Official Pytorch implementation of 'RoI Tanh-polar Transformer Network for Face Parsing in the Wild.'

Overview

ibug.face_parsing

RoI Tanh-polar Transformer Network for Face Parsing in the Wild.

Note: If you use this repository in your research, we kindly rquest you to cite the following paper:

@article{lin2021roi,
title = {RoI Tanh-polar transformer network for face parsing in the wild},
journal = {Image and Vision Computing},
volume = {112},
pages = {104190},
year = {2021},
issn = {0262-8856},
doi = {https://doi.org/10.1016/j.imavis.2021.104190},
url = {https://www.sciencedirect.com/science/article/pii/S0262885621000950},
author = {Yiming Lin and Jie Shen and Yujiang Wang and Maja Pantic},
keywords = {Face parsing, In-the-wild dataset, Head pose augmentation, Tanh-polar representation},
}

Dependencies

How to Install

git clone https://github.com/hhj1897/face_parsing
cd face_parsing
git lfs pull
pip install -e .

How to Test

python face_warping_test.py -i 0 -e rtnet50 --decoder fcn -n 11 -d cuda:0

Command-line arguments:

-i VIDEO: Index of the webcam to use (start from 0) or
          path of the input video file
-d: Device to be used by PyTorch (default=cuda:0)
-e: Encoder (default=rtnet50)
--decoder: Decoder (default=fcn)
-n: Number of facial classes, can be 11 or 14 for now (default=11)

iBugMask Dataset

The training and testing images, bounding boxes, landmarks, and parsing maps can be found in the following:

Label Maps

Label map for 11 classes:

0 : background
1 : skin (including face and scalp)
2 : left_eyebrow
3 : right_eyebrow
4 : left_eye
5 : right_eye
6 : nose
7 : upper_lip
8 : inner_mouth
9 : lower_lip
10 : hair

Label map for 14 classes:

0 : background
1 : skin (including face and scalp)
2 : left_eyebrow
3 : right_eyebrow
4 : left_eye
5 : right_eye
6 : nose
7 : upper_lip
8 : inner_mouth
9 : lower_lip
10 : hair
11 : left_ear
12 : right_ear
13 : glasses

Visualisation

You might also like...
VSR-Transformer - This paper proposes a new Transformer for video super-resolution (called VSR-Transformer).
VSR-Transformer - This paper proposes a new Transformer for video super-resolution (called VSR-Transformer).

VSR-Transformer By Jiezhang Cao, Yawei Li, Kai Zhang, Luc Van Gool This paper proposes a new Transformer for video super-resolution (called VSR-Transf

A python implementation of Yolov5 to detect fire or smoke in the wild in Jetson Xavier nx and Jetson nano
A python implementation of Yolov5 to detect fire or smoke in the wild in Jetson Xavier nx and Jetson nano

yolov5-fire-smoke-detect-python A python implementation of Yolov5 to detect fire or smoke in the wild in Jetson Xavier nx and Jetson nano You can see

The official implementation of CSG-Stump: A Learning Friendly CSG-Like Representation for Interpretable Shape Parsing

CSGStumpNet The official implementation of CSG-Stump: A Learning Friendly CSG-Like Representation for Interpretable Shape Parsing Paper | Project page

Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing

Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing Paper Introduction Multi-task indoor scene understanding is widely considered a

Pytorch implementation of face attention network
Pytorch implementation of face attention network

Face Attention Network Pytorch implementation of face attention network as described in Face Attention Network: An Effective Face Detector for the Occ

Official pytorch code for SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal
Official pytorch code for SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal

SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal This is the official pytorch code for SSAT: A Symmetric Semantic-

Non-Official Pytorch implementation of
Non-Official Pytorch implementation of "Face Identity Disentanglement via Latent Space Mapping" https://arxiv.org/abs/2005.07728 Using StyleGAN2 instead of StyleGAN

Face Identity Disentanglement via Latent Space Mapping - Implement in pytorch with StyleGAN 2 Description Pytorch implementation of the paper Face Ide

Official PyTorch implementation of
Official PyTorch implementation of "Improving Face Recognition with Large AgeGaps by Learning to Distinguish Children" (BMVC 2021)

Inter-Prototype (BMVC 2021): Official Project Webpage This repository provides the official PyTorch implementation of the following paper: Improving F

Official Pytorch Implementation of 3DV2021 paper: SAFA: Structure Aware Face Animation.
Official Pytorch Implementation of 3DV2021 paper: SAFA: Structure Aware Face Animation.

SAFA: Structure Aware Face Animation (3DV2021) Official Pytorch Implementation of 3DV2021 paper: SAFA: Structure Aware Face Animation. Getting Started

Comments
  • cannot convert to tflite

    cannot convert to tflite

    Hello, thanks for sharing this great study. I'm researching face parsing and i'm trying to port to Tflite and compare the performance, but I can't since this is using special ops - it uses "grid sample"

    What do you suggest I can do in order to test on Tflite/CoreML?

    Will training on Lapa dataset improve the accuracy? if not why?

    opened by ofirkris 1
  • _pickle.UnpicklingError: invalid load key, 'v'

    _pickle.UnpicklingError: invalid load key, 'v'

    How to fix it

    Traceback (most recent call last): File "face_parsing_test.py", line 141, in main() File "face_parsing_test.py", line 50, in main face_parser = RTNetPredictor( File "/home/ml/radishevskii/face_parsing/ibug/face_parsing/parser.py", line 81, in init ckpt = torch.load(ckpt, 'cpu') File "/home/ml/radishevskii/anaconda3/envs/inga_vlad/lib/python3.8/site-packages/torch/serialization.py", line 593, in load return _legacy_load(opened_file, map_location, pickle_module, **pickle_load_args) File "/home/ml/radishevskii/anaconda3/envs/inga_vlad/lib/python3.8/site-packages/torch/serialization.py", line 762, in _legacy_load magic_number = pickle_module.load(f, **pickle_load_args) _pickle.UnpicklingError: invalid load key, 'v'.

    opened by vladradishevsky 1
  • face parsing label

    face parsing label

    It seems that the dataset released contains only the annotation of 11 facial parts. However, the repository also provide the model trained with dataset containing labels of 14 facial parts. Thus, we wonder how can we get the labels of 14 facial parts. Can you provide the download link? Thanks!

    opened by HowToNameMe 0
Releases(v0.2.0)
Owner
Jie Shen
Jie Shen
Official implementation of Sparse Transformer-based Action Recognition

STAR Official implementation of S parse T ransformer-based A ction R ecognition Dataset download NTU RGB+D 60 action recognition of 2D/3D skeleton fro

Chonghan_Lee 15 Nov 02, 2022
Code for the ICME 2021 paper "Exploring Driving-Aware Salient Object Detection via Knowledge Transfer"

TSOD Code for the ICME 2021 paper "Exploring Driving-Aware Salient Object Detection via Knowledge Transfer" Usage For training, open train_test, run p

Jinming Su 2 Dec 23, 2021
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features

CleanRL (Clean Implementation of RL Algorithms) CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementation

Costa Huang 1.8k Jan 01, 2023
Multi-query Video Retreival

Multi-query Video Retreival

Princeton Visual AI Lab 17 Nov 22, 2022
Zsseg.baseline - Zero-Shot Semantic Segmentation

This repo is for our paper A Simple Baseline for Zero-shot Semantic Segmentation

98 Dec 20, 2022
PyTorch Implementation of AnimeGANv2

PyTorch implementation of AnimeGANv2

4k Jan 07, 2023
Tacotron 2 - PyTorch implementation with faster-than-realtime inference

Tacotron 2 (without wavenet) PyTorch implementation of Natural TTS Synthesis By Conditioning Wavenet On Mel Spectrogram Predictions. This implementati

NVIDIA Corporation 4.1k Jan 03, 2023
View model summaries in PyTorch!

torchinfo (formerly torch-summary) Torchinfo provides information complementary to what is provided by print(your_model) in PyTorch, similar to Tensor

Tyler Yep 1.5k Jan 05, 2023
This repository is an implementation of our NeurIPS 2021 paper (Stylized Dialogue Generation with Multi-Pass Dual Learning) in PyTorch.

MPDL---TODO This repository is an implementation of our NeurIPS 2021 paper (Stylized Dialogue Generation with Multi-Pass Dual Learning) in PyTorch. Ci

CodebaseLi 3 Nov 27, 2022
Official code for 'Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentationon Complex Urban Driving Scenes'

PEBAL This repo contains the Pytorch implementation of our paper: Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urb

Yu Tian 117 Jan 03, 2023
[ACM MM 2019 Oral] Cycle In Cycle Generative Adversarial Networks for Keypoint-Guided Image Generation

Contents Cycle-In-Cycle GANs Installation Dataset Preparation Generating Images Using Pretrained Model Train and Test New Models Acknowledgments Relat

Hao Tang 67 Dec 14, 2022
[ICML 2020] DrRepair: Learning to Repair Programs from Error Messages

DrRepair: Learning to Repair Programs from Error Messages This repo provides the source code & data of our paper: Graph-based, Self-Supervised Program

Michihiro Yasunaga 155 Jan 08, 2023
This is the source code for our ICLR2021 paper: Adaptive Universal Generalized PageRank Graph Neural Network.

GPRGNN This is the source code for our ICLR2021 paper: Adaptive Universal Generalized PageRank Graph Neural Network. Hidden state feature extraction i

Jianhao 92 Jan 03, 2023
Source code of AAAI 2022 paper "Towards End-to-End Image Compression and Analysis with Transformers".

Towards End-to-End Image Compression and Analysis with Transformers Source code of our AAAI 2022 paper "Towards End-to-End Image Compression and Analy

37 Dec 21, 2022
This is an official implementation of our CVPR 2021 paper "Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression" (https://arxiv.org/abs/2104.02300)

Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression Introduction In this paper, we are interested in the bottom-up paradigm of estima

HRNet 367 Dec 27, 2022
OBBDetection: an oriented object detection toolbox modified from MMdetection

OBBDetection note: If you have questions or good suggestions, feel free to propose issues and contact me. introduction OBBDetection is an oriented obj

MIXIAOXIN_HO 3 Nov 11, 2022
Continuous Augmented Positional Embeddings (CAPE) implementation for PyTorch

PyTorch implementation of Continuous Augmented Positional Embeddings (CAPE), by Likhomanenko et al. Enhance your Transformer positional embeddings with easy-to-use augmentations!

Guillermo Cámbara 26 Dec 13, 2022
The code uses SegFormer for Semantic Segmentation on Drone Dataset.

SegFormer_Segmentation The code uses SegFormer for Semantic Segmentation on Drone Dataset. The details for the SegFormer can be obtained from the foll

Dr. Sander Ali Khowaja 1 May 08, 2022
Turi Create simplifies the development of custom machine learning models.

Quick Links: Installation | Documentation | WWDC 2019 | WWDC 2018 Turi Create Check out our talks at WWDC 2019 and at WWDC 2018! Turi Create simplifie

Apple 10.9k Jan 01, 2023
Benchmarks for semi-supervised domain generalization.

Semi-Supervised Domain Generalization This code is the official implementation of the following paper: Semi-Supervised Domain Generalization with Stoc

Kaiyang 49 Dec 10, 2022