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Add multi-GPU support and fix scale bar / location map overlap

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Multi-GPU:
- gpu.py: lazy CuPy initialization so CUDA_VISIBLE_DEVICES takes
  effect before context creation in worker processes
- gpu.py: detect GPU count via nvidia-smi (no CUDA import needed)
- gpu.py: add set_active_gpu() to assign workers to specific GPUs
- pipeline.py: distribute files across GPUs (file % num_gpus) in
  parallel mode so both GPUs are used simultaneously
- pipeline.py: log GPU count when multiple GPUs detected

Layout fixes:
- rendering.py: move scale bar left of location map to avoid overlap
  (scale bar ends at fig_x=0.78, map starts at 0.82)
- rendering.py: expand location map inset to 0.16x0.13 fig coords
- rendering.py: return bounds from _download_location_map so imshow
  extent matches the actual IGN tile coverage (80km context)
- ign.py: add min_zoom parameter to download_ign_tiles, fixing the
  location map that was broken (zoom 10 blocked by hardcoded min_zoom=15)
This commit is contained in:
Antoine Jacquin
2026-05-15 12:00:34 +02:00
parent 4848f25326
commit 5af53a390f
3 changed files with 145 additions and 31 deletions
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24
lidar_pipeline/pipeline.py
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@ -63,7 +63,7 @@ from .visualizations import (
generate_roughness, generate_wavelet,
generate_svf, generate_aniso_open,
)
from .gpu import gpu_cleanup
from .gpu import gpu_cleanup, num_gpus
from .ign import generate_ign_overlay
from .rendering import tif_to_png
@ -447,14 +447,20 @@ class LidarArchaeoPipeline:
t_pipeline_start = time.time()
if self.workers > 1 and len(files) > 1:
logger.info(f"Traitement parallèle avec {self.workers} workers...")
n_gpus = num_gpus()
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...")
logger.info(f"Fichiers: {len(files)}")
with ProcessPoolExecutor(max_workers=self.workers) as executor:
# Pass resolutions as comma-separated string for multiprocessing serialization
resolutions_str = ','.join(str(r) for r in self.resolutions)
n_gpus = num_gpus() or 1
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.force_classify, self.keep_tif, self.quality, self.only_viz, self.skip_viz, self.output_format): laz_file
for laz_file in files
executor.submit(_process_file_standalone, str(laz_file), str(self.input_dir), str(self.output_dir), resolutions_str, self.force, self.ground_method, self.force_classify, self.keep_tif, self.quality, self.only_viz, self.skip_viz, self.output_format, gpu_id % n_gpus): laz_file
for gpu_id, laz_file in enumerate(files)
}
done = 0
try:
@ -526,11 +532,19 @@ class LidarArchaeoPipeline:
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', force_classify=False, keep_tif=False, quality=98, only_viz=None, skip_viz=None, output_format='avif'):
def _process_file_standalone(laz_file_str, input_dir, output_dir, resolution, force=False, ground_method='auto', force_classify=False, keep_tif=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.
"""
# Assign GPU FIRST — before any CuPy import happens
# This sets CUDA_VISIBLE_DEVICES and resets lazy CuPy init
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