d27b92a26a
Prevents indefinite hang if a worker gets stuck (deadlocked PDAL, I/O stall). 2-hour safety net for the entire batch; remaining futures are cancelled on timeout.
720 lines
33 KiB
Python
720 lines
33 KiB
Python
"""Pipeline orchestration for LiDAR archaeological analysis.
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LidarArchaeoPipeline coordinates the full processing chain:
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1. Ground classification (PDAL/SMRF)
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2. DTM generation
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3. Visualization generation (17 products)
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4. Rendering (AVIF/WebP conversion)
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"""
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import logging
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import multiprocessing
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import shutil
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import time
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from concurrent.futures import ProcessPoolExecutor, as_completed
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from datetime import datetime
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from pathlib import Path
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import subprocess
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# Use 'spawn' to avoid CUDA context corruption in forked subprocesses
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try:
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multiprocessing.set_start_method('spawn')
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except RuntimeError:
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pass # Already set (e.g. in tests or when called multiple times)
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logger = logging.getLogger("lidar")
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def _file_basename(path):
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"""Extract base name from a LAZ/LAS file, removing all known extensions.
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Handles double extensions like .copc.laz correctly:
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'file.copc.laz' -> 'file', not 'file.copc'
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"""
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name = Path(path).name
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# Remove known LiDAR extensions (order matters: longest first)
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for ext in ['.copc.laz', '.copc.las', '.laz', '.las']:
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if name.lower().endswith(ext):
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return name[:-len(ext)]
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return Path(path).stem
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class FilePrefixFilter(logging.Filter):
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"""Adds a file prefix to log messages when processing a specific file."""
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def __init__(self):
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super().__init__()
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self.basename = None
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def filter(self, record):
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if self.basename:
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record.msg = f"[{self.basename}] {record.msg}"
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return True
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# Module-level filter instance so process_file can set it
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_file_filter = FilePrefixFilter()
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from .progress import report_event
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from .dtm import classify_ground, create_dtm_fast
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from .visualizations import (
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SharedDEM,
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generate_hillshade, generate_slope, generate_aspect,
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generate_openness,
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generate_mslrm, generate_sailore,
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generate_roughness, generate_wavelet,
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generate_solar,
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generate_svf,
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generate_flow_accumulation,
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generate_anomaly_mask,
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)
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from .gpu import gpu_cleanup, num_gpus, available_gpu_ids, restrict_gpus, safe_gpu_call
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from .ign import generate_ign_overlay
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from .rendering import tif_to_crop
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# Ordered list of visualization steps.
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# Each entry: (name, function_or_lambda)
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# Adding a new visualization = add a generate_* function + register here.
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VIZ_STEPS = [
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('hillshade', generate_hillshade),
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('slope', generate_slope),
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('aspect', generate_aspect),
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('mslrm', generate_mslrm),
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('sailore', generate_sailore),
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('pos_open', lambda d, b, v, r, shared=None: generate_openness(d, b, v, r, positive=True, shared=shared)),
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('neg_open', lambda d, b, v, r, shared=None: generate_openness(d, b, v, r, positive=False, shared=shared)),
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('svf', generate_svf),
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('roughness', generate_roughness),
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('wavelet', generate_wavelet),
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('flow_acc', generate_flow_accumulation),
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('solar', generate_solar),
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('anomaly', generate_anomaly_mask),
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('ortho', lambda d, b, v, r: generate_ign_overlay(
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d, b, v, r,
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layer='ORTHOIMAGERY.ORTHOPHOTOS',
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title='Photographie Aérienne IGN',
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legend_label='Orthophotographie\nImage aérienne',
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description='Photographie aérienne IGN (Orthophoto)',
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out_suffix='ortho')),
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('topo', lambda d, b, v, r: generate_ign_overlay(
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d, b, v, r,
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layer='GEOGRAPHICALGRIDSYSTEMS.PLANIGNV2',
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title='Carte Topographique IGN',
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legend_label='Carte IGN\nPlan topographique',
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description='Carte topographique IGN (Plan IGN)',
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out_suffix='topo')),
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]
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class LidarArchaeoPipeline:
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"""Orchestrates the LiDAR archaeological analysis pipeline."""
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def __init__(self, input_dir, output_dir, resolution=0.5, workers=1, force=False, ground_method='auto', ign_classes="sol", force_classify=False, keep_tif=False, bare_earth=False, quality=98, only_viz=None, skip_viz=None, output_format='avif', gpu_ids=None, no_index=False, incremental_index=False):
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self.input_dir = Path(input_dir)
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self.output_dir = Path(output_dir)
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# Accept single float or comma-separated string for multi-resolution
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if isinstance(resolution, str):
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self.resolutions = [float(r.strip()) for r in resolution.split(',')]
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elif isinstance(resolution, (list, tuple)):
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self.resolutions = [float(r) for r in resolution]
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else:
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self.resolutions = [float(resolution)]
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self.resolution = self.resolutions[0] # Primary resolution (backward compat)
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self.workers = workers
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self.force = force
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self.ground_method = ground_method
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self.ign_classes = ign_classes
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self.force_classify = force_classify
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self.bare_earth = bare_earth
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self.keep_tif = keep_tif
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self.quality = quality
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self.only_viz = only_viz
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self.skip_viz = skip_viz
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self.output_format = output_format
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self.gpu_ids = gpu_ids
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self.no_index = no_index
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self.incremental_index = incremental_index
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self._last_index_rebuild = 0.0
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self.temp_dir = self.output_dir / "temp"
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if not self.input_dir.exists():
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raise ValueError(f"Répertoire introuvable: {self.input_dir}")
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self.output_dir.mkdir(parents=True, exist_ok=True)
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self.temp_dir.mkdir(exist_ok=True)
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self.dtm_dir = self.output_dir / "DTM"
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self.vis_dir = self.output_dir / "visualisations"
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for d in [self.dtm_dir, self.vis_dir]:
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d.mkdir(exist_ok=True)
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# Filter visualizations based on --only / --skip
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all_viz_names = [name for name, _ in VIZ_STEPS]
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if only_viz:
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invalid = set(only_viz) - set(all_viz_names)
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if invalid:
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raise ValueError(f"Visualisations inconnues: {', '.join(invalid)}. Disponibles: {', '.join(all_viz_names)}")
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self.viz_steps = [(n, f) for n, f in VIZ_STEPS if n in only_viz]
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elif skip_viz:
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invalid = set(skip_viz) - set(all_viz_names)
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if invalid:
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raise ValueError(f"Visualisations inconnues: {', '.join(invalid)}. Disponibles: {', '.join(all_viz_names)}")
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self.viz_steps = [(n, f) for n, f in VIZ_STEPS if n not in skip_viz]
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else:
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self.viz_steps = VIZ_STEPS
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logger.info("Pipeline initialisé")
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logger.info(f" Entrée : {self.input_dir}")
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logger.info(f" Sortie : {self.output_dir}")
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if len(self.resolutions) > 1:
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logger.info(f" Résolutions : {', '.join(f'{r}m/px' for r in self.resolutions)}")
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else:
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logger.info(f" Résolution : {self.resolution}m/px")
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logger.info(f" Workers : {workers}")
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logger.info(f" Force : {'OUI' if self.force else 'non (skip existing)'}")
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logger.info(f" Classification sol : {self.ground_method}")
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logger.info(f" Force classif.: {'OUI' if self.force_classify else 'non'}")
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logger.info(f" Keep TIFF : {'OUI' if self.keep_tif else 'non'}")
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logger.info(f" Qualité {self.output_format.upper()}: {self.quality if self.quality < 100 else 'lossless'}")
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if only_viz:
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logger.info(f" Visualisations: uniquement {', '.join(only_viz)}")
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elif skip_viz:
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logger.info(f" Visualisations: tout sauf {', '.join(skip_viz)}")
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logger.info(f" Visualisations: {len(self.viz_steps)}/{len(VIZ_STEPS)}")
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def find_laz_files(self):
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"""Find all LAZ/LAS files in input directory."""
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files = list(self.input_dir.glob("*.laz")) + list(self.input_dir.glob("*.las"))
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logger.info(f"{len(files)} fichier(s) LiDAR trouvé(s)")
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for f in sorted(files):
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logger.debug(f" {f.name}")
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return sorted(files)
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def check_tools(self):
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"""Check that required external tools are available."""
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for name, cmd in [('pdal', 'pdal --version'), ('gdal', 'gdalinfo --version')]:
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try:
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result = subprocess.run(cmd.split(), capture_output=True, check=True, text=True)
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version = result.stdout.strip().split('\n')[0]
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logger.info(f" ✓ {name}: {version}")
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except (subprocess.CalledProcessError, FileNotFoundError):
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logger.error(f" ✗ {name} non disponible")
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return False
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return True
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@staticmethod
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def _expected_output_path(name, basename, file_vis_dir, output_format='avif'):
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"""Return the expected output filename for a visualization step."""
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ext = 'avif' if output_format == 'avif' else 'webp'
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if name == 'pos_open':
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return file_vis_dir / f"{basename}_positive_openness.{ext}"
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elif name == 'neg_open':
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return file_vis_dir / f"{basename}_negative_openness.{ext}"
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elif name == 'hillshade':
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return file_vis_dir / f"{basename}_hillshade_multi.{ext}"
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else:
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return file_vis_dir / f"{basename}_{name}.{ext}"
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def generate_all_visualizations(self, dtm_file, basename, resolution=None, vis_dir=None, force_images=None):
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"""Generate all archaeological visualizations for one DTM file.
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Optimisation: SharedDEM is only computed if at least one visualization
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needs to be generated. When all WebP outputs exist, SharedDEM is
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skipped entirely (saves ~2min per file on re-runs).
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"""
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if resolution is None:
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resolution = self.resolution
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logger.info(" Génération visualisations:")
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# Use provided vis_dir (for multi-resolution subdirectories) or default
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file_vis_dir = vis_dir if vis_dir else (self.vis_dir / basename)
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file_vis_dir.mkdir(exist_ok=True)
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total = len(self.viz_steps)
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# Phase 1: determine which visualizations need generation
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force_viz = self.force if force_images is None else force_images
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needs_generation = {} # name -> True/False
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for name, func in self.viz_steps:
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if force_viz:
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needs_generation[name] = True
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else:
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expected_webp = self._expected_output_path(name, basename, file_vis_dir, self.output_format)
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needs_generation[name] = not expected_webp.exists()
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to_generate = [n for n, needed in needs_generation.items() if needed]
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ign_only = all(name in ('ortho', 'topo') for name in to_generate)
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needs_shared = any(name not in ('ortho', 'topo') for name in to_generate)
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if not to_generate:
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logger.info(" Toutes les visualisations déjà existantes — ignorées")
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# Still need to return results dict for PDF check
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vis_results = {}
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for name, func in self.viz_steps:
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vis_results[name] = self._expected_output_path(name, basename, file_vis_dir, self.output_format)
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return vis_results
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# Phase 2: compute SharedDEM only if needed
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shared = None
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if needs_shared:
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logger.info(" Pré-calcul données partagées (gradient, LRM)...")
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t_shared = time.time()
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shared = SharedDEM(dtm_file, resolution)
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logger.info(f" ✓ Données partagées prêtes ({time.time()-t_shared:.1f}s)")
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# Phase 3: generate visualizations
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vis_results = {}
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for idx, (name, func) in enumerate(self.viz_steps, 1):
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if not needs_generation[name]:
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logger.info(f" [{idx}/{total}] {name}: déjà existant, ignoré")
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self._report(basename, "viz", "skip", name, res=resolution)
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vis_results[name] = self._expected_output_path(name, basename, file_vis_dir, self.output_format)
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continue
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# When regenerating, delete existing TIF to ensure clean regeneration
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if force_viz:
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for tif in file_vis_dir.glob(f"{basename}_{name}.tif"):
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tif.unlink(missing_ok=True)
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if name == 'pos_open':
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for tif in file_vis_dir.glob(f"{basename}_positive_openness.tif"):
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tif.unlink(missing_ok=True)
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elif name == 'neg_open':
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for tif in file_vis_dir.glob(f"{basename}_negative_openness.tif"):
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tif.unlink(missing_ok=True)
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elif name == 'hillshade':
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for tif in file_vis_dir.glob(f"{basename}_hillshade_multi.tif"):
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tif.unlink(missing_ok=True)
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logger.info(f" [{idx}/{total}] {name}...")
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self._report(basename, "viz", "start", name, res=resolution)
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t0 = time.time()
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try:
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# IGN overlays don't use SharedDEM (they download external data)
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# Non-IGN visualizations use safe_gpu_call for GPU→CPU fallback
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if name in ('ortho', 'topo'):
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result = func(dtm_file, basename, file_vis_dir, resolution)
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else:
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result = safe_gpu_call(func, dtm_file, basename, file_vis_dir, resolution, shared=shared)
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vis_results[name] = result
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elapsed = time.time() - t0
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if result:
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logger.info(f" [{idx}/{total}] ✓ {name} ({elapsed:.1f}s)")
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self._report(basename, "viz", "ok", name, res=resolution)
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else:
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logger.warning(f" [{idx}/{total}] ✗ {name} — no output ({elapsed:.1f}s)")
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self._report(basename, "viz", "fail", name, res=resolution)
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except Exception as e:
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vis_results[name] = None
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logger.error(f" [{idx}/{total}] ✗ {name}: {e}", exc_info=True)
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self._report(basename, "viz", "fail", name, res=resolution)
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# Free GPU memory between visualizations to prevent OOM
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gpu_cleanup()
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# Convert to output format (only newly generated TIFs, not skipped ones)
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fmt_label = self.output_format.upper()
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logger.info(f" Conversion images {fmt_label}:")
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for name, tif_file in vis_results.items():
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if tif_file and isinstance(tif_file, Path) and tif_file.suffix == '.tif' and tif_file.exists():
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img_file = tif_to_crop(tif_file, file_vis_dir, resolution, keep_tif=self.keep_tif, quality=self.quality, output_format=self.output_format)
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if img_file:
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logger.info(f" ✓ {img_file.name}")
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# Clean up remaining TIF files unless --keep-tif
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if not self.keep_tif:
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for tif in file_vis_dir.glob("*.tif"):
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tif.unlink(missing_ok=True)
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return vis_results
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@staticmethod
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def _res_suffix(resolution):
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"""Return suffix for additional resolutions (empty string for primary)."""
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if resolution == 0.5:
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return "" # Default resolution — no suffix
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res_str = f"{resolution}".replace('.', 'p')
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return f"_r{res_str}"
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def _dtm_method_path(self, basename, res_suffix):
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"""Sidecar path storing which ground method produced a DTM."""
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return self.dtm_dir / f"{basename}_dtm{res_suffix}_method.txt"
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def _dtm_method_name(self, basename, res_suffix):
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"""Read the recorded ground method for a DTM, or None if unknown."""
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p = self._dtm_method_path(basename, res_suffix)
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if p.exists():
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try:
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return p.read_text(encoding="utf-8").strip() or None
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except Exception:
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return None
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return None
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def _effective_ground_method(self):
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"""Méthode effective pour le suivi de cache, classes IGN incluses.
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La méthode 'ign' est étiquetée avec les classes choisies (ex. 'ign_1_2')
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pour qu'un changement de --ign-classes déclenche la reclassification.
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"""
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if self.ground_method == 'ign':
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from .dtm import parse_ign_classes, ign_method_label
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return ign_method_label(parse_ign_classes(self.ign_classes))
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return self.ground_method
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def _dtm_method_matches(self, basename, res_suffix):
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"""True if the recorded ground method matches the requested one.
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A DTM without a recorded method is treated as matching so the existing
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cache is preserved; the method is adopted on its next reclassification.
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"""
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recorded = self._dtm_method_name(basename, res_suffix)
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return recorded is None or recorded == self._effective_ground_method()
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def _write_dtm_method(self, basename, res_suffix):
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"""Record the ground classification method used to build a DTM."""
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try:
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self._dtm_method_path(basename, res_suffix).write_text(
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self._effective_ground_method(), encoding="utf-8")
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except Exception:
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pass
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def _report(self, basename, phase, state, detail=None, res=None):
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"""Émet un événement de progression (file de génération, best-effort)."""
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report_event(self.output_dir, basename, phase, state, detail=detail, res=res)
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def process_file(self, laz_file):
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"""Process a single LAZ file through the full pipeline.
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If self.resolutions has multiple entries, processes each resolution:
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- Primary resolution uses current naming (no suffix)
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- Additional resolutions use _r0p2 suffix in directories/filenames
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- Ground classification is done once and shared across resolutions
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"""
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basename = _file_basename(laz_file)
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_file_filter.basename = basename
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t_start = time.time()
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logger.info("=" * 60)
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logger.info(f"FICHIER : {basename}")
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logger.info("=" * 60)
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# Validate file integrity before any processing
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from .dtm import validate_laz
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if not validate_laz(laz_file):
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self._report(basename, "tile", "fail", "fichier LAZ invalide")
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return False
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# Step 1: Ground classification (shared across all resolutions)
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las_file = None
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t_classif = 0
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dtm_rebuilt = False
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# The ground method is shared across resolutions. It is recorded per DTM
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# in a sidecar so that changing --ground-classification invalidates the
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# cache; otherwise the cached DTM would be reused and the new method
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# never applied (nothing would change visually).
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primary_suffix = self._res_suffix(self.resolutions[0])
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method_matches = self._dtm_method_matches(basename, primary_suffix)
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for i, res in enumerate(self.resolutions):
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res_suffix = self._res_suffix(res)
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dtm_path = self.dtm_dir / f"{basename}_dtm{res_suffix}.tif"
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if dtm_path.exists() and not self.force_classify:
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if method_matches:
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import rasterio
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try:
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with rasterio.open(dtm_path) as src:
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existing_res = abs(src.transform.a)
|
|
if abs(existing_res - res) > 0.01:
|
|
logger.info(f" DTM{res_suffix} existant à {existing_res}m/px — résolution demandée {res}m/px → régénération")
|
|
dtm_path.unlink()
|
|
else:
|
|
if i == 0:
|
|
logger.info(f"[1/5] Classification du sol — sautée (DTM existant)")
|
|
logger.info(f"[2/5] Génération DTM {res}m/px — sautée (DTM existant)")
|
|
self._report(basename, "classif", "skip", "DTM existant")
|
|
else:
|
|
logger.info(f" DTM {res}m/px déjà existant — ignoré")
|
|
self._report(basename, "dtm", "skip", res=res)
|
|
continue
|
|
except Exception:
|
|
logger.warning(f"Impossible de lire le DTM existant — régénération")
|
|
dtm_path.unlink()
|
|
else:
|
|
logger.info(f" DTM{res_suffix} produit par {self._dtm_method_name(basename, primary_suffix) or '?'} ≠ {self._effective_ground_method()} → reclassification")
|
|
dtm_path.unlink()
|
|
|
|
# Need to classify/generate DTM for this resolution
|
|
if las_file is None:
|
|
# First time: do ground classification
|
|
logger.info("[1/5] Classification du sol...")
|
|
self._report(basename, "classif", "start")
|
|
t1 = time.time()
|
|
las_file = classify_ground(laz_file, self.temp_dir, method=self.ground_method, force=self.force_classify, ign_classes=self.ign_classes)
|
|
t_classif = time.time() - t1
|
|
if not las_file:
|
|
logger.error(f" ✗ Échec classification ({t_classif:.1f}s)")
|
|
self._report(basename, "classif", "fail")
|
|
self._report(basename, "tile", "fail", "échec classification")
|
|
return False
|
|
logger.info(f" ✓ Classification terminée ({t_classif:.1f}s)")
|
|
self._report(basename, "classif", "ok")
|
|
|
|
# Generate DTM at this resolution
|
|
logger.info(f"{'[2/5]' if i == 0 else ' '} Génération DTM {res}m/px...")
|
|
self._report(basename, "dtm", "start", res=res)
|
|
t2 = time.time()
|
|
# Classification IGN → mode pur : DTM = rasterisation brute des
|
|
# classes choisies, sans plancher ni comblement (sauf --bare-earth)
|
|
pure_ign = "_ground_ign" in Path(las_file).name
|
|
dtm_file = create_dtm_fast(las_file, basename, self.dtm_dir, res,
|
|
force=self.force or self.force_classify,
|
|
output_suffix=res_suffix,
|
|
source_laz=laz_file,
|
|
bare_earth=self.bare_earth,
|
|
pure=pure_ign)
|
|
t_dtm = time.time() - t2
|
|
if not dtm_file:
|
|
logger.error(f" ✗ Échec DTM {res}m/px ({t_dtm:.1f}s)")
|
|
self._report(basename, "dtm", "fail", res=res)
|
|
if i == 0:
|
|
self._report(basename, "tile", "fail", "échec DTM")
|
|
return False # Primary resolution failure is fatal
|
|
continue # Additional resolution failure is non-fatal
|
|
logger.info(f" ✓ DTM {res}m/px terminé ({t_dtm:.1f}s)")
|
|
self._report(basename, "dtm", "ok", res=res)
|
|
dtm_rebuilt = True
|
|
self._write_dtm_method(basename, res_suffix)
|
|
|
|
# Process each resolution: visualizations + PDF
|
|
all_vis_results = {}
|
|
for res in self.resolutions:
|
|
res_suffix = self._res_suffix(res)
|
|
dtm_path = self.dtm_dir / f"{basename}_dtm{res_suffix}.tif"
|
|
|
|
if not dtm_path.exists():
|
|
logger.warning(f" DTM {res}m/px manquant — visualisations ignorées")
|
|
continue
|
|
|
|
import rasterio
|
|
with rasterio.open(dtm_path) as src:
|
|
actual_res = abs(src.transform.a)
|
|
|
|
if len(self.resolutions) > 1:
|
|
logger.info(f" --- Résolution {res}m/px ---")
|
|
|
|
# For additional resolutions, use suffixed subdirectory
|
|
if res_suffix:
|
|
vis_dir = self.vis_dir / f"{basename}{res_suffix}"
|
|
else:
|
|
vis_dir = self.vis_dir / basename
|
|
|
|
vis_dir.mkdir(exist_ok=True)
|
|
|
|
self.generate_all_visualizations(
|
|
dtm_path, basename, actual_res, vis_dir=vis_dir,
|
|
force_images=self.force or self.force_classify or dtm_rebuilt)
|
|
|
|
t_total = time.time() - t_start
|
|
logger.info(f"✓ {basename} terminé en {t_total:.1f}s")
|
|
self._report(basename, "tile", "ok", f"{t_total:.0f}s")
|
|
_file_filter.basename = None
|
|
return True
|
|
|
|
def _rebuild_index_incremental(self):
|
|
"""Régénère la carte juste après une tuile terminée (mode incrémental).
|
|
|
|
Réécrit index.html + index_tiles.json pour que la webapp affiche la
|
|
tuile sans attendre la fin du run. Anti-rebond : 3 s minimum entre
|
|
deux passes — les tuiles terminées pendant l'intervalle sont couvertes
|
|
par la passe suivante ou par la passe finale. Les logs de build_index
|
|
sont masqués pour ne pas noyer le journal du run.
|
|
"""
|
|
if self.no_index:
|
|
return
|
|
now = time.time()
|
|
if now - self._last_index_rebuild < 3.0:
|
|
return
|
|
self._last_index_rebuild = now
|
|
try:
|
|
from .index import build_index
|
|
saved_level = logger.getEffectiveLevel()
|
|
logger.setLevel(logging.WARNING)
|
|
try:
|
|
build_index(self.output_dir, self.output_format)
|
|
finally:
|
|
logger.setLevel(saved_level)
|
|
except Exception as e:
|
|
logger.debug(f"Rebuild incrémental de l'index ignoré : {e}")
|
|
|
|
def process_all(self, files=None):
|
|
"""Process all LAZ files in input directory (or an explicit list)."""
|
|
files = files if files is not None else self.find_laz_files()
|
|
|
|
if not files:
|
|
logger.error("Aucun fichier LAZ/LAS trouvé !")
|
|
return
|
|
|
|
logger.info("=" * 60)
|
|
logger.info("PIPELINE ARCHÉOLOGIQUE LiDAR")
|
|
logger.info("=" * 60)
|
|
|
|
logger.info("Vérification des outils...")
|
|
if not self.check_tools():
|
|
logger.error("Outils manquants — abandon")
|
|
return
|
|
|
|
results = {}
|
|
t_pipeline_start = time.time()
|
|
|
|
# Restrict visible GPUs in the main process before spawning workers
|
|
if self.gpu_ids is not None:
|
|
restrict_gpus(self.gpu_ids)
|
|
|
|
if self.workers > 1 and len(files) > 1:
|
|
n_gpus = num_gpus() or 1
|
|
if n_gpus > 1:
|
|
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:
|
|
# Round-robin assign each file to a real GPU host index
|
|
active_ids = self.gpu_ids if self.gpu_ids else available_gpu_ids()
|
|
resolutions_str = ','.join(str(r) for r in self.resolutions)
|
|
future_to_file = {
|
|
executor.submit(_process_file_standalone, str(laz_file), str(self.input_dir), str(self.output_dir), resolutions_str, self.force, self.ground_method, self.ign_classes, self.force_classify, self.keep_tif, self.bare_earth, self.quality, self.only_viz, self.skip_viz, self.output_format, active_ids[file_idx % len(active_ids)] if active_ids else None): laz_file
|
|
for file_idx, laz_file in enumerate(files)
|
|
}
|
|
done = 0
|
|
t_deadline = time.time() + 7200
|
|
try:
|
|
for future in as_completed(future_to_file):
|
|
if time.time() > t_deadline:
|
|
logger.error("Délai dépassé (2h) — annulation des workers restants")
|
|
for f in future_to_file:
|
|
f.cancel()
|
|
break
|
|
laz_file = future_to_file[future]
|
|
done += 1
|
|
try:
|
|
success = future.result()
|
|
results[laz_file.name] = success
|
|
status = "✓" if success else "✗"
|
|
logger.info(f" [{done}/{len(files)}] {status} {laz_file.name}")
|
|
if success and self.incremental_index:
|
|
self._rebuild_index_incremental()
|
|
except Exception as e:
|
|
logger.error(f" [{done}/{len(files)}] ✗ {laz_file.name}: {e}")
|
|
logger.debug(f" Traceback:", exc_info=True)
|
|
report_event(self.output_dir, _file_basename(laz_file),
|
|
"tile", "fail", detail=str(e))
|
|
results[laz_file.name] = False
|
|
except KeyboardInterrupt:
|
|
logger.info("Interruption — annulation des travaux en cours...")
|
|
for f in future_to_file:
|
|
f.cancel()
|
|
executor.shutdown(wait=False, cancel_futures=True)
|
|
logger.info("Travaux annulés.")
|
|
return
|
|
else:
|
|
total = len(files)
|
|
for idx, laz_file in enumerate(files, 1):
|
|
logger.info(f"--- Fichier {idx}/{total} ---")
|
|
try:
|
|
results[laz_file.name] = self.process_file(laz_file)
|
|
if results[laz_file.name] and self.incremental_index:
|
|
self._rebuild_index_incremental()
|
|
except KeyboardInterrupt:
|
|
logger.info("Interruption — arrêt immédiat.")
|
|
return
|
|
except Exception as e:
|
|
logger.error(f"✗ Erreur traitement {laz_file.name}: {e}")
|
|
logger.debug("Traceback:", exc_info=True)
|
|
report_event(self.output_dir, _file_basename(laz_file),
|
|
"tile", "fail", detail=str(e))
|
|
results[laz_file.name] = False
|
|
|
|
# Summary
|
|
t_pipeline_total = time.time() - t_pipeline_start
|
|
success_count = sum(1 for v in results.values() if v)
|
|
fail_count = sum(1 for v in results.values() if not v)
|
|
|
|
logger.info("=" * 60)
|
|
logger.info("RÉSUMÉ")
|
|
logger.info("=" * 60)
|
|
for name, ok in results.items():
|
|
status = "✓" if ok else "✗"
|
|
logger.info(f" {status} {name}")
|
|
logger.info("-" * 60)
|
|
logger.info(f" Succès : {success_count}/{len(results)}")
|
|
if fail_count:
|
|
logger.info(f" Échecs : {fail_count}/{len(results)}")
|
|
logger.info(f" Durée totale : {t_pipeline_total:.1f}s ({t_pipeline_total/60:.1f}min)")
|
|
|
|
logger.info(f"\nRésultats dans: {self.output_dir}")
|
|
logger.info(f" • DTM : {self.dtm_dir}")
|
|
logger.info(f" • Visualisations: {self.vis_dir}")
|
|
|
|
# Génère la carte globale interactive des tuiles traitées
|
|
if not self.no_index:
|
|
try:
|
|
from .index import build_index
|
|
index_path = build_index(self.output_dir, self.output_format)
|
|
if index_path:
|
|
logger.info(f" • Carte globale : {index_path}")
|
|
except Exception as e:
|
|
logger.warning(f"Index global non généré: {e}")
|
|
|
|
# Clean up temporary files
|
|
logger.info("Nettoyage des fichiers temporaires...")
|
|
try:
|
|
if self.temp_dir.exists():
|
|
shutil.rmtree(self.temp_dir)
|
|
logger.info(" ✓ Fichiers temporaires supprimés")
|
|
except Exception as e:
|
|
logger.warning(f" Note: Impossible de supprimer les fichiers temporaires: {e}")
|
|
|
|
|
|
def _process_file_standalone(laz_file_str, input_dir, output_dir, resolution, force=False, ground_method='auto', ign_classes="sol", force_classify=False, keep_tif=False, bare_earth=False, quality=98, only_viz=None, skip_viz=None, output_format='avif', gpu_id=None):
|
|
"""Standalone function for multiprocessing — creates its own pipeline instance.
|
|
|
|
Each worker gets its own temp directory to avoid file conflicts.
|
|
When multiple GPUs are available, each worker is assigned a GPU via
|
|
CUDA_VISIBLE_DEVICES to balance load across GPUs.
|
|
"""
|
|
if gpu_id is not None and gpu_id >= 0:
|
|
from .gpu import set_active_gpu
|
|
set_active_gpu(gpu_id)
|
|
|
|
# Configure logging in worker process (spawn doesn't inherit parent config)
|
|
import logging
|
|
import sys
|
|
# Ensure UTF-8 output — spawn workers may default to ASCII
|
|
if hasattr(sys.stdout, 'reconfigure'):
|
|
sys.stdout.reconfigure(encoding='utf-8', errors='replace')
|
|
if hasattr(sys.stderr, 'reconfigure'):
|
|
sys.stderr.reconfigure(encoding='utf-8', errors='replace')
|
|
worker_logger = logging.getLogger("lidar")
|
|
if not worker_logger.handlers:
|
|
handler = logging.StreamHandler(sys.stdout)
|
|
handler.setFormatter(logging.Formatter("%(message)s"))
|
|
worker_logger.setLevel(logging.INFO)
|
|
worker_logger.addHandler(handler)
|
|
worker_logger.addFilter(_file_filter)
|
|
|
|
pipeline = LidarArchaeoPipeline(input_dir, output_dir, resolution=resolution, workers=1, force=force, ground_method=ground_method, ign_classes=ign_classes, force_classify=force_classify, keep_tif=keep_tif, bare_earth=bare_earth, quality=quality, only_viz=only_viz, skip_viz=skip_viz, output_format=output_format)
|
|
basename = _file_basename(laz_file_str)
|
|
pipeline.temp_dir = pipeline.output_dir / "temp" / basename
|
|
pipeline.temp_dir.mkdir(exist_ok=True)
|
|
laz_file = Path(laz_file_str)
|
|
result = pipeline.process_file(laz_file)
|
|
|
|
# Clean up per-file temp directory
|
|
try:
|
|
if pipeline.temp_dir.exists():
|
|
shutil.rmtree(pipeline.temp_dir)
|
|
except Exception:
|
|
pass
|
|
|
|
return result |