feature dim

[CvierXi]

xrlocalization/xrloc/features/d2net.py

Line 50 in b0756b2

'descriptors': torch.from_numpy(descriptors.T)[None],

D2Net here output features with 512 dim. But feature I/O and XRSfm only support 256 dim by default.

[HailinYu0414]

Thank you for your reminder. The bug has been fixed 36f6fbe

We recommend you use SuperPoint, which can provide faster and more accurate localization in common scenes. The usage can be referred to here.

[zhd861564272]

Hi,thank you for your answer.A new problem occurred when I used the fix file in xrlocalization.Can you give me a hand ?Thank you.
Here is what went wrong.
Step 3: Re-extract/match with superpoint
100%|█████████████████████████████████████████| 540/540 [00:58<00:00, 9.25it/s]

100%|██████████████████████████████████████| 7162/7162 [00:52<00:00, 136.84it/s]
Step 4: Re-triangulate
terminate called after throwing an instance of 'std::bad_alloc'
what(): std::bad_alloc
recon.sh：行 56: 8591 已放弃 （核心已转储） ./bin/run_triangulation {SFM_DIR}/features.bin {REFINE_DIR}
run triangulation failed