Facial detection, landmark tracking and expression transfer library for Windows, Linux and Mac

Overview

Welcome to the CSIRO Face Analysis SDK. Documentation for the SDK can be found in doc/documentation.html.

All code in this SDK is provided according to the license found in LICENSE.

If you use the CSIRO Face Analysis SDK in any publications, we ask that you reference our works.

The face tracking component is based on the publication: J. Saragih, S. Lucey and J. Cohn, "Deformable Model Fitting by Regularized Landmark Mean-Shift", IJCV 2011.

The expression transfer component is based on the publication: J. Saragih, S. Lucey and J. Cohn, "Real-time Avatar Animation from a Single Image", AFGR Workshop 2011.

If you use the SDK, we ask that you reference the following paper: M. Cox, J. Nuevo, J. Saragih and S. Lucey, "CSIRO Face Analysis SDK", AFGR 2013.


Here are the updates in the original code included in this fork of the project:

  • The dependency of Qt in the qt-gui project was upgraded from Qt4 to Qt5.
  • Some OpenCV missing includes were added (perhaps they are due to changes in version used).
  • The type casts were made explicit to remove related warning messages.
  • Some static array allocations were replaced with the operator new[].
  • The Windows/POSIX-specific function calls were enclosed in #ifdefs based on the operating system defined at compilation time, and the the best corresponding functions were used for Windows (for instance: PathRemoveFileSpec and PathStripPath respectively replaced dirname and basename in Windows).
  • The class ForkRunner was completely replaced in Windows by the implementation proposed by Ben Howell here. Although, there is no direct equivalent of fork (used by the original class) on Windows and CreateProcess does not have the same behaviour (further tests required).
  • The libraries utilities, clmTracker and avatarAnim, that were originally created as shared libraries, were transformed into static libraries only for the Windows configuration. This was just simpler to do at this time, because the use of the __declspec(dllexport) directive (to export the functions/classes to be usable through a DLL) was causing problems related to third part objects not being equally exported (for instance, in some classes/functions, the compiler was producing messages like: "warning C4251: class 'cv::Mat' needs to have dll-interface to be used by clients of class ").
Owner
Luiz Carlos Vieira
Luiz Carlos Vieira
Extreme Lightwegith Portrait Segmentation

Extreme Lightwegith Portrait Segmentation Please go to this link to download code Requirements python 3 pytorch = 0.4.1 torchvision==0.2.1 opencv-pyt

HYOJINPARK 59 Dec 16, 2022
The official repository for "Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds"

Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds The why Im

3 Mar 29, 2022
Deep learning for spiking neural networks

A deep learning library for spiking neural networks. Norse aims to exploit the advantages of bio-inspired neural components, which are sparse and even

Electronic Vision(s) Group — BrainScaleS Neuromorphic Hardware 59 Nov 28, 2022
Unofficial implementation of Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segmentation

Point-Unet This is an unofficial implementation of the MICCAI 2021 paper Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segment

Namt0d 9 Dec 07, 2022
DiSECt: Differentiable Simulator for Robotic Cutting

DiSECt: Differentiable Simulator for Robotic Cutting Website | Paper | Dataset | Video | Blog post DiSECt is a simulator for the cutting of deformable

NVIDIA Research Projects 73 Oct 29, 2022
Radar-to-Lidar: Heterogeneous Place Recognition via Joint Learning

radar-to-lidar-place-recognition This page is the coder of a pre-print, implemented by PyTorch. If you have some questions on this project, please fee

Huan Yin 37 Oct 09, 2022
PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids

PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids The electric grid is a key enabling infrastructure for the a

Texas A&M Engineering Research 19 Jan 07, 2023
Dense Contrastive Learning (DenseCL) for self-supervised representation learning, CVPR 2021.

Dense Contrastive Learning for Self-Supervised Visual Pre-Training This project hosts the code for implementing the DenseCL algorithm for se

Xinlong Wang 491 Jan 03, 2023
minimizer-space de Bruijn graphs (mdBG) for whole genome assembly

rust-mdbg: Minimizer-space de Bruijn graphs (mdBG) for whole-genome assembly rust-mdbg is an ultra-fast minimizer-space de Bruijn graph (mdBG) impleme

Barış Ekim 148 Dec 01, 2022
The Self-Supervised Learner can be used to train a classifier with fewer labeled examples needed using self-supervised learning.

Published by SpaceML • About SpaceML • Quick Colab Example Self-Supervised Learner The Self-Supervised Learner can be used to train a classifier with

SpaceML 92 Nov 30, 2022
Ascend your Jupyter Notebook usage

Jupyter Ascending Sync Jupyter Notebooks from any editor About Jupyter Ascending lets you edit Jupyter notebooks from your favorite editor, then insta

Untitled AI 254 Jan 08, 2023
Algorithms for outlier, adversarial and drift detection

Alibi Detect is an open source Python library focused on outlier, adversarial and drift detection. The package aims to cover both online and offline d

Seldon 1.6k Dec 31, 2022
PyTorch Implementation of "Light Field Image Super-Resolution with Transformers"

LFT PyTorch implementation of "Light Field Image Super-Resolution with Transformers", arXiv 2021. [pdf]. Contributions: We make the first attempt to a

Squidward 62 Nov 28, 2022
High performance distributed framework for training deep learning recommendation models based on PyTorch.

PERSIA (Parallel rEcommendation tRaining System with hybrId Acceleration) is developed by AI 340 Dec 30, 2022

Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"

BEGAN in Tensorflow Tensorflow implementation of BEGAN: Boundary Equilibrium Generative Adversarial Networks. Requirements Python 2.7 or 3.x Pillow tq

Taehoon Kim 922 Dec 21, 2022
Implementation of CVPR 2020 Dual Super-Resolution Learning for Semantic Segmentation

Dual super-resolution learning for semantic segmentation 2021-01-02 Subpixel Update Happy new year! The 2020-12-29 update of SISR with subpixel conv p

Sam 79 Nov 24, 2022
Submission to Twitter's algorithmic bias bounty challenge

Twitter Ethics Challenge: Pixel Perfect Submission to Twitter's algorithmic bias bounty challenge, by Travis Hoppe (@metasemantic). Abstract We build

Travis Hoppe 4 Aug 19, 2022
Clinica is a software platform for clinical research studies involving patients with neurological and psychiatric diseases and the acquisition of multimodal data

Clinica Software platform for clinical neuroimaging studies Homepage | Documentation | Paper | Forum | See also: AD-ML, AD-DL ClinicaDL About The Proj

ARAMIS Lab 165 Dec 29, 2022
An implementation of the 1. Parallel, 2. Streaming, 3. Randomized SVD using MPI4Py

PYPARSVD This implementation allows for a singular value decomposition which is: Distributed using MPI4Py Streaming - data can be shown in batches to

Romit Maulik 44 Dec 31, 2022
TensorFlow-based implementation of "Pyramid Scene Parsing Network".

PSPNet_tensorflow Important Code is fine for inference. However, the training code is just for reference and might be only used for fine-tuning. If yo

HsuanKung Yang 323 Dec 20, 2022