AryaKoureshi/Emotion-Detection

This repository contains the code for an Emotion Detection project using deep learning models and real-time processing. The project is implemented in Python using the TensorFlow framework and focuses on detecting human emotions from images and real-time video streams.

20
/ 100
Experimental

This system helps analyze human emotions from still images or live video feeds. It takes an image or video stream as input and identifies various emotions like happy, sad, or angry. This tool would be useful for researchers studying human behavior, marketers analyzing audience reactions, or developers building interactive applications.

No commits in the last 6 months.

Use this if you need to automatically detect and classify human emotions from visual data, either from existing image files or in real-time video streams.

Not ideal if you require emotion detection from audio-only inputs or need to analyze subtle micro-expressions that go beyond basic emotion categories.

human-behavior-analysis market-research audience-engagement facial-recognition video-analytics
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 0 / 25

How are scores calculated?

Stars

8

Forks

Language

Jupyter Notebook

License

MIT

Last pushed

Sep 14, 2023

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/AryaKoureshi/Emotion-Detection"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.