bentley_ottmann | Detection of line segments & polygon edges intersections | Computer Vision library

by lycantropos Python Version: v8.0.0 License: MIT

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kandi X-RAY | bentley_ottmann Summary

bentley_ottmann is a Python library typically used in Artificial Intelligence, Computer Vision applications. bentley_ottmann has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install bentley_ottmann' or download it from GitHub, PyPI.

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bentley_ottmann has a low active ecosystem.

It has 14 star(s) with 2 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 2 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of bentley_ottmann is v8.0.0

Quality

bentley_ottmann has 0 bugs and 0 code smells.

Security

bentley_ottmann has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

bentley_ottmann code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

bentley_ottmann is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

bentley_ottmann releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

It has 933 lines of code, 97 functions and 21 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Performs a sweep of the given segments
Create a LeftEvent from a given segment
Adds an event to the set
Remove and return an event from the queue
Return the next event from the queue
Convert start to a sorted tuple
Register a relation
Remove an event from the set
Returns the previous event prior to the given event
Return the first event above the given event
Detects the intersection of the given event
Push an event onto the queue
Find the left event that matches the given event
Create an EventQueue from segments
Merges the left event with another
Divide the given point into two parts
Return the relationship between two points
Complete the relationship between the same start and end events
Read a file

Get all kandi verified functions for this library.

bentley_ottmann Key Features

No Key Features are available at this moment for bentley_ottmann.

bentley_ottmann Examples and Code Snippets

No Code Snippets are available at this moment for bentley_ottmann.

Community Discussions

Trending Discussions on bentley_ottmann

Detecting tennis court lines intercepts

QUESTION

Detecting tennis court lines intercepts

Asked 2019-Apr-03 at 20:40

I am trying to improve my code to find the tennis court line intercepts so that I can find the boundaries of the different quadrants of the court.

Input image

Output Image

I achieved this by first finding the white pixels in the image, then applying canny edge detection with some preprocessing such as Gaussian blur. Then the canny edge output is dilated to help prepare it for hough lines detection.

Then taking the hough lines output I used the python implementation of the Bentley–Ottmann algorithm by github user ideasman42 to find the hough line intercepts.

This seems to work pretty well, but I'm struggling to tune my system to find the last 4 intercept points. If anyone could give me advice to improve or tune this implementation or even offer up some ideas for a better way to solve the problem of finding the court boundaries I would appreciate it.

...

ANSWER

Answered 2019-Apr-03 at 13:58

Here is my solution, using a different approach. I use the Harris corner detector to detect corners. The parameters were just tweaked in a hurry, so feel free to play with them. Here is a tutorial from OpenCV on it.

I use the OpenCV Wrapper library for some easier OpenCV code. It should be pretty easy to translate if you don't want it.

Source https://stackoverflow.com/questions/55496402

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

Vulnerabilities

No vulnerabilities reported

Install bentley_ottmann

Install the latest pip & setuptools packages versions.

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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