Easy lightweight emotion detection with webcam
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Updated
Jul 4, 2024 - Python
Easy lightweight emotion detection with webcam
A Streamlit application that predicts facial emotions from uploaded images or pictures taken with the camera.
Sentiment analysis and emotion classification for Italian using BERT (fine-tuning). Published at the WASSA workshop (EACL2021).
Detect the emotion behind a piece of text
detect tone of voice in a text message using BERT model in pytorch.
Face Detection and Emotion Recognition models to capture and interpret facial expressions
Alert police and switch off ATM upon finding the emotion “fear” on user face.
NLP Text Emotion Detection using tensorflow keras. This is a web based project.
A hackathon project to use a realtime feed of in-ear EEG data from IDUN Guardian to analyze emotional state and control Spotify with it.
Files uploaded from the Raspberry Pi that uses emotional detection to prompt two outputs via the LCD screen and speaker. For more information, please read the README.md.
Bechelor thesis: BERT-based model for emotion detection applied to Stack Overflow.
Fast emotion classification model
Code repository for paper: "The Face of Populism: Examining Differences in Facial Emotional Expressions of Political Leaders Using Machine Learning"
The AI-powered ser Python package is a tool for recognizing and analyzing emotions in speech. Employing state-of-the-art machine learning and audio processing techniques, it classifies emotions in audio recordings, extracts transcripts, and integrates these with a timeline of emotional states
The detection of emotion is made by using the machine learning concept. You can use the trained dataset to detect the emotion of the human being. For detecting the different emotions, first, you need to train those different emotions, or you can use a dataset already available on the internet.
A modern GUI Based Face Recognition and Emotion Predictor using Machine Learning
Project to infere emotional expressions and benchmark datasets by Niklas Wagner, Felix Mätzler, Samed R. Vossberg, Helen Schneider and Svetlana Pavlitska.
Real-time Facial Emotion Detection using deep learning
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