pfe-pytorch | Probabilistic Face Embeddings

by Ontheway361 Python Version: Current License: No License

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

kandi X-RAY | pfe-pytorch Summary

pfe-pytorch is a Python library. pfe-pytorch has no bugs, it has no vulnerabilities and it has low support. However pfe-pytorch build file is not available. You can download it from GitHub.

pfe-pytorch

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Quality

Security

License

Reuse

Support

pfe-pytorch has a low active ecosystem.

It has 8 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 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pfe-pytorch is current.

Quality

pfe-pytorch has 0 bugs and 0 code smells.

Security

pfe-pytorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

pfe-pytorch code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pfe-pytorch 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

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

pfe-pytorch has no build file. You will be need to create the build yourself to build the component from source.

It has 1051 lines of code, 64 functions and 16 files.

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

Top functions reviewed by kandi - BETA

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

Verify runner
Find the highest threshold for the training and test
Run the test runner
Evaluate the fw
Run train runner
Create data loader
Train the model
Main loop
Embed inference
Scale x and beta
Compute the loss of the loss function
Negative difference between mu and Sigma
Compute the mutual likelihood loss
Computes negative MLS
Calculate the mls score of two faces
Calculate the distance between mu and mu
Get the image for a pair
Load image
Factory for ResNet
Create a layer from block
Infer argparse arguments

Get all kandi verified functions for this library.

pfe-pytorch Key Features

No Key Features are available at this moment for pfe-pytorch.

pfe-pytorch Examples and Code Snippets

No Code Snippets are available at this moment for pfe-pytorch.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install pfe-pytorch

You can download it from GitHub.
You can use pfe-pytorch 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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