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Using encoder-decoder to restruct one face
locc = tf.square(y - pos)
loss_x = tf.reduce_mean(tf.multiply(locc[:, :, :, 0], m))
loss_y = tf.reduce_mean(tf.multiply(locc[:, :, :, 1], m))
loss_z = tf.reduce_mean(tf.multiply(locc[:, :, :, 2], m))
loss = loss_x + loss_y + loss_z
Hi, thank you for your contribution!!
I am using your code for training, but I did not get the ideal result. Did you get good result before?
I have trained the model to produce the model file.
Which file in the project is to load the model to produce the UV map?
I checked run_one.py and found it does not run the model at all.
from mm3d import mesh
from mm3d.morphable_model import MorphabelModel
from mm3d.morphable_model.load import load_uv_coords
these imports report errors and what's the mm3d, is that a py file? could you offer this file? Looking forward !
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