ORL_faces | bp神经网络 0.8 pcabp神经网络 | Machine Learning library

by Frank-qlu Python Version: Current License: No License

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

kandi X-RAY | ORL_faces Summary

ORL_faces is a Python library typically used in Artificial Intelligence, Machine Learning, OpenCV applications. ORL_faces has no bugs, it has no vulnerabilities and it has low support. However ORL_faces build file is not available. You can download it from GitHub.

ORL人脸识别不同算法的实现，用到了scikit-learn,tensorflow等，任选5张训练，5张测试。因为每次训练随机挑选，所以每次输出识别率有偏差算法识别率 bp神经网络 0.8 pca+bp神经网络 0.85 小波变换+pca+bp神经网络 0.95 CNN 0.98 小波变换+pca+SVM 0.98####同时希望大家提出宝贵意见，欢迎学习交流，如果你喜欢该项目，请star或者fork一下，你的主动将是我前行的动力####

Support

Quality

Security

License

Reuse

Support

ORL_faces has a low active ecosystem.

It has 42 star(s) with 30 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 439 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of ORL_faces is current.

Quality

ORL_faces has 0 bugs and 0 code smells.

Security

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

ORL_faces code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

ORL_faces 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

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

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

ORL_faces saves you 214 person hours of effort in developing the same functionality from scratch.

It has 524 lines of code, 23 functions and 5 files.

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

Top functions reviewed by kandi - BETA

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

Main function for training images .
load images from folder
Adds a single layer .
Compute the PCCA .
2d conv layer .
Creates a weight variable .
Bias tensor .
Max pooling op .

Get all kandi verified functions for this library.

ORL_faces Key Features

No Key Features are available at this moment for ORL_faces.

ORL_faces Examples and Code Snippets

No Code Snippets are available at this moment for ORL_faces.

Community Discussions

Trending Discussions on ORL_faces

Match a number that is preceded by 's' and succeeded by '/'

QUESTION

Match a number that is preceded by 's' and succeeded by '/'

Asked 2018-Jan-12 at 19:06

I have a list of filenames which are all like so:

...

ANSWER

Answered 2018-Jan-12 at 18:41

You can use group operators:

Source https://stackoverflow.com/questions/48232204

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

Vulnerabilities

No vulnerabilities reported

Install ORL_faces

You can download it from GitHub.
You can use ORL_faces 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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