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Facial Emotions Image Detection
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Facial Emotions Image Detection

Developed by dima806
A facial emotion recognition model fine-tuned based on Google's ViT-base model, achieving 91% accuracy on the test set.
Face-related
Transformers
Open Source License:Apache-2.0#High-precision emotion recognition#ViT Vision Transformer#Real-time facial analysis
Downloads 198.83k
Release Time : 10/2/2023

Model Overview

This model uses the Vision Transformer architecture to recognize seven basic emotions from facial images: sadness, disgust, anger, neutral, fear, surprise, and happiness.

Model Features

High Accuracy
Achieves 91% overall accuracy on the test set, with an F1 score of 0.995 for the disgust category.
Multi-emotion Recognition
Can recognize seven basic facial emotions, covering common emotional expressions.
ViT-based Architecture
Uses the Vision Transformer model with powerful image feature extraction capabilities.

Model Capabilities

Facial emotion recognition
Image classification
Real-time emotion analysis

Use Cases

Human-Computer Interaction
Emotion-aware Systems
Used to enhance human-computer interaction by adjusting system responses based on user expressions.
Accurately identifies user emotional states.
Psychological Research
Emotional Response Analysis
Used for recording and analyzing subjects' emotional responses in psychological experiments.
Provides objective emotion classification data.
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