Installer depuis requirements.txt et retirer les paquets jamais importés
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24
Dockerfile
24
Dockerfile
@ -21,29 +21,9 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
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WORKDIR /app
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WORKDIR /app
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# Install Python packages via pip
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# Install Python packages via pip (liste unique : requirements.txt)
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COPY requirements.txt .
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COPY requirements.txt .
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RUN pip3 install --no-cache-dir \
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RUN pip3 install --no-cache-dir -r requirements.txt
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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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cmcrameri
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# CuPy on CUDA 12.9 with JIT compilation (CUPY_CUDA_COMPILE_WITH_CACHE=1).
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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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# JIT allows CuPy to compile kernels at runtime for GPU architectures not in
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@ -1,10 +1,22 @@
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pdal>=3.0
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# Dépendances Python de l'image complète (Dockerfile) — installées via
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# `pip install --no-cache-dir -r requirements.txt`.
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# PDAL n'est PAS installé par pip : binaire conda (cf. Dockerfile), invoqué
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# en ligne de commande. L'image webapp légère (Dockerfile.webapp) a sa propre
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# liste minimale (fastapi, uvicorn, Pillow, pyproj).
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# CuPy est installé séparément (cupy-cuda12x) selon la cible CUDA.
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numpy>=1.24
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numpy>=1.24
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scipy>=1.10
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matplotlib>=3.7
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matplotlib>=3.7
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whitebox>=2.0
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rasterio>=1.3
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rasterio>=1.3
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laspy[lazrs]>=2.5
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laspy[lazrs]>=2.5
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scikit-image>=0.21
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numba>=0.58
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tqdm>=4.65
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Pillow>=10.0
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scikit-learn>=1.3
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pillow-avif-plugin>=1.4
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cmcrameri>=2.0
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fastapi>=0.110
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uvicorn>=0.29
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pydantic>=2.6
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pyproj>=3.6
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cmcrameri>=1.8
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# Tests (./run.sh --test)
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pytest>=7.4
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