sid230798/Facial-emotion-Recognition

This Repo consist code for transfer learning for facial emotion detection via valence and arousal levels. We used pretrained weights from VGG-16 net and apply on that features deep neural network and lstm model in pytorch. We tested our model on Aff-wild net dataset.

26
/ 100
Experimental

This tool helps researchers and analysts automatically categorize human facial expressions from video footage. By processing video frames, it identifies and quantifies the underlying emotional state, expressed as valence (how positive or negative) and arousal (how intense). This is useful for anyone studying emotional responses in naturalistic settings.

No commits in the last 6 months.

Use this if you need to analyze emotional content from video data to understand human sentiment or reactions.

Not ideal if you need real-time emotion detection on a live feed or require highly specialized emotion categories beyond valence and arousal.

emotion-analysis behavioral-research video-analysis human-computer-interaction psychology-research
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 12 / 25

How are scores calculated?

Stars

20

Forks

3

Language

Python

License

Last pushed

May 03, 2020

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/sid230798/Facial-emotion-Recognition"

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