Added Dockerfile and requirement#139
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requirements doesn't setup sufficient cuda environment, and may lead to miss understanding for new developers. I would suggest write it in the dockerfile or use a |
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@tauzn-clock here is a version that uses CUDA 11.7 and puts the requirements inside the Dockerfile to avoid confusion for new developers: FROM nvidia/cuda:11.7.1-devel-ubuntu20.04
ENV DEBIAN_FRONTEND=noninteractive
ENV DISPLAY=:0
ENV TORCH_CUDA_ARCH_LIST="7.0;7.5;8.0;8.6"
ENV NVIDIA_DRIVER_CAPABILITIES="all"
RUN apt-get update && apt-get install -y \
lsb-release \
wget \
ffmpeg \
libsm6 \
libxext6 \
freeglut3-dev \
mesa-utils \
libxmu-dev \
libxi-dev \
git \
python3 \
python3-dev \
python3-pip \
libc6 \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
RUN git clone https://github.com/tauzn-clock/MonoGS/ --recursive
WORKDIR /MonoGS
RUN pip install --upgrade pip
RUN pip install torchaudio --index-url https://download.pytorch.org/whl/cu117
RUN pip install torchvision --index-url https://download.pytorch.org/whl/cu117
RUN pip install torch --index-url https://download.pytorch.org/whl/cu117
RUN pip install --default-timeout=600 \
torchmetrics==1.4.1 \
opencv-python==4.8.1.78 \
munch==4.0.0 \
trimesh==4.4.7 \
evo==1.11.0 \
open3d==0.18.0 \
imgviz==1.7.5 \
PyOpenGL==3.1.7 \
glfw==2.7.0 \
PyGLM==2.7.1 \
wandb==0.17.8 \
lpips==0.1.4 \
rich==13.8.0 \
ruff==0.6.2 \
plyfile==1.0.3
# Building the submodules requires ninja
RUN pip install ninja --upgrade
RUN pip install submodules/diff-gaussian-rasterization
RUN pip install submodules/simple-knn |
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I have updated this further at #183 so I think this PR 139 should be closed without merging. |
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To help those who wants to play with the repo, I have added a working Dockerfile and requirement.txt for pip install.
Note that the repo needs to be updated before merging.