https://github.com/LynnHo/DTLC-GAN-Tensorflow

DTLC-GAN Tensorflow
https://github.com/LynnHo/DTLC-GAN-Tensorflow

dtlc-gan

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DTLC-GAN Tensorflow

• Host: GitHub
• URL: https://github.com/LynnHo/DTLC-GAN-Tensorflow
• Owner: LynnHo
• License: mit
• Archived: true
• Created: 2018-08-25T13:10:02.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-08-29T02:48:17.000Z (over 6 years ago)
• Last Synced: 2024-08-01T17:32:31.403Z (4 months ago)
• Topics: dtlc-gan
• Language: Python
• Homepage:
• Size: 329 KB
• Stars: 12
• Watchers: 4
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# 
 DTLC-GAN 


Tensorflow implementation of [DTLC-GAN (CVPR 2018):

Generative Adversarial Image Synthesis with Decision Tree Latent Controller](https://arxiv.org/abs/1805.10603).

## Usage

- Prerequisites

    - Tensorflow 1.9

    - Python 3.6

- Training

    - Important Arguments (See the others in [train.py](train.py))

        - `att`: attribute to learn (default: `''`)

        - `ks`: # of outputs of each node of each layer (default: `[2, 3, 3]`)

        - `lambdas`: loss weights of each layer (default: `[1.0, 1.0, 1.0]`)

        - `--n_d`: # of d steps in each iteration (default: `1`)

        - `--n_g`: # of g steps in each iteration (default: `1`)

        - `--loss_mode`: gan loss (choices: `[gan, lsgan, wgan, hinge]`, default: `gan`)

        - `--gp_mode`: type of gradient penalty (choices: `[none, dragan, wgan-gp]`, default: `none`)

        - `--norm`: normalization (choices: `[batch_norm, instance_norm, layer_norm, none]`, default: `batch_norm`)

        - `--experiment_name`: name for current experiment (default: `default`)

    - Example

        ```console

        CUDA_VISIBLE_DEVICES=0 \

        python train.py \

        --att Eyeglasses \

        --ks 2 3 3 \

        --lambdas 1 1 1 \

        --n_d 1 \

        --n_g 1 \

        --loss_mode hinge \

        --gp_mode dragan \

        --norm layer_norm \

        --experiment_name att{Eyeglasses}_ks{2-3-3}_lambdas{1-1-1}_continuous_last{False}_loss{hinge}_gp{dragan}_norm{layer_norm}

        ```

## Dataset

- [Celeba](http://openaccess.thecvf.com/content_iccv_2015/papers/Liu_Deep_Learning_Face_ICCV_2015_paper.pdf) dataset

    - [Images](https://www.dropbox.com/sh/8oqt9vytwxb3s4r/AADSNUu0bseoCKuxuI5ZeTl1a/Img?dl=0&preview=img_align_celeba.zip) should be placed in ***./data/img_align_celeba/\*.jpg***

    - [Attribute labels](https://www.dropbox.com/sh/8oqt9vytwxb3s4r/AAA8YmAHNNU6BEfWMPMfM6r9a/Anno?dl=0&preview=list_attr_celeba.txt) should be placed in ***./data/list_attr_celeba.txt***

    - the above links might be inaccessible, the alternatives are

        - ***img_align_celeba.zip***

            - https://pan.baidu.com/s/1eSNpdRG#list/path=%2FCelebA%2FImg or

            - https://drive.google.com/drive/folders/0B7EVK8r0v71pTUZsaXdaSnZBZzg

        - ***list_attr_celeba.txt***

            - https://pan.baidu.com/s/1eSNpdRG#list/path=%2FCelebA%2FAnno&parentPath=%2F or

            - https://drive.google.com/drive/folders/0B7EVK8r0v71pOC0wOVZlQnFfaGs

## Exemplar Results

1. Eyeglasses, 3 layers

  


2. Bangs, 3 layers