k]), (n, n) )
        x2 = Images.imresize( repeat(x[:, :, 2], inner = [1, k]), (n, n) )
        x3 = Images.imresize( repeat(x[:, :, 3], inner = [1, k]), (n, n) )
        l = zeros(n, n, 3)
        l[:, :, 1] = x1
        l[:, :, 2] = x2
        l[:, :, 3] = x3
        return l
    else
        return Images.imresize( repeat(x[:, :], inner = [1, k]), (n, n) )
    end
end

m = f -> repeat3( mean(f, 3), 3)
function contrast_image(f, gamma)
    f1 = clamP(m(f).^gamma + f[:, :, 1] - m(f))
    f2 = clamP(m(f).^gamma + f[:, :, 2] - m(f))
    f3 = clamP(m(f).^gamma + f[:, :, 3] - m(f))
    l = zeros(length(f[:, 1, 1]), length(f[:, 1, 1]), 3)
    l[:, :, 1] = f1
    l[:, :, 2] = f2
    l[:, :, 3] = f3
    return l
end

gamma_list = [.5, .75, 1, 1.5, 2, 3]
for i in 1:length(gamma_list)
   gamma = gamma_list[i]
    subplot(2, 3, i)
    imageplot(contrast_image(f, gamma));
    title(string(L"$\gamma$ = ", string(gamma)))
end

name = "NtToolBox/src/data/flowers.png"
n = 502
A = load_image(name, n, 0, 1)

B1 = A[:, :, 1]'; B2 = A[:, :, 2]'; B3 = A[:, :, 3]'
B = zeros(n, n, 3)
B[:, :, 1] = B1; B[:, :, 2] = B2; B[:, :, 3] = B3
imageplot(A, "Image A", [1,2,1])
imageplot(B, "Image B", [1,2,2])

C = A
C = C[end:-1:1, :, :]

C1 = C[:, :, 1]'; C2 = C[:, :, 2]'; C3 = C[:, :, 3]'
C = zeros(n, n, 3)
C[:, :, 1] = C1; C[:, :, 2] = C2; C[:, :, 3] = C3

imageplot(A, "Image A", [1,2,1])
imageplot(C, "Image C", [1,2,2])

name1 = "NtToolBox/src/data/flowers.png"
name2 = "NtToolBox/src/data/hibiscus.png"
n = 502
A = load_image(name1, n, 0, 1)
B = load_image(name2, n, 0, 1)
imageplot(A, "Image A", [1,2,1])
imageplot(B, "Image B", [1,2,2])

p = 6
t = linspace(0, 1, p)
for i in 1:p
    imageplot(t[i]*A + (1-t[i])*B, string("t = ", string(t[i])), [2, p/2, i])
end
<script>
  $(document).ready(function(){
      $('div.prompt').hide();
  });
</script>