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import numpy as np
import scipy.misc
import mcubes
import argparse
from sklearn.neighbors import NearestNeighbors
parser = argparse.ArgumentParser(description='Visualise the 3D volume')
parser.add_argument('--image', dest='image',
help="The background image to display")
parser.add_argument('--volume', dest='volume',
help="The volume to render")
parser.add_argument('--obj', dest='obj',
help="The file path of the object")
args = parser.parse_args()
im = scipy.misc.imread(args.image, False, 'RGB')
vol = np.fromfile(args.volume, dtype=np.int8)
vol = vol.reshape((200,192,192))
vol = vol.astype(float)
vertices, triangles = mcubes.marching_cubes(vol, 10)
vertices = vertices[:,(2,1,0)]
vertices[:,2] *= 0.5 # scale the Z component correctly
r = im[:,:,0].flatten()
g = im[:,:,1].flatten()
b = im[:,:,2].flatten()
vcx,vcy = np.meshgrid(np.arange(0,192),np.arange(0,192))
vcx = vcx.flatten()
vcy = vcy.flatten()
vc = np.vstack((vcx, vcy, r, g, b)).transpose()
neigh = NearestNeighbors(n_neighbors=1)[:,:2])
n = neigh.kneighbors(vertices[:,(0,1)], return_distance=False)
colour = vc[n,2:].reshape((vertices.shape[0],3)).astype(float) / 255
vc = np.hstack((vertices, colour))
with open(args.obj, 'w') as f:
for v in range(0,vc.shape[0]):
f.write('v %0.2f %0.2f %0.2f %0.2f %0.2f %0.2f\n' % (vc[v,0],vc[v,1],vc[v,2],vc[v,3],vc[v,4],vc[v,5]))
for t in range(0,triangles.shape[0]):
f.write('f {} {} {}\n'.format(*triangles[t,:]+1))
print('Calculated the isosurface.')
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