bpartis | Official implementation of Bayesian Particle Instance
kandi X-RAY | bpartis Summary
kandi X-RAY | bpartis Summary
bpartis is a Python library. bpartis has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.
Bayesian Particle Instance Segmentation for Electron Microscopy Image Quantification. This repository contains the official implementation of bpartis — a Bayesian deep neural network for nanoparticle instance segmentation.
Bayesian Particle Instance Segmentation for Electron Microscopy Image Quantification. This repository contains the official implementation of bpartis — a Bayesian deep neural network for nanoparticle instance segmentation.
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bpartis has a low active ecosystem.
It has 2 star(s) with 0 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
bpartis has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of bpartis is current.
Quality
bpartis has no bugs reported.
Security
bpartis has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
bpartis is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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bpartis 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.
Top functions reviewed by kandi - BETA
kandi has reviewed bpartis and discovered the below as its top functions. This is intended to give you an instant insight into bpartis implemented functionality, and help decide if they suit your requirements.
- Perform clustering .
- Compute tp and fp .
- Compute the metrics for the given pred and gt .
- get an image
- Run monte carlo model .
- Calculate the IOU sum of the confidence interval .
- Calculate the mean of a list .
- Compute the softmax loss for each label .
- Calculate the gradient of the likelihood of the given labels .
- Creates training and test embedding .
Get all kandi verified functions for this library.
bpartis Key Features
No Key Features are available at this moment for bpartis.
bpartis Examples and Code Snippets
No Code Snippets are available at this moment for bpartis.
Community Discussions
No Community Discussions are available at this moment for bpartis.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install bpartis
You can download it from GitHub.
You can use bpartis 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.
You can use bpartis 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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