LichtFeld-Studio安装记录

https://github.com/MrNeRF/LichtFeld-Studio

docker pull ubuntu:24.04

安装 GPU 支持的 Docker 运行时

如果没有安装docker container 对应的gpu支持，可以先按照以下步骤进行

• 添加 NVIDIA Container Toolkit 仓库

curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list |   sed 's#deb https://deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' |   sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list

sudo apt update

• 安装运行时支持

sudo apt install -y nvidia-container-toolkit

• 配置 Docker 使用它

sudo nvidia-ctk runtime configure --runtime=docker
sudo systemctl restart docker

• 测试 GPU 是否可见

docker run --rm --gpus all nvidia/cuda:12.8.0-base-ubuntu24.04 nvidia-smi

运行docker

docker run -it --gpus all --name LichtFeld-build \
    -v $(pwd):/workspace \
    nvidia/cuda:12.8.0-develop-ubuntu24.04 /bin/bash

1️⃣ 进入容器后，更新系统并安装基础工具

apt update && apt upgrade -y
apt install -y build-essential gcc-14 g++-14 cmake ninja-build git wget unzip python3 python3-pip

2️⃣ 安装 vcpkg（依赖管理）

cd /workspace  # 你的挂载目录
git clone https://github.com/microsoft/vcpkg.git
cd vcpkg
./bootstrap-vcpkg.sh

3️⃣ 安装 LibTorch 2.7.0（CUDA 12.8 版本）

mkdir -p /opt/libtorch && cd /opt/libtorch
wget https://download.pytorch.org/libtorch/cu128/libtorch-cxx11-abi-shared-with-deps-2.7.0%2Bcu128.zip
unzip libtorch-cxx11-abi-shared-with-deps-2.7.0+cu128.zip

4️⃣ 克隆 LichtFeld Studio 并创建构建目录

cd /workspace
git clone https://github.com/MrNeRF/LichtFeld-Studio.git
cd LichtFeld-Studio
mkdir build && cd build

5️⃣ 编译 LichtFeld Studio

cmake .. -DCMAKE_C_COMPILER=gcc-14 -DCMAKE_CXX_COMPILER=g++-14 \
         -DCMAKE_PREFIX_PATH=/opt/libtorch \
         -DCMAKE_TOOLCHAIN_FILE=/workspace/vcpkg/scripts/buildsystems/vcpkg.cmake
make -j$(nproc)