drivable-area-segmentation

There are 9 repositories under drivable-area-segmentation topic.

  • hustvl/YOLOP

    You Only Look Once for Panopitic Driving Perception.(MIR2022)

    Language:Python1.8k30197405
  • hpc203/YOLOP-opencv-dnn

    使用OpenCV部署全景驾驶感知网络YOLOP,可同时处理交通目标检测、可驾驶区域分割、车道线检测,三项视觉感知任务,包含C++和Python两种版本的程序实现。本套程序只依赖opencv库就可以运行, 从而彻底摆脱对任何深度学习框架的依赖。

    Language:Python2518861
  • hpc203/yolopv2-opencv-onnxrun-cpp-py

    分别使用OpenCV、ONNXRuntime部署YOLOPV2目标检测+可驾驶区域分割+车道线分割,一共包含54个onnx模型,依然是包含C++和Python两个版本的程序。仅仅只依赖OpenCV就能运行,彻底摆脱对任何深度学习框架的依赖。

    Language:C++631107
  • hpc203/hybridnets-opencv-dnn

    使用OpenCV部署HybridNets,同时处理车辆检测、可驾驶区域分割、车道线分割,三项视觉感知任务,包含C++和Python两种版本的程序实现。本套程序只依赖opencv库就可以运行, 彻底摆脱对任何深度学习框架的依赖。

    Language:C++12111
  • balnarendrasapa/road-detection

    This is a course project for DSCI-6011 - Deep Learning. deals with Drivable Area and lane segmentation for self driving cars

    Language:Jupyter Notebook4101
  • harrylal/TwinLiteNet-onnxruntime

    Perform inference with TwinLiteNet model using ONNX Runtime. TwinLiteNet is a lightweight and efficient deep learning model designed for drivable area and lane segmentation

    Language:C++4100
  • christofel04/Argoverse-API-and-Visualization-for-3D-Drivable-Road-Detection

    Argoverse API for manipulating Argoverse 1 and Argoverse 2 Dataset for 3D Drivable Area Detection using LiDAR

    Language:Jupyter Notebook3200
  • harrylal/TwinLiteNet-onnx-opencv-dnn

    An easy-to-use implementation for performing inferencing with TwinLiteNet model using OpenCV DNN module. TwinLiteNet is a lightweight and efficient deep learning model designed for drivable area and lane segmentation

    Language:C++1100
  • ntkhoa95/Self-Supervised-Label-Generator

    This is an unofficial Python demo of the Self-Supervised Label Generator (SSLG), presented in "Self-Supervised Drivable Area and Road Anomaly Segmentation using RGB-D Data for Robotic Wheelchairs. Our SSLG can be used effectively for self-supervised drivable area and road anomaly segmentation based on RGB-D data".

    Language:Python10