eac482874d
- Fix gpu_cleanup import missing in visualizations.py (NameError in workers) - Fix t_pdf referenced before assignment when PDF is skipped - Skip classification+DTM when DTM exists regardless of --force - --force now only regenerates WebP/PDF, not classification/DTM - --force-classification forces reclassification when needed - Add laspy repair fallback for corrupt LAZ files (EVLR errors) - Keep DTM TIF by default for reuse (--no-keep-tif to delete) - Increase space between image and bottom cartouche (0.12→0.19) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
243 lines
8.3 KiB
Python
243 lines
8.3 KiB
Python
"""Command-line interface for the LiDAR archaeological pipeline.
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Handles argument parsing, logging configuration, and entry point.
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"""
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import argparse
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import logging
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import os
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import shutil
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import signal
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import sys
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from .pipeline import LidarArchaeoPipeline
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from .gpu import log_gpu_status
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logger = logging.getLogger("lidar")
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def setup_logging(verbose=False, debug=False):
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"""Configure the 'lidar' logger.
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Args:
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verbose: If True, include timestamps and level names.
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debug: If True, set level to DEBUG and add file:line info.
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"""
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# Ensure UTF-8 output for French messages (é, è, ê, etc.)
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if hasattr(sys.stdout, 'reconfigure'):
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sys.stdout.reconfigure(encoding='utf-8', errors='replace')
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if hasattr(sys.stderr, 'reconfigure'):
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sys.stderr.reconfigure(encoding='utf-8', errors='replace')
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if debug:
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level = logging.DEBUG
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fmt = "%(asctime)s.%(msecs)03d %(levelname)-5s [%(filename)s:%(lineno)d] %(message)s"
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elif verbose:
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level = logging.INFO
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fmt = "%(asctime)s %(levelname)-5s %(message)s"
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else:
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level = logging.INFO
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fmt = "%(message)s"
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handler = logging.StreamHandler(sys.stdout)
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handler.setFormatter(logging.Formatter(fmt, datefmt="%H:%M:%S"))
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logger.setLevel(level)
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logger.handlers.clear()
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logger.addHandler(handler)
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logger.propagate = False # Prevent double logging via root logger
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# Also configure the root logger so worker processes log properly
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root_logger = logging.getLogger()
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root_logger.setLevel(level)
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if not root_logger.handlers:
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root_handler = logging.StreamHandler(sys.stdout)
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root_handler.setFormatter(logging.Formatter(fmt, datefmt="%H:%M:%S"))
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root_logger.addHandler(root_handler)
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return logger
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def main():
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"""Entry point for the LiDAR archaeological pipeline."""
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parser = argparse.ArgumentParser(
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description="Pipeline LiDAR pour détection archéologique",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""\
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Exemples:
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Traitement standard:
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python -m lidar_pipeline /data/input -o /data/output
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Haute résolution avec accélération GPU:
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python -m lidar_pipeline /data/input -o /data/output -r 0.2 -g
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Mode verbeux (timestamps):
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python -m lidar_pipeline /data/input -o /data/output -v
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Mode debug (détails internes):
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python -m lidar_pipeline /data/input -o /data/output --debug
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Forcer la régénération de tous les fichiers:
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python -m lidar_pipeline /data/input -o /data/output --force
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Traiter un seul fichier (pour tests):
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python -m lidar_pipeline /data/input -o /data/output --file LHD_FXX_1000_6881_PTS_LAMB93_IGN69.copc
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Traitement parallèle (4 workers):
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python -m lidar_pipeline /data/input -o /data/output -w 4
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"""
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)
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parser.add_argument(
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"input",
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help="Dossier contenant les fichiers LAZ/LAS"
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)
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parser.add_argument(
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"-o", "--output",
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default="/data/output",
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help="Dossier de sortie (défaut: /data/output)"
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)
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parser.add_argument(
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"-r", "--resolution",
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type=float,
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default=0.5,
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help="Résolution en mètres par pixel (défaut: 0.5)"
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)
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parser.add_argument(
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"-w", "--workers",
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type=int,
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default=1,
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help="Nombre de workers pour traitement parallèle (défaut: 1)"
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)
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parser.add_argument(
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"-f", "--force",
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action="store_true",
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help="Régénérer tous les fichiers même si les WebP existent déjà"
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)
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parser.add_argument(
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"--force-classification",
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action="store_true",
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help="Reclassifier le sol même si le fichier .las existe déjà"
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)
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parser.add_argument(
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"--no-keep-tif",
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action="store_true",
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help="Supprimer les fichiers TIFF intermédiaires après conversion WebP (par défaut: conservés)"
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)
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parser.add_argument(
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"--ground-classification",
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choices=["auto", "smrf", "pmf", "csf"],
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default="auto",
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help="Méthode de classification du sol : auto (détection), smrf, pmf, csf (défaut: auto)"
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)
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parser.add_argument(
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"--file",
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nargs="+",
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type=str,
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default=None,
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help="Traiter un ou plusieurs fichiers LAZ/LAS (nom complet sans extension, ex: LHD_FXX_1000_6882_PTS_LAMB93_IGN69.copc)"
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)
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parser.add_argument(
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"-v", "--verbose",
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action="store_true",
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help="Mode verbeux : affiche les timestamps et niveaux"
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)
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parser.add_argument(
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"--debug",
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action="store_true",
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help="Mode debug : affiche les détails internes (fichier:ligne)"
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)
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args = parser.parse_args()
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# Configure logging before any other output
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setup_logging(verbose=args.verbose, debug=args.debug)
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# Add file prefix filter for parallel processing
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from .pipeline import _file_filter
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logger.addFilter(_file_filter)
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logger.info("=" * 60)
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logger.info("Pipeline LiDAR Archéologique")
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logger.info("=" * 60)
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# Kill orphan PDAL processes on interrupt or termination
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signal.signal(signal.SIGINT, _kill_orphan_pdal)
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signal.signal(signal.SIGTERM, _kill_orphan_pdal)
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import atexit
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atexit.register(_kill_orphan_pdal)
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log_gpu_status()
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try:
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pipeline = LidarArchaeoPipeline(
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input_dir=args.input,
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output_dir=args.output,
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resolution=args.resolution,
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workers=args.workers,
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force=args.force,
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ground_method=args.ground_classification,
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force_classify=args.force_classification,
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keep_tif=not args.no_keep_tif,
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)
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# If --file is specified, process only matching files
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if args.file:
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from pathlib import Path
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input_dir = Path(args.input)
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# Each pattern is the full filename without extension (e.g. LHD_FXX_1000_6882_PTS_LAMB93_IGN69.copc)
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# Also supports bare name without .copc (e.g. LHD_FXX_1000_6882_PTS_LAMB93_IGN69)
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selected_files = []
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for pattern in args.file:
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matches = (list(input_dir.glob(f"{pattern}.laz"))
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+ list(input_dir.glob(f"{pattern}.las"))
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+ list(input_dir.glob(f"{pattern}.copc.laz"))
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+ list(input_dir.glob(f"{pattern}.copc.las")))
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# Remove duplicates
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matches = list(dict.fromkeys(matches))
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if not matches:
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logger.warning(f"Aucun fichier trouvé pour: {pattern}")
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continue
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selected_files.extend(matches)
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# Remove duplicates across patterns
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seen = set()
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unique_files = []
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for f in selected_files:
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if f not in seen:
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seen.add(f)
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unique_files.append(f)
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if not unique_files:
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logger.error("Aucun fichier trouvé pour les motifs spécifiés")
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sys.exit(1)
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logger.info(f"Traitement de {len(unique_files)} fichier(s) sélectionné(s)")
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for laz_file in unique_files:
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logger.info(f" → {laz_file.name}")
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for laz_file in unique_files:
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pipeline.process_file(laz_file)
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# Clean up temporary files
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logger.info("Nettoyage des fichiers temporaires...")
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try:
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if pipeline.temp_dir.exists():
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shutil.rmtree(pipeline.temp_dir)
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temp_base = pipeline.output_dir / "temp"
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if temp_base.exists():
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shutil.rmtree(temp_base)
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logger.info(" ✓ Fichiers temporaires supprimés")
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except Exception as e:
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logger.warning(f" Note: Impossible de supprimer les fichiers temporaires: {e}")
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else:
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pipeline.process_all()
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except Exception as e:
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logger.error(f"Erreur fatale: {e}", exc_info=True)
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sys.exit(1)
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def _kill_orphan_pdal(signum=None, frame=None):
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"""Kill orphan PDAL processes on interrupt or exit."""
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import subprocess
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try:
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subprocess.run(["pkill", "-f", "pdal"], capture_output=True, timeout=5)
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except Exception:
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pass
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if signum is not None:
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logger.info("Interruption — nettoyage des processus PDAL")
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sys.exit(130) |