JJLi0427 Lane Detection Opencv Save

A lane detection program developed using OpenCV

Project README

lane_detect

This is a lane detection program developed using OpenCV. It uses techniques such as Canny Edge Detection, Hough Transform, and RANSAC for line fitting. The program allows users to select the Region of Interest (ROI) before running.
select roi
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Technologies Used

Canny Edge Detection: A multi-stage algorithm to detect a wide range of edges in images. It was developed by John F. Canny in 1986.

Hough Transform: A feature extraction technique used in image analysis, computer vision, and digital image processing. It is used to detect simple shapes such as lines and circles.

RANSAC (Random Sample Consensus): An iterative method to estimate parameters of a mathematical model from a set of observed data that contains outliers.

How to Run

The dependencies for this program are listed in the requirements.txt file. You can install them using pip:

pip install -r requirements.txt

To run the program, use the following command:

python lane_detect.py {$video_path}

Replace {$video_path} with the path to your video file.

Note

This program is designed to work with video files. The user is required to select the ROI before the program starts processing the video for lane detection.
``canny.pyVisual Canny Edge Detection works. command:python canny.py {$path_to_your_video}` canny work

Open Source Agenda is not affiliated with "JJLi0427 Lane Detection Opencv" Project. README Source: JJLi0427/Lane_detection_opencv
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