Efficient face emotion recognition in photos and videos
The repo contains an audio emotion detection model, facial emotion detection model, and a model that combines both these models to predict emotions from a video
A computer vision project.
Moody is a web application allowing the host of online meetings (e.g. via Zoom, Microsoft Teams or Google Meet) to collect real-time feedback of the participant's emotions.
Face emotion detection system .
Recognition of Iranian human facial emotions across four categories: Happy, Sad, Angry, and Neutral.
A Face Emotion Recognizer
This project is a part of "Deep Learning + ML Engineering” curriculum as capstone projects at Almabetter School.
Build a Face Emotion Recognition (FER) Algorithm
Super lite Flask app that can perform emotion detection
This web app uses face-api to detect face using webcam live video feed.
Face Emotion Recognition using FER2013 dataset. Test accuracy: 69.35%
Face-Emotion-Recognition using a model trained over MobileNet with an accuracy of 70%
Face emotion recognition technology detects emotions and mood patterns invoked in human faces. This technology is used as a sentiment analysis tool to identify the six universal expressions, namely, happiness, sadness, anger, surprise, fear and disgust. Identifying facial expressions has a wide range of applications in human social interaction d…
Building and testing several models for real-time facial emotion recognition.
A from-scratch SOTA PyTorch implementation of the Inception-ResNet-V2 model designed by Szegedy et. al., adapted for Face Emotion Recognition (FER), with custom dataset support.
Recognising facial emotions using a library from pytorch
Face Emotion Detection using CNN
Facial emotion recognition (FER) using convolutional neural networks
Facial Emotion Recognition (FER) is a computer vision task aimed at identifying and categorizing emotional expressions depicted on a human face. The goal is to automate the process of determining emotions in real-time, by analyzing the various features of a face.
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