基于keras的语义分割代码

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  • 2022-06-11 21:19
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内有训练,预测及可视化代码,有unet,fcn8s,fcn32s,segnet网络架构,做好数据集就可以直接跑
keras语义分割.zip
  • keras-segmentation -master
  • Models
  • FCN8.py
    4.7KB
  • SegNet.py
    5.1KB
  • utils.py
    4.3KB
  • UNet.py
    2.2KB
  • __pycache__
  • SegNet.cpython-36.pyc
    3.1KB
  • FCN8.cpython-36.pyc
    2.5KB
  • utils.cpython-36.pyc
    3.8KB
  • FCN32.cpython-36.pyc
    1.5KB
  • UNet.cpython-36.pyc
    1.9KB
  • model_fcn32.png
    143.7KB
  • fcn.py
    4KB
  • model_unet.png
    326.8KB
  • utils_cpu.py
    4.6KB
  • model_segnet.png
    506KB
  • FCN32.py
    1.5KB
  • model_fcn8.png
    238.5KB
  • readme_zh.md
    2.3KB
  • readme.md
    2.1KB
  • train.py
    3KB
  • __pycache__
  • LoadBatches.cpython-36.pyc
    1.9KB
  • predict.py
    2.6KB
  • output
  • .idea
  • misc.xml
    300B
  • keras-segmentation-master.iml
    330B
  • modules.xml
    309B
  • workspace.xml
    9.3KB
  • .gitignore
    184B
  • inspectionProfiles
  • profiles_settings.xml
    174B
  • LoadBatches.py
    2.2KB
  • .gitignore
    60B
  • visualizeDataset.py
    2KB
内容介绍
<h1 align="center"><a href="https://github.com/lsh1994/keras-segmentation" target="_blank" rel='nofollow' onclick='return false;'>keras-segmentation</a></h1> <p align="center"> Implementation is not original papers. The purpose of this project is to get started with semantic segmentation and master the basic process. </p> <font color=red>FCN32/8、SegNet、U-Net [Model published](https://github.com/lsh1994/keras-segmentation/releases). Thank you for your support.</font> [中文说明](readme_zh.md) ## Environment Item | Value | Item | Value :---: | :---: | :---: | :---: keras | 2.2.4 | OS | win10 tensorflow-gpu | 1.10/1.12 | Python| 3.6.7 ## Reference https://github.com/divamgupta/image-segmentation-keras https://github.com/ykamikawa/SegNet Data: https://drive.google.com/file/d/0B0d9ZiqAgFkiOHR1NTJhWVJMNEU/view?usp=sharing Data or: https://github.com/alexgkendall/SegNet-Tutorial/tree/master/CamVid ## Project Strcutre ![在这里插入图片描述](https://img-blog.csdnimg.cn/20181218212010847.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L25pbWExOTk0,size_16,color_FFFFFF,t_70) `python visualizeDataset.py`: Visual samples ![在这里插入图片描述](https://img-blog.csdnimg.cn/20181113165336706.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L25pbWExOTk0,size_16,color_FFFFFF,t_70) `python train.py`: Execution train `python predict.py`: Execution predict You can modify the parameter in project switching model or cloning the historical version. ## About ### FCN32 Visualization results: ![在这里插入图片描述](https://img-blog.csdnimg.cn/2018111410255134.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L25pbWExOTk0,size_16,color_FFFFFF,t_70) ### FCN8 Visualization results: ![在这里插入图片描述](https://img-blog.csdnimg.cn/20181114103306961.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L25pbWExOTk0,size_16,color_FFFFFF,t_70) ### SegNet ### U-Net
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