semantic_segmentation:在给定图像中语义分割道路
道路分割
客观的
在自动驾驶的情况下，给定前摄像头视图，汽车需要知道道路在哪里。 在这个项目中，我们训练了神经网络，通过使用一种称为完全卷积网络（FCN）的方法来标记图像中道路的像素。 在此项目中，使用KITTI数据集实施FCN-VGG16并对其进行了培训，以进行道路分割。
演示版
（单击以查看完整的视频）
1代码和文件
1.1我的项目包括以下文件和文件夹
是演示的主要代码
包含单元测试
包含一些帮助程序功能
是带有GPU和Python3.5的环境文件
文件夹包含KITTI道路数据，VGG模型和源图像。
文件夹用于保存训练后的模型
文件夹包含测试数据的细分示例
1.2依赖关系和我的环境
Miniconda用于管理我的。
Python3.5，tensorflow-gpu，CUDA8，Numpy，SciPy
操作系统：Ubuntu 16.04
CPU：Intel:registered:Core:trade_mark:i7-68
文件下载
资源详情
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