Closed artursahak closed 2 years ago
Hi, could you try to reduce the number of faces in the remeshed OBJ files? I modified a bit weeks ago in geometric_proc/compute_pretrain_attn.py . Take a look at Line 209-210
if subsampling:
mesh = mesh.simplify_quadric_decimation(3000)
You can do similar things here. In general, this is because your remeshed OBJ file has too many faces. I will also modify here when I have more time.
Yes, thank you. I manually updated models with meshlab to contain 3000 faces.
In the meantime I have an invalid literal int for files in train folder after gen_dataset.py worked.
File "C:\JavaTemp\RigNet\datasets\skeleton_dataset.py", line 107, in process name = int(v_filename.split('/')[-1].split('_')[0]) ValueError: invalid literal for int() with base 10: 'C:\\JavaTemp\\Dataset\\train\\1'
Would be great to hear your advice.
In addition to that the rigs are "mixamo" rigs. Can it affect anyhow the result and spawn the error?
Instead of ".split('/')", you may need ".split('\')", also check the value of "vfilename.split('/')[-1].split('')[0]". You can modify the code to adapt to your path. I didn't try mixamo data on rignet before. I assume you might need to tune the threshold to for it.
Thank you very much, all the files are organized and trained, but there is another issue which I am working hard on(opened an issue :D).
Dear zhan-xu, I tried to run compute_volumetric_geodesic.py on my own dataset(much like the preprocessed folder you have), but here is my issue. Unable to allocate 76.2 GiB for an array with shape (1136630306, 3, 3)