lane-detection | Find lane lines using camera calibration undistortion | Computer Vision library

by BillZito Python Version: Current License: No License

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

kandi X-RAY | lane-detection Summary

lane-detection is a Python library typically used in Telecommunications, Media, Media, Entertainment, Artificial Intelligence, Computer Vision, Deep Learning, OpenCV applications. lane-detection has no bugs, it has no vulnerabilities and it has low support. However lane-detection build file is not available. You can download it from GitHub.

Given a video of a car driving in its lane, the program identifies the lane and draws it onto the image. Output video is output.mp4.

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lane-detection has a low active ecosystem.

It has 15 star(s) with 10 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 914 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of lane-detection is current.

Quality

lane-detection has 0 bugs and 0 code smells.

Security

lane-detection has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

lane-detection code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

lane-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-detection releases are not available. You will need to build from source code and install.

lane-detection has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

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

Reduce the image
Compute the lrature curve
Plot thresholding threshold
Draws a lane on the image
Change perspective of an image
Calculate the absolute value of a gridded image
Calculate the magnitude of a pixel
Calculate the difference between two images
Thresholds the input image
Filter an image by a threshold
Undistorted image by distance

Get all kandi verified functions for this library.

lane-detection Key Features

No Key Features are available at this moment for lane-detection.

lane-detection Examples and Code Snippets

No Code Snippets are available at this moment for lane-detection.

Community Discussions

Trending Discussions on lane-detection

How can I replace `plt.imsave` with `cmap` option set to `gray` with opencv operations?

QUESTION

How can I replace `plt.imsave` with `cmap` option set to `gray` with opencv operations?

Asked 2020-Jan-12 at 08:46

This is the source image I am working with:

I am using this github repository (the file I'm using is tools/test_lanenet.py) to do binary lane segmentation. now I get this image:

The second image is actually an image resulted from this command:

...

ANSWER

Answered 2020-Jan-12 at 07:36

Your images are not the same size. To mask the black/white image onto the color image, they need to align. I tried to simply crop them to the same minimum dimensions at the top left corner, but that did not align them properly.

However, this Python/OpenCV code will give you some idea how to start once you figure out how to align them.

Color Input:

B/W Lane Image:

Source https://stackoverflow.com/questions/59701484

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

Vulnerabilities

No vulnerabilities reported

Install lane-detection

You can download it from GitHub.
You can use lane-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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