smartcar-perception Goto Github PK

carnd-vehicle-detection

Monocular vehicle detection using SVM and Deep Learning classifiers

lanesegnet

[ICLR 2024] Map Learning with Lane Segment for Autonomous Driving

lego-loam

LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain

lidar_closest_distance_detector

Calculate the closest distance to the nearest obstacle using the convex polygons of pointcloud

lidar_ground_plane_and_obstacles_detections

Python and C++ examples that show shows how to process 3-D Lidar data by segmenting the ground plane and finding obstacles.

lidar_obstacle_detection

CropBox ROI filtering | VoxelGrid downsampling | Ground plane segmentation using RANSAC | Euclidean clustering optimised with a k-d tree | Bounding boxes | Custom C++ implementations and PCL.

lidar_obstacle_detector

3D LiDAR Object Detection & Tracking using Euclidean Clustering, RANSAC, & Hungarian Algorithm

lidar_obstacle_detector-1

lidar_rcnn

LiDAR R-CNN: An Efficient and Universal 3D Object Detector

lidarobstacledetection

Lidar Obstacle Detection

sfnd_lidar_obstacle_detection

优达自动驾驶课程

twinlitenet

voronoi_planner

A global planner plugin for ROS navigation stack, in which A* search on a discrete gneralized Voronoi diagram (GVD) is implemented.

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。

yolop_plus

基于YoloP模型实现的多目标检测与车道线分割改进版的模型。

yolopv2

YOLOPv2: Better, Faster, Stronger for Panoptic driving Perception

yolopv2-ncnn

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。