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README.md

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@@ -78,6 +78,32 @@ cmake -GNinja -DCMAKE_PREFIX_PATH=/path/to/libtorch/ -DGPU_RUNTIME="HIP" -DHIP_R
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jinja
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```
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### Windows
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There's several ways to build on Windows, but this particular configuration has been confirmed to work:
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* Visual Studio 2022 C++
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* https://github.com/Kitware/CMake/releases/download/v3.28.3/cmake-3.28.3-windows-x86_64.msi
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* https://developer.download.nvidia.com/compute/cuda/11.8.0/network_installers/cuda_11.8.0_windows_network.exe
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* https://download.pytorch.org/libtorch/cu118/libtorch-win-shared-with-deps-2.1.2%2Bcu118.zip
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* https://github.com/opencv/opencv/releases/download/4.9.0/opencv-4.9.0-windows.exe
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Then run:
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```console
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"C:/Program Files/Microsoft Visual Studio/2022/Community/VC/Auxiliary/Build/vcvars64.bat"
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git clone https://github.com/pierotofy/OpenSplat OpenSplat
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cd OpenSplat
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mkdir build && cd build
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cmake -DCMAKE_PREFIX_PATH=C:/path_to/libtorch_2.1.2_cu11.8 -DOPENCV_DIR=C:/path_to/OpenCV_4.9.0/build -DCMAKE_BUILD_TYPE=Release ..
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cmake --build . --config Release
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```
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Optional: Edit cuda target (only if required) before `cmake --build .`
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C:/path_to/OpenSplat/build/gsplat.vcxproj
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for example: arch=compute_75,code=sm_75
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## Docker Build
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### CUDA

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