Dockerfile

FROM nvidia/cuda:11.6.1-cudnn8-devel-ubuntu20.04

ARG DEBIAN_FRONTEND=noninteractive

RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
    libgl1 \ 
    freeglut3-dev \
    unzip \
    ffmpeg \
    libsm6 \
    libxext6 \
    libgl1-mesa-dri \
    libegl1-mesa \
    libgbm1 \
    build-essential \
    libeigen3-dev \
    python3.8 \
    python3-pip \
    nvidia-cuda-toolkit

# Set up a new user named "user" with user ID 1000
RUN useradd -m -u 1000 user

# Switch to the "user" user
USER user

FROM python:3.8

ENV PYTHONUNBUFFERED=1

ENV TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0 7.5 8.0 8.6"
ENV TCNN_CUDA_ARCHITECTURES=86;80;75;70;61;60
ENV FORCE_CUDA=1

ENV CUDA_HOME=/usr/local/cuda
ENV PATH=${CUDA_HOME}/bin:/home/${USER_NAME}/.local/bin:/usr/bin:${PATH}
ENV LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
ENV LIBRARY_PATH=${CUDA_HOME}/lib64/stubs:${LIBRARY_PATH}


# Set home to the user's home directory
ENV HOME=/home/user \
    PYTHONPATH=$HOME/app \
	PYTHONUNBUFFERED=1 \
	GRADIO_ALLOW_FLAGGING=never \
	GRADIO_NUM_PORTS=1 \
	GRADIO_SERVER_NAME=0.0.0.0 \
	GRADIO_THEME=huggingface \
	SYSTEM=spaces

RUN pip install --upgrade pip ninja
RUN pip install setuptools==69.5.1

COPY requirements.txt /tmp
RUN cd /tmp && pip install -r requirements.txt

RUN pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py38_cu116_pyt1130/download.html
RUN python -c "import torch; print(torch.version.cuda)"

# Set the working directory to the user's home directory
WORKDIR $HOME/app

# Copy the current directory contents into the container at $HOME/app setting the owner to the user
COPY --chown=user . $HOME/app

CMD ["python", "app.py"]