Emotion Recognition from Facial Images

Last update: Feb 09, 2022

Related tags

Overview

Reconhecimento de Emoções a partir de imagens faciais

Este projeto implementa um classificador simples que utiliza técncias de deep learning e transferência de aprendizado para distinguir a emoção do usuário em tempo real a partir de uma imagem fornecida pela câmera do computador.

Contato

Como executar?

Digite em seu terminal na pasta raiz do projeto: python3 main.py [argumento].
O parâmetro argumento pode ser: 'capture', 'train' ou 'analysis'.
Eles executam respectivamente: 
- captura e reconhecimento da imagem via webcam;
- treinamento da rede neural;
- análise dos dados utilizados para o treinamento.

Direitos Autorais:

Este projeto tem objetivo recreativo e nem o conjunto de dados utilizado nem o classificador cascade são de autoria própria.

Todos os direitos ficam reservados aos autores.

Owner

Gabriel

Student at School of Arts, Science and Humanities | University of São Paulo (EACH-USP). I'm software developer intern and data science enthusiastic.

GitHub Repository

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Emotion Recognition from Facial Images

Related tags

Overview

Reconhecimento de Emoções a partir de imagens faciais

Contato

Como executar?

Direitos Autorais:

Owner

Gabriel

Official implementation of Protected Attribute Suppression System, ICCV 2021

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Emotion Recognition from Facial Images

Related tags

Overview

Reconhecimento de Emoções a partir de imagens faciais

Contato

Como executar?

Direitos Autorais:

Owner

Gabriel

Official implementation of Protected Attribute Suppression System, ICCV 2021

As a part of the HAKE project, includes the reproduced SOTA models and the corresponding HAKE-enhanced versions (CVPR2020).

Yet Another Robotics and Reinforcement (YARR) learning framework for PyTorch.

Contrastive Fact Verification

This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL [Deep Graph Library] and PyTorch.

This package contains deep learning models and related scripts for RoseTTAFold

Libraries, tools and tasks created and used at DeepMind Robotics.

Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning

Python Rapid Artificial Intelligence Ab Initio Molecular Dynamics

Certified Patch Robustness via Smoothed Vision Transformers

An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates neural fields, predictive coding, top-down-bottom-up, and attention (consensus between columns)

THIS IS THE **OLD** PYMC PROJECT. PLEASE USE PYMC3 INSTEAD:

Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite and .pb from .tflite.

official implementation for the paper "Simplifying Graph Convolutional Networks"

A deep-learning pipeline for segmentation of ambiguous microscopic images.

Augmented Traffic Control: A tool to simulate network conditions

An implementation of RetinaNet in PyTorch.

Bayesian Generative Adversarial Networks in Tensorflow

True per-item rarity for Loot

This is implementation of AlexNet(2012) with 3D Convolution on TensorFlow (AlexNet 3D).

THIS IS THE OLD PYMC PROJECT. PLEASE USE PYMC3 INSTEAD: