Sniffer-Net

A unified network structure specialized for smoke detection and concentration evaluation in the wild.

Demo

This is a demo of our Sniffer-Net (including smoke detection, optical flow inpainting, smoke concentration evaluation).

Several smoke datasets

Institution	Website	Size	Quantity
Italy Modena University	http://imagelab.ing.unimore.it/visor/	/	/
Keimyung University	http://cvpr.kmu.ac.kr/	320x240 video	38
University of Bilkent	http://signal.ee.bilkent.edu.tr/visifire/	720x576 video	4
University of Split	http://wildfire.fesb.hr/index.php	720x576 video	5
University of Salerno	https://mivia.unisa.it/	multi-resolution video	149
University of Milan	http://homes.di.unimi.it/genovese/wild/wildfire.htm	320x240 video	20
FIRESENSE	http://doi.org/10.5281/zenodo.836749	multi-resolution video	49
USTC smoke dataset	http://smoke.ustc.edu.cn/	1920x1080 video	>30
Ours(Sniffer-Net)	https://github.com/namemzy/Sniffer-Net	1920x1080 video	30

Foreign Websites Download slowly. We have downloaded them and put them on Baidu Yunpan.

The dataset is available on:

image pairs

https://pan.baidu.com/s/1dJS7aKZKILOK5LffN1nu4Q

videos

https://pan.baidu.com/s/1BDkt2sEjZI5gRH5NZaJflw

Some other datasets：

https://pan.baidu.com/s/11uJgfiKI8_Ew2eG-h7sF4A

fisheye lens images

https://pan.baidu.com/s/1woqMBD7qwQMciccOpmU2CQ

Implementation

Prerequisites

• Ubuntu 16.04
• Pytorch 1.0
• CUDA 8.0 and cuDNN 5.1
• opencv3

Installation

• Clone this repo
• Install PyTorch and dependencies from http://pytorch.org
• Waiting for update ...

MIT License

Copyright (c) 2019 namemzy

Citation

If you find this project useful for your research, please cite:

@{smoke detection project,
author = {namemzy},
title = {Sniffer-Net},
website = {https://github.com/namemzy/Sniffer-Net},
month = {April},
year = {2019}
}