extremely slow running time of Gendarmenmarkt dataset about local-feature-evaluation HOT 12 CLOSED

Which Matlab version are you using and what GPU does your system have?

from local-feature-evaluation.

matlab R2015b, GPU is TITAN X (Pascal). Below is the last output information I got:
....
WARNING: Ignoring image 981374980_1126f5a860_o.jpg, because input does not exist.
WARNING: Ignoring image 999273378_59e22a0646_o.jpg, because input does not exist.
Fusing image [1/1016] in 8.973s (29945 points)

I downloaded your supplied database file, and have not seen these warnings when loading features and matches by using your script: reconstruction_pipeline.py

from local-feature-evaluation.

You need MATLAB 2016b or newer to run the matching on the GPU, which is why the pipeline is so slow for you. The matching part takes most of the time for most datasets. If you don’t have access to a newer matlab version, you could try and code the matching yourself using OpenCV.

from local-feature-evaluation.

Matching has done. I already run the matching_pipeline in Matlab. The slow running time is the final step in your instruction, i.e.,

After finishing the matching pipeline, run the reconstruction using:
python scripts/reconstruction_pipeline.py
--dataset_path path/to/Fountain
--colmap_path path/to/colmap/build/src/exe

And it comes to the final step "dense_fuser" as I saw the running thread of it.
According to your instruction, this step should not be so slow. Do I need to setup something?

from local-feature-evaluation.

Are you running the dense fusion on a network drive by any chance? Or a slow drive in general?

from local-feature-evaluation.

Should not be this case. The disk I/O works well. I checked that there is no newer file was generated even the thread of "dense_fuser" was running over 5 days....
Previously, I used the smaller dataset "Fountain", everything went well.
Can you give me some instructions to solve this problem?

from local-feature-evaluation.

How much RAM do you have on the machine?

from local-feature-evaluation.

256GB with 40 CPU(2.6GHz).

from local-feature-evaluation.

Could you share the dense reconstruction folder with me?

from local-feature-evaluation.

Sure. The size of folder is large (over 1 GB), so I uploaded it on my homepage. Please refer to: www.nlpr.ia.ac.cn/fanbin/dense.rar
to get it.

from local-feature-evaluation.

Did you find any problem in my running?

from local-feature-evaluation.

Please retry with the latest version of the benchmark. I upgraded the benchmark to the latest COLMAP version and am currently updating the numbers for the existing descriptors.

from local-feature-evaluation.