Passive-None-Line-of-Sight-Recognition

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Passive-None-Line-of-Sight-Recognition

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Passive-None-Line-of-Sight-Recognition 최신버젼 다운로드

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# Passive-None-Line-of-Sight-Recognition

# About
Code for the paper 'Accurate but Fragile Passive None-Line-of-Sight Recognition'. 
Implementation is done in Pytorch 1.1 and runs with 3.6. This repository contains implementation code for CNN NLOS Recognition and using white-box attacks to verify its robustness. 
Paper: [地址] 
The datasets generated during and/or analyzed during the current study are available at https://pan.baidu.com/s/13pAX1el0fH-lKhpqanSFfw the password of “iy7d”.
 
![二维码](https://user-images.githubusercontent.com/52912822/198873284-36e596b9-a35e-41f0-adfa-a3b7b6991799.png) 
Prepare dataset 
The files of the data folder are used to reproducing results in the manuscript (and its supplementary information). 
Here we demonstrate how to prepare data for NLOS Recognition. 
1. How to get simulation data 
Assume that you have already through below urls downloaded the Mnist data to Passive \data\raw. 
urls = [ 
 'http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz', 
 'http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz', 
 'http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz', 
 'http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz', 
 ] 
Assumption that the prior information of the setting (supplementary information, Table S2) has known, then refer to https://github.com/Computational-Periscopy/Ordinary-Camera Ordinary-Camera/Functions/simulate_A.py to compute light transport matrix A. 
2. How to get reconstruction data 
Assume that camera measurement have obtained, refer to https://github.com/Computational-Periscopy/Ordinary-Camera script 'fig4_column_c.m', then you can got reconstruction data. 
Note that: You should modify the parameter settings according to your experimental system. 
# Reproduction
If you have any questions about the reproduction of the article, please contact Yaqin Zhang. E-mail number: 493834755@qq.com or zhangyaqin202102@163.com.

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