Open tkzky opened 3 years ago
Either you take the output mesh in FLAME topology and extract the 3D landmarks from this mesh using the provided barycentric landmark embedding (you could do that by calling the function vertices2landmarks in lbs.py. The forward function in FLAME.py demonstrates how this is done during training). Another possibility is to return the landmarks2d or landmarks 3d (depending if static or dynamic face contour) as return from the self.flame function call in the decode function of deca.py. These landmarks are later projected into the image and only the projection is returned. Instead you would need to return the landmarks before projecting them into the image. Does that answer your question?
I have a good idea, use pytorch3d to show this landmarks in 3D space, you can see and draw directly, and it will show the coordinates if you hangover one landmark.
Either you take the output mesh in FLAME topology and extract the 3D landmarks from this mesh using the provided barycentric landmark embedding (you could do that by calling the function vertices2landmarks in lbs.py. The forward function in FLAME.py demonstrates how this is done during training). Another possibility is to return the landmarks2d or landmarks 3d (depending if static or dynamic face contour) as return from the self.flame function call in the decode function of deca.py. These landmarks are later projected into the image and only the projection is returned. Instead you would need to return the landmarks before projecting them into the image. Does that answer your question?
hi, i've just return the 68 keypoints from the self.flame function call in the decode function of deca.py. However, I got keypoints as follows and it seemed something went wrong.The numbers were too small and I even got minus. Do you have any ideas?
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@tkzky Hi , do you know how to solve this problem now?
Hi, thanks for making this great work open sourced. I want to know how to obtain the coordinates of 68 landmarks of the reconstructed model like (x,y,z) ? Thank you!