Layout uniforme WebP: axes fixes + aspect='equal' pour superposition géolocalisée
- Positions d'axes fixes (data_left/bottom/width/height_frac) pour alignement pixel-parfait entre terrain et ortho/topo - aspect='equal' au lieu de 'auto' pour conserver les proportions géographiques - Colorbar descriptive pour les visualisations RGB (ortho/topo) - Comblage des petits trous DTM (< 1m) via rasterio.fill.fillnodata - Suppression de la visualisation "dépressions" - Hillshade composite: 0.7*hillshade + 0.3*cos(slope) - D8 flow accumulation accéléré par numba JIT (fallback Python) - Flag --keep-tif pour conserver les TIFF intermédiaires - --force supprime aussi les TIF existants avant régénération - ETA affiché pendant la génération des visualisations - Répertoires temp dans temp/ pour traitement parallèle Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Jacquin Antoine
@ -3,7 +3,7 @@
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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 (18 products)
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3. Visualization generation (17 products)
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4. Rendering (WebP + PDF report)
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"""
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@ -57,7 +57,7 @@ from .dtm import classify_ground, create_dtm_fast
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from .visualizations import (
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generate_hillshade, generate_slope, generate_aspect, generate_curvature,
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generate_lrm, generate_svf, generate_openness,
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generate_mslrm, generate_tpi, generate_depressions, generate_sailore,
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generate_mslrm, generate_tpi, generate_sailore,
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generate_roughness, generate_anomalies, generate_wavelet,
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generate_flow,
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)
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@ -80,7 +80,6 @@ VIZ_STEPS = [
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('neg_open', lambda d, b, v, r: generate_openness(d, b, v, r, positive=False)),
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('mslrm', generate_mslrm),
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('tpi', generate_tpi),
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('depressions', generate_depressions),
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('sailore', generate_sailore),
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('roughness', generate_roughness),
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('anomalies', generate_anomalies),
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@ -106,7 +105,7 @@ VIZ_STEPS = [
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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', force_classify=False):
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def __init__(self, input_dir, output_dir, resolution=0.5, workers=1, force=False, ground_method='auto', force_classify=False, keep_tif=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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self.resolution = resolution
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@ -114,6 +113,7 @@ class LidarArchaeoPipeline:
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self.force = force
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self.ground_method = ground_method
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self.force_classify = force_classify
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self.keep_tif = keep_tif
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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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@ -137,6 +137,7 @@ class LidarArchaeoPipeline:
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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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def find_laz_files(self):
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"""Find all LAZ/LAS files in input directory."""
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@ -171,8 +172,24 @@ class LidarArchaeoPipeline:
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vis_results = {}
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total = len(VIZ_STEPS)
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elapsed_times = []
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for idx, (name, func) in enumerate(VIZ_STEPS, 1):
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# When --force, delete existing TIF to ensure clean regeneration
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if self.force:
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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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# Special cases for differently-named TIFs
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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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# Check if output WebP already exists (skip unless --force)
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if not self.force:
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# Determine expected WebP filename from the viz name
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@ -199,8 +216,14 @@ class LidarArchaeoPipeline:
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result = func(dtm_file, basename, file_vis_dir, self.resolution)
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vis_results[name] = result
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elapsed = time.time() - t0
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elapsed_times.append(elapsed)
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if result:
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logger.info(f" [{idx}/{total}] ✓ {name} ({elapsed:.1f}s)")
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eta = ""
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if len(elapsed_times) > 1:
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avg_time = sum(elapsed_times) / len(elapsed_times)
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remaining = (total - idx) * avg_time
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eta = f" — ETA: {remaining:.0f}s"
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logger.info(f" [{idx}/{total}] ✓ {name} ({elapsed:.1f}s){eta}")
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else:
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logger.warning(f" [{idx}/{total}] ✗ {name} — no output ({elapsed:.1f}s)")
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except Exception as e:
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@ -214,7 +237,7 @@ class LidarArchaeoPipeline:
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logger.info(" Conversion images WebP:")
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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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webp_file = tif_to_png(tif_file, file_vis_dir, self.resolution)
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webp_file = tif_to_png(tif_file, file_vis_dir, self.resolution, keep_tif=self.keep_tif)
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if webp_file:
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logger.info(f" ✓ {webp_file.name}")
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@ -293,7 +316,7 @@ class LidarArchaeoPipeline:
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logger.info(f"Fichiers: {len(files)}")
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with ProcessPoolExecutor(max_workers=self.workers) as executor:
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future_to_file = {
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executor.submit(_process_file_standalone, str(laz_file), str(self.input_dir), str(self.output_dir), self.resolution, self.force, self.ground_method, self.force_classify): laz_file
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executor.submit(_process_file_standalone, str(laz_file), str(self.input_dir), str(self.output_dir), self.resolution, self.force, self.ground_method, self.force_classify, self.keep_tif): laz_file
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for laz_file in files
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}
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done = 0
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@ -346,16 +369,16 @@ class LidarArchaeoPipeline:
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try:
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if self.temp_dir.exists():
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shutil.rmtree(self.temp_dir)
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# Also clean up per-file temp directories from parallel workers
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for d in self.output_dir.glob("temp_*"):
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if d.is_dir():
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shutil.rmtree(d, ignore_errors=True)
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# Also clean up any subdirectories inside temp/
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temp_base = self.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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def _process_file_standalone(laz_file_str, input_dir, output_dir, resolution, force=False, ground_method='auto', force_classify=False):
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def _process_file_standalone(laz_file_str, input_dir, output_dir, resolution, force=False, ground_method='auto', force_classify=False, keep_tif=False):
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"""Standalone function for multiprocessing — creates its own pipeline instance.
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Each worker gets its own temp directory to avoid file conflicts.
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@ -371,9 +394,9 @@ def _process_file_standalone(laz_file_str, input_dir, output_dir, resolution, fo
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worker_logger.addHandler(handler)
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worker_logger.addFilter(_file_filter)
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pipeline = LidarArchaeoPipeline(input_dir, output_dir, resolution=resolution, workers=1, force=force, ground_method=ground_method, force_classify=force_classify)
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pipeline = LidarArchaeoPipeline(input_dir, output_dir, resolution=resolution, workers=1, force=force, ground_method=ground_method, force_classify=force_classify, keep_tif=keep_tif)
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basename = _file_basename(laz_file_str)
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pipeline.temp_dir = pipeline.output_dir / f"temp_{basename}"
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pipeline.temp_dir = pipeline.output_dir / "temp" / basename
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pipeline.temp_dir.mkdir(exist_ok=True)
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laz_file = Path(laz_file_str)
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result = pipeline.process_file(laz_file)
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