Facial-Emotion-Recognition-PyTorch-ONNX

by shangeth Python Version: Current License: No License

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

kandi X-RAY | Facial-Emotion-Recognition-PyTorch-ONNX Summary

Facial-Emotion-Recognition-PyTorch-ONNX is a Python library. Facial-Emotion-Recognition-PyTorch-ONNX has no bugs, it has no vulnerabilities and it has low support. However Facial-Emotion-Recognition-PyTorch-ONNX build file is not available. You can download it from GitHub.

Facial-Emotion-Recognition-PyTorch-ONNX

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Facial-Emotion-Recognition-PyTorch-ONNX has a low active ecosystem.

It has 24 star(s) with 12 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

Facial-Emotion-Recognition-PyTorch-ONNX has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Facial-Emotion-Recognition-PyTorch-ONNX is current.

Quality

Facial-Emotion-Recognition-PyTorch-ONNX has 0 bugs and 0 code smells.

Security

Facial-Emotion-Recognition-PyTorch-ONNX has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Facial-Emotion-Recognition-PyTorch-ONNX code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Facial-Emotion-Recognition-PyTorch-ONNX 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

Facial-Emotion-Recognition-PyTorch-ONNX releases are not available. You will need to build from source code and install.

Facial-Emotion-Recognition-PyTorch-ONNX has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 33506 lines of code, 16 functions and 10 files.

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

Top functions reviewed by kandi - BETA

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

Define a FER video
Load a trained model
Returns a list of Datasets
Load the faces and emotions
Generate FER image
Convert a torch model into a TF model
Load a tensorflow graph from a file
Loads a trained model
Return the number of parameters in this module

Get all kandi verified functions for this library.

Facial-Emotion-Recognition-PyTorch-ONNX Key Features

No Key Features are available at this moment for Facial-Emotion-Recognition-PyTorch-ONNX.

Facial-Emotion-Recognition-PyTorch-ONNX Examples and Code Snippets

No Code Snippets are available at this moment for Facial-Emotion-Recognition-PyTorch-ONNX.

Community Discussions

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

Vulnerabilities

No vulnerabilities reported

Install Facial-Emotion-Recognition-PyTorch-ONNX

You can download it from GitHub.
You can use Facial-Emotion-Recognition-PyTorch-ONNX 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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