FaceChannel Library - Facial Expression Recognition Models!
This repository holds the FaceChannel Library. The FaceChannel contains different facial expression recognition models, and makes it easier to deploy and use them.
Instalation and Documentation
You can install the library using pip:
pip install facechannel
and you can check the full documentation for more information.
Also check the examples folder for a full set of ready-to-use demos!
Avaliable Models
FaceChannel is a python library that holds several facial expression recognition models. The main idea behind the FaceChannel is to facilitate the use of this technology by reducing the deployment effort. This is the current list of available models:
| Model | Input Type | Output Type |
|---|---|---|
| FaceChannelV1 Cat | Single Image (64x64) | ["Neutral", "Happiness", "Surprise", "Sadness", "Anger", "Disgust", "Fear", "Contempt"] |
| FaceChannelV1 Dim | Single Image (64x64) | ["Arousal", "Valence"] |
| Self Affective Memory | Single Image (64x64) | ["Arousal", "Valence"] |
- FaceChannelV1 - Barros, P., Churamani, N., & Sciutti, A. (2020). The facechannel: A fast and furious deep neural network for facial expression recognition. SN Computer Science, 1(6), 1-10
- Self Affective Memory - Barros, P., & Wermter, S. (2017, May). A self-organizing model for affective memory. In 2017 International Joint Conference on Neural Networks (IJCNN) (pp. 31-38). IEEE.
License
All the examples in this repository are distributed under a Non-Comercial license. If you use this environment, you have to agree with the following itens:
-
To cite our associated references in any of your publication that make any use of these examples.
-
To use the environment for research purpose only.
-
To not provide the environment to any second parties.
Contact
Pablo Barros - pablo.alvesdebarros@iit.it
1 maintainer
Metadata
1 maintainer
Release files for FaceChannel 0.0.3.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| FaceChannel-0.0.3.4-py3-none-any.whl | Python 3 | none | any | Details for FaceChannel-0.0.3.4-py3-none-any.whl |
Release files / FaceChannel-0.0.3.4-py3-none-any.whl
| Download URL | FaceChannel-0.0.3.4-py3-none-any.whl |
|---|---|
| Size | 16.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
146dc4526d2258dce33ed00f7d9bd40d608c622b7797c04cf92cb76fabe5dd6a
|
|
BLAKE2b-256 checksum How to use checksums |
73b6c363d978e2e801ed04686ffae61f6d718f2d9b541a5d2a663d547c663f14
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.10.4
|
Security for FaceChannel 0.0.3.4
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
