# ── Base images ─────────────────────────────────────────────────────────────── # amd64 + gpu: NVIDIA CUDA 12.8 + cuDNN on Ubuntu 24.04 (highest Ubuntu NVIDIA publishes) # amd64 + rocm: Ubuntu 26.04 (AMD GPU via ROCm — pass /dev/kfd and /dev/dri) # amd64 + intel: Ubuntu 22.04 (Intel Arc / iGPU via OpenVINO — pass /dev/dri) # Note: intel stays on 22.04 — Intel's GPU repo only publishes for jammy # amd64 + cpu: Ubuntu 26.04 (CPU-only, ~2 GB smaller image) # arm64: Ubuntu 24.04 (CPU-only; no CUDA/ROCm wheels on ARM) ARG VARIANT=gpu FROM --platform=$BUILDPLATFORM nvidia/cuda:12.8.1-cudnn-runtime-ubuntu24.04 AS base-amd64-gpu FROM ubuntu:26.04 AS base-amd64-rocm FROM ubuntu:22.04 AS base-amd64-intel FROM ubuntu:26.04 AS base-amd64-cpu FROM ubuntu:24.04 AS base-arm64-gpu FROM ubuntu:24.04 AS base-arm64-rocm FROM ubuntu:24.04 AS base-arm64-intel FROM ubuntu:24.04 AS base-arm64-cpu # ── Build stage ─────────────────────────────────────────────────────────────── ARG TARGETARCH FROM base-${TARGETARCH}-${VARIANT} AS build ARG VARIANT=gpu ENV DEBIAN_FRONTEND=noninteractive # All base images get Python 3.13 from the deadsnakes PPA (26.04 ships 3.14 natively; # 3.13 is used to keep dependencies tested and aligned). GNUPGHOME is isolated # so gpg never contacts an agent socket under QEMU. RUN apt-get update && apt-get install -y --no-install-recommends \ ca-certificates curl gnupg software-properties-common \ && GNUPGHOME=$(mktemp -d) add-apt-repository ppa:deadsnakes/ppa -y \ && apt-get update \ && apt-get install -y --no-install-recommends \ python3.13 python3.13-venv python3.13-dev \ libgl1 libglib2.0-0 libxext6 g++ \ && rm -rf /var/lib/apt/lists/* \ && ln -sf /usr/bin/python3.13 /usr/bin/python3 COPY --from=ghcr.io/astral-sh/uv:0.11.21 /uv /usr/local/bin/uv WORKDIR /app COPY pyproject.toml uv.lock ./ RUN if [ "$VARIANT" = "cpu" ]; then \ uv sync --frozen --no-dev --extra cpu; \ elif [ "$VARIANT" = "rocm" ]; then \ uv sync --frozen --no-dev --extra rocm; \ elif [ "$VARIANT" = "intel" ]; then \ uv sync --frozen --no-dev --extra intel; \ elif [ "$VARIANT" = "gpu" ]; then \ uv sync --frozen --no-dev --extra gpu; \ else \ echo "Unknown VARIANT: '$VARIANT'. Must be one of: cpu, rocm, intel, gpu" >&2; \ exit 1; \ fi && \ uv cache clean COPY winnow/ winnow/ COPY entrypoint.sh scheduler.py ./ RUN chmod +x /app/entrypoint.sh # ── Runtime stage ───────────────────────────────────────────────────────────── # Starts fresh from the base image — excludes build tools (g++, # python3.13-dev, gnupg, software-properties-common) not needed at runtime. FROM base-${TARGETARCH}-${VARIANT} AS runtime ARG VARIANT=gpu ARG VERSION=dev LABEL org.opencontainers.image.title="winnow" \ org.opencontainers.image.description="Selects diverse, high-quality photos from Immich as training data for Frigate face recognition." \ org.opencontainers.image.source="https://github.com/sudolulo/winnow" \ org.opencontainers.image.licenses="AGPL-3.0-or-later" \ org.opencontainers.image.version="${VERSION}" ENV DEBIAN_FRONTEND=noninteractive RUN apt-get update && apt-get install -y --no-install-recommends \ ca-certificates curl gnupg software-properties-common tini \ && GNUPGHOME=$(mktemp -d) add-apt-repository ppa:deadsnakes/ppa -y \ && apt-get update \ && apt-get install -y --no-install-recommends \ python3.13 python3.13-venv \ libgl1 libglib2.0-0 libxext6 \ && apt-get purge -y --auto-remove curl gnupg software-properties-common \ && rm -rf /var/lib/apt/lists/* \ && ln -sf /usr/bin/python3.13 /usr/bin/python3 # Copy app (with .venv) and uv from build stage COPY --from=build /app /app COPY --from=build /usr/local/bin/uv /usr/local/bin/uv # NVIDIA: register pip-installed nvidia lib/ dirs with ldconfig so onnxruntime-gpu # and torch can find libcudnn, libcublas, etc. Skipped silently on other variants. RUN if [ "$VARIANT" = "gpu" ]; then \ find /app/.venv/lib/python3.*/site-packages/nvidia -type d -name "lib" \ 2>/dev/null > /etc/ld.so.conf.d/nvidia-pip.conf && ldconfig || true; \ fi # Intel: install GPU compute runtime so OpenVINO EP can target Intel Arc / iGPU. # onnxruntime-openvino bundles OpenVINO itself; only the userspace GPU driver # (OpenCL ICD + Level Zero) is needed from the OS. # These packages aren't in Ubuntu 22.04 main, so this block adds Intel's # official GPU repo first, then installs. libze-intel-gpu1 was renamed to # level-zero in Intel's repo. RUN if [ "$VARIANT" = "intel" ]; then \ apt-get update \ && apt-get install -y --no-install-recommends curl gnupg \ && curl -fsSL https://repositories.intel.com/graphics/intel-graphics.key \ | gpg --dearmor > /usr/share/keyrings/intel-graphics.gpg \ && echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] \ https://repositories.intel.com/graphics/ubuntu jammy flex" \ > /etc/apt/sources.list.d/intel-graphics.list \ && apt-get update \ && apt-get install -y --no-install-recommends \ intel-opencl-icd intel-level-zero-gpu level-zero \ && apt-get remove -y --autoremove curl gnupg \ && rm -rf /var/lib/apt/lists/*; \ fi RUN groupadd -g 568 apps && useradd -u 568 -g apps -m -s /bin/bash appuser \ && mkdir -p /models/.insightface \ && chown -R appuser:apps /app /models WORKDIR /app USER appuser # PYTHONPATH=/app makes the winnow package importable from the entry point script. # uv sync builds the wheel before winnow/ is COPY'd, so site-packages has only # the dist-info. Explicitly adding /app lets Python find winnow/__init__.py there. ENV INSIGHTFACE_HOME=/models/.insightface PYTHONPATH=/app HEALTHCHECK --interval=60s --timeout=5s --start-period=120s --retries=3 \ CMD sh -c 'if [ -f /tmp/winnow.pid ]; then kill -0 "$(cat /tmp/winnow.pid)"; fi' ENTRYPOINT ["tini", "--", "/app/entrypoint.sh"]