A Python implementation of the Locality Preserving Matching (LPM) method for pruning outliers in image matching.

Related tags

Deep Learning LPM_Python
Overview

LPM_Python

A Python implementation of the Locality Preserving Matching (LPM) method for pruning outliers in image matching.

The code is established according to the MATLAB version https://github.com/jiayi-ma/LPM and supposed to have the same output and similar time cost. The parameters are tunable inside the function LPM_filter in LPM.py.

If you find this code useful for your research, plese cite the paper:

@article{ma2019locality,
  title={Locality preserving matching},
  author={Ma, Jiayi and Zhao, Ji and Jiang, Junjun and Zhou, Huabing and Guo, Xiaojie},
  journal={International Journal of Computer Vision},
  volume={127},
  number={5},
  pages={512--531},
  year={2019},
  publisher={Springer}
}

USAGE

Dependencies: numpy and sklearn packages are required for the core function LPM_filter,

opencv-python and scipy are additionally required to run the demo.

After installing dependencies, just run

python demo.py

for a simple example.

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Comments
  • Understanding .mat file with your code

    Understanding .mat file with your code

    Thank you for sharing your work. Could you please answer this question what are I1, I2, X and Y meant, and how do they relate to the ground truth? And how do you compute TP, TN, FP, FN to get the precision and recall?

    I appreciate any help you can provide.

    opened by Mohamed-DL 2
Owner
AoxiangFan
Master student @WuhanUniversity, China. Interested in machine learning and 3D computer vision.
AoxiangFan
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