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Hi, thank you for this code! Can you please upload and share the models needed to run it successfully?
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In my experiment， lightglue+superpoint is better than LightGlue + disk，which is not consistent with lightglue paper:
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Hit the subscribe button on the right of this issue if you wish to be notified of the training and evaluation code release in a separate repo. Please do not reply to this issue to not spam other subsc…
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Hi, your work is really great and helpful. Thank for your effort to maintain this repo. I wonder if Superpoint+LightGlue onnx have any issues of license for commercial use ?
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Hello,
Has anybody tried to use these ONNX models on C++? I'm trying to do so but I'm getting a Segmentation Fault during the inference. The model is loaded without any problem and the input shape …
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Hi, you did a good job, this repo is really help ! I wonder if Superpoint+LightGlue have any issues of license for commercial use ? Does it infringe copyright of Superpoint of MagicLeap ( https://gith…
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# 平台(如果交叉编译请再附上交叉编译目标平台):
# Platform(Include target platform as well if cross-compiling):
ubuntu 18.04.6 LTS
# Github版本:
# Github Version:
commit ID：1ea55f467fb231655cf1e08f77d4a0f1043c4c29
…
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Hi! Thanks for your great work! But I don't quite understand some parts of the code
# About the training and results
1. How much does the pre-training affect the final performance ? Have you tried…
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use the command to export the end2end model
`python export.py \
--img_size 512 \
--extrac…
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I exported the SuperPoint model with the maximum keypoint count of 1024. Then, I integrated this model for a SLAM system. For some images, inference takes around 6-8s with this warning and gives 1024 …