Council-GAN - Implementation for our paper Breaking the Cycle - Colleagues are all you need (CVPR 2020)

Overview

Council-GAN

Implementation of our paper Breaking the Cycle - Colleagues are all you need (CVPR 2020)

Paper

Ori Nizan , Ayellet Tal, Breaking the Cycle - Colleagues are all you need [Project]

gan_council_teaser

gan_council_overview

male2female_gif

glasses_gif

anime_gif

Temporary Telegram Bot

Send image to this telegram bot and it will send you back its female translation using our implementation

Usage

Install requirements

conda env create -f conda_requirements.yml

Downloading the dataset

Download the selfie to anime dataset:

bash ./scripts/download.sh U_GAT_IT_selfie2anime

Download the celeba glasses removal dataset:

bash ./scripts/download.sh celeba_glasses_removal

Download the celeba male to female dataset:

bash ./scripts/download.sh celeba_male2female

use your on dataset:

├──datasets
    └──DATASET_NAME
        ├──testA
            ├──im1.png
            ├──im2.png
            └── ...
        ├──testB
            ├──im3.png
            ├──im4.png
            └── ...
        ├──trainA
            ├──im5.png
            ├──im6.png
            └── ...
        └──trainB
            ├──im7.png
            ├──im8.png
            └── ...

and change the data_root attribute to ./datasets/DATASET_NAME in the yaml file

Training:

Selfie to anime:

python train.py --config configs/anime2face_council_folder.yaml --output_path ./outputs/council_anime2face_256_256 --resume

Glasses removel:

python train.py --config configs/galsses_council_folder.yaml --output_path ./outputs/council_glasses_128_128 --resume

Male to female:

python train.py --config configs/male2female_council_folder.yaml --output_path ./outputs/male2famle_256_256 --resume

Testing:

for converting all the images in input_folder using all the members in the council:

python test_on_folder.py --config configs/anime2face_council_folder.yaml --output_folder ./outputs/council_anime2face_256_256 --checkpoint ./outputs/council_anime2face_256_256/anime2face_council_folder/checkpoints/01000000 --input_folder ./datasets/selfie2anime/testB --a2b 0

or using spsified memeber:

python test_on_folder.py --config configs/anime2face_council_folder.yaml --output_folder ./outputs/council_anime2face_256_256 --checkpoint ./outputs/council_anime2face_256_256/anime2face_council_folder/checkpoints/b2a_gen_3_01000000.pt --input_folder ./datasets/selfie2anime/testB --a2b 0

Download Pretrain Models

Download pretrain male to female model:

bash ./scripts/download.sh pretrain_male_to_female
Then to convert images in --input_folder run:
python test_on_folder.py --config pretrain/m2f/256/male2female_council_folder.yaml --output_folder ./outputs/male2famle_256_256 --checkpoint pretrain/m2f/256/01000000 --input_folder ./datasets/celeba_male2female/testA --a2b 1

Download pretrain glasses removal model:

bash ./scripts/download.sh pretrain_glasses_removal
Then to convert images in --input_folder run:
python test_on_folder.py --config pretrain/glasses_removal/128/galsses_council_folder.yaml --output_folder ./outputs/council_glasses_128_128 --checkpoint pretrain/glasses_removal/128/01000000 --input_folder ./datasets/glasses/testA --a2b 1

Download pretrain selfie to anime model:

bash ./scripts/download.sh pretrain_selfie_to_anime
Then to convert images in --input_folder run:
python test_on_folder.py --config pretrain/anime/256/anime2face_council_folder.yaml --output_folder ./outputs/council_anime2face_256_256 --checkpoint pretrain/anime/256/01000000 --input_folder ./datasets/selfie2anime/testB --a2b 0

Test GUI:

gan_council_overview

test GUI on pretrain model:

male2female
python test_gui.py --config pretrain/m2f/128/male2female_council_folder.yaml --checkpoint pretrain/m2f/128/a2b_gen_0_01000000.pt --a2b 1
glasses Removal
python test_gui.py --config pretrain/glasses_removal/128/galsses_council_folder.yaml --checkpoint pretrain/glasses_removal/128/a2b_gen_3_01000000.pt --a2b 1
selfie2anime
python test_gui.py --config pretrain/anime/256/anime2face_council_folder.yaml --checkpoint pretrain/anime/256/b2a_gen_3_01000000.pt --a2b 0

Open In Colab

Citation

@inproceedings{nizan2020council,
  title={Breaking the Cycle - Colleagues are all you need},
  author={Ori Nizan and Ayellet Tal},
  booktitle={IEEE conference on computer vision and pattern recognition (CVPR)},
  year={2020}
}

Acknowledgement

In this work we based our code on MUNIT implementation. Please cite the original MUNIT if you use their part of the code.

Owner
ori nizan
Computer Vision & Deep Learning PhD student
ori nizan
A Simple Framwork for CV Pre-training Model (SOCO, VirTex, BEiT)

A Simple Framwork for CV Pre-training Model (SOCO, VirTex, BEiT)

Sense-GVT 14 Jul 07, 2022
Self-supervised Multi-modal Hybrid Fusion Network for Brain Tumor Segmentation

JBHI-Pytorch This repository contains a reference implementation of the algorithms described in our paper "Self-supervised Multi-modal Hybrid Fusion N

FeiyiFANG 5 Dec 13, 2021
This repository is based on Ultralytics/yolov5, with adjustments to enable rotate prediction boxes.

Rotate-Yolov5 This repository is based on Ultralytics/yolov5, with adjustments to enable rotate prediction boxes. Section I. Description The codes are

xinzelee 90 Dec 13, 2022
Differentiable Neural Computers, Sparse Access Memory and Sparse Differentiable Neural Computers, for Pytorch

Differentiable Neural Computers and family, for Pytorch Includes: Differentiable Neural Computers (DNC) Sparse Access Memory (SAM) Sparse Differentiab

ixaxaar 302 Dec 14, 2022
PyContinual (An Easy and Extendible Framework for Continual Learning)

PyContinual (An Easy and Extendible Framework for Continual Learning) Easy to Use You can sumply change the baseline, backbone and task, and then read

Zixuan Ke 176 Jan 05, 2023
Encode and decode text application

Text Encoder and Decoder Encode and decode text in many ways using this application! Encode in: ASCII85 Base85 Base64 Base32 Base16 Url MD5 Hash SHA-1

Alice 1 Feb 12, 2022
PyTorch version implementation of DORN

DORN_PyTorch This is a PyTorch version implementation of DORN Reference H. Fu, M. Gong, C. Wang, K. Batmanghelich and D. Tao: Deep Ordinal Regression

Zilin.Zhang 3 Apr 27, 2022
TransReID: Transformer-based Object Re-Identification

TransReID: Transformer-based Object Re-Identification [arxiv] The official repository for TransReID: Transformer-based Object Re-Identification achiev

569 Dec 30, 2022
[ICCV 2021] Deep Hough Voting for Robust Global Registration

Deep Hough Voting for Robust Global Registration, ICCV, 2021 Project Page | Paper | Video Deep Hough Voting for Robust Global Registration Junha Lee1,

Junha Lee 10 Dec 02, 2022
Human Action Controller - A human action controller running on different platforms.

Human Action Controller (HAC) Goal A human action controller running on different platforms. Fun Easy-to-use Accurate Anywhere Fun Examples Mouse Cont

27 Jul 20, 2022
PyTorch Kafka Dataset: A definition of a dataset to get training data from Kafka.

PyTorch Kafka Dataset: A definition of a dataset to get training data from Kafka.

ERTIS Research Group 7 Aug 01, 2022
PyTorch implementation of "Conformer: Convolution-augmented Transformer for Speech Recognition" (INTERSPEECH 2020)

PyTorch implementation of Conformer: Convolution-augmented Transformer for Speech Recognition. Transformer models are good at capturing content-based

Soohwan Kim 565 Jan 04, 2023
This is a collection of all challenges in HKCERT CTF 2021

香港網絡保安新生代奪旗挑戰賽 2021 (HKCERT CTF 2021) This is a collection of all challenges (and writeups) in HKCERT CTF 2021 Challenges ID Chinese name Name Score S

10 Jan 27, 2022
WebUAV-3M: A Benchmark Unveiling the Power of Million-Scale Deep UAV Tracking

WebUAV-3M: A Benchmark Unveiling the Power of Million-Scale Deep UAV Tracking [Paper Link] Abstract In this work, we contribute a new million-scale Un

25 Jan 01, 2023
Robot Servers and Server Manager software for robo-gym

robo-gym-server-modules Robot Servers and Server Manager software for robo-gym. For info on how to use this package please visit the robo-gym website

JR ROBOTICS 4 Aug 16, 2021
Cooperative multi-agent reinforcement learning for high-dimensional nonequilibrium control

Cooperative multi-agent reinforcement learning for high-dimensional nonequilibrium control Official implementation of: Cooperative multi-agent reinfor

0 Nov 16, 2021
Official repository for CVPR21 paper "Deep Stable Learning for Out-Of-Distribution Generalization".

StableNet StableNet is a deep stable learning method for out-of-distribution generalization. This is the official repo for CVPR21 paper "Deep Stable L

120 Dec 28, 2022
La source de mon module 'pyfade' disponible sur Pypi.

Version: 1.2 Introduction Pyfade est un module permettant de créer des dégradés colorés. Il vous permettra de changer chaque ligne de votre texte par

Billy 20 Sep 12, 2021
This repo in the implementation of EMNLP'21 paper "SPARQLing Database Queries from Intermediate Question Decompositions" by Irina Saparina, Anton Osokin

SPARQLing Database Queries from Intermediate Question Decompositions This repo is the implementation of the following paper: SPARQLing Database Querie

Yandex Research 20 Dec 19, 2022
Official implementations of PSENet, PAN and PAN++.

News (2021/11/03) Paddle implementation of PAN, see Paddle-PANet. Thanks @simplify23. (2021/04/08) PSENet and PAN are included in MMOCR. Introduction

395 Dec 14, 2022