fb892ea9f2
Comments, docstrings, logs, CLI help, map UI, legends, PDF sheet, scripts, compose files and AGENTS.md are now English. Data keys stay unchanged (relief_oriente, densite_sol, visualisations/, API JSON keys, link params). Wrong comments and help defaults found along the way are corrected. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
65 lines
2.5 KiB
Docker
65 lines
2.5 KiB
Docker
FROM nvidia/cuda:12.9.2-devel-ubuntu22.04
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ENV DEBIAN_FRONTEND=noninteractive
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ENV TZ=Europe/Paris
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# Install system packages + Miniforge for PDAL >= 2.5 (Ubuntu 22.04 ships PDAL 2.3 which can't read COPC v1.1)
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RUN apt-get update && apt-get install -y --no-install-recommends \
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gdal-bin \
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python3-gdal \
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python3-pip \
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python3-dev \
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build-essential \
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wget \
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&& rm -rf /var/lib/apt/lists/* \
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&& wget -q https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh -O /tmp/miniforge.sh \
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&& bash /tmp/miniforge.sh -b -p /opt/conda \
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&& rm /tmp/miniforge.sh \
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&& /opt/conda/bin/conda install -y -c conda-forge pdal \
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&& ln -sf /opt/conda/bin/pdal /usr/local/bin/pdal \
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&& /opt/conda/bin/conda clean -afy
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WORKDIR /app
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# Install Python packages via pip (single list: requirements.txt)
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COPY requirements.txt .
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RUN pip3 install --no-cache-dir -r requirements.txt
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# CuPy on CUDA 12.9 with JIT compilation (CUPY_CUDA_COMPILE_WITH_CACHE=1).
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# JIT allows CuPy to compile kernels at runtime for GPU architectures not in
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# the pre-built wheel (sm_89 = RTX 4060 Ti, sm_120 = RTX 5060 Ti).
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# nvcc must be in PATH at runtime for JIT compilation.
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ENV CUPY_CUDA_COMPILE_WITH_CACHE=1
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# numba kernel cache (relief_oriente, flow accumulation): without it, every
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# worker (spawned process per tile) recompiles its kernels (~1 s per tile).
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ENV NUMBA_CACHE_DIR=/tmp/numba-cache
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ENV PATH=/usr/local/cuda/bin:${PATH}
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RUN pip3 install --no-cache-dir cupy-cuda12x
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# Copy and install the pipeline package
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COPY setup.py .
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COPY lidar_pipeline/ ./lidar_pipeline/
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RUN pip3 install --no-cache-dir .
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# Map interface CSS/JS (app.js/app.css from web/map.*, + vendored Leaflet)
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# baked into the image: mapserve serves them from mapserve_assets/ of the
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# installed package. cd /tmp: without it, python3 -c puts the current
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# directory (/app, the source copy) on sys.path and the bake would land in
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# that copy instead of the installed package (dist-packages) the container
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# uses at runtime.
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RUN cd /tmp && python3 -c "import pathlib, lidar_pipeline.mapui as m; m.write_map_assets(pathlib.Path(m.__file__).resolve().parent / m.ASSETS_DIRNAME)"
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# Create user with uid/gid 1000:1000 and run as that user
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RUN groupadd -g 1000 lidar && \
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useradd -u 1000 -g lidar -m lidar && \
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mkdir -p /data/output /data/input && \
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chown -R lidar:lidar /data /data/output /data/input
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WORKDIR /data
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USER lidar
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VOLUME ["/data"]
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CMD ["python3", "-m", "lidar_pipeline", "/data/input", "-o", "/data/output"] |