Supprimer le code mort (imports inutilisés, variable _xp, conseil GPU inatteignable)

lidar_pipeline/cli.py

@@ -5,8 +5,6 @@ Handles argument parsing, logging configuration, and entry point.
 
 import argparse
 import logging
-import os
-import shutil
 import signal
 import sys
 

lidar_pipeline/dtm.py

@@ -457,7 +457,7 @@ def classify_ground(laz_file, temp_dir, method='auto', force=False, ign_classes=
     Returns:
         Path to classified ground LAS file, or None on failure.
     """
-    import laspy  # noqa: ensure available
+    import laspy
 
     # Auto-detect method if requested
     if method == 'auto':

lidar_pipeline/gpu.py

@@ -80,7 +80,6 @@ except Exception:
 # ---------------------------------------------------------------------------
 # Lazy CuPy initialization — tries each GPU until one works
 # ---------------------------------------------------------------------------
-_xp = np
 _cp = None
 _cp_ndimage = None
 _cupy_ndarray = None  # type ref qui survit à disable_gpu() pour que to_cpu() récupère les tableaux orphelins
@@ -154,7 +153,7 @@ def _init_gpu():
        import CuPy directly (no subprocess test needed)
     3. Otherwise: test each GPU in a subprocess, pick the first that works
     """
-    global _xp, _cp, _cp_ndimage, _cupy_ndarray, _gpu_initialized, HAS_GPU, _best_gpu_id, _gpu_name, _gpu_mem_gb
+    global _cp, _cp_ndimage, _cupy_ndarray, _gpu_initialized, HAS_GPU, _best_gpu_id, _gpu_name, _gpu_mem_gb
     if _gpu_initialized:
         return
     _gpu_initialized = True
@@ -165,7 +164,6 @@ def _init_gpu():
         candidates = _filter_candidates(_runtime_candidates())
     if not candidates:
         logger.info("Pas de GPU utilisable — mode CPU uniquement")
-        _xp = np
         _cp = None
         _cp_ndimage = None
         HAS_GPU = False
@@ -191,14 +189,12 @@ def _init_gpu():
             _gpu_name = name
             _gpu_mem_gb = mem_mi // 1024
             HAS_GPU = True
-            _xp = _real_cupy
             _cp = _real_cupy
             _cp_ndimage = _real_cupy_ndimage
             _cupy_ndarray = _real_cupy.ndarray
             return
         except Exception as e:
             logger.warning(f"GPU indisponible (CUDA_VISIBLE_DEVICES={cuda_visible}): {e}")
-            _xp = np
             _cp = None
             _cp_ndimage = None
             HAS_GPU = False
@@ -230,7 +226,6 @@ def _init_gpu():
 
     if _working_gpu is None:
         logger.info("Pas de GPU utilisable — mode CPU uniquement")
-        _xp = np
         _cp = None
         _cp_ndimage = None
         HAS_GPU = False
@@ -248,7 +243,6 @@ def _init_gpu():
     _gpu_name = name
     _gpu_mem_gb = mem_mi // 1024
     HAS_GPU = True
-    _xp = _real_cupy
     _cp = _real_cupy
     _cp_ndimage = _real_cupy_ndimage
     _cupy_ndarray = _real_cupy.ndarray
@@ -444,13 +438,12 @@ def disable_gpu():
     Libère le memory pool GPU avant de nuller les références (anti-fuite VRAM).
     Garde _cupy_ndarray vivant pour que to_cpu() récupère les tableaux orphelins.
     """
-    global HAS_GPU, _xp, _cp, _cp_ndimage
+    global HAS_GPU, _cp, _cp_ndimage
     if not HAS_GPU:
         return
     logger.warning("GPU désactivé — passage en mode CPU pour la suite du processus")
     gpu_cleanup()
     HAS_GPU = False
-    _xp = np
     _cp = None
     _cp_ndimage = None
 

lidar_pipeline/ign.py

@@ -7,7 +7,6 @@ GeoTIFF overlays matching the LiDAR DTM extent.
 import logging
 import math
 import time
-from pathlib import Path
 
 import numpy as np
 import rasterio

lidar_pipeline/pipeline.py

@@ -243,7 +243,6 @@ class LidarArchaeoPipeline:
                 needs_generation[name] = not expected_webp.exists()
 
         to_generate = [n for n, needed in needs_generation.items() if needed]
-        ign_only = all(name in ('ortho', 'topo') for name in to_generate)
         needs_shared = any(name not in ('ortho', 'topo') for name in to_generate)
 
         if not to_generate:
@@ -574,8 +573,6 @@ class LidarArchaeoPipeline:
                 logger.info(f"Traitement parallèle avec {self.workers} workers sur {n_gpus} GPUs...")
             else:
                 logger.info(f"Traitement parallèle avec {self.workers} workers...")
-            if n_gpus > 1 and self.workers == 1:
-                logger.info(f"Conseil: utilisez -w {n_gpus} pour exploiter tous les GPUs")
             logger.info(f"Fichiers: {len(files)}")
 
             with ProcessPoolExecutor(max_workers=self.workers) as executor:
@@ -624,6 +621,10 @@ class LidarArchaeoPipeline:
                     return
         else:
             total = len(files)
+            if self.workers == 1 and len(files) > 1:
+                n_gpus = num_gpus() or 1
+                if n_gpus > 1:
+                    logger.info(f"Conseil : utilisez -w {n_gpus} pour exploiter tous les GPUs")
             for idx, laz_file in enumerate(files, 1):
                 logger.info(f"--- Fichier {idx}/{total} ---")
                 try:

lidar_pipeline/rendering.py

@@ -28,16 +28,9 @@ import matplotlib
 matplotlib.use('Agg')
 import matplotlib.pyplot as plt
 from matplotlib import rcParams
-from matplotlib.patches import Polygon as MplPolygon, Rectangle as RectPatch, FancyBboxPatch
-from matplotlib.colors import ListedColormap
+from matplotlib.patches import Polygon as MplPolygon, Rectangle as RectPatch
 from matplotlib.ticker import ScalarFormatter
 
-try:
-    from cmcrameri import cm as cmc
-    HAS_CMCRAmeri = True
-except ImportError:
-    HAS_CMCRAmeri = False
-
 rcParams['figure.dpi'] = 150
 rcParams['savefig.dpi'] = 300
 rcParams['font.size'] = 10
@@ -284,8 +277,6 @@ def _download_location_map(min_x, max_x, min_y, max_y):
         Tuple (image_array, bounds_dict) where bounds_dict has keys
         'min_x', 'max_x', 'min_y', 'max_y' in Lambert 93, or None on failure.
     """
-    import hashlib
-
     # Cache key based on rounded coordinates (1km grid)
     cache_key = (round(min_x, -3), round(max_x, -3), round(min_y, -3), round(max_y, -3))
     if cache_key in _location_map_cache:

requirements.txt

@@ -16,7 +16,6 @@ fastapi>=0.110
 uvicorn>=0.29
 pydantic>=2.6
 pyproj>=3.6
-cmcrameri>=1.8
 
 # Tests (./run.sh --test)
 pytest>=7.4