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8d5502db1a
* pixi installation optiont * chore: Update .gitignore to include /third_party and include pixi lock file * feat: Update download and training commands for dozer data The commit updates the download and training commands for the dozer data in the `pixi.toml` file. It renames the `download-sample-data` command to `download-dozer-data` and modifies the `train-example-splat` and `train-example-nerf` commands to include the dozer data as a dependency. This makes it easy to run an example training for both nerfacto and splatfacto * update to include range between 3.8 -3.10 * Add Pixi installation instructions to the installation.md file --------- Co-authored-by: maturk <30566358+maturk@users.noreply.github.com>
37 lines
1.8 KiB
TOML
37 lines
1.8 KiB
TOML
[project]
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name = "nerfstudio"
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version = "1.0.3"
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description = "All-in-one repository for state-of-the-art NeRFs"
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channels = ["nvidia/label/cuda-11.8.0", "nvidia", "conda-forge", "pytorch"]
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platforms = ["linux-64"]
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[system-requirements]
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libc = { family="glibc", version="2.30" }
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[tasks]
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# || operator in pixi allows running a command after only if the command before || fails
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tcnn-install = "python -c 'import tinycudann as tcnn' || python -m pip install ninja git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch"
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make-third_party-dir = {cmd="ls third_party || mkdir third_party"}
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clone-hloc = {cmd="ls Hierarchical-Localization || git clone --recursive https://github.com/cvg/Hierarchical-Localization/", cwd = "third_party", depends_on=["make-third_party-dir"] }
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hloc-install = {cmd="python -m pip install -e .", cwd = "third_party/Hierarchical-Localization" , depends_on=["clone-hloc"], outputs=["third_party/Hierarchical-Localization/hloc.egg-info/PKG-INFO"]}
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post-install = {cmd="pwd", depends_on=["hloc-install", "tcnn-install"]}
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download-dozer-data = {cmd="ls data/nerfstudio/dozer || ns-download-data nerfstudio --capture-name dozer"}
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train-example-splat = {cmd="ns-train splatfacto --data data/nerfstudio/dozer/", depends_on=["post-install", "download-dozer-data"]}
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train-example-nerf = {cmd="ns-train nerfacto --data data/nerfstudio/dozer/", depends_on=["post-install", "download-dozer-data"]}
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[dependencies]
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python = ">=3.8,<3.11"
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pip = ">=24.0,<25"
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cuda = {version = "*", channel="nvidia/label/cuda-11.8.0"}
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pytorch-cuda = {version = "11.8.*", channel="pytorch"}
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pytorch = {version = ">=2.2.0,<2.3", channel="pytorch"}
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torchvision = {version = ">=0.17.0,<0.18", channel="pytorch"}
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pyarrow = ">=15.0.2,<15.1"
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colmap = ">=3.9.1,<3.10"
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[pypi-dependencies]
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nerfstudio = { path = ".", editable = true}
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