Lane-Line-Detection | Using OpenCV to detect Lane Lines | Machine Learning library

by rbhatia46 Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | Lane-Line-Detection Summary

Lane-Line-Detection is a Python library typically used in Manufacturing, Utilities, Automotive, Artificial Intelligence, Machine Learning, Deep Learning, OpenCV applications. Lane-Line-Detection has no bugs, it has no vulnerabilities and it has low support. However Lane-Line-Detection build file is not available. You can download it from GitHub.

Detecting Lane lines is one of the most fundamental concepts for building a Self Driving Car. In this repository, I have used OpenCV to detect lane lines in a sample video sample obtained from a camera places on a car. You need OpenCV to run this project on your local machine and it can be installed simply by a single command - pip install opencv-python.

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Support

Lane-Line-Detection has a low active ecosystem.

It has 17 star(s) with 9 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

Lane-Line-Detection has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Lane-Line-Detection is current.

Quality

Lane-Line-Detection has 0 bugs and 0 code smells.

Security

Lane-Line-Detection has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Lane-Line-Detection code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Lane-Line-Detection does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

Lane-Line-Detection releases are not available. You will need to build from source code and install.

Lane-Line-Detection has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed Lane-Line-Detection and discovered the below as its top functions. This is intended to give you an instant insight into Lane-Line-Detection implemented functionality, and help decide if they suit your requirements.

Calculate the average slope and intercept
Make the coordinates of the image
Creates a masked region of the image
Displays a list of lines
Calculate canny of a given image

Get all kandi verified functions for this library.

Lane-Line-Detection Key Features

No Key Features are available at this moment for Lane-Line-Detection.

Lane-Line-Detection Examples and Code Snippets

No Code Snippets are available at this moment for Lane-Line-Detection.

Community Discussions

Trending Discussions on Lane-Line-Detection

TypeError: dst is not a numpy array, neither a scalar

QUESTION

TypeError: dst is not a numpy array, neither a scalar

Asked 2017-May-25 at 10:19

I use anaconda2 in python script, but it showed me these error information:

...

ANSWER

Answered 2017-May-25 at 10:19

You need to call it as:

Source https://stackoverflow.com/questions/44171287

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Lane-Line-Detection

You can download it from GitHub.
You can use Lane-Line-Detection like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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