etrulls

(disk-cpu) trulls ~/src/disk $ colmap exhaustive_matcher --database_path out/xxx-10fps-disk-16d/database2.db --SiftMatching.use_gpu 0

============================================================================== 
Exhaustive feature matching
============================================================================== 

Matching block [1/31, 1/31] in 19.855s
Matching block [1/31, 2/31] in 0.016s
Matching block [1/31, 3/31] in 0.010s
Matching block [1/31, 4/31] in 0.017s

etrulls

root@e6c5456fa8b4:/home/trulls/src/disco-code/points# python extract_benchmark.py

[['2020-05-25/768-depth', 504, True]]

Processing /home/trulls/imw-2020/sagrada_familia and saving to out/2020-05-25/768-depth-imsize-504-nms-5/sagrada_familia
  0%|                                                                                                                               | 0/100 [00:00<?, ?it/s]
Traceback (most recent call last):
  File "detect.py", line 144, in <module>
    described_samples = extract(extraction_method, dataset, args.h5_path)
  File "detect.py", line 101, in extract

etrulls

Processing /home/trulls/imw-2020/milan_cathedral and saving to out/2020-05-25/768-depth-imsize-960/milan_cathedral
  0%|                                                                                                                               | 0/100 [00:00<?, ?it/s]ERROR: Unexpected bus error encountered in worker. This might be caused by insufficient shared memory (shm).
ERROR: Unexpected bus error encountered in worker. This might be caused by insufficient shared memory (shm).
Traceback (most recent call last):
  File "/usr/lib/python3.8/multiprocessing/queues.py", line 239, in _feed
    obj = _ForkingPickler.dumps(obj)
  File "/usr/lib/python3.8/multiprocessing/reduction.py", line 51, in dumps
    cls(buf, protocol).dump(obj)
  File "/usr/local/lib/python3.8/dist-packages/torch/multiprocessing/reductions.py", line 333, in reduce_storage
    fd, size = storage._share_fd_()

etrulls

WAF-N16 (8k)

CV2-RANSAC, Best : 0.75 -> 0.4290487232505875
NODEGENSAC, Best : 0.5 -> 0.45799136562326015
DEGENSAC, Best : 1 -> 0.5441916837751245
GCRANSAC, Best : 1.25 -> 0.5153767755827378
MAGSAC, Best : 2 -> 0.5071992512758609

WASF-N16 (8k)

etrulls

NODEGENSAC, CV-AKAZE -> Best mAP=0.3438 at th=0.25
NODEGENSAC, CV-DoG/GeoDesc -> Best mAP=0.5078 at th=0.2
NODEGENSAC, CV-DoG/HardNet -> Best mAP=0.6288 at th=0.25
NODEGENSAC, CV-DoG/LogPolarDesc -> Best mAP=0.5732 at th=0.2
NODEGENSAC, CV-DoG/SOSNet -> Best mAP=0.5701 at th=0.25
NODEGENSAC, CV-ORB -> Best mAP=0.2359 at th=0.75
NODEGENSAC, CV-RootSIFT -> Best mAP=0.5638 at th=0.25
NODEGENSAC, CV-SIFT -> Best mAP=0.5386 at th=0.25
NODEGENSAC, CV-SURF -> Best mAP=0.3052 at th=0.75
NODEGENSAC, ContextDesc -> Best mAP=0.6058 at th=0.5

etrulls

diff --git a/run.py b/run.py
index 2d1fffd5..8f7d66ae 100644
--- a/run.py
+++ b/run.py
@@ -165,7 +165,10 @@ def main(cfg):
             match_jobs = create_eval_jobs(feature_jobs, "match", cfg, job_dict)

             # Filter
-            match_inlier_jobs = create_eval_jobs(match_jobs, "filter", cfg, job_dict)
+            if cfg_m.refine_inliers:

etrulls

import numpy as np
from third_party.colmap.scripts.python.read_write_model import read_model, qvec2rotmat

src = '../rebuttal/results-colmap/'
considered = [5, 10, 25, 50, 100, 150, 200, 250, 300, 400, 500, 600]

cameras = {}
images = {}
names = {}

etrulls

(...)
-- Packing "phototourism"/"united_states_capitol"/stereo, fold: 1/3, metric: avg_num_keypoints [0.69 s]
 -- Packing "phototourism"/"united_states_capitol"/stereo, fold: 1/3, metric: num_inliers [28.87 s]
 -- Packing "phototourism"/"united_states_capitol"/stereo, fold: 1/3, metric: matching_scores_depth_projection [32.78 s]
 -- Packing "phototourism"/"united_states_capitol"/stereo, fold: 1/3, metric: repeatability [6.53 s]
 -- Packing "phototourism"/"united_states_capitol"/stereo, fold: 1/3, metric: qt_map [6.49 s]
 -- Packing "phototourism"/"united_states_capitol"/stereo, fold: 1/3, metric: timings [0.06 s]
 -- Packing "phototourism"/"united_states_capitol"/stereo, fold: 2/3, metric: avg_num_keypoints [0.06 s]
 -- Packing "phototourism"/"united_states_capitol"/stereo, fold: 2/3, metric: num_inliers [30.00 s]
 -- Packing "phototourism"/"united_states_capitol"/stereo, fold: 2/3, metric: matching_scores_depth_projection [33.06 s]

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 -- computing filter
WARNING: ./jobs/5e2d15ede4bfc131456db7c0063449b99f62fbe4bbb159ab2a9b835454958907 already exists!
/home/trulls_google_com/miniconda3/envs/opencv-3.7/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint8 = np.dtype([("qint8", np.int8, 1)])
/home/trulls_google_com/miniconda3/envs/opencv-3.7/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_quint8 = np.dtype([("quint8", np.uint8, 1)])
/home/trulls_google_com/miniconda3/envs/opencv-3.7/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will

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STEREO ON TEST

mAPs -> [0.5286 0.5233 0.5125 0.508  0.4971 0.4921 0.4856 0.4787 0.47   0.4659
 0.4653 0.4643 0.4608 0.4556 0.4489 0.4204 0.3142 0.2669 0.2481 0.2253
 0.1836 0.1723 0.1639]
consecutive diffs -> [0.0053 0.0108 0.0045 0.0109 0.005  0.0065 0.0069 0.0087 0.0041 0.0006
 0.001  0.0035 0.0052 0.0067 0.0285 0.1062 0.0473 0.0188 0.0228 0.0417
 0.0113 0.0084]
Stereo on "test" (23 methods): Mean -> 0.4022, min -> 0.1639, max -> 0.5286, std -> 0.1230, smallest delta -> 0.0006, mean delta -> 0.0166