Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.

一个简单高效的车道线检测模型。

ADAS system implementation on gazebo using opencv and yolo

Lane detection using tensorflow pre-trained model

This is a very simple lane detection made with python.

Lane detection and tracking

Weakly-supervised road-lane markings detection for autonomous driving, mitigating the lack of training data

A deep learning and computer vision based warning indicator system for the vehicle drivers using live dash-cam footage.

The project can achieve FCWS, LDWS, and LKAS functions solely using only visual sensors. using YOLOv5 / YOLOv5-lite / YOLOv6 / YOLOv7 / YOLOv8 / YOLOv9 / EfficientDet and Ultra-Fast-Lane-Detection-v2 .

Autonomous car powered by the Raspberry Pi with image processing (OpenCV)

Integration of YOLOv5 Model and Lane Detection

Advanced Driver-Assistance System using Python and Computer Vision

An autonomous lane detection system leveraging OpenCV to process images and videos, accurately identifying lanes and providing key visualizations.

Official code for "OMR: Occlusion-Aware Memory-Based Refinement for Video Lane Detection", ECCV 2024

Lane and curve Detection.

Project that estimates the distance a car is on a road based on the relationship between the real size of the car and the size it appears in the video obtained. It also estimates the lane the car are traveling in at any given time based on the angle between the position of the car and camera, even guess lane change intentions. Also included is a

车道线检测项目

This repository contains the implementation of a lane detection system using the UNet architecture. The model is trained on the BDD100K dataset, leveraging its diverse and large-scale data to ensure robust performance under various weather conditions and different times of day.

Welcome to the Computer Vision Projects repository! This collection showcases various computer vision applications, with a focus on face detection and lane detection.

A system that senses the lanes and vehicles, to help control steering or V2V distance