PyTorch Implementation of Exploring Explicit Domain Supervision for Latent Space Disentanglement in Unpaired Image-to-Image Translation.

Overview

DosGAN-PyTorch

PyTorch Implementation of Exploring Explicit Domain Supervision for Latent Space Disentanglement in Unpaired Image-to-Image Translation.

Dependency:

Python 2.7

PyTorch 0.4.0

Usage:

Multiple identity translation

  1. Downloading Facescrub dataset following http://www.vintage.winklerbros.net/facescrub.html, and save it to root_dir.

  2. Splitting training and testing sets into train_dir and val_dir:

    $ python split2train_val.py root_dir train_dir val_dir

  3. Train a classifier for domain feature extraction and save it to dosgan_cls:

    $ python main_dosgan.py --mode cls --model_dir dosgan_cls --train_data_path train_dir --test_data_path val_dir

  4. Train DosGAN:

    $ python main_dosgan.py --mode train --model_dir dosgan --cls_save_dir dosgan_cls/models --train_data_path train_dir --test_data_path val_dir

  5. Train DosGAN-c:

    $ python main_dosgan.py --mode train --model_dir dosgan_c --cls_save_dir dosgan_cls/models --non_conditional false --train_data_path train_dir --test_data_path val_dir

  6. Test DosGAN:

    $ python main_dosgan.py --mode test --model_dir dosgan_c --cls_save_dir dosgan_cls/models --train_data_path train_dir --test_data_path val_dir

  7. Test DosGAN-c:

    $ python main_dosgan.py --mode test --model_dir dosgan_c --cls_save_dir dosgan_cls/models --non_conditional false --train_data_path train_dir --test_data_path val_dir

Other mutliple domain translation

  1. For other kinds of dataset, you can place train set and test set like:

    data
    ├── YOUR_DATASET_train_dir
        ├── damain1
        |   ├── 1.jpg
        |   ├── 2.jpg
        |   └── ...
        ├── domain2
        |   ├── 1.jpg
        |   ├── 2.jpg
        |   └── ...
        ├── domain3
        |   ├── 1.jpg
        |   ├── 2.jpg
        |   └── ...
        ...
    
    data
    ├── YOUR_DATASET_val_dir
        ├── damain1
        |   ├── 1.jpg
        |   ├── 2.jpg
        |   └── ...
        ├── domain2
        |   ├── 1.jpg
        |   ├── 2.jpg
        |   └── ...
        ├── domain3
        |   ├── 1.jpg
        |   ├── 2.jpg
        |   └── ...
        ...
    
  2. Giving multiple season translation for example (season dataset). Train a classifier for season domain feature extraction and save it to dosgan_season_cls:

    $ python main_dosgan.py --mode cls --model_dir dosgan_season_cls --ft_num 64 --c_dim 4 --image_size 256 --train_data_path season_train_dir --test_data_path season_val_dir

  3. Train DosGAN for multiple season translation:

    $ python main_dosgan.py --mode train --model_dir dosgan_season --cls_save_dir dosgan_season_cls/models --ft_num 64 --c_dim 4 --image_size 256 --lambda_fs 0.15 --num_iters 300000 --train_data_path season_train_dir --test_data_path season_val_dir

Results:

1. Multiple identity translation

# Results of DosGAN:

# Results of DosGAN-c:

2. Multiple season translation:

Owner
Ph.D. Candidate of University of Science and Technology of China
This project contains an implemented version of Face Detection using OpenCV and Mediapipe. This is a code snippet and can be used in projects.

Live-Face-Detection Project Description: In this project, we will be using the live video feed from the camera to detect Faces. It will also detect so

Hassan Shahzad 3 Oct 02, 2021
Godot RL Agents is a fully Open Source packages that allows video game creators

Godot RL Agents The Godot RL Agents is a fully Open Source packages that allows video game creators, AI researchers and hobbiest the opportunity to le

Edward Beeching 326 Dec 30, 2022
Bag of Tricks for Natural Policy Gradient Reinforcement Learning

Bag of Tricks for Natural Policy Gradient Reinforcement Learning [ArXiv] Setup Python 3.8.0 pip install -r req.txt Mujoco 200 license Main Files main.

Brennan Gebotys 1 Oct 10, 2022
This repository includes the code of the sequence-to-sequence model for discontinuous constituent parsing described in paper Discontinuous Grammar as a Foreign Language.

Discontinuous Grammar as a Foreign Language This repository includes the code of the sequence-to-sequence model for discontinuous constituent parsing

Daniel Fernández-González 2 Apr 07, 2022
Code for the ICCV2021 paper "Personalized Image Semantic Segmentation"

PSS: Personalized Image Semantic Segmentation Paper PSS: Personalized Image Semantic Segmentation Yu Zhang, Chang-Bin Zhang, Peng-Tao Jiang, Ming-Ming

张宇 15 Jul 09, 2022
The story of Chicken for Club Bing

Chicken Story tl;dr: The time when Microsoft banned my entire country for cheating at Club Bing. (A lot of the details are from memory so I've recreat

Eyal 142 May 16, 2022
Pre-trained NFNets with 99% of the accuracy of the official paper

NFNet Pytorch Implementation This repo contains pretrained NFNet models F0-F6 with high ImageNet accuracy from the paper High-Performance Large-Scale

Benjamin Schmidt 133 Dec 09, 2022
Implementation of paper "Graph Condensation for Graph Neural Networks"

GCond A PyTorch implementation of paper "Graph Condensation for Graph Neural Networks" Code will be released soon. Stay tuned :) Abstract We propose a

Wei Jin 66 Dec 04, 2022
FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing

FairEdit Relevent Publication FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing

5 Feb 04, 2022
RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation

RIFE RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation Ported from https://github.com/hzwer/arXiv2020-RIFE Dependencies NumPy

49 Jan 07, 2023
Self-Supervised Monocular DepthEstimation with Internal Feature Fusion(arXiv), BMVC2021

DIFFNet This repo is for Self-Supervised Monocular Depth Estimation with Internal Feature Fusion(arXiv), BMVC2021 A new backbone for self-supervised d

Hang 94 Dec 25, 2022
Export CenterPoint PonintPillars ONNX Model For TensorRT

CenterPoint-PonintPillars Pytroch model convert to ONNX and TensorRT Welcome to CenterPoint! This project is fork from tianweiy/CenterPoint. I impleme

CarkusL 149 Dec 13, 2022
Trajectory Prediction with Graph-based Dual-scale Context Fusion

DSP: Trajectory Prediction with Graph-based Dual-scale Context Fusion Introduction This is the project page of the paper Lu Zhang, Peiliang Li, Jing C

HKUST Aerial Robotics Group 103 Jan 04, 2023
Python scripts using the Mediapipe models for Halloween.

Mediapipe-Halloween-Examples Python scripts using the Mediapipe models for Halloween. WHY Mainly for fun. But this repository also includes useful exa

Ibai Gorordo 23 Jan 06, 2023
Official implementation of EdiTTS: Score-based Editing for Controllable Text-to-Speech

EdiTTS: Score-based Editing for Controllable Text-to-Speech Official implementation of EdiTTS: Score-based Editing for Controllable Text-to-Speech. Au

Neosapience 98 Dec 25, 2022
Official implementation of CVPR2020 paper "Deep Generative Model for Robust Imbalance Classification"

Deep Generative Model for Robust Imbalance Classification Deep Generative Model for Robust Imbalance Classification Xinyue Wang, Yilin Lyu, Liping Jin

9 Nov 01, 2022
Like Dirt-Samples, but cleaned up

Clean-Samples Like Dirt-Samples, but cleaned up, with clear provenance and license info (generally a permissive creative commons licence but check the

TidalCycles 39 Nov 30, 2022
Implementation of Hierarchical Transformer Memory (HTM) for Pytorch

Hierarchical Transformer Memory (HTM) - Pytorch Implementation of Hierarchical Transformer Memory (HTM) for Pytorch. This Deepmind paper proposes a si

Phil Wang 63 Dec 29, 2022
A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling"

SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th

Zekarias Tilahun 24 Jun 21, 2022
A model that attempts to learn and benefit from data collected on card counting.

A model that attempts to learn and benefit from data collected on card counting. A decision tree like model is built to win more often than loose and increase the bet of the player appropriately to c

1 Dec 17, 2021