Dockerfile-neuralangelo

# docker build -f docker/Dockerfile-neuralangelo -t chenhsuanlin/neuralangelo:23.04-py3 .
# docker push chenhsuanlin/neuralangelo:23.04-py3

# FROM nvcr.io/nvidia/pytorch:23.04-py3 
FROM nvidia/cuda:11.8.0-devel-ubuntu22.04 as conda_builder
ENV DEBIAN_FRONTEND noninteractive

ARG FORCE_CUDA=1
ARG TCNN_CUDA_ARCHITECTURES=70,72,75,80,86

SHELL ["/bin/bash", "--login", "-c"]

RUN echo ttf-mscorefonts-installer msttcorefonts/accepted-mscorefonts-eula select true | debconf-set-selections
RUN --mount=type=cache,target=/var/cache/apt,sharing=private \
    --mount=type=cache,target=/var/lib/apt,sharing=private \
    --mount=type=secret,id=passwd,target=/root/.secret \
    rm -f /etc/apt/apt.conf.d/docker-clean && \
    echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' > /etc/apt/apt.conf.d/keep-cache && \
    apt-get update && \
    apt-get install -y --no-install-recommends --reinstall \
    ca-certificates \
    wget \
    sudo \
    curl \
    tree \
    vim \
    libglew-dev \
    libassimp-dev \
    libboost-all-dev \
    libgtk-3-dev \
    libopencv-dev \
    libglfw3-dev \
    libavdevice-dev \
    libavcodec-dev \
    libeigen3-dev \
    libxxf86vm-dev \
    libembree-dev \
    libboost-program-options-dev \
    libboost-filesystem-dev \
    libboost-graph-dev \
    libboost-system-dev \
    libflann-dev \
    libfreeimage-dev \
    libmetis-dev \
    libgoogle-glog-dev \
    libgtest-dev \
    libsqlite3-dev \
    qtbase5-dev \
    libqt5opengl5-dev \
    libcgal-dev \
    libceres-dev \
    gcc-10 \
    g++-10 \
    cmake \
    build-essential \
    build-essential \
    bzip2 \
    ca-certificates \
    cmake \
    curl \
    ffmpeg \
    g++ \
    git \
    libx264-dev \
    tmux \
    wget \
    ninja-build \
    git && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

# Copy Miniconda from a prebuilt image
COPY --from=continuumio/miniconda3:23.10.0-1 /opt/conda /opt/conda

# Set environment variables for Conda and CUDA
ENV PATH=/opt/conda/bin:$PATH
ENV TORCH_CUDA_ARCH_LIST="3.5;5.0;6.0;6.1;7.0;7.5;8.0;8.6+PTX"

# Update and install necessary packages, using cache mounts for efficiency
RUN --mount=type=cache,target=/var/cache/apt,sharing=private \
    --mount=type=cache,target=/var/lib/apt,sharing=private \
    rm -f /etc/apt/apt.conf.d/docker-clean && \
    echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' > /etc/apt/apt.conf.d/keep-cache && \
    apt-get update && \
    apt-get install -y build-essential

# COLMAP
RUN export CC=/usr/bin/gcc-10 && \
    export CXX=/usr/bin/g++-10 && \
    export CUDAHOSTCXX=/usr/bin/g++-10 && \
    mkdir -p /home/$USER/workspace/ && \
    cd /home/$USER/workspace/ && \
    git clone https://github.com/colmap/colmap.git && \
    cd colmap && \
    mkdir build && \
    cd build && \
    cmake .. -GNinja -DCMAKE_CUDA_ARCHITECTURES=$CMAKE_CUDA_ARCHITECTURES \
                     -DCMAKE_INSTALL_PREFIX=/colmap_installed && \
    ninja && \
    ninja install
RUN cd /home/$USER/workspace/ && \
    cp -r /colmap_installed/* /usr/local/

RUN apt-get update && apt-get install -y --no-install-recommends \
    cuda-nvrtc-11-8 \
    cuda-cudart-dev-11-8 \
    cuda-driver-dev-11-8 \
    && apt-get clean \
    && rm -rf /var/lib/apt/lists/*

# Install base Python libraries for Imaginaire
WORKDIR /neuralangelo-copy
COPY . .

FROM conda_builder
RUN conda env create --file neuralangelo.yaml
SHELL ["conda", "run", "-n", "neuralangelo", "/bin/bash", "-c"]

RUN conda install pytorch==2.2.1 torchvision==0.17.1 torchaudio==2.2.1 pytorch-cuda=11.8 -c pytorch -c nvidia
RUN conda init
RUN source /root/.bashrc

WORKDIR /neuralangelo-hci

# after this do
# conda activate neuralangelo
# pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch