96 lines
3.3 KiB
Docker
96 lines
3.3 KiB
Docker
# syntax=docker/dockerfile:1.7
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# ──────────────────────────────────────────────────────────────────────────
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# Forensic Features API — Lean Container
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#
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# Imagine finală estimată: ~1.5 GB
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# (vs ~8 GB cu transformers/torch/autogluon — neincluse aici)
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#
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# Build: docker build -t forensic-features:latest .
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# Run: docker run -p 8080:8080 forensic-features:latest
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# ──────────────────────────────────────────────────────────────────────────
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# ═══ Stage 1: Builder ═══════════════════════════════════════════════════
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FROM python:3.12-slim-bookworm AS builder
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RUN apt-get update && apt-get install -y --no-install-recommends \
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build-essential \
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gcc \
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g++ \
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&& rm -rf /var/lib/apt/lists/*
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ENV VIRTUAL_ENV=/opt/venv
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RUN python -m venv $VIRTUAL_ENV
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ENV PATH="$VIRTUAL_ENV/bin:$PATH"
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RUN pip install --no-cache-dir --upgrade pip setuptools wheel
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COPY requirements.txt /tmp/requirements.txt
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RUN pip install --no-cache-dir -r /tmp/requirements.txt
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# ═══ Stage 2: Runtime ═══════════════════════════════════════════════════
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FROM python:3.12-slim-bookworm AS runtime
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# Sistem deps minime:
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# ffmpeg — frame + audio extraction
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# libgl1 — OpenCV runtime
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# libglib2.0-0 — OpenCV glib runtime
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# libgles2 — MediaPipe OpenGL ES (libGLESv2.so.2)
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# libegl1 — MediaPipe EGL (libEGL.so.1)
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# libgomp1 — OpenMP
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# curl — pentru healthcheck
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RUN apt-get update && apt-get install -y --no-install-recommends \
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ffmpeg \
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libgl1 \
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libglib2.0-0 \
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libgomp1 \
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libgles2 \
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libegl1 \
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curl \
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&& rm -rf /var/lib/apt/lists/* \
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&& apt-get clean
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# Copiem venv-ul pre-construit
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COPY --from=builder /opt/venv /opt/venv
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ENV VIRTUAL_ENV=/opt/venv
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ENV PATH="$VIRTUAL_ENV/bin:$PATH"
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# Non-root user pentru securitate
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RUN groupadd --system --gid 1001 app \
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&& useradd --system --uid 1001 --gid app --create-home --home-dir /home/app app
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WORKDIR /app
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# ── Copiere cod (ordine: stabil → modificat des, pentru cache optim) ────
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# 1. MediaPipe model (rar modificat, ~3.6 MB)
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COPY --chown=app:app face_landmarker.task ./
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# 2. Tools forensice (5 module)
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COPY --chown=app:app tools/ ./tools/
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# 3. Glue layer
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COPY --chown=app:app forensic/ ./forensic/
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# 4. Core API + preprocessing (cele mai des modificate)
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COPY --chown=app:app api.py preprocessing.py ./
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COPY --chown=app:app requirements.txt ./
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# Directoare runtime
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RUN mkdir -p /app/data/inference /app/data/results \
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&& chown -R app:app /app
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USER app
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ENV PYTHONUNBUFFERED=1 \
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PYTHONDONTWRITEBYTECODE=1 \
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API_HOST=0.0.0.0 \
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API_PORT=8080
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EXPOSE 8080
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HEALTHCHECK --interval=30s --timeout=10s --start-period=30s --retries=3 \
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CMD curl --fail --silent --max-time 5 http://localhost:8080/health || exit 1
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CMD ["python", "api.py"]
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