A TensorFlow implementation of the Mnemonic Descent Method.

Related tags

Deep Learningsnapchatdeep-learningtensorflowfacemdmpretrained-modelsmenpoface-alignment
Overview

MDM

A Tensorflow implementation of the Mnemonic Descent Method.

Mnemonic Descent Method: A recurrent process applied for end-to-end face alignment
G. Trigeorgis, P. Snape, M. A. Nicolaou, E. Antonakos, S. Zafeiriou.
Proceedings of IEEE International Conference on Computer Vision & Pattern Recognition (CVPR'16).
Las Vegas, NV, USA, June 2016.

Installation Instructions

Menpo

We are an avid supporter of the Menpo project (http://www.menpo.org/) which we use in various ways throughout the implementation.

Please look at the installation instructions at:

http://www.menpo.org/installation/

TensorFlow

Follow the installation instructions of Tensorflow at and install it inside the conda enviroment you have created

https://www.tensorflow.org/versions/r0.9/get_started/os_setup.html#installing-from-sources

but use

git clone https://github.com/trigeorgis/tensorflow.git

as the TensorFlow repo. This is a fork of Tensorflow (#ff75787c) but it includes some extra C++ ops, such as for the extraction of patches around the landmarks.

Pretrained models

Disclaimer: The pretrained models can only be used for non-commercial academic purposes.

A pretrained model on 300W train set can be found at: https://www.doc.ic.ac.uk/~gt108/theano_mdm.pb

Training a model

Currently the TensorFlow implementation does not contain the same data augmnetation steps as we did in the paper, but this will be updated shortly.

    # Activate the conda environment where tf/menpo resides.
    source activate menpo
    
    # Start training
    python mdm_train.py --datasets='databases/lfpw/trainset/*.png:databases/afw/*.jpg:databases/helen/trainset/*.jpg'
    
    # Track the train process and evaluate the current checkpoint against the validation set
    python mdm_eval.py --dataset_path="./databases/ibug/*.jpg" --num_examples=135 --eval_dir=ckpt/eval_ibug  --device='/cpu:0' --checkpoint_dir=$PWD/ckpt/train
    
    python mdm_eval.py --dataset_path="./databases/lfpw/testset/*.png" --num_examples=300 --eval_dir=ckpt/eval_lfpw  --device='/cpu:0' --checkpoint_dir=$PWD/ckpt/train
    
    python mdm_eval.py --dataset_path="./databases/helen/testset/*.jpg" --num_examples=330 --eval_dir=ckpt/eval_helen  --device='/cpu:0' --checkpoint_dir=$PWD/ckpt/train
    
    # Run tensorboard to visualise the results
    tensorboard --logdir==$PWD/ckpt
Owner
GitHub Repository
Pretrained models for Jax/Flax: StyleGAN2, GPT2, VGG, ResNet.

Pretrained models for Jax/Flax: StyleGAN2, GPT2, VGG, ResNet.

Matthias Wright 169 Dec 26, 2022
Official implementation of the paper: "LDNet: Unified Listener Dependent Modeling in MOS Prediction for Synthetic Speech"

LDNet Author: Wen-Chin Huang (Nagoya University) Email: Wen-Chin Huang (unilight) 40 Nov 20, 2022

This repository contains python code necessary to replicated the experiments performed in our paper "Invariant Ancestry Search"

InvariantAncestrySearch This repository contains python code necessary to replicated the experiments performed in our paper "Invariant Ancestry Search

Phillip Bredahl Mogensen 0 Feb 02, 2022
A learning-based data collection tool for human segmentation

FullBodyFilter A Learning-Based Data Collection Tool For Human Segmentation Contents Documentation Source Code and Scripts Overview of Project Usage O

Robert Jiang 4 Jun 24, 2022
Train an RL agent to execute natural language instructions in a 3D Environment (PyTorch)

Gated-Attention Architectures for Task-Oriented Language Grounding This is a PyTorch implementation of the AAAI-18 paper: Gated-Attention Architecture

Devendra Chaplot 234 Nov 05, 2022
Air Quality Prediction Using LSTM

AirQualityPredictionUsingLSTM In this Repo, i present to you the winning solution of smart gujarat hackathon 2019 where the task was to predict the qu

Deepak Nandwani 2 Dec 13, 2022
Koopman operator identification library in Python

pykoop pykoop is a Koopman operator identification library written in Python. It allows the user to specify Koopman lifting functions and regressors i

DECAR Systems Group 34 Jan 04, 2023
Tensorflow implementation of Character-Aware Neural Language Models.

Character-Aware Neural Language Models Tensorflow implementation of Character-Aware Neural Language Models. The original code of author can be found h

Taehoon Kim 751 Dec 26, 2022
PyTorch implementation of our Adam-NSCL algorithm from our CVPR2021 (oral) paper "Training Networks in Null Space for Continual Learning"

Adam-NSCL This is a PyTorch implementation of Adam-NSCL algorithm for continual learning from our CVPR2021 (oral) paper: Title: Training Networks in N

Shipeng Wang 34 Dec 21, 2022
The code succinctly shows how our ensemble learning based on deep learning CNN is used for LAM-avulsion-diagnosis.

deep-learning-LAM-avulsion-diagnosis The code succinctly shows how our ensemble learning based on deep learning CNN is used for LAM-avulsion-diagnosis

1 Jan 12, 2022
MIMO-UNet - Official Pytorch Implementation

MIMO-UNet - Official Pytorch Implementation This repository provides the official PyTorch implementation of the following paper: Rethinking Coarse-to-

Sungjin Cho 248 Jan 02, 2023
Autonomous Robots Kalman Filters

Autonomous Robots Kalman Filters The Kalman Filter is an easy topic. However, ma

20 Jul 18, 2022
PyTorch code for MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning

MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning PyTorch code for our ACL 2020 paper "MART: Memory-Augmented Recur

Jie Lei 雷杰 151 Jan 06, 2023
Semantic code search implementation using Tensorflow framework and the source code data from the CodeSearchNet project

Semantic Code Search Semantic code search implementation using Tensorflow framework and the source code data from the CodeSearchNet project. The model

Chen Wu 24 Nov 29, 2022
A tool for making map images from OpenTTD save games

OpenTTD Surveyor A tool for making map images from OpenTTD save games. This is not part of the main OpenTTD codebase, nor is it ever intended to be pa

Aidan Randle-Conde 9 Feb 15, 2022
用强化学习DQN算法，训练AI模型来玩合成大西瓜游戏，提供Keras版本和PARL（paddle）版本

用强化学习玩合成大西瓜 代码地址：https://github.com/Sharpiless/play-daxigua-using-Reinforcement-Learning 用强化学习DQN算法，训练AI模型来玩合成大西瓜游戏，提供Keras版本、PARL（paddle）版本和pytorch版本

72 Dec 17, 2022
Official Pytorch implementation for 2021 ICCV paper "Learning Motion Priors for 4D Human Body Capture in 3D Scenes" and trained models / data

Learning Motion Priors for 4D Human Body Capture in 3D Scenes (LEMO) Official Pytorch implementation for 2021 ICCV (oral) paper "Learning Motion Prior

165 Dec 19, 2022
Covid-19 Test AI (Deep Learning - NNs) Software. Accuracy is the %96.5, loss is the 0.09 :)

Covid-19 Test AI (Deep Learning - NNs) Software I developed a segmentation algorithm to understand whether Covid-19 Test Photos are positive or negati

Emirhan BULUT 28 Dec 04, 2021
CLIP (Contrastive Language–Image Pre-training) for Italian

Italian CLIP CLIP (Radford et al., 2021) is a multimodal model that can learn to represent images and text jointly in the same space. In this project,

Italian CLIP 114 Dec 29, 2022
PyTorch implementation of U-TAE and PaPs for satellite image time series panoptic segmentation.

Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks (ICCV 2021) This repository is the official implem

71 Jan 04, 2023