登录
首页 » Python » AbnormalBehaviorDetection-master

AbnormalBehaviorDetection-master

于 2019-04-23 发布
0 189
下载积分: 1 下载次数: 17

代码说明:

说明:  基于光流特征的监控视频异常行为检测 使用CNN,RNN在UCSD数据库中实现 使用Keras,python3.6(Abnormal Behavior Detection of Monitoring Video Based on Optical Flow Characteristics)

文件列表:

AbnormalBehaviorDetection-master, 0 , 2017-06-14
AbnormalBehaviorDetection-master\README.md, 196 , 2017-06-14
AbnormalBehaviorDetection-master\bak, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.1, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.1\__pycache__, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.1\__pycache__\cnn_abd.cpython-36.pyc, 1662 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.1\__pycache__\prepdata.cpython-36.pyc, 4685 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.1\cnn_abd.py, 1540 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.1\exec.py, 1227 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.1\prepdata.py, 5471 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2.1, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2.1\__pycache__, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2.1\__pycache__\abd_model_ini.cpython-36.pyc, 1933 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2.1\__pycache__\prepdata.cpython-36.pyc, 4200 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2.1\abd_model_ini.py, 1789 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2.1\bicnn_eval.py, 461 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2.1\bicnn_train.py, 1515 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2.1\prepdata.py, 4401 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2.1\try.py, 558 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2\__pycache__, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2\__pycache__\abd_model_ini.cpython-36.pyc, 1933 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2\__pycache__\prepdata.cpython-36.pyc, 4200 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2\abd_model_ini.py, 1789 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2\bicnn_eval.py, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2\bicnn_train.py, 1270 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2\prepdata.py, 4401 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.2\try.py, 558 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3.1_rnndone, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3.1_rnndone\__pycache__, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3.1_rnndone\__pycache__\abd_model_ini.cpython-36.pyc, 2468 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3.1_rnndone\__pycache__\prepdata.cpython-36.pyc, 6144 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3.1_rnndone\abd_model_ini.py, 2405 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3.1_rnndone\bicnn_train.py, 1984 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3.1_rnndone\bilrnn_train.py, 2918 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3.1_rnndone\eval.py, 823 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3.1_rnndone\prepdata.py, 6636 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3.1_rnndone\try.py, 137 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3_rnn_cnn%2B, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3_rnn_cnn%2B\__pycache__, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3_rnn_cnn%2B\__pycache__\abd_model_ini.cpython-36.pyc, 1933 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3_rnn_cnn%2B\__pycache__\prepdata.cpython-36.pyc, 4200 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3_rnn_cnn%2B\abd_model_ini.py, 2398 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3_rnn_cnn%2B\bicnn_train.py, 1984 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3_rnn_cnn%2B\bilrnn_train.py, 2358 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3_rnn_cnn%2B\eval.py, 823 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3_rnn_cnn%2B\prepdata.py, 6636 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0.3_rnn_cnn%2B\try.py, 137 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0\__pycache__, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0\__pycache__\cnn_abd.cpython-36.pyc, 122 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0\__pycache__\prepdata.cpython-36.pyc, 3704 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0\cnn_abd.py, 0 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0\exec.py, 969 , 2017-06-14
AbnormalBehaviorDetection-master\bak\src0\prepdata.py, 4236 , 2017-06-14
AbnormalBehaviorDetection-master\demosrc, 0 , 2017-06-14
AbnormalBehaviorDetection-master\demosrc\lstm_text_generation.py, 3350 , 2017-06-14
AbnormalBehaviorDetection-master\demosrc\rnn_lstm.py, 5064 , 2017-06-14
AbnormalBehaviorDetection-master\doc, 0 , 2017-06-14
AbnormalBehaviorDetection-master\doc\arrary_decl.txt, 467 , 2017-06-14
AbnormalBehaviorDetection-master\doc\bicnn_struct.txt, 409 , 2017-06-14
AbnormalBehaviorDetection-master\doc\process.txt, 390 , 2017-06-14
AbnormalBehaviorDetection-master\doc\project_struct.txt, 380 , 2017-06-14
AbnormalBehaviorDetection-master\image, 0 , 2017-06-14
AbnormalBehaviorDetection-master\image\avg_picture.png, 27479 , 2017-06-14
AbnormalBehaviorDetection-master\image\resize.png, 26869 , 2017-06-14
AbnormalBehaviorDetection-master\image\subavg_picture1.png, 24934 , 2017-06-14
AbnormalBehaviorDetection-master\image\subavg_picture2.png, 26832 , 2017-06-14
AbnormalBehaviorDetection-master\script, 0 , 2017-06-14
AbnormalBehaviorDetection-master\script\gen_tag.cmd, 109 , 2017-06-14
AbnormalBehaviorDetection-master\src, 0 , 2017-06-14
AbnormalBehaviorDetection-master\src\__pycache__, 0 , 2017-06-14
AbnormalBehaviorDetection-master\src\__pycache__\abd_model_ini.cpython-36.pyc, 2667 , 2017-06-14
AbnormalBehaviorDetection-master\src\__pycache__\prepdata.cpython-36.pyc, 6144 , 2017-06-14
AbnormalBehaviorDetection-master\src\abd_model_ini.py, 2778 , 2017-06-14
AbnormalBehaviorDetection-master\src\bicnn_train.py, 2060 , 2017-06-14
AbnormalBehaviorDetection-master\src\bilrnn_train.py, 3428 , 2017-06-14
AbnormalBehaviorDetection-master\src\eval.py, 2190 , 2017-06-14
AbnormalBehaviorDetection-master\src\prepdata.py, 6636 , 2017-06-14
AbnormalBehaviorDetection-master\src\try.py, 185 , 2017-06-14

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论


0 个回复

  • 新标准C++习题解答
    说明:  新标准C++程序设计教程/重点大学计算机专业系列教材配套习题解答(New Standard C++ Programming Course/Solutions to Exercises in Computer Series Textbooks of Key Universities)
    2021-01-05 20:38:53下载
    积分:1
  • 18第十八章值迭代策略迭代
    说明:  机器学习及其matlab实现一书第十八章的代码,有详细的注释,供初学者借鉴,比较好学习强化学习资料。(Machine learning and matlab implementation Chapter 18 of the code, there are detailed notes for beginners to learn from, better reinforcement learning materials.)
    2021-01-27 21:58:40下载
    积分:1
  • 迭代法求根
    说明:  用迭代法求 x=根号a。求平方根的迭代公式为:X(n+1)=(Xn+a/Xn) /2。(Iterative method is used to find x = root a. The iteration formula for finding square root is X(n+1)=(Xn+a/Xn)/2.)
    2020-06-24 19:20:02下载
    积分:1
  • the_2
    永磁同步电机静态仿真,ansoft15.0编程的(Static simulation of permanent magnet synchronous motor)
    2018-03-26 19:01:08下载
    积分:1
  • efem3d
    清华大学张雄的物质点法源程序,非常好的一本书。(Tsinghua University Zhang Xiong material point source, a very good book.)
    2021-01-08 12:18:51下载
    积分:1
  • NMES_Margrave
    书中详细介绍了地震勘探中的一些非常重要的数值计算方法,并用matlab将其算法实现,有助于理解地震勘探的基本原理 。(The book details some of the most important numerical calculation methods in seismic exploration, and uses Matlab to implement its algorithm, which is helpful to understand the basic principles of seismic exploration.)
    2018-08-10 11:30:07下载
    积分:1
  • 恒虚警监测
    用于雷达的恒虚警检测程序,这里你可以进行雷达信号的恒虚警检测(The constant virtual police detection procedure for radar, where you can detect the constant false alarm of radar signal)
    2017-12-15 22:26:16下载
    积分:1
  • mutisencer navgation
    GNSS与惯性及多传感器组合导航系统原理(第二版)-光盘资料(GNSS and inertial and multi-sensor integrated navigation system principles (Second Edition) - CD-ROM data)
    2017-08-22 11:09:27下载
    积分:1
  • sourcecode
    说明:  C++程序设计 机械工业出版社 书本例题源码(C + + industrial machinery Publishing House)
    2020-09-24 19:57:05下载
    积分:1
  • CA-CFAR
    这是一个关于单元平均恒虚警的程序,当做目标检测时,单元平均恒虚警检测非常有用!(this is a programm about CA-CFAR, u can use it to perform constant false alarm rate detection when needed.)
    2017-09-29 20:31:29下载
    积分:1
  • 696518资源总数
  • 104603会员总数
  • 38今日下载