otaha178/Emotion-recognition
Real time emotion recognition
This tool helps analyze human facial expressions in real-time video streams, identifying emotions like happiness, anger, and more. It takes live camera footage of a person's face and outputs the likelihood of various emotions being displayed at that moment. This is useful for researchers studying non-verbal communication, UX designers observing user reactions, or marketers assessing engagement.
1,222 stars. No commits in the last 6 months.
Use this if you need to automatically detect and quantify the emotional states expressed on faces in live video for research or observational purposes.
Not ideal if you require extremely high accuracy for critical decision-making or need to analyze emotions from still images rather than video.
Stars
1,222
Forks
375
Language
Python
License
MIT
Category
Last pushed
Aug 30, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/otaha178/Emotion-recognition"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Related frameworks
HumeAI/hume-api-examples
Example projects built with the Hume AI APIs
amineHorseman/facial-expression-recognition-using-cnn
Deep facial expressions recognition using Opencv and Tensorflow. Recognizing facial expressions...
atulapra/Emotion-detection
Real-time Facial Emotion Detection using deep learning
MauryaRitesh/Facial-Expression-Detection
Facial Expression or Facial Emotion Detector can be used to know whether a person is sad, happy,...
isseu/emotion-recognition-neural-networks
Emotion recognition using DNN with tensorflow