ADDA.PyTorch-resnet
Implementation of "Adversarial Discriminative Domain Adaptation" in PyTorch.
This repo is mostly based on https://github.com/Fujiki-Nakamura/ADDA.PyTorch
Note
Before running the training code, make sure that DATASETDIR environment variable is set to dataset directory.
Environment
- Python 3.8.5
- PyTorch 1.6.0
Example
For training on SVHN-MNIST
$ python train_source.py --logdir outputs
$ python main.py --logdir outputs --trained outputs/best_model.pt --slope 0.2
For training on Office dataset using ResNet-50
$ python core/train_source_rn50.py --n_classes 31 --lr 1e-5 --src_cat amazon --tgt_cat webcam
$ python main.py --n_classes 31 --trained outputs/garbage/best_model.pt --lr 1e-5 --d_lr 1e-4 --logdir outputs --model resnet50 --src-cat amazon --tgt-cat webcam
Result
SVHN -> MNIST
| Paper | This Repo | |
|---|---|---|
| Source only | 0.601 | 0.646 |
| ADDA | 0.760 | 0.805 |
Office-31 Amazon -> Office-31 Webcam
| Paper | This Repo | |
|---|---|---|
| Source only | 0.684 | 0.714 |
| ADDA | 0.862 | 0.831 |