FacialExpressionRecognition | Related source code of facial expression recognition project

by luanshiyinyang Python Version: Current License: GPL-3.0

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

kandi X-RAY | FacialExpressionRecognition Summary

FacialExpressionRecognition is a Python library. FacialExpressionRecognition has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

Related source code of facial expression recognition project

Support

Quality

Security

License

Reuse

Support

FacialExpressionRecognition has a low active ecosystem.

It has 401 star(s) with 121 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 21 open issues and 10 have been closed. On average issues are closed in 89 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of FacialExpressionRecognition is current.

Quality

FacialExpressionRecognition has 0 bugs and 0 code smells.

Security

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

FacialExpressionRecognition code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

FacialExpressionRecognition is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

FacialExpressionRecognition 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.

FacialExpressionRecognition saves you 11506 person hours of effort in developing the same functionality from scratch.

It has 23274 lines of code, 86 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 FacialExpressionRecognition and discovered the below as its top functions. This is intended to give you an instant insight into FacialExpressionRecognition implemented functionality, and help decide if they suit your requirements.

Evaluate the RBF model
Wrapper for SVM
Build the filters
Compute the PCA decomposition
Setup UI widget
Translate the UI
Evaluate validation
This function is called when the main function is called
Equivalent of equalization
Add noise to the image
Predict expression
3 - layer convolutional layer
Evaluate the Gabor model
Function to plot data
Evaluate LBP
3D convolutional layer
Generate test
Generate valid images
Displays the feature map
Plot the feature map
Get the feature map for a given layer
Load image
Generate anchors
Get faces from image
Plot training accuracy
Plot training loss
Load history from file
Generate training data

Get all kandi verified functions for this library.

FacialExpressionRecognition Key Features

No Key Features are available at this moment for FacialExpressionRecognition.

FacialExpressionRecognition Examples and Code Snippets

No Code Snippets are available at this moment for FacialExpressionRecognition.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install FacialExpressionRecognition

You can download it from GitHub.
You can use FacialExpressionRecognition 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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