Cruiser-GroundStation

Introduction

Ground station algorithms for Cruiser project which is used to detect whether there is any abnormal behavior you have defined occurs in the video surveillance. It’s going to alert when it happens.

Collaborators

• @ShoupingShan
• @finaldong

  Functions

• Object detection and classification
• Behavior detection

  Platform

• Ubuntu 14.04
• OpenCV 2.4.10
• CUDA 8.0

• Darknet YOLO CNN

  Demo

  

  How to run

   $: git clone git@github.com:ShoupingShan/Abnormal-behavior-Detection.git
   $: cd Abnormal-behavior-Detection
   $: make
   $: wget https://pjreddie.com/media/files/yolo.weights
   $: ./darknet detector demo cfg/coco.data cfg/yolo.cfg yolo.weights -c 0

  Notes

  Makefile
  This is what I use, uncomment if you know your arch and want to specify

  ARCH= -gencode arch=compute_50,code=compute_50

  demo.c

  line 147 and line 154

  Make sure you have replaced your own path!

  How to train

  First, suppose you have collected your training video files such as "samples.avi".

  Please open and run Video_cut/main.cpp then you can get many subfiles and each of them is 1 second. Delete some wrong files if exist(sometimes happens).

  Mark sure these subfiles obeying this principle: rename the filename as "f****.avi"(starts with ‘f’) if it is abnormal. Otherwise, you needn’t rename it.

  Return to the Terminal:ls > ../dir.txt(get file path)

  Make a copy of yolo program, and replace src/ by train/src,you can get same number of subfiles but ended with ‘.dat‘.

  Return to the Terminal:ls > ../dir.txt(get file path)

  Open train/SVM, train this model automatically.

  Copy alpha.txt and out.txt to yolo files, and amend demo.c.

Contact Us

Email: shp395210@outlook.com