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https://github.com/graphdeco-inria/gaussian-splatting
synced 2024-11-22 08:18:17 +00:00
added missing parameters for remote viewer
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parent
182afc95b2
commit
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2
train.py
2
train.py
@ -78,7 +78,7 @@ def training(dataset, opt, pipe, testing_iterations, saving_iterations, checkpoi
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net_image_bytes = None
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net_image_bytes = None
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custom_cam, do_training, pipe.convert_SHs_python, pipe.compute_cov3D_python, keep_alive, scaling_modifer = network_gui.receive()
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custom_cam, do_training, pipe.convert_SHs_python, pipe.compute_cov3D_python, keep_alive, scaling_modifer = network_gui.receive()
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if custom_cam != None:
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if custom_cam != None:
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net_image = render(custom_cam, gaussians, pipe, background, scaling_modifer)["render"]
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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"]
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net_image_bytes = memoryview((torch.clamp(net_image, min=0, max=1.0) * 255).byte().permute(1, 2, 0).contiguous().cpu().numpy())
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net_image_bytes = memoryview((torch.clamp(net_image, min=0, max=1.0) * 255).byte().permute(1, 2, 0).contiguous().cpu().numpy())
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network_gui.send(net_image_bytes, dataset.source_path)
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network_gui.send(net_image_bytes, dataset.source_path)
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if do_training and ((iteration < int(opt.iterations)) or not keep_alive):
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if do_training and ((iteration < int(opt.iterations)) or not keep_alive):
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