Animation of Artificial Images

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import warnings; warnings.filterwarnings('ignore')

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import numpy as np; from skimage import transform,io

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def randcoef():

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    a=(.5+.1**6*randint(1,999999))*choice([-1,1])

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    b=randint(3,10)

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    c=.1**3*randint(1,99)*choice([-1,1])

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    return a,b,c

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def randcoord(a,b,c):

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    t=[0,n(1/(720*b)),..,n(12*pi)]

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    f=[(sin(t0/6)+a*sin(b*t0)*cos(t0)-c*sin(16*b*t0),

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        cos(t0/6)+a*sin(b*t0)*sin(t0)-c*cos(16*b*t0)) for t0 in t]

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    return f

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def create_png(n):

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    for i in range(n):

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        a,b,c=randcoef(); f=randcoord(a,b,c)

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        p=list_plot(f,size=1,axes=False,figsize=7,aspect_ratio=1)

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        p.save('pic%d'%i+'.png')

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create_png(2)

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def load_img(file_name,img_size):

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    img=io.imread(file_name)

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    img=transform.resize(img,(img_size,img_size))

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    return img[:,:,:3]

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def interpolate_hypersphere(v1,v2,steps):

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    v1norm=np.linalg.norm(v1); v2norm=np.linalg.norm(v2)

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    v2normalized=v2*(v1norm/v2norm)

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    vectors=[]

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    for step in range(1,steps+1):

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        interpolated=v1+(v2normalized-v1)*step/steps

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        interpolated_norm=np.linalg.norm(interpolated)

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        interpolated_normalized=\

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        interpolated*(v1norm/interpolated_norm)

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        vectors.append(interpolated_normalized)

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    return np.array(vectors)

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file_name1,file_name2='pic0.png','pic1.png'

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img_size=700; steps=60

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img1=load_img(file_name1,img_size)

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img2=load_img(file_name2,img_size)

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imgs=np.vstack([interpolate_hypersphere(img1,img2,steps),

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                interpolate_hypersphere(img2,img1,steps)])

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animate([matrix_plot(

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    imgs[i],transparent=True,frame=False,

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    figsize=(4,4)) for i in range(2*steps)])

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