imgui_datascience | imgui for data and computer vision scientists

by pthom Python Version: 0.2.7 License: Non-SPDX

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

kandi X-RAY | imgui_datascience Summary

imgui_datascience is a Python library. imgui_datascience has no bugs, it has no vulnerabilities, it has build file available and it has low support. However imgui_datascience has a Non-SPDX License. You can install using 'pip install imgui_datascience' or download it from GitHub, PyPI.

(py)imgui for data and computer vision scientists

Support

Quality

Security

License

Reuse

Support

imgui_datascience has a low active ecosystem.

It has 57 star(s) with 4 fork(s). There are 4 watchers for this library.

It had no major release in the last 12 months.

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

It has a neutral sentiment in the developer community.

The latest version of imgui_datascience is 0.2.7

Quality

imgui_datascience has 0 bugs and 0 code smells.

Security

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

imgui_datascience code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

imgui_datascience has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

imgui_datascience releases are available to install and integrate.

Deployable package is available in PyPI.

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

imgui_datascience saves you 519 person hours of effort in developing the same functionality from scratch.

It has 1217 lines of code, 119 functions and 15 files.

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

Top functions reviewed by kandi - BETA

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

Launch a demo demo
Convert a matplotlib figure to an image
Push an image
Shows ImageLister
Heartbeat the window
Select the first image from the list
Converts an RGB image to a texture
Show the current image
Implementation of GUI
Show one feature
Compute the average fps
Show FPS
Display image types
Creates a zoom info
Generates an image from an image
Creates an image explorer
Show image explorer
Make a contour image
Example demo function for example
Show buttons
Show a togglable window
Make a unique label
Show image list
Returns True if mouse is hovering
Show a demo image
Example demo

Get all kandi verified functions for this library.

imgui_datascience Key Features

No Key Features are available at this moment for imgui_datascience.

imgui_datascience Examples and Code Snippets

No Code Snippets are available at this moment for imgui_datascience.

Community Discussions

No Community Discussions are available at this moment for imgui_datascience.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install imgui_datascience

You can install using 'pip install imgui_datascience' or download it from GitHub, PyPI.
You can use imgui_datascience 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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