Complete system for facial identity system

Related tags

Deep Learningpythonfirebasegoogle-cloud-storagepytorchface-recognitionone-shot-learningjetson-nano
Overview

Facial Identity system

⭐️ ⭐️ ⭐ This repo is still updating ⭐ ⭐ ⭐

Introduction

This project is to utilize facial recognition to create a facial identity system. Our backend is constructed by one-shot models which is more flexible for adding a new face. The system is built on personal computer and Jetson Nano. Jetson Nano is used to recognized the faces and upload the detected information to Firebase. Users who used our application with account and password can log in to control the database and also see the information.

Folder structure

| - backend - For Personal computer
|
| - csv_file - Contribution for the CelebA dataset
|
| - jetson - Files for Jetson Nano
|
| - model - Model we used for training and detecting

Features

Our facial identity system includes below features:

  • One-shot face recognition, add your faces without extra training
  • Complete database operation (upload, delete, update)
  • Fine-tuned your model at any time
  • Use as a monitor
  • Visualize the features

Installation

Personal computer

$ pip install -r requirements.txt

Jetson Nano

$ pip install -r requirements.txt

Increase swap space on Jetson Nano (Optional)

Our nano would crush when using cuda until we increase its swap memory 🥳

> /etc/fstab'"> 
# 4.0G is the swap space
$ sudo fallocate -l 4.0G /swapfile
$ sudo chmod 600 /swapfile
$ sudo mkswap /swapfile
$ sudo swapon /swapfile

# Create swap memory on every reboot
$ sudo bash -c 'echo "/var/swapfile swap swap defaults 0 0" >> /etc/fstab'

Experiments

Result for real-time training

Type Original New
Cosine Similarity Positive 0.9889 0.9863
Negative 0.7673 0.6695
L2 Distance Positive 0.1491 0.1655
Negative 0.6822 0.8130

Run time using different methods

  • second per image (s / img)
CPU (Pytorch) Cuda (Pytorch) ONNX TensorRT
4.11s 75.329s 0.1260s 1.975s

It is surprising that cuda consumes lots of time. We guess it is because cuda rely on huge amount of swap memory that slow down its runtime 😢 .

Contribution to CelebA

In order to train one-shot model, we obtain the face's coordinates beforehand. All files are placed in csv_file.

The coordinates were obtained from facenet-pytorch

File name Description
id_multiple.csv To ensure each celebrity have at least two images (For positive usage).
cropped.csv Include the face's coordinates and ensure each celebrity has at least two images.

Citation

@inproceedings{liu2015faceattributes,
  title = {Deep Learning Face Attributes in the Wild},
  author = {Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
  booktitle = {Proceedings of International Conference on Computer Vision (ICCV)},
  month = {December},
  year = {2015} 
}

@inproceedings{koch2015siamese,
  title={Siamese neural networks for one-shot image recognition},
  author={Koch, Gregory and Zemel, Richard and Salakhutdinov, Ruslan and others},
  booktitle={ICML deep learning workshop},
  volume={2},
  year={2015},
  organization={Lille}
}

@inproceedings{chen2020simple,
  title={A simple framework for contrastive learning of visual representations},
  author={Chen, Ting and Kornblith, Simon and Norouzi, Mohammad and Hinton, Geoffrey},
  booktitle={International conference on machine learning},
  pages={1597--1607},
  year={2020},
  organization={PMLR}
}

@inproceedings{schroff2015facenet,
  title={Facenet: A unified embedding for face recognition and clustering},
  author={Schroff, Florian and Kalenichenko, Dmitry and Philbin, James},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={815--823},
  year={2015}
}
You might also like...
GazeScroller - Using Facial Movements to perform Hands-free Gesture on the system

GazeScroller Using Facial Movements to perform Hands-free Gesture on the system

null 2 Jan 5, 2022
An automated facial recognition based attendance system (desktop application)

Facial_Recognition_based_Attendance_System An automated facial recognition based attendance system (desktop application) Made using Python, Tkinter an

null 1 Jun 21, 2022
The world's simplest facial recognition api for Python and the command line
The world's simplest facial recognition api for Python and the command line

Face Recognition You can also read a translated version of this file in Chinese 简体中文版 or in Korean 한국어 or in Japanese 日本語. Recognize and manipulate fa

Adam Geitgey 46.9k Jan 3, 2023
Spontaneous Facial Micro Expression Recognition using 3D Spatio-Temporal Convolutional Neural Networks

Spontaneous Facial Micro Expression Recognition using 3D Spatio-Temporal Convolutional Neural Networks Abstract Facial expression recognition in video

Bogireddy Sai Prasanna Teja Reddy 103 Dec 29, 2022
Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution
Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution

FAU Implementation of the paper: Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution. Yingruo

Evelyn 78 Nov 29, 2022
Py-FEAT: Python Facial Expression Analysis Toolbox

Py-FEAT is a suite for facial expressions (FEX) research written in Python. This package includes tools to detect faces, extract emotional facial expressions (e.g., happiness, sadness, anger), facial muscle movements (e.g., action units), and facial landmarks, from videos and images of faces, as well as methods to preprocess, analyze, and visualize FEX data.

Computational Social Affective Neuroscience Laboratory 147 Jan 6, 2023
Instant Real-Time Example-Based Style Transfer to Facial Videos
Instant Real-Time Example-Based Style Transfer to Facial Videos

FaceBlit: Instant Real-Time Example-Based Style Transfer to Facial Videos The official implementation of FaceBlit: Instant Real-Time Example-Based Sty

Aneta Texler 131 Dec 19, 2022
Keeping it safe - AI Based COVID-19 Tracker using Deep Learning and facial recognition
Keeping it safe - AI Based COVID-19 Tracker using Deep Learning and facial recognition

Keeping it safe - AI Based COVID-19 Tracker using Deep Learning and facial recognition

Vansh Wassan 15 Jun 17, 2021
Official PyTorch implementation of Retrieve in Style: Unsupervised Facial Feature Transfer and Retrieval.
Official PyTorch implementation of Retrieve in Style: Unsupervised Facial Feature Transfer and Retrieval.

Retrieve in Style: Unsupervised Facial Feature Transfer and Retrieval PyTorch This is the PyTorch implementation of Retrieve in Style: Unsupervised Fa

null 60 Oct 12, 2022
Releases(weight)
Owner
GitHub Repository
Distributed Evolutionary Algorithms in Python

DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru

Distributed Evolutionary Algorithms in Python 4.9k Jan 05, 2023
Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM

Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Tested on many Common CNN Networks and Vision Transformers. ⭐ Includes smoo

Jacob Gildenblat 6.6k Jan 06, 2023
SE-MSCNN: A Lightweight Multi-scaled Fusion Network for Sleep Apnea Detection Using Single-Lead ECG Signals

SE-MSCNN: A Lightweight Multi-scaled Fusion Network for Sleep Apnea Detection Using Single-Lead ECG Signals Abstract Sleep apnea (SA) is a common slee

9 Dec 21, 2022
DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting

DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting Created by Yongming Rao*, Wenliang Zhao*, Guangyi Chen, Yansong Tang, Zheng Z

Yongming Rao 321 Dec 27, 2022
Pytorch implementation of Feature Pyramid Network (FPN) for Object Detection

fpn.pytorch Pytorch implementation of Feature Pyramid Network (FPN) for Object Detection Introduction This project inherits the property of our pytorc

Jianwei Yang 912 Dec 21, 2022
MTCNN face detection implementation for TensorFlow, as a PIP package.

MTCNN Implementation of the MTCNN face detector for Keras in Python3.4+. It is written from scratch, using as a reference the implementation of MTCNN

Iván de Paz Centeno 1.9k Dec 30, 2022
Franka Emika Panda manipulator kinematics&dynamics simulation

pybullet_sim_panda Pybullet simulation environment for Franka Emika Panda Dependency pybullet, numpy, spatial_math_mini Simple example (please check s

0 Jan 20, 2022
PyTorch implementation of our method for adversarial attacks and defenses in hyperspectral image classification.

Self-Attention Context Network for Hyperspectral Image Classification PyTorch implementation of our method for adversarial attacks and defenses in hyp

22 Dec 02, 2022
Arabic Car License Recognition. A solution to the kaggle competition Machathon 3.0.

Transformers Arabic licence plate recognition 🚗 Solution to the kaggle competition Machathon 3.0. Ranked in the top 6️⃣ at the final evaluation phase

Noran Hany 17 Dec 04, 2022
MINOS: Multimodal Indoor Simulator

MINOS Simulator MINOS is a simulator designed to support the development of multisensory models for goal-directed navigation in complex indoor environ

194 Dec 27, 2022
Code for Universal Semi-Supervised Semantic Segmentation models paper accepted in ICCV 2019

USSS_ICCV19 Code for Universal Semi Supervised Semantic Segmentation accepted to ICCV 2019. Full Paper available at https://arxiv.org/abs/1811.10323.

Tarun K 68 Nov 24, 2022
Hyperbolic Procrustes Analysis Using Riemannian Geometry

Hyperbolic Procrustes Analysis Using Riemannian Geometry The code in this repository creates the figures presented in this article: Please notice that

Ronen Talmon's Lab 2 Jan 08, 2023
Resources for our AAAI 2022 paper: "LOREN: Logic-Regularized Reasoning for Interpretable Fact Verification".

LOREN Resources for our AAAI 2022 paper (pre-print): "LOREN: Logic-Regularized Reasoning for Interpretable Fact Verification". DEMO System Check out o

Jiangjie Chen 37 Dec 27, 2022
Open-source code for Generic Grouping Network (GGN, CVPR 2022)

Open-World Instance Segmentation: Exploiting Pseudo Ground Truth From Learned Pairwise Affinity Pytorch implementation for "Open-World Instance Segmen

Meta Research 99 Dec 06, 2022
Implementation of Geometric Vector Perceptron, a simple circuit for 3d rotation equivariance for learning over large biomolecules, in Pytorch. Idea proposed and accepted at ICLR 2021

Geometric Vector Perceptron Implementation of Geometric Vector Perceptron, a simple circuit with 3d rotation equivariance for learning over large biom

Phil Wang 59 Nov 24, 2022
Data Engineering ZoomCamp

Data Engineering ZoomCamp I'm partaking in a Data Engineering Bootcamp / Zoomcamp and will be tracking my progress here. I can't promise these notes w

Aaron 61 Jan 06, 2023
A LiDAR point cloud cluster for panoptic segmentation

Divide-and-Merge-LiDAR-Panoptic-Cluster A demo video of our method with semantic prior: More information will be coming soon! As a PhD student, I don'

YimingZhao 65 Dec 22, 2022
VQGAN+CLIP Colab Notebook with user-friendly interface.

VQGAN+CLIP and other image generation system VQGAN+CLIP Colab Notebook with user-friendly interface. Latest Notebook: Mse regulized zquantize Notebook

Justin John 227 Jan 05, 2023
Cl datasets - PyTorch image dataloaders and utility functions to load datasets for supervised continual learning

Continual learning datasets Introduction This repository contains PyTorch image

berjaoui 5 Aug 28, 2022
A very impractical 3D rendering engine that runs in the python terminal.

Terminal-3D-Render A very impractical 3D rendering engine that runs in the python terminal. do NOT try to run this program using the standard python I

23 Dec 31, 2022