Fast Facial Emotion Monitoring (FFEM)
This package provides a simple and efficient way to perform Facial Emotion Recognition (FER). It leverages advanced techniques and algorithms to detect and classify emotions from facial expressions.
How to Install
$ pip install ffem
Main Function
MonitorEmotion_From_Video(video_path: str | int, output_path:str) -> NoneThis function takes a video file or a webcam feed as input and performs FER. The results are saved to the specified output path.
Main Class
FaceEmotion_Detection()This class is the backbone of the FER process. It performs face detection and emotion recognition using DeepFace and MediaPipe. TheMonitorEmotion_From_Videofunction utilizes this class to carry out its operations.
This package is designed with user-friendliness in mind, making the complex task of FER accessible and straightforward for users. Whether you’re a researcher, a developer, or someone interested in FER, this package can be a valuable tool for your projects.
!!About FFEM
Use only FEEM version >= 0.3, previous versions had requiriments issues.
2 maintainers
Metadata
2 maintainers
Release files for FFEM 0.4.4
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| FFEM-0.4.4.tar.gz | 6.5 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| FFEM-0.4.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 16.8 kB
Release files / FFEM-0.4.4.tar.gz
| Download URL | FFEM-0.4.4.tar.gz |
|---|---|
| Size | 6.5 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / FFEM-0.4.4-py3-none-any.whl
| Download URL | FFEM-0.4.4-py3-none-any.whl |
|---|---|
| Size | 10.3 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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No |
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twine/5.0.0 CPython/3.11.2
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Security for FFEM 0.4.4
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