登录
首页 » Python » Keras-vgg16--Dogs-vs.-Cats-master

Keras-vgg16--Dogs-vs.-Cats-master

于 2020-04-28 发布
0 224
下载积分: 1 下载次数: 4

代码说明:

说明:  VGG16的猫狗大战代码,效果不错,精度可以达到95%以上。(Vgg16 cat and dog battle code, good effect, accuracy can reach more than 95%.)

文件列表:

Keras-vgg16--Dogs-vs.-Cats-master, 0 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\500.csv, 3405 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\README.md, 483 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\predict.py, 1476 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500, 0 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\1.jpg, 24178 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\10.jpg, 22194 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\100.jpg, 25445 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\101.jpg, 2892 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\102.jpg, 23507 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\103.jpg, 23854 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\104.jpg, 30559 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\105.jpg, 20046 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\106.jpg, 29881 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\107.jpg, 9849 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\108.jpg, 15645 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\109.jpg, 27724 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\11.jpg, 14493 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\110.jpg, 49602 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\111.jpg, 28184 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\112.jpg, 7942 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\113.jpg, 14915 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\114.jpg, 23524 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\115.jpg, 21832 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\116.jpg, 17152 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\117.jpg, 12380 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\118.jpg, 41669 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\119.jpg, 22233 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\12.jpg, 31153 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\120.jpg, 15552 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\121.jpg, 21544 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\122.jpg, 28778 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\123.jpg, 13829 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\124.jpg, 11992 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\125.jpg, 23146 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\126.jpg, 6176 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\127.jpg, 28220 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\128.jpg, 10121 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\129.jpg, 13497 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\13.jpg, 27646 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\130.jpg, 11246 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\131.jpg, 38384 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\132.jpg, 14513 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\133.jpg, 12481 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\134.jpg, 27229 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\135.jpg, 24136 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\136.jpg, 31743 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\137.jpg, 3941 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\138.jpg, 16681 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\139.jpg, 30803 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\14.jpg, 16401 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\140.jpg, 20660 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\141.jpg, 25882 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\142.jpg, 14676 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\143.jpg, 36497 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\144.jpg, 29547 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\145.jpg, 43452 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\146.jpg, 51313 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\147.jpg, 22760 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\148.jpg, 29448 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\149.jpg, 18110 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\15.jpg, 32734 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\150.jpg, 12254 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\151.jpg, 6917 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\152.jpg, 27236 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\153.jpg, 12325 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\154.jpg, 17401 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\155.jpg, 31571 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\156.jpg, 24636 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\157.jpg, 27835 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\158.jpg, 33418 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\159.jpg, 20936 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\16.jpg, 16940 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\160.jpg, 26919 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\161.jpg, 16398 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\162.jpg, 15312 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\163.jpg, 14995 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\164.jpg, 16433 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\165.jpg, 18869 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\166.jpg, 19327 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\167.jpg, 22777 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\168.jpg, 16914 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\169.jpg, 14633 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\17.jpg, 15062 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\170.jpg, 33889 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\171.jpg, 26681 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\172.jpg, 27951 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\173.jpg, 12119 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\174.jpg, 15461 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\175.jpg, 16278 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\176.jpg, 54845 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\177.jpg, 27985 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\178.jpg, 35940 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\179.jpg, 26115 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\18.jpg, 34690 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\180.jpg, 32033 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\181.jpg, 36390 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\182.jpg, 22893 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\183.jpg, 20642 , 2019-11-07
Keras-vgg16--Dogs-vs.-Cats-master\test500\184.jpg, 9277 , 2019-11-07

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

  • FPGA
    一种基于FPGA实现的FFT结构 调从基本元器件开始的计算机硬件系统的设计与实现,大多设置在自动控制系,形成了与应用系统结合的计算机教育。 1966年多处理器平台FPGA 学习目标 (1) 理解为什么嵌入式系统使用多处理器 (2) 指出处理器中CPU和硬件逻辑的折衷 (FPGA-based FFT realize the structure of the tune from the beginning of the basic components of computer hardware system design and implementation, most of them located in the Automatic Control Department, formed a combination and application of computer education system. 1966 multi-processor FPGA platform for learning goals (1) to understand why the use of multi-processor embedded system (2) pointed out that the processor CPU and the hardware logic of compromise)
    2008-05-03 14:31:10下载
    积分:1
  • Lab1-Sortari+Cautari
    说明:  Basic sort methods implementation
    2019-03-25 19:49:13下载
    积分:1
  • matalab--optimization
    最优化理论和算法日益受到重视,已经渗透到各行各业中,并得到了广泛应用(Optimization theory and algorithm have attracted more and more attention, and have penetrated into all walks of life, and have been widely used)
    2017-11-20 16:43:11下载
    积分:1
  • 在matlab的simulink平台搭建闭环boost
    在matlab的simulink平台搭建闭环boost(Build Closed Loop Boost on the Simlink Platform of MATLAB)
    2020-06-22 02:40:01下载
    积分:1
  • Android手机应用管理源码
    Android手机应用管理源码,一个安卓手机上的应用管理程序,附有完整的源代码,Android的环境真不好调啊,没抓到运行截图,Android达人自己下载源码摸索吧,这个软件不但可以却手机上的应用进行管理,还具备进程管理、文件管理和系统管理等功能。
    2023-05-26 20:45:03下载
    积分:1
  • iSIGHT_ANSYS_Example
    关于isight工程实例,与ansys集成,实用性强(About iSIGHT project example, practicability is strong.)
    2018-09-17 16:11:23下载
    积分:1
  • Radar-Principle_3_DingLuFei
    雷达原理(第三版)丁鹭飞,雷达研究领域经典的基础类教材。文件包括各章的PPT以及PDF格式的电子全书。方便快速查阅和仔细研读相关知识。(The book, Radar Principles (3rd edition) by Ding Lufei, is a classical fundamental teaching material in the field of Radar research. The package includes PPT file of each chapter and the detailed e-book in pdf-format, which is very convnient for fast looking for or close reading up related knowledge.)
    2016-05-11 10:35:48下载
    积分:1
  • Propeuurties
    c++Primer书籍电子版,让读者可以在电脑或者手机方便的阅读。(C++ Primer Book Electronic edition, so that readers can easily read on the computer or mobile phone.)
    2020-06-24 19:20:02下载
    积分:1
  • pangbanduixiao
    说明:  基于MMSE准则的自适应旁瓣对消,平面阵的三维天线方向图计算,matlab仿真(Adaptive sidelobe cancellation based on MMSE criterion, 3-D antenna pattern calculation of planar array, matlab simulation)
    2020-08-03 21:48:34下载
    积分:1
  • Given more than ten kinds of relevant OFDM channel estimation methods MATLAB cla...
    给出了十余种有关OFDM信道估计方法的MATLAB经典程序-Given more than ten kinds of relevant OFDM channel estimation methods MATLAB classical procedures
    2023-01-15 12:15:04下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载