Dockerfile

ARG CUDA_IMAGE="12.1.1-devel-ubuntu22.04"
FROM nvidia/cuda:${CUDA_IMAGE}

# We need to set the host to 0.0.0.0 to allow outside access
ENV HOST 0.0.0.0

RUN apt-get update && apt-get upgrade -y \
    && apt-get install -y git build-essential \
    python3 python3-pip gcc wget python-is-python3 \
    ocl-icd-opencl-dev opencl-headers clinfo \
    libclblast-dev libopenblas-dev \
    libgl1 libgl1-mesa-glx libglib2.0-0 \
    && mkdir -p /etc/OpenCL/vendors && echo "libnvidia-opencl.so.1" > /etc/OpenCL/vendors/nvidia.icd
COPY . .

# setting build related env vars
ENV CUDA_DOCKER_ARCH=all

# Install depencencies
RUN python -m pip install --upgrade pip pytest cmake \
    scikit-build setuptools fastapi uvicorn sse-starlette \
    pydantic-settings starlette-context gradio huggingface_hub hf_transfer

# Install PyTorch for CUDA 11.3
RUN python -m pip install torch==2.0.1 torchvision==0.15.2 torchaudio --extra-index-url https://download.pytorch.org/whl/cu121

# Install MMCV MMDetection
RUN pip install -U openmim
RUN mim install mmcv-full==1.7.2
RUN mim install mmdet==2.28.2

# Install MMRotate
RUN git clone https://github.com/open-mmlab/mmrotate.git
WORKDIR mmrotate

ENV FORCE_CUDA="1"
RUN pip install -r requirements/build.txt
RUN pip install --no-cache-dir -e .

RUN useradd -m -u 1000 user

# Switch to the "user" user
USER user

# Specific requirements for current project
COPY requirements.txt .
RUN python -m pip install --user -r requirements.txt

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

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 ["python3", "app.py"]