Image-to-Image Translation with Conditional Adversarial Nets
An implementation of pix2pix described in the paper using tensorflow.
Published in CVPR 2017, written by P. Isola, J-Y Zhu, T. Zhou and A. Efros
Requirement
- Python 3.6.4
- Tensorflow 1.8.0
- Pillow 5.0.0
- numpy 1.14.5
How to Run
If you want to see more example commands, please refer to run.sh file in my repository.
Train
python main.py --tr_data_path ./dataSet/facades/train --transfer_type B_to_A --model_name facades
test
python main.py --mode test --val_data_path ./dataSet/facedes/val --transfer_type B_to_A --load_size 256 --pre_trained_model ./model/pix2pix-facades
Datasets
Shell script which downloads datasets will be uploaded soon!
Pre-trained model
Experimental Results
Experimental results on map dataset(map to aeriel)
| Input | result | Target |
|---|---|---|
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
Experimental results on map dataset(aeriel to map)
| Input | result | Target |
|---|---|---|
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
Experimental results on facades dataset
| Input | result | Target |
|---|---|---|
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
Experimental results on edges2shoes dataset
| Input | result | Target |
|---|---|---|
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
Comments
If you have any questions or comments on my codes, please email to me. son1113@snu.ac.kr