nr_projections = 15
src = "/home/andrei/low-dose/DATASET-REGULARIZED/"
dest = "/home/andrei/low-dose/DATASET-256 LOW-DOSE/"
new_dest = os.path.join(dest, "{}_projections/".format(nr_projections))
try:
os.mkdir(new_dest)
data = DataInterface(src)
scans = data.get_tomo_list()
t = 0
for x in scans:
vol = data.get_tomo_volume(x)
ct = ConeBeamCT(vol)
rec = ct.run_new_scan(nr_projections)
maxim = rec.max()
_, _, z = rec.shape
for slice in range(z):
im = rec[:, :, slice]
# print(im[150])
# im = (normalize.normalize(im))
# im *= 255 / maxim
# print(skimage.img_as_ubyte(im)* m)
# io.imsave(os.path.join(new_dest, "Tomo_{}_slice_{}.png".format(str(x).zfill(3),str(slice).zfill(3))), skimage.img_as_ubyte(im)* maxim)
# im = np.round((im + 1) * 255 / 2)
# im = im.astype(np.uin)
transform = pp.QuantileTransformer(random_state=0)
astra.algorithm.run(alg_id)
rec = astra.data3d.get(rec_id)
astra.algorithm.delete(alg_id)
astra.data3d.delete(rec_id)
astra.data3d.delete(proj_id)
return rec
if __name__ == "__main__":
import pylab
from DataInterface import DataInterface
src = "/home/andrei/Área de Trabalho/Pesquisa/DATASET-256/"
dataset = DataInterface(src)
vol = dataset.get_tomo_volume(90)
ct = ConeBeamCT(vol)
rec = ct.run_new_scan(15)
pylab.gray()
pylab.figure(1)
pylab.imshow(vol[:, :, 128])
pylab.figure(2)
pylab.imshow(rec[:, :, 128])
pylab.show()
