Dockerfile

# Base image with Python 3.9 for app dependencies
FROM python:3.9 as base

# Create a user and set environment variables
RUN useradd -m -u 1000 user
USER user
ENV PATH="/home/user/.local/bin:$PATH"

# Set working directory
WORKDIR /app

# Copy and install Python dependencies
COPY --chown=user ./requirements.txt requirements.txt
RUN pip install --no-cache-dir --upgrade -r requirements.txt

# Copy application files
COPY --chown=user . /app

# Expose application port and set default command
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

# Base image for CUDA support
FROM nvidia/cuda:11.1.1-cudnn8-devel-ubuntu18.04 as cuda

# Use noninteractive mode for apt-get
ENV DEBIAN_FRONTEND=noninteractive

# Install dependencies
RUN apt-get update && apt-get install -y \
    python3-opencv \
    python3-pip \
    ca-certificates \
    python3-dev \
    git \
    wget \
    sudo \
    ninja-build

# Link Python and Pip to default commands
RUN ln -sv /usr/bin/python3 /usr/bin/python && ln -sv /usr/bin/pip3 /usr/bin/pip

# Install Python packages
RUN pip install --no-cache-dir --upgrade -r requirements.txt
RUN pip install --user tensorboard cmake onnx

# Install fvcore
RUN pip install --user 'git+https://github.com/facebookresearch/fvcore'

# Clone Detectron2 repository
RUN git clone https://github.com/facebookresearch/detectron2 detectron2_repo

# Set environment variables for Detectron2
ENV FORCE_CUDA="1"
ARG TORCH_CUDA_ARCH_LIST="Kepler;Kepler+Tesla;Maxwell;Maxwell+Tegra;Pascal;Volta;Turing"
ENV TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST}"

# Install Detectron2 in editable mode
RUN pip install --user -e detectron2_repo

# Set fvcore cache directory
ENV FVCORE_CACHE="/tmp"

# Set working directory
WORKDIR /home/user/detectron2_repo