原作者github链接:https://github.com/cfzd/Ultra-Fast-Lane-Detection Ultra-Fast-Lane-Detection PyTorch implementation of the paper "Ultra Fast Structure-aware Deep Lane Detection". [July 18, 2022] Updates: The new version of our method has been accepted by TPAMI 2022. Code is available here....
1、代码下载地址 :https://github.com/cfzd/Ultra-Fast-Lane-Detection 或者 git clonehttps://github.com/cfzd/Ultra-Fast-Lane-Detection.git 2、数据集准备 CULane:CULane是用于行车道检测学术研究的大规模具有挑战性的数据集。它由安装在六辆由北京不同驾驶员驾驶的不同车辆上的摄像机收集。收集了超过55小时...
PyTorch implementation of the paper "Ultra Fast Structure-aware Deep Lane Detection". [July 18, 2022] Updates: The new version of our method has been accepted by TPAMI 2022. Code is availablehere. [June 28, 2021] Updates: we will release an extended version, which improves6.3points of F1...
代码链接:https://github.com/cfzd/Ultra-Fast-Lane-Detection-v2 现代的方法主要把车道线检测看作像素级的分割问题,这导致效率问题以及遮挡和极端光照条件场景等问题变得很难解决。受人类感知的启发,严重遮挡和极端光照条件下的车道线识别主要基于上下文和全局信息。基于这一观察结果,我们提出了一种新颖、简单、有效的...
git clone https://github.com/Dreamdreams8/Ultra-Fast-Lane-Detection-Test.git cd Ultra-Fast-Lane-Detection-Test 二、创建虚拟环境 conda create -n lane-det python=3.7 -y conda activate lane-det 三、安装依赖环境 # If you dont havepytorchconda install pytorch torchvision cudatoolkit=10.1 -c pyto...
代码链接:https://github.com/cfzd/Ultra-Fast-Lane-Detection-v2 摘要 现代的方法主要把车道线检测看作像素级的分割问题,这导致效率问题以及遮挡和极端光照条件场景等问题变得很难解决。受人类感知的启发,严重遮挡和极端光照条件下的车道线...
git clone https://github.com/cfzd/Ultra-Fast-Lane-Detection cd Ultra-Fast-Lane-Detection b. Create a conda virtual environment and activate it conda create -n lane-det python=3.7 -y conda activate lane-det c. Install dependencies # If you don't have pytorch conda install pytorch torchv...
github地址:https://github.com/cfzd/Ultra-Fast-Lane-Detection-v2 Ultra Fast Deep Lane Detection With Hybrid Anchor Driven Ordinal Classification (TPAMI 2022) 效果 项目 模型信息 Inputs --- name:input tensor:Float[1, 3, 320, 1600] --- Outputs --- name:loc_row ...
git clone https://github.com/cfzd/Ultra-Fast-Lane-Detection cd Ultra-Fast-Lane-Detection b. Create a conda virtual environment and activate it conda create -n lane-det python=3.7 -y conda activate lane-det c. Install dependencies # If you don't have pytorch conda install pytorch torchvisio...
ultra fast lane detection提供了很好的源码,根据演示视频来看,效果似乎不赖,很有必要试一试该算法。 一、基本情况 作者知乎:超快的车道线检测 - 知乎 (zhihu.com) 简单来说,作者认为卷积层形式的输出,导致局部感受野小,很明显车道线识别需要结合全局特征来分析。而全连接层形式的输出,运用了全局特征,也就没有感受...