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https://github.com/graphdeco-inria/gaussian-splatting
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Bumped SIBR, documentation, always save at end
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@ -71,8 +71,13 @@ Our provided install method is based on Conda package and environment management
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conda env create --file environment.yml
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conda activate gaussian_splatting
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```
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Note for Windows: if setup stops and you are prompted to set ```DISTUTILS_USE_SDK=1```, please complete the environment setup with:
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```shell
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SET DISTUTILS_USE_SDK=1
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conda env update --file environment.yml
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```
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Note that downloading packages and creating a new environment with Conda can require a significant amount of disk space. By default, Conda will use the main system hard drive. You can avoid this by specifying a different package download location and an environment on a different drive:
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Tip: Downloading packages and creating a new environment with Conda can require a significant amount of disk space. By default, Conda will use the main system hard drive. You can avoid this by specifying a different package download location and an environment on a different drive:
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```shell
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conda config --add pkgs_dirs <Drive>/<pkg_path>
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@ -1 +1 @@
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Subproject commit eb1b8513ecc0cdb1dfbd9dae4e0fe64c9dcef2ab
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Subproject commit 0a1620ace38f1d26e685312a533cc95064902c15
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train.py
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train.py
@ -180,6 +180,8 @@ if __name__ == "__main__":
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parser.add_argument("--save_iterations", nargs="+", type=int, default=[7_000, 30_000])
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parser.add_argument("--quiet", action="store_true")
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args = parser.parse_args(sys.argv[1:])
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args.save_iterations.append(args.iterations)
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print("Optimizing " + args.model_path)
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# Initialize system state (RNG)
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