登录
首页 » Python » unet-master 2

unet-master 2

于 2020-06-29 发布
0 230
下载积分: 1 下载次数: 4

代码说明:

说明:  使用unet对图像进行分割的源码,里面有训练集,可以根据自己的需要更换训练数据。(Use the source code of the image segmentation using UNET, which has a training set, you can change the training data according to your own needs.)

文件列表:

unet-master, 0 , 2020-06-24
unet-master\trainUnet.ipynb, 9916 , 2020-06-24
__MACOSX, 0 , 2020-06-29
__MACOSX\unet-master, 0 , 2020-06-29
__MACOSX\unet-master\._trainUnet.ipynb, 212 , 2020-06-24
unet-master\.DS_Store, 6148 , 2020-06-29
__MACOSX\unet-master\._.DS_Store, 120 , 2020-06-29
unet-master\dataPrepare.ipynb, 3831 , 2019-02-21
__MACOSX\unet-master\._dataPrepare.ipynb, 212 , 2019-02-21
unet-master\LICENSE, 1065 , 2019-02-21
__MACOSX\unet-master\._LICENSE, 212 , 2019-02-21
unet-master\Untitled.ipynb, 11919 , 2020-06-24
unet-master\__pycache__, 0 , 2020-06-24
unet-master\__pycache__\model.cpython-36.pyc, 2097 , 2020-06-24
unet-master\__pycache__\data.cpython-36.pyc, 3898 , 2020-06-24
unet-master\model.py, 3745 , 2019-02-21
__MACOSX\unet-master\._model.py, 212 , 2019-02-21
unet-master\README.md, 2552 , 2019-02-21
__MACOSX\unet-master\._README.md, 212 , 2019-02-21
unet-master\img, 0 , 2019-02-21
unet-master\img\0label.png, 178720 , 2019-02-21
__MACOSX\unet-master\img, 0 , 2020-06-29
__MACOSX\unet-master\img\._0label.png, 212 , 2019-02-21
unet-master\img\0test.png, 400739 , 2019-02-21
__MACOSX\unet-master\img\._0test.png, 212 , 2019-02-21
unet-master\img\u-net-architecture.png, 40580 , 2019-02-21
__MACOSX\unet-master\img\._u-net-architecture.png, 212 , 2019-02-21
__MACOSX\unet-master\._img, 212 , 2019-02-21
unet-master\.ipynb_checkpoints, 0 , 2020-06-24
unet-master\.ipynb_checkpoints\trainUnet-checkpoint.ipynb, 9802 , 2020-06-24
unet-master\.ipynb_checkpoints\Untitled-checkpoint.ipynb, 72 , 2020-06-24
unet-master\main.py, 821 , 2019-02-21
__MACOSX\unet-master\._main.py, 212 , 2019-02-21
unet-master\data, 0 , 2020-06-24
unet-master\data\.DS_Store, 6148 , 2020-06-29
__MACOSX\unet-master\data, 0 , 2020-06-29
__MACOSX\unet-master\data\._.DS_Store, 120 , 2020-06-29
unet-master\data\membrane, 0 , 2020-06-24
unet-master\data\membrane\.DS_Store, 8196 , 2020-06-29
__MACOSX\unet-master\data\membrane, 0 , 2020-06-29
__MACOSX\unet-master\data\membrane\._.DS_Store, 120 , 2020-06-29
unet-master\data\membrane\test, 0 , 2020-06-29
unet-master\data\membrane\test\.DS_Store, 6148 , 2020-06-29
__MACOSX\unet-master\data\membrane\test, 0 , 2020-06-29
__MACOSX\unet-master\data\membrane\test\._.DS_Store, 120 , 2020-06-29
unet-master\data\membrane\test\0_predict.png, 48695 , 2019-02-21
__MACOSX\unet-master\data\membrane\test\._0_predict.png, 212 , 2019-02-21
unet-master\data\membrane\test\1_predict.png, 54547 , 2019-02-21
__MACOSX\unet-master\data\membrane\test\._1_predict.png, 212 , 2019-02-21
unet-master\data\membrane\test\1.png, 213325 , 2019-02-21
__MACOSX\unet-master\data\membrane\test\._1.png, 212 , 2019-02-21
unet-master\data\membrane\test\0.png, 214932 , 2019-02-21
__MACOSX\unet-master\data\membrane\test\._0.png, 212 , 2019-02-21
__MACOSX\unet-master\data\membrane\._test, 212 , 2020-06-29
unet-master\data\membrane\test-volume.tif, 7871660 , 2019-02-21
__MACOSX\unet-master\data\membrane\._test-volume.tif, 212 , 2019-02-21
unet-master\data\membrane\train-volume.tif, 7870730 , 2019-02-21
__MACOSX\unet-master\data\membrane\._train-volume.tif, 212 , 2019-02-21
unet-master\data\membrane\train-labels.tif, 7869573 , 2019-02-21
__MACOSX\unet-master\data\membrane\._train-labels.tif, 212 , 2019-02-21
unet-master\data\membrane\train, 0 , 2020-06-24
unet-master\data\membrane\train\.DS_Store, 10244 , 2020-06-29
__MACOSX\unet-master\data\membrane\train, 0 , 2020-06-29
__MACOSX\unet-master\data\membrane\train\._.DS_Store, 120 , 2020-06-29
unet-master\data\membrane\train\aug, 0 , 2020-06-29
unet-master\data\membrane\train\aug\.DS_Store, 6148 , 2020-06-29
__MACOSX\unet-master\data\membrane\train\aug, 0 , 2020-06-29
__MACOSX\unet-master\data\membrane\train\aug\._.DS_Store, 120 , 2020-06-29
__MACOSX\unet-master\data\membrane\train\._aug, 212 , 2020-06-29
unet-master\data\membrane\train\label, 0 , 2020-06-29
unet-master\data\membrane\train\label\.DS_Store, 6148 , 2020-06-29
__MACOSX\unet-master\data\membrane\train\label, 0 , 2020-06-29
__MACOSX\unet-master\data\membrane\train\label\._.DS_Store, 120 , 2020-06-29
unet-master\data\membrane\train\label\4.png, 14312 , 2019-02-21
__MACOSX\unet-master\data\membrane\train\label\._4.png, 212 , 2019-02-21
unet-master\data\membrane\train\label\2.png, 14052 , 2019-02-21
__MACOSX\unet-master\data\membrane\train\label\._2.png, 212 , 2019-02-21
unet-master\data\membrane\train\label\3.png, 13829 , 2019-02-21
__MACOSX\unet-master\data\membrane\train\label\._3.png, 212 , 2019-02-21
unet-master\data\membrane\train\label\1.png, 13977 , 2019-02-21
__MACOSX\unet-master\data\membrane\train\label\._1.png, 212 , 2019-02-21
unet-master\data\membrane\train\label\0.png, 14322 , 2019-02-21
__MACOSX\unet-master\data\membrane\train\label\._0.png, 212 , 2019-02-21
__MACOSX\unet-master\data\membrane\train\._label, 212 , 2020-06-29
unet-master\data\membrane\train\image, 0 , 2020-06-29
unet-master\data\membrane\train\image\.DS_Store, 6148 , 2020-06-29
__MACOSX\unet-master\data\membrane\train\image, 0 , 2020-06-29
__MACOSX\unet-master\data\membrane\train\image\._.DS_Store, 120 , 2020-06-29
unet-master\data\membrane\train\image\4.png, 189054 , 2019-02-21
__MACOSX\unet-master\data\membrane\train\image\._4.png, 212 , 2019-02-21
unet-master\data\membrane\train\image\2.png, 188971 , 2019-02-21
__MACOSX\unet-master\data\membrane\train\image\._2.png, 212 , 2019-02-21
unet-master\data\membrane\train\image\3.png, 187963 , 2019-02-21
__MACOSX\unet-master\data\membrane\train\image\._3.png, 212 , 2019-02-21
unet-master\data\membrane\train\image\1.png, 188189 , 2019-02-21
__MACOSX\unet-master\data\membrane\train\image\._1.png, 212 , 2019-02-21
unet-master\data\membrane\train\image\0.png, 187651 , 2019-02-21
__MACOSX\unet-master\data\membrane\train\image\._0.png, 212 , 2019-02-21
__MACOSX\unet-master\data\membrane\train\._image, 212 , 2020-06-29
__MACOSX\unet-master\data\membrane\._train, 212 , 2020-06-24

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

  • echarts-master 各种表 例子源码
    echarts-master  
    2014-10-13下载
    积分:1
  • ELMexam
    使用极限学习机ELM算法进行遥感图像分类的源代码,很好的例子(Use extreme learning machine ELM remote sensing image classification algorithm source code, a good example)
    2020-12-27 10:29:03下载
    积分:1
  • threshold-roc
    一些基本的图像处理算法的matlab实现,包括边缘提取和roc分析等(some basic image processing algorithms to achieve Matlab, including edge detection and analysis roc)
    2006-12-27 10:59:08下载
    积分:1
  • facelocation
    说明:  在一幅图像中对单人脸进行定位,原理是基于多模板匹配(locate face in one picture in which there is a single face,its theory base on many templates matching)
    2021-04-18 10:48:51下载
    积分:1
  • immosaic-by--sift
    基于sift的图像特征点提取和图像拼接,有可直接运行的代码和图片(Sift the image feature point extraction and image stitching, can be directly run the code and pictures)
    2012-07-08 21:35:02下载
    积分:1
  • PF
    说明:  序贯重要性采样——标准粒子滤波算法。可直接使用。(Sequential importance sampling- standard particle filter. Can be used directly.)
    2013-10-26 21:02:56下载
    积分:1
  • deblurr
    利用多用方法进行数字图像去模糊实例,便于初学者理解反卷积去模糊、伪逆去模糊等基本算法(Example scripts for image debluring, try to give general introduction of some basic algorithms, such as pseudo inverse debluring.)
    2013-05-11 14:35:55下载
    积分:1
  • byxf
    本程序能够实现图像处理中的图像细化,是基于matlab的。(This procedure can realize image processing image thinning is based on the matlab.)
    2008-03-16 11:01:19下载
    积分:1
  • pts
    说明:  OFDM中的降低PAPR中的pts方法的程序,里面包括随机,交织,相邻分割(it is a simulation papr of pts)
    2011-03-03 22:46:37下载
    积分:1
  • ICBI
    一种基于双立方插值的新型图像插值算法,较好的保存边缘信息(Based on bicubic new image interpolation algorithm, the preservation of edge information better)
    2021-03-29 15:59:11下载
    积分:1
  • 696516资源总数
  • 106633会员总数
  • 4今日下载