2cc5b2a5f3
- Dockerfile avec PDAL, GDAL, Python - Script Python de traitement avec visualisations archéologiques - Configuration docker-compose avec UID 1000:1000 - Support des fichiers LAZ/LAS pour détection de cavités et structures - Génération de 6 visualisations JPEG (Hillshade, Slope, SVF, LRM, Openness) - Légendes explicites avec unités et descriptions - Nettoyage automatique des fichiers temporaires Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
47 lines
1.2 KiB
YAML
47 lines
1.2 KiB
YAML
version: '3.8'
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services:
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lidar:
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build: .
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container_name: lidar-archeo
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user: "1000:1000"
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volumes:
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# Mount your LAZ files directory here
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- ./input:/data/input:ro
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# Output directory
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- ./output:/data/output
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# Optional: Mount a large data directory
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# - /path/to/your/laz/files:/data/input:ro
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environment:
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- TZ=Europe/Paris
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# Processing parameters
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- RESOLUTION=0.5
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- WHITEBOX_THREADS=4
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# Resource limits (adjust based on your system)
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deploy:
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resources:
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limits:
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cpus: '4'
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memory: 8G
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reservations:
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cpus: '2'
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memory: 4G
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# Override default command
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command: ["process_lidar.py", "/data/input", "-o", "/data/output", "-r", "0.5"]
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# Optional: Jupyter notebook for interactive exploration
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jupyter:
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build: .
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container_name: lidar-jupyter
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ports:
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- "8888:8888"
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volumes:
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- ./input:/data/input
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- ./output:/data/output
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- ./notebooks:/workspace
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command: >
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bash -c "pip install jupyter && \
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jupyter notebook --ip=0.0.0.0 --port=8888 --no-browser --allow-root --NotebookApp.token=''"
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profiles:
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- interactive
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