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.
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.
1 maintainer
Metadata
1 maintainer
Release files for FFEMcv 0.3.0
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| FFEMcv-0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Release files / FFEMcv-0.3.0-py3-none-any.whl
| Download URL | FFEMcv-0.3.0-py3-none-any.whl |
|---|---|
| Size | 10.2 kB |
| Tags | Python 3 |
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