Comments (3)
3) Extract global features (we will use AP-GeM here)
cd ${WORKING_DIR}/deep-image-retrieval
${PYTHONBIN} -m dirtorch.extract_kapture --kapture-root ${WORKING_DIR}/${DATASET}/map_plus_test/ --checkpoint dirtorch/data/Resnet101-AP-GeM-LM18.pt --gpu 0 1 2 3
mkdir -p ${WORKING_DIR}/${DATASET}/global_features/Resnet101-AP-GeM-LM18/global_features
mv ${WORKING_DIR}/${DATASET}/map_plus_test/reconstruction/global_features/Resnet101-AP-GeM-LM18/* ${WORKING_DIR}/${DATASET}/global_features/Resnet101-AP-GeM-LM18/global_features/
rm -rf ${WORKING_DIR}/${DATASET}/map_plus_test/reconstruction/global_features/Resnet101-AP-GeM-LM18
4) Extract local features (we will use R2D2 here)
cd ${WORKING_DIR}/r2d2
${PYTHONBIN} extract_kapture.py --model models/r2d2_WASF_N8_big.pt --kapture-root ${WORKING_DIR}/${DATASET}/map_plus_test/ --min-scale 0.3 --min-size 128 --max-size 9999 --top-k ${KPTS} --gpu 0 1 2 3
mkdir -p ${WORKING_DIR}/${DATASET}/local_features/r2d2_WASF_N8_big/descriptors
mv ${WORKING_DIR}/${DATASET}/map_plus_test/reconstruction/descriptors/r2d2_WASF_N8_big/* ${WORKING_DIR}/${DATASET}/local_features/r2d2_WASF_N8_big/descriptors/
mkdir -p ${WORKING_DIR}/${DATASET}/local_features/r2d2_WASF_N8_big/keypoints
mv ${WORKING_DIR}/${DATASET}/map_plus_test/reconstruction/keypoints/r2d2_WASF_N8_big/* ${WORKING_DIR}/${DATASET}/local_features/r2d2_WASF_N8_big/keypoints/
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.57.02 Driver Version: 470.57.02 CUDA Version: 11.4 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA RTX A6000 Off | 00000000:1D:00.0 Off | Off |
| 54% 79C P2 260W / 300W | 41931MiB / 48685MiB | 83% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 NVIDIA RTX A6000 Off | 00000000:20:00.0 Off | Off |
| 30% 27C P8 11W / 300W | 2MiB / 48685MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 2 NVIDIA RTX A6000 Off | 00000000:21:00.0 Off | Off |
| 30% 27C P8 11W / 300W | 2MiB / 48685MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 3 NVIDIA RTX A6000 Off | 00000000:24:00.0 Off | Off |
| 30% 27C P8 7W / 300W | 2MiB / 48685MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 489977 C .../envs/kapture/bin/python3 41929MiB |
+-----------------------------------------------------------------------------+
from kapture-localization.
Hi,
the feature extraction scripts (deep-image-retrieval / r2d2) do not support multi-gpu (neither does the matching scripts).
If your dataset is too big, you can always split the kapture data in 4 (you would have to create 4 kapture folders each with a fourth of records_camera.txt, and using symlinks for the rest, to avoid copying the images) and launch it on each individual gpu (then move the extracted features back to the main folder).
from kapture-localization.
Thanks. I'll check it!
from kapture-localization.
Related Issues (20)
- localize pipeline doesn't make trajectories.txt for localized result HOT 4
- Implementation of precision@k and recall@k evaluation HOT 1
- Pairsfile for Inloc dataset HOT 2
- Localization Pipeline HOT 1
- No trajectory.txt for the query images in RobotCar and Aachen Datasets HOT 1
- RGBD pipeline HOT 2
- Time Profiling HOT 1
- Visualization of feature correspondence between query image to mapping image HOT 1
- How to apply netVLAD + SIFT with kapture-localization? HOT 4
- Some images are not localized using localSfM HOT 4
- colmap_gv does not work. HOT 1
- What's the role of depth information in rgbd pipeline? HOT 3
- Error in running kapture_download_dataset.py update HOT 3
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- Get global_SFM and local_SFM results different from the listed benchmark results HOT 4
- Question regarding pipeline_localization
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- About the pretrained checkpoint for r2d2 local features used on the benchmark HOT 2
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from kapture-localization.