Add WebP quality control and selective visualization (--only / --skip)
- WebP output now uses quality=85 by default (down from lossless), reducing file size by ~75% (35MB → 5-8MB per visualization) - Added --quality N (1-100) and --lossless flags in CLI and run.sh - Added --only and --skip to select/exclude specific visualizations (e.g., --only hillshade,svf,lrm or --skip ortho,topo) - VIZ_STEPS filtering is done in LidarArchaeoPipeline.__init__ - SharedDEM is skipped when all selected visualizations already exist - Invalid visualization names are validated at startup with clear error Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Jacquin Antoine
@ -108,7 +108,7 @@ 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, keep_tif=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, quality=85, only_viz=None, skip_viz=None):
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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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@ -117,6 +117,9 @@ class LidarArchaeoPipeline:
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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.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.temp_dir = self.output_dir / "temp"
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if not self.input_dir.exists():
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@ -132,6 +135,21 @@ class LidarArchaeoPipeline:
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for d in [self.dtm_dir, self.vis_dir, self.pdf_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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@ -141,6 +159,12 @@ class LidarArchaeoPipeline:
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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 WebP: {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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@ -188,11 +212,11 @@ class LidarArchaeoPipeline:
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# Create per-file subdirectory
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file_vis_dir = self.vis_dir / basename
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file_vis_dir.mkdir(exist_ok=True)
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total = len(VIZ_STEPS)
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total = len(self.viz_steps)
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# Phase 1: determine which visualizations need generation
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needs_generation = {} # name -> True/False
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for name, func in VIZ_STEPS:
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for name, func in self.viz_steps:
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if self.force:
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needs_generation[name] = True
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else:
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@ -207,7 +231,7 @@ class LidarArchaeoPipeline:
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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 VIZ_STEPS:
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for name, func in self.viz_steps:
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vis_results[name] = self._expected_webp_path(name, basename, file_vis_dir)
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return vis_results
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@ -221,7 +245,7 @@ class LidarArchaeoPipeline:
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# Phase 3: generate visualizations
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vis_results = {}
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for idx, (name, func) in enumerate(VIZ_STEPS, 1):
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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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vis_results[name] = self._expected_webp_path(name, basename, file_vis_dir)
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@ -271,7 +295,7 @@ class LidarArchaeoPipeline:
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}
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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, resolution, keep_tif=self.keep_tif, source_info=source_info)
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webp_file = tif_to_png(tif_file, file_vis_dir, resolution, keep_tif=self.keep_tif, source_info=source_info, quality=self.quality)
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if webp_file:
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logger.info(f" ✓ {webp_file.name}")
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@ -393,7 +417,7 @@ 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, self.keep_tif): 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, self.quality, self.only_viz, self.skip_viz): 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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@ -456,7 +480,7 @@ class LidarArchaeoPipeline:
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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, keep_tif=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, quality=85, only_viz=None, skip_viz=None):
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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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@ -477,7 +501,7 @@ 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, keep_tif=keep_tif)
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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, quality=quality, only_viz=only_viz, skip_viz=skip_viz)
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basename = _file_basename(laz_file_str)
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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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