The regression issue has been fixed. The main issue: 853e9f0 . The colmap gauge fixing also gets the results more stable (before the results vary with different frame fixing).
Another regression issue is the ceres solver options: 4a92dc5 , where the glomap solver options seem to slightly outperform colmap auto solver selection. The difference is not significant enough to get conclusion but i keep this auto selector option in colmap (and pycolmap) for consistency.
A: glomap solver options
B: colmap auto solver selection
I20251228 21:00:45.225546 3042027 compare.py:main:58] Results A - B:
=====scenes===== ======AUC @ X deg (%)====== ===images=== =components=
0.5 1.0 5.0 10.0 reg all num largest
==============================eth3d=dslr==============================
botanical_garden -0.00 -0.00 -0.00 -0.00 0 0 0 0
boulders -0.04 -0.02 -0.01 -0.00 0 0 0 0
bridge 0.13 0.05 0.02 0.04 0 0 0 0
courtyard 0.17 0.09 0.01 0.01 0 0 0 0
delivery_area 0.03 0.08 0.28 0.06 0 0 0 0
door 0.00 0.00 -0.00 -0.00 0 0 0 0
electro 0.00 0.00 0.00 0.00 0 0 0 0
exhibition_hall 2.57 2.82 1.19 0.83 0 0 0 0
facade 0.03 0.02 0.00 0.00 0 0 0 0
kicker -0.00 0.00 -0.00 -0.00 0 0 0 0
lecture_room -0.46 -0.70 -0.10 -0.05 0 0 0 0
living_room 0.03 0.03 0.01 0.01 0 0 0 0
lounge 0.00 0.00 0.00 0.00 0 0 0 0
meadow -0.00 -0.00 0.00 0.00 0 0 0 0
observatory -0.00 -0.00 -0.00 -0.00 0 0 0 0
office -0.00 -0.00 -0.00 -0.00 0 0 0 0
old_computer -0.00 -0.00 -0.00 -0.00 0 0 0 0
pipes 0.00 0.00 0.00 0.00 0 0 0 0
playground 0.00 0.00 0.00 0.00 0 0 0 0
relief -0.00 0.01 0.00 0.00 0 0 0 0
relief_2 -0.00 -0.00 -0.00 -0.00 0 0 0 0
statue -0.00 0.00 0.00 0.00 0 0 0 0
terrace 0.00 0.00 0.00 0.00 0 0 0 0
terrace_2 0.00 0.00 0.00 0.00 0 0 0 0
terrains 0.00 0.00 0.00 -0.00 0 0 0 0
----------------------------------------------------------------------
overall 0.30 0.30 0.14 0.10 0 0 0 0
----------------------------------------------------------------------
average 0.10 0.10 0.06 0.04 0 0 0 0