# atulapra/Emotion-detection

Real-time Facial Emotion Detection using deep learning

Repository: https://github.com/atulapra/Emotion-detection
Canonical: https://ross.abutalabs.com/products/emotion-detection
Language: Python
License: MIT
License Family: permissive
Topics: emotion-recognition, tflearn, haar-cascade, deep-learning, emotion-detection, computer-vision, opencv, opencv-python
Last push: 2024-08-30T23:52:21+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": 3314, "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 1359, forks 552 (observed 2026-08-28T04:04:29.710257+00:00)

## What it is
A Python application that performs real-time facial emotion detection from a webcam feed using a CNN trained on the FER-2013 dataset. It uses Haar cascades for face detection and TensorFlow/Keras to classify faces into seven emotions.

## Use cases
- detect emotions from faces in a webcam feed in real time
- classify facial expressions into seven emotion categories
- train a CNN on the FER-2013 dataset
- learn how to combine OpenCV face detection with a deep learning classifier
- run a pretrained facial emotion recognition model

## When to choose
- you want a simple, working real-time facial emotion recognition demo
- you need a reference implementation for FER-2013 with TensorFlow 2.x and Keras
- you are learning computer vision pipelines combining Haar cascades and CNNs

## When to avoid
- you need production-grade accuracy - the model only reaches ~63% test accuracy
- you need a maintained library or API rather than a demo project
- you need emotion recognition beyond the seven FER-2013 categories or on static images at scale

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

## Member repositories
- atulapra/Emotion-detection (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:29.710257+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 2026-08-30T04:41:41.917129+00:00, confidence not recorded.
  - readme: https://github.com/atulapra/Emotion-detection (fetched 2026-08-28T04:04:29.710257+00:00, sha 98acffd495af)
- Data as of 2026-08-30T08:39:29.467469+00:00.