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Visual Localization with DUSt3R
Dataset preparation
CambridgeLandmarks
Each subscene should look like this:
Cambridge_Landmarks
ββ mapping
β ββ GreatCourt
β β ββ colmap/reconstruction
β β ββ cameras.txt
β β ββ images.txt
β β ββ points3D.txt
ββ kapture
β ββ GreatCourt
β β ββ query # https://github.com/naver/kapture/blob/main/doc/datasets.adoc#cambridge-landmarks
β ...
ββ GreatCourt
β ββ pairsfile/query
β β ββ AP-GeM-LM18_top50.txt # https://github.com/naver/deep-image-retrieval/blob/master/dirtorch/extract_kapture.py followed by https://github.com/naver/kapture-localization/blob/main/tools/kapture_compute_image_pairs.py
β ββ seq1
β ...
...
7Scenes
Each subscene should look like this:
7-scenes
ββ chess
β ββ mapping/ # https://github.com/naver/kapture/blob/main/doc/datasets.adoc#1-7-scenes
β ββ query/ # https://github.com/naver/kapture/blob/main/doc/datasets.adoc#1-7-scenes
β ββ pairsfile/query/
β ββ APGeM-LM18_top20.txt # https://github.com/naver/deep-image-retrieval/blob/master/dirtorch/extract_kapture.py followed by https://github.com/naver/kapture-localization/blob/main/tools/kapture_compute_image_pairs.py
...
Aachen-Day-Night
Aachen-Day-Night-v1.1
ββ mapping
β ββ colmap/reconstruction
β β ββ cameras.txt
β β ββ images.txt
β β ββ points3D.txt
ββ kapture
β ββ query # https://github.com/naver/kapture/blob/main/doc/datasets.adoc#2-aachen-day-night-v11
ββ images
β ββ db
β ββ query
β ββ sequences
ββ pairsfile/query
ββ fire_top50.txt # https://github.com/naver/fire/blob/main/kapture_compute_pairs.py
InLoc
InLoc
ββ mapping # https://github.com/naver/kapture/blob/main/doc/datasets.adoc#6-inloc
ββ query # https://github.com/naver/kapture/blob/main/doc/datasets.adoc#6-inloc
ββ pairsfile/query
ββ pairs-query-netvlad40-temporal.txt # https://github.com/cvg/Hierarchical-Localization/blob/master/pairs/inloc/pairs-query-netvlad40-temporal.txt
Example Commands
With visloc.py
you can run our visual localization experiments on Aachen-Day-Night, InLoc, Cambridge Landmarks and 7 Scenes.
# Aachen-Day-Night-v1.1:
# scene in 'day' 'night'
# scene can also be 'all'
python3 visloc.py --model_name DUSt3R_ViTLarge_BaseDecoder_512_dpt --dataset "VislocAachenDayNight('/path/to/prepared/Aachen-Day-Night-v1.1/', subscene='${scene}', pairsfile='fire_top50', topk=20)" --pnp_mode poselib --reprojection_error_diag_ratio 0.008 --output_dir /path/to/output/Aachen-Day-Night-v1.1/${scene}/loc
# InLoc
python3 visloc.py --model_name DUSt3R_ViTLarge_BaseDecoder_512_dpt --dataset "VislocInLoc('/path/to/prepared/InLoc/', pairsfile='pairs-query-netvlad40-temporal', topk=20)" --pnp_mode poselib --reprojection_error_diag_ratio 0.008 --output_dir /path/to/output/InLoc/loc
# 7-scenes:
# scene in 'chess' 'fire' 'heads' 'office' 'pumpkin' 'redkitchen' 'stairs'
python3 visloc.py --model_name MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt --dataset "VislocSevenScenes('/path/to/prepared/7-scenes/', subscene='${scene}', pairsfile='APGeM-LM18_top20', topk=1)" --pnp_mode poselib --reprojection_error_diag_ratio 0.008 --output_dir /path/to/output/7-scenes/${scene}/loc
# Cambridge Landmarks:
# scene in 'ShopFacade' 'GreatCourt' 'KingsCollege' 'OldHospital' 'StMarysChurch'
python3 visloc.py --model_name DUSt3R_ViTLarge_BaseDecoder_512_dpt --dataset "VislocCambridgeLandmarks('/path/to/prepared/Cambridge_Landmarks/', subscene='${scene}', pairsfile='APGeM-LM18_top20', topk=1)" --pnp_mode poselib --reprojection_error_diag_ratio 0.008 --output_dir /path/to/output/Cambridge_Landmarks/${scene}/loc