Implementation of "Adversarial Discriminative Domain Adaptation" in PyTorch

deep-learning domain-adaptation pytorch

Fazil Altinel 8cb1886af9 ResNet-50 implementation for office dataset		4 years ago
core	ResNet-50 implementation for office dataset	4 years ago
input	add .gitignore	6 years ago
models	ResNet-50 implementation for office dataset	4 years ago
outputs	add .gitignore	6 years ago
utils	ResNet-50 implementation for office dataset	4 years ago
.gitignore	Add gitignore	4 years ago
README.md	ResNet-50 implementation for office dataset	4 years ago
__init__.py	Changes for new file organization	4 years ago
main.py	ResNet-50 implementation for office dataset	4 years ago

README.md

ADDA.PyTorch-resnet

Implementation of "Adversarial Discriminative Domain Adapation" 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 --logdir outputs
$ python main.py --n_classes 31 --trained outputs/best_model.pt --logdir outputs --model resnet50 --src-cat amazon --tgt-cat webcam

Result

SVHN -> MNIST

	Paper	This Repo
Source only	0.601	0.659
ADDA	0.760	~0.83