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InstaGAN: Instance-aware Image-to-Image Translation

Warning: This repo contains a model which has potential ethical concerns. Remark that the task of jeans<->skirt was a bad application and should not be used in future research. See the twitter thread for the discussion.


PyTorch implementation of "InstaGAN: Instance-aware Image-to-Image Translation" (ICLR 2019). The implementation is based on the official CycleGAN code. Our major contributions are in ./models/insta_gan_model.py and ./models/networks.py.

<img src='imgs/intro.png'> <img src='imgs/model.png'>

Getting Started

Installation

git clone https://github.com/sangwoomo/instagan
pip install -r requirements.txt

Download base datasets

git clone https://github.com/bearpaw/clothing-co-parsing ./datasets/clothing-co-parsing
# Download "LV-MHP-v1" from the link and locate in ./datasets
./datasets/download_coco.sh

Generate two-domain datasets

python ./datasets/generate_ccp_dataset.py --save_root ./datasets/jeans2skirt_ccp --cat1 jeans --cat2 skirt
python ./datasets/generate_mhp_dataset.py --save_root ./datasets/pants2skirt_mhp --cat1 pants --cat2 skirt
python ./datasets/generate_coco_dataset.py --save_root ./datasets/shp2gir_coco --cat1 sheep --cat2 giraffe

Run experiments

python train.py --dataroot ./datasets/jeans2skirt_ccp --model insta_gan --name jeans2skirt_ccp_instagan --loadSizeH 330 --loadSizeW 220 --fineSizeH 300 --fineSizeW 200 --niter 400 --niter_decay 200
python train.py --dataroot ./datasets/pants2skirt_mhp --model insta_gan --name pants2skirt_mhp_instagan --loadSizeH 270 --loadSizeW 180 --fineSizeH 240 --fineSizeW 160
python train.py --dataroot ./datasets/shp2gir_coco --model insta_gan --name shp2gir_coco_instagan --loadSizeH 220 --loadSizeW 220 --fineSizeH 200 --fineSizeW 200
python train.py --dataroot ./datasets/shp2gir_coco --model insta_gan --name shp2gir_coco_instagan --loadSizeH 220 --loadSizeW 220 --fineSizeH 200 --fineSizeW 200 --batch_size 4 --gpu_ids 0,1,2,3
python test.py --dataroot ./datasets/jeans2skirt_ccp --model insta_gan --name jeans2skirt_ccp_instagan --loadSizeH 300 --loadSizeW 200 --fineSizeH 300 --fineSizeW 200
python test.py --dataroot ./datasets/pants2skirt_mhp --model insta_gan --name pants2skirt_mhp_instagan --loadSizeH 240 --loadSizeW 160 --fineSizeH 240 --fineSizeW 160 --ins_per 2 --ins_max 20
python test.py --dataroot ./datasets/shp2gir_coco --model insta_gan --name shp2gir_coco_instagan --loadSizeH 200 --loadSizeW 200 --fineSizeH 200 --fineSizeW 200 --ins_per 2 --ins_max 20

Apply a pre-trained model

python test.py --dataroot ./datasets/pants2skirt_mhp --model insta_gan --name pants2skirt_mhp_instagan --loadSizeH 240 --loadSizeW 160 --fineSizeH 240 --fineSizeW 160 --ins_per 2 --ins_max 20 --phase sample --epoch 200
python test.py --dataroot ./datasets/shp2gir_coco --model insta_gan --name shp2gir_coco_instagan --loadSizeH 200 --loadSizeW 200 --fineSizeH 200 --fineSizeW 200 --ins_per 2 --ins_max 20 --phase sample --epoch 200

Results

We provide some translation results of our model. See the link for more translation results.

1. Fashion dataset (pants->skirt)

<img src='imgs/results-1.png'>

2. COCO dataset (sheep->giraffe)

<img src='imgs/results-2.png'>

3. Results on Google-searched images (pants->skirt)

<img src='imgs/results-3.png'>

4. Results on YouTube-searched videos (pants->skirt)

<img src='imgs/results-4.png'>

Citation

If you use this code for your research, please cite our papers.

@inproceedings{
    mo2019instagan,
    title={InstaGAN: Instance-aware Image-to-Image Translation},
    author={Sangwoo Mo and Minsu Cho and Jinwoo Shin},
    booktitle={International Conference on Learning Representations},
    year={2019},
    url={https://openreview.net/forum?id=ryxwJhC9YX},
}