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https://github.com/graphdeco-inria/gaussian-splatting
synced 2024-11-25 13:26:47 +00:00
Random background flag added
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414b553ef1
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@ -86,6 +86,7 @@ class OptimizationParams(ParamGroup):
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self.densify_from_iter = 500
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self.densify_from_iter = 500
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self.densify_until_iter = 15_000
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self.densify_until_iter = 15_000
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self.densify_grad_threshold = 0.0002
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self.densify_grad_threshold = 0.0002
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self.random_background = False
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super().__init__(parser, "Optimization Parameters")
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super().__init__(parser, "Optimization Parameters")
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def get_combined_args(parser : ArgumentParser):
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def get_combined_args(parser : ArgumentParser):
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5
train.py
5
train.py
@ -80,7 +80,10 @@ def training(dataset, opt, pipe, testing_iterations, saving_iterations, checkpoi
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# Render
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# Render
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if (iteration - 1) == debug_from:
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if (iteration - 1) == debug_from:
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pipe.debug = True
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pipe.debug = True
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render_pkg = render(viewpoint_cam, gaussians, pipe, background)
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bg = torch.rand((3), device="cuda") if opt.random_background else background
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render_pkg = render(viewpoint_cam, gaussians, pipe, bg)
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image, viewspace_point_tensor, visibility_filter, radii = render_pkg["render"], render_pkg["viewspace_points"], render_pkg["visibility_filter"], render_pkg["radii"]
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image, viewspace_point_tensor, visibility_filter, radii = render_pkg["render"], render_pkg["viewspace_points"], render_pkg["visibility_filter"], render_pkg["radii"]
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# Loss
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# Loss
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