Advanced Lane Finding (project 2 of 9 from Udacity Self-Driving Car Engineer Nanodegree)
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Updated
May 24, 2020 - Python
Advanced Lane Finding (project 2 of 9 from Udacity Self-Driving Car Engineer Nanodegree)
Applied signal processing to dash-cam video feed to detect lane lines on the road and used numerical methods to derive approximate real-world measurements of the lane lines.
Software pipeline to identify lane boundaries from a video streaming from a front-facing camera on a car using color transform and gradient
GIMP3 plugin for correcting Chromatic Aberration (CA)
Identify the lane boundaries in a video from a front-facing camera on a car
This project utilizes a software pipeline to identify the lane boundaries in a video.
A python library for image stitching with distortion correction
Алгоритм, который позволяет убирать или добавлять дисторсию на изображениях
Udacity Self Driving Engineer Nanodegree - Project 4 - Advanced Lane Finding
Advance Lane Line Finder on a Video Stream
Advanced Lane Tracking Project - uses perspective transforms to track lane position
In this project, a software pipeline was written to identify the lane boundaries in a video from a front-facing camera on a car using computer vision techniques with openCV.
Advanced lane line fining including camera calibration
Camera Calibration and Distortion Correction
A cv2-based implementation of a self-driving car module responsible for lane lines detection under different lighting conditions, pavement textures and curves.
SW Pipeline to identify the lane boundaries from a front-facing camera on a car (use of OpenCV)
Camera calibration and visual depth perception
Computer Vision Algorithms
Udacity Self Driving Car Nanodegree - Advanced Lane Finding
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