box_utils | box utils , including iou | Computer Vision library

by leon-liangwu Python Version: Current License: No License

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kandi X-RAY | box_utils Summary

box_utils is a Python library typically used in Artificial Intelligence, Computer Vision, Minecraft applications. box_utils has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

box utils, including iou and nms of bbox and rbbox. a pure version from

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box_utils has a low active ecosystem.

It has 5 star(s) with 2 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

box_utils has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of box_utils is current.

Quality

box_utils has 0 bugs and 0 code smells.

Security

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

box_utils code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

box_utils 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

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

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

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

It has 139 lines of code, 5 functions and 3 files.

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

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box_utils Key Features

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box_utils Examples and Code Snippets

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Community Discussions

Trending Discussions on box_utils

Encoded and decoded version of bouding box regression offsets are different

QUESTION

Encoded and decoded version of bouding box regression offsets are different

Asked 2020-Aug-21 at 08:23

I'm trying to replicate bounding box regression technique used in faster-rcnn as given here. I've made a decoding fuunction and an encoding function. Ideally, when passing a bounding box to the encoder and then decoding it, I should get the same bounding box.

Here, are my input bounding boxes:

...

ANSWER

Answered 2020-Aug-21 at 08:23

The problem was in my decode function in calculating [x_min, y_min, x_max, y_max]. It should have been like this:

Source https://stackoverflow.com/questions/63434199

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

Vulnerabilities

No vulnerabilities reported

Install box_utils

You can download it from GitHub.
You can use box_utils 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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