https://github.com/iv4n-ga6l/Advanced-Lanes-Detection

An advanced lane detection system using OpenCV approach
https://github.com/iv4n-ga6l/Advanced-Lanes-Detection

advanced-lane-finding advanced-lanes-detection opencv python ultralytics

Last synced: 6 months ago
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An advanced lane detection system using OpenCV approach

• Host: GitHub
• URL: https://github.com/iv4n-ga6l/Advanced-Lanes-Detection
• Owner: iv4n-ga6l
• Created: 2024-07-23T21:10:15.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-11-02T11:52:40.000Z (11 months ago)
• Last Synced: 2025-04-05T08:05:10.826Z (6 months ago)
• Topics: advanced-lane-finding, advanced-lanes-detection, opencv, python, ultralytics
• Language: Python
• Homepage:
• Size: 118 MB
• Stars: 3
• Watchers: 1
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

          
## Advanced Lane Detection

An advanced lane detection system using Using OpenCV, canny edge detector and hough transform algorithms

![Demo](demo.png)

The Project

---

The steps of this project are the following:

* Compute the camera calibration matrix and distortion coefficients given a set of chessboard images.

* Apply a distortion correction to raw images.

* Apply a perspective transform to rectify binary image ("birds-eye view").

* Use color transforms, gradients, etc., to create a thresholded binary image.

* Detect lane pixels and fit to find the lane boundary.

* Determine the curvature of the lane and vehicle position to the center.

* Warp the detected lane boundaries back onto the original image.

* Lane Width: Computes the width of the lane based on polynomial coefficients.

* Get Top Down View of the lane using "birds-eye view" technique

* Vehicles Detection with YOLO11 by Ultralytics

* Distance Estimation of each Vehicle from others based on the centroids of the bounding boxes

The images for camera calibration are stored in the folder called `camera_cal`.

### Requirements

```bash

pip install -r requirements.txt

```

### Run 

```bash

py main.py --choice CHOICE --input INPUT_PATH 

```