计划执行与检查节点
executing-plans
按既定实施计划完成工作,保持过程检查和反馈。
mapping-localization【效率与协作】Operate hloc pair generation, COLMAP/pycolmap mapping, triangulation, SfM localization, InLoc localization, and pose outputs.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this sub-skill when the task is to turn prepared hloc features, retrieval descriptors, matches, image lists, and/or existing camera poses into image pairs, COLMAP/pycolmap sparse models, triangulated reference models, or query poses.
hloc.reconstruction.main / python -m hloc.reconstruction sparse reconstruction.hloc.triangulation.main / python -m hloc.triangulation triangulation from known camera poses.hloc.localize_sfm.main / python -m hloc.localize_sfm query localization against a COLMAP/pycolmap SfM model.hloc.localize_inloc.main / python -m hloc.localize_inloc InLoc-style RGB-D scan localization.python -m hloc.colmap_from_nvm.../feature-retrieval/.../dataset-pipelines/.../custom-interop/.Before running mapping or localization, identify these artifacts explicitly:
Run the bundled validator when accepting user-supplied paths or text files:
python sub-skills/mapping-localization/scripts/validate_hloc_inputs.py \
--workflow localize-sfm \
--query-list queries_with_intrinsics.txt \
--pairs retrieval.txt \
--features features.h5 \
--matches matches.h5 \
--reference-model sfm_model