shape-detection | abstract shapes with neural networks | Machine Learning library

by jrieke Jupyter Notebook Version: Current License: MIT

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

kandi X-RAY | shape-detection Summary

shape-detection is a Jupyter Notebook library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow applications. shape-detection has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

🟣 Object detection of abstract shapes with neural networks

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shape-detection has a low active ecosystem.

It has 180 star(s) with 115 fork(s). There are 8 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 4 have been closed. On average issues are closed in 75 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of shape-detection is current.

Quality

shape-detection has 0 bugs and 0 code smells.

Security

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

shape-detection code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

shape-detection 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

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

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shape-detection Key Features

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shape-detection Examples and Code Snippets

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Community Discussions

Trending Discussions on shape-detection

Tolerance issue while detecting Trapezium and Rhombus using Opencv

QUESTION

Tolerance issue while detecting Trapezium and Rhombus using Opencv

Asked 2020-Nov-01 at 14:04

I am supposed to write a code to recognise different shape, we were given a folder in which images of different shapes are given (Circle/ Triangle/ Trapezium/ Rhombus/ Square/ Quadrilateral/ Parallelogram/ Pentagon/ Hexagon). On recognising them it should return the output in the following format: { 'Shape': ['color', Area, cX, cY] }

My code keeps confusing Trapezium and Rhombus. I debugged it and found it's because of +/-1 tolerance in sides and angle. What should I do?.

Here are some of the links of StackOverflow that I tried: OpenCV: How to detect rhombus on an image? Detecting trapezium, rhombus, square, quadrilateral, parallelogram by Opencv in Python OpenCV shape detection Tutorial for iPhone OpenCV on shape recognising [closed]

There were more but they had community issues, so I won't waste your time on them. Long story short I did not find anything useful.

...

ANSWER

Answered 2020-Nov-01 at 14:04

As I mentioned, I was getting a tolerance of +/-1, so I used that tolerance to create a range and set if-elif-else conditions. I guess that's it. Correct this if you think it's not enough

p.s. I already have less reputation point so please don't vote. I am always open to constructive suggestions.

Source https://stackoverflow.com/questions/64621024

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

Vulnerabilities

No vulnerabilities reported

Install shape-detection

You can download it from GitHub.

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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