How to run only dmtet without initialization from nerf #36
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giving error
Traceback (most recent call last):
File "/home/jupyter/Magic123/main.py", line 622, in
trainer.train(train_loader, valid_loader, test_loader, max_epoch)
File "/home/jupyter/Magic123/nerf/utils.py", line 1049, in train
self.train_one_epoch(train_loader, max_epochs)
File "/home/jupyter/Magic123/nerf/utils.py", line 1278, in train_one_epoch
loss, losses_dict, outputs = self.train_step(data)
File "/home/jupyter/Magic123/nerf/utils.py", line 645, in train_step
outputs = self.model.render(rays_o, rays_d, mvp, H, W, staged=False, perturb=True, bg_color=bg_color, ambient_ratio=ambient_ratio, shading=shading, binarize=binarize)
File "/home/jupyter/Magic123/nerf/renderer.py", line 1521, in render
results = self.run_dmtet(rays_o, rays_d, mvp, h, w, **kwargs)
File "/home/jupyter/Magic123/nerf/renderer.py", line 1264, in run_dmtet
rast, rast_db = dr.rasterize(self.glctx, verts_clip, faces, (h, w))
File "/home/jupyter/Magic123/venv_magic123/lib/python3.10/site-packages/nvdiffrast/torch/ops.py", line 310, in rasterize
return _rasterize_func.apply(glctx, pos, tri, resolution, ranges, grad_db, -1)
File "/home/jupyter/Magic123/venv_magic123/lib/python3.10/site-packages/torch/autograd/function.py", line 506, in apply
return super().apply(*args, **kwargs) # type: ignore[misc]
File "/home/jupyter/Magic123/venv_magic123/lib/python3.10/site-packages/nvdiffrast/torch/ops.py", line 248, in forward
out, out_db = _get_plugin().rasterize_fwd_cuda(raster_ctx.cpp_wrapper, pos, tri, resolution, ranges, peeling_idx)
RuntimeError: instance mode - pos must have shape [>0, >0, 4]
Not the focus of this work. Thanks. You can look at the code of Fantansia3D.