Official code for "Harmonious Semantic Line Detection via Maximal Weight Clique Selection", CVPR 2021
Detecting road lanes using OpenCV and Python
Official code for "OMR: Occlusion-Aware Memory-Based Refinement for Video Lane Detection", ECCV 2024
Using Python and Computer Vision to Detect Road Lane Lines
This project detects road lane lines using Python, OpenCV, and NumPy. It applies grayscale conversion, Gaussian blur, Canny edge detection, and Hough Transform to identify lane boundaries. The pipeline highlights lanes on images, serving as a foundation for self-driving car vision systems.
The objective of this project is to develop a lane detection system that processes video footage to identify and highlight lane markings on roadways. The system provides real-time visual feedback to drivers by overlaying lane boundaries and issuing warnings when the vehicle deviates from its lane.
Developed a data science project that detects and highlights road lane lines from images or video feeds, aiding autonomous vehicle navigation.
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