# Dynamic Adversarial Domain Adaptation (DADA)

## Used Dataset

Office31 dataset can be found [here](https://people.eecs.berkeley.edu/~jhoffman/domainadapt/) (we have also provided it under the `data` folder). Please put the unzipped dataset `office31` under the `data` folder before training.

## Requirements
The code is implemented with Python(3.6) and Pytorch(1.0.0).

To install the required python packages, run

```
pip install -r requirements.txt
```

## Example on Office31, W->A setting:
### training on the source domain 'webcam', testing on the target domain 'amazon':
python train_image.py --gpu_id 0 --num_iterations 16004 --dset office --s_dset_path ./data/office/webcam_list.txt --t_dset_path ./data/office/amazon_list.txt --test_interval 500 --output_root /PATH_TO_SAVE_RESULTS/ --output_dir NAME_OF_SAVED_MODEL --seed 2757


