Automatically align face images ๐Ÿ™ƒโ†’๐Ÿ™‚. Can also do windowing and warping.

Overview

Automatic Face Alignment (AFA)

Carl M. Gaspar & Oliver G.B. Garrod

You have lots of photos of faces like this:

But you want to line up all of the faces like this:

Perhaps you would also like to window the faces to show only inner facial features like this:

All of the above can be done using AFA like this:

import alignfaces as afa

faces_path = "/Users/Me/faces_for_my_study/"
afa.get_landmarks(faces_path)
aligned_path = afa.align_procrustes(faces_path)
afa.get_landmarks(aligned_path)
the_aperture, aperture_path = afa.place_aperture(aligned_path)

To better understand how to write a script for your specific purposes, we direct you to demo 1. Demo 1 also describes how AFA alignment works.

All of these functions depend on reliable detection of facial landmarks, which is provided by the DLIB library. Alignment is based on generalized Procrustes analysis (GPA), which extensively unit tested.

Additional functions (warping)

Automatic landmark detection means that it is also easy to separate shape and texture in order to produce various kinds of warped images.

AFA provides functions for two types of face-warping manipulations common in face perception research.

Morphing between faces

To learn how to do this please see demo 2.

Enhanced average of facial identity

To learn how to do this please see demo 3.

Setup

It is highly recommended that you have conda installed, preferably miniconda rather than full fat anaconda.

If you do have conda, then do the following to install:

=3.9" scikit-image conda activate myenv pip install "alignfaces @ git+https://[email protected]/SourCherries/auto-face-align.git" ">
conda create --name myenv conda-forge::dlib "python>=3.9" scikit-image

conda activate myenv

pip install "alignfaces @ git+https://[email protected]/SourCherries/auto-face-align.git"

This will create a new virtual environment called myenv. You can use another name for that. You'll need to activate this environment using conda activate myenv whenever you want to use AFA. To deactivate, simply type conda deactivate myenv.

Windows users may encounter a problem with plotting. That is a general issue with Matplotlib on Windows. To fix, simply type the following while your myenv is activated:

conda install freetype=2.10.4

How well does this work?

In addition to unit-testing critical computations, I evaluated both landmark estimation (DLIB) and the outcome of the entire alignment procedure using various face databases. The results are described here.

Citation

If you use this package for your research, please cite the following preprint:

Gaspar, C. M., & Garrod, O. G. B. (2021, November 8). A Python toolbox for Automatic Face Alignment (AFA). Retrieved from psyarxiv.com/erc8a

DOI:

10.31234/osf.io/erc8a

License

This module is under an Apache-2.0 license.

Owner
Carl Michael Gaspar
Scientist focussed on human visual perception and neuroscience.
Carl Michael Gaspar
Locally cache assets that are normally streamed in POPULATION: ONE

Population One Localizer This is no longer needed as of the build shipped on 03/03/22, thank you bigbox :) Locally cache assets that are normally stre

Ahman Woods 2 Mar 04, 2022
A visualisation tool for Deep Reinforcement Learning

DRLVIS - Visualising Deep Reinforcement Learning Created by Marios Sirtmatsis with the support of Alex Bรคuerle. DRLVis is an application used for visu

Marios Sirtmatsis 1 Nov 04, 2021
Jremesh-tools - Blender addon for quad remeshing

JRemesh Tools Blender 2.8 - 3.x addon for quad remeshing. Currently it is a wrap

Jayanam 89 Dec 30, 2022
IJCAI2020 & IJCV 2020 :city_sunrise: Unsupervised Scene Adaptation with Memory Regularization in vivo

Seg_Uncertainty In this repo, we provide the code for the two papers, i.e., MRNet๏ผšUnsupervised Scene Adaptation with Memory Regularization in vivo, IJ

Zhedong Zheng 348 Jan 05, 2023
Pytorch implementation of DeepMind's differentiable neural computer paper.

DNC pytorch This is a Pytorch implementation of DeepMind's Differentiable Neural Computer (DNC) architecture introduced in their recent Nature paper:

Yuanpu Xie 91 Nov 21, 2022
As-ViT: Auto-scaling Vision Transformers without Training

As-ViT: Auto-scaling Vision Transformers without Training [PDF] Wuyang Chen, Wei Huang, Xianzhi Du, Xiaodan Song, Zhangyang Wang, Denny Zhou In ICLR 2

VITA 68 Sep 05, 2022
Official code for paper "Optimization for Oriented Object Detection via Representation Invariance Loss".

Optimization for Oriented Object Detection via Representation Invariance Loss By Qi Ming, Zhiqiang Zhou, Lingjuan Miao, Xue Yang, and Yunpeng Dong. Th

ming71 56 Nov 28, 2022
An implementation of RetinaNet in PyTorch.

RetinaNet An implementation of RetinaNet in PyTorch. Installation Training COCO 2017 Pascal VOC Custom Dataset Evaluation Todo Credits Installation In

Conner Vercellino 297 Jan 04, 2023
EncT5: Fine-tuning T5 Encoder for Non-autoregressive Tasks

EncT5 (Unofficial) Pytorch Implementation of EncT5: Fine-tuning T5 Encoder for Non-autoregressive Tasks About Finetune T5 model for classification & r

Jangwon Park 34 Jan 01, 2023
Reading Group @mila-iqia on Computational Optimal Transport for Machine Learning Applications

Computational Optimal Transport for Machine Learning Reading Group Over the last few years, optimal transport (OT) has quickly become a central topic

Ali Harakeh 11 Aug 26, 2022
StarGAN - Official PyTorch Implementation (CVPR 2018)

StarGAN - Official PyTorch Implementation ***** New: StarGAN v2 is available at https://github.com/clovaai/stargan-v2 ***** This repository provides t

Yunjey Choi 5.1k Jan 04, 2023
Bidimensional Leaderboards: Generate and Evaluate Language Hand in Hand

Bidimensional Leaderboards: Generate and Evaluate Language Hand in Hand Introduction We propose a generalization of leaderboards, bidimensional leader

4 Dec 03, 2022
Official code of "Mitigating the Mutual Error Amplification for Semi-Supervised Object Detection"

CrossTeaching-SSOD 0. Introduction Official code of "Mitigating the Mutual Error Amplification for Semi-Supervised Object Detection" This repo include

Bruno Ma 9 Nov 29, 2022
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data

FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well i

0 Sep 06, 2022
Implementation of Multistream Transformers in Pytorch

Multistream Transformers Implementation of Multistream Transformers in Pytorch. This repository deviates slightly from the paper, where instead of usi

Phil Wang 47 Jul 26, 2022
BEGAN in PyTorch

BEGAN in PyTorch This project is still in progress. If you are looking for the working code, use BEGAN-tensorflow. Requirements Python 2.7 Pillow tqdm

Taehoon Kim 260 Dec 07, 2022
This is an example of a reproducible modelling project

An example of a reproducible modelling project What are we doing? This example was created for the 2021 fall lecture series of Stanford's Center for O

Armin Thomas 2 Oct 26, 2021
Codes for paper "KNAS: Green Neural Architecture Search"

KNAS Codes for paper "KNAS: Green Neural Architecture Search" KNAS is a green (energy-efficient) Neural Architecture Search (NAS) approach. It contain

90 Dec 22, 2022
Pytorch implementation of Compressive Transformers, from Deepmind

Compressive Transformer in Pytorch Pytorch implementation of Compressive Transformers, a variant of Transformer-XL with compressed memory for long-ran

Phil Wang 118 Dec 01, 2022
Ganilla - Official Pytorch implementation of GANILLA

GANILLA We provide PyTorch implementation for: GANILLA: Generative Adversarial Networks for Image to Illustration Translation. Paper Arxiv Updates (Fe

Samet Hi 462 Dec 05, 2022