# otaha178/Emotion-recognition

Real time emotion recognition

Repository: https://github.com/otaha178/Emotion-recognition
Canonical: https://ross.abutalabs.com/products/emotion-recognition
Language: Python
License: MIT
License Family: permissive
Topics: computer-vision, deep-learning, emotion-recognition, emotion-analysis, convolutional-neural-networks
Last push: 2024-08-30T23:52:29+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2930, "days_push": 733, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1236, forks 372 (observed 2026-08-28T04:04:05.220736+00:00)

## What it is
A Python application that performs real-time facial emotion recognition from a webcam feed using a convolutional neural network. It displays detected emotion probabilities and includes a pretrained model plus training scripts based on the FER2013 dataset.

## Use cases
- recognize emotions from webcam video in real time
- classify facial expressions like happy or angry
- run a pretrained emotion detection demo
- train a CNN emotion classifier on FER2013
- show probability bars for mixed emotions on a face

## When to choose
- you need a quick real-time facial emotion recognition demo
- you want a pretrained FER2013 model to experiment with
- you are learning how CNNs are applied to facial expression recognition

## When to avoid
- you need production-grade accuracy (test accuracy is only ~66%)
- you need a maintained library with an API rather than a demo script
- you need multi-face tracking or advanced emotion models

## Facets
- artifact type: application
- maturity: maintenance
- function: computer-vision, image-processing, machine-learning, deep-learning
- domain: computer-vision, artificial-intelligence, deep-learning
- platform: python, cross-platform
- tags: emotion-recognition, facial-expression-analysis, cnn, fer2013, webcam, real-time

## Member repositories
- otaha178/Emotion-recognition (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:05.220736+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T08:22:00.138865+00:00, confidence not recorded.
  - readme: https://github.com/otaha178/Emotion-recognition (fetched 2026-08-28T04:04:05.220736+00:00, sha d00792781030)
- Data as of 2026-08-30T08:39:29.467469+00:00.