Convolutional Patch Networks with Spatial Prior for Road Detection and Urban Scene Understanding

深度学习思想越来越火，在今年的CVPR 2015 文章中相关文章就有20多篇，可见是很火的。近期在做关于语义切割和场景解析的内容，看到这篇文章后也是很高兴。

CN24 is a complete semantic segmentation framework using fully convolutional networks. It supports a wide variety of platforms (Linux, Mac OS X and Windows) and libraries (OpenCL, Intel MKL, AMD ACML...) while providing dependency-free reference implementations. The software is developed at the Computer Vision Group, University of Jena.

文章说能够在Windows、Mac和Linux系统上很好的执行，又能够支持OpenCL、Intel MKL , AMD ACML 来并行计算加速。看起来还真不错！

官方源代码地址：

[ CN24 ]

接下来先上实验结果：

实验环境[ubuntu 15.04]。临时没实用GPU加速

代码程序文件夹：

执行后的结果:

单张图片測试结果，左側是语义切割后的结果，右側是真实的測试图。

没实用GPU加速，果然处理一张图片还是挺慢的，耗时还是挺多的，例如以下图所看到的：

以下就是摸索代码。下一节会继续分享学习过程，谢谢！

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