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yingxin-jia / SuperGlue-pytorch

[SuperGlue: Learning Feature Matching with Graph Neural Networks] This repo includes PyTorch code for training the SuperGlue matching network on top of SIFT keypoints and descriptors.
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How to evaluate and test the data after training #9

Open ZhouAo-ZA opened 4 years ago

ZhouAo-ZA commented 4 years ago

After using the COCO data set for training, 1、 how to evaluate and test the accuracy, 2、the training efficiency is too low. Has anyone tried to modify it to batch training? 3、The single-machine multi-card merge time reports the dimensionality error. Does anyone try to solve it?

Thanks to HeatherJiaZG for the training code, but unfortunately he doesn't seem to maintain this library anymore. Someone can provide some help, thanks a lot

Liukailong9560 commented 2 years ago

Hi, Did you solve this problem?

sunset326 commented 1 year ago

老哥，请问你知道训练结束后如何评估吗

Shuhul24 commented 1 year ago

I think we can execute the match_pairs.py to check the matching (visualizations), but the problem is that when I run the match_path.py file, the error comes to be

Will write matches to directory "dump_match_pairs"
[ WARN:0@1.733] global loadsave.cpp:248 findDecoder imread_('/home/shuhulh/assets/scannet_sample_images/scene0711_00_frame-001680.jpg'): can't open/read file: check file path/integrity
[ WARN:0@1.733] global loadsave.cpp:248 findDecoder imread_('/home/shuhulh/assets/scannet_sample_images/scene0711_00_frame-001995.jpg'): can't open/read file: check file path/integrity
Problem reading image pair: /home/shuhulh/assets/scannet_sample_images/scene0711_00_frame-001680.jpg /home/shuhulh/assets/scannet_sample_images/scene0711_00_frame-001995.jpg

Is there any way I can check how this can be avoided?