nerfstudio-Dockerfile-p2

ARG CUDA_VERSION=11.8.0
ARG OS_VERSION=22.04
ARG USER_ID=1000
# Define base image.
FROM nerfstudio-base
ARG CUDA_VERSION
ARG OS_VERSION
ARG USER_ID

# metainformation
LABEL org.opencontainers.image.version = "0.1.18"
LABEL org.opencontainers.image.source = "https://github.com/nerfstudio-project/nerfstudio"
LABEL org.opencontainers.image.licenses = "Apache License 2.0"
LABEL org.opencontainers.image.base.name="docker.io/library/nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${OS_VERSION}"

# Variables used at build time.
## CUDA architectures, required by Colmap and tiny-cuda-nn.
## NOTE: All commonly used GPU architectures are included and supported here. To speedup the image build process remove all architectures but the one of your explicit GPU. Find details here: https://developer.nvidia.com/cuda-gpus (8.6 translates to 86 in the line below) or in the docs.
ARG CUDA_ARCHITECTURES=86

# Set environment variables.
## Set non-interactive to prevent asking for user inputs blocking image creation.
ENV DEBIAN_FRONTEND=noninteractive
## Set timezone as it is required by some packages.
ENV TZ=Europe/Berlin
## CUDA Home, required to find CUDA in some packages.
ENV CUDA_HOME="/usr/local/cuda"

# Install pixel perfect sfm.
RUN git clone --branch v1.0 --recursive https://github.com/cvg/pixel-perfect-sfm.git && \
    cd pixel-perfect-sfm && \
    sed -i "s/'-j'/'-j', '1'/g" setup.py && \
    python3.10 -m pip install -e . && \
    cd ..

RUN python3.10 -m pip install omegaconf
# Copy nerfstudio folder and give ownership to user.
ADD . /home/user/nerfstudio
USER root
RUN chown -R user /home/user/nerfstudio
USER ${USER_ID}

# Install nerfstudio dependencies.
RUN cd nerfstudio && \
    python3.10 -m pip install -e . && \
    cd ..

# Change working directory
WORKDIR /workspace

# Install nerfstudio cli auto completion
# RUN ns-install-cli --mode install

# Bash as default entrypoint.
CMD /bin/bash -l