d334892880
- MSRM/TPI/roughness/anomalies: revert z-score (x-mean)/std to std normalization x/std to preserve contrast and visibility of linear features (paths, ditches, trenches) - MSRM: adaptive scales based on resolution, archaeological weight combination - TPI: extend from 2 to 4 scales (3m/15m/50m/200m) with weighted combination - Hillshade: 8 directions instead of 4, altitude 35° instead of 30° - LRM: adaptive sigma based on resolution - Openness: doubled radius (100m instead of 50m) - Roughness: multi-scale (3m fine + 15m broad) instead of single 5x5 window - Anomalies: uses MSRM multi-scale relief instead of single LRM 15m - Wavelet: 8 adaptive scales, std normalization, archaeological weights - Remove svf (Sky-View Factor) and local_dominance visualizations - Add AVIF format support (default), quality 98 - Add multi-resolution support (-r 0.5,0.2) - Improve Ctrl+C handling for immediate process termination - Update rendering.py descriptions for all modified visualizations Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
71 lines
1.9 KiB
Docker
71 lines
1.9 KiB
Docker
FROM nvidia/cuda:12.4.0-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
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COPY requirements.txt .
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RUN pip3 install --no-cache-dir \
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numpy \
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matplotlib \
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whitebox \
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rasterio \
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'laspy[lazrs]' \
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lazrs \
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scikit-image \
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scikit-learn \
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scipy \
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tqdm \
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Pillow \
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pytest \
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numba \
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rio-cogeo \
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titiler.core \
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fastapi \
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uvicorn \
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piexif \
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pillow-avif-plugin
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# Install CuPy for GPU acceleration (optional - will fallback to numpy if not available)
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RUN pip3 install --no-cache-dir cupy-cuda12x || echo "CuPy not available - GPU acceleration disabled"
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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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# Copy backward-compatible entry point
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COPY process_lidar.py /usr/local/bin/
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RUN chmod +x /usr/local/bin/process_lidar.py
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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"] |