UniqAI/gaussian-splatting
1
0
Fork 0
mirror of https://github.com/graphdeco-inria/gaussian-splatting synced 2024-11-22 00:08:02 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity

added missing parameters for remote viewer

Browse Source
This commit is contained in:
alanvinx 2024-10-24 17:14:43 +02:00
parent 182afc95b2
commit dd795e2e15
1 changed files with 1 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
train.py
View File

@ -78,7 +78,7 @@ def training(dataset, opt, pipe, testing_iterations, saving_iterations, checkpoi
net_image_bytes = None net_image_bytes = None
custom_cam, do_training, pipe.convert_SHs_python, pipe.compute_cov3D_python, keep_alive, scaling_modifer = network_gui.receive() custom_cam, do_training, pipe.convert_SHs_python, pipe.compute_cov3D_python, keep_alive, scaling_modifer = network_gui.receive()
if custom_cam != None: if custom_cam != None:
net_image = render(custom_cam, gaussians, pipe, background, scaling_modifer)["render"] net_image = render(custom_cam, gaussians, pipe, background, scaling_modifier=scaling_modifer, use_trained_exp=dataset.train_test_exp, separate_sh=SPARSE_ADAM_AVAILABLE)["render"]
net_image_bytes = memoryview((torch.clamp(net_image, min=0, max=1.0) * 255).byte().permute(1, 2, 0).contiguous().cpu().numpy()) net_image_bytes = memoryview((torch.clamp(net_image, min=0, max=1.0) * 255).byte().permute(1, 2, 0).contiguous().cpu().numpy())
network_gui.send(net_image_bytes, dataset.source_path) network_gui.send(net_image_bytes, dataset.source_path)
if do_training and ((iteration < int(opt.iterations)) or not keep_alive): if do_training and ((iteration < int(opt.iterations)) or not keep_alive):