options = vars(parser.parse_args())
sys.path.append(os.path.dirname(os.path.dirname(__file__)))
from dataloader import CustomDataloader, FlexibleCustomDataloader
from training import train_classifier
from networks import build_networks, save_networks, get_optimizers
from options import load_options, get_current_epoch
from comparison import evaluate_with_comparison
from evaluation import save_evaluation
options = load_options(options)
dataloader = FlexibleCustomDataloader(fold='train', **options)
networks = build_networks(dataloader.num_classes, **options)
optimizers = get_optimizers(networks, finetune=True, **options)
eval_dataloader = CustomDataloader(last_batch=True,
shuffle=False,
fold='test',
**options)
start_epoch = get_current_epoch(options['result_dir']) + 1
for epoch in range(start_epoch, start_epoch + options['epochs']):
train_classifier(networks, optimizers, dataloader, epoch=epoch, **options)
#print(networks['classifier_kplusone'])
#weights = networks['classifier_kplusone'].fc1.weight
eval_results = evaluate_with_comparison(networks, eval_dataloader,
**options)
pprint(eval_results)
save_evaluation(eval_results, options['result_dir'], epoch)
save_networks(networks, epoch, options['result_dir'])
help='Save Z in .npy format for later visualization')
parser.add_argument('--comparison_dataset',
type=str,
help='Dataset for off-manifold comparison')
options = vars(parser.parse_args())
# Import the rest of the project
sys.path.append(os.path.dirname(os.path.dirname(__file__)))
from dataloader import CustomDataloader
from networks import build_networks
from options import load_options, get_current_epoch
from evaluation import evaluate_classifier, evaluate_openset, save_evaluation
options = load_options(options)
if not options.get('epoch'):
options['epoch'] = get_current_epoch(options['result_dir'])
options['random_horizontal_flip'] = False
dataloader = CustomDataloader(last_batch=True, shuffle=False, **options)
networks = build_networks(dataloader.num_classes, **options)
comparison_dataloader = None
if options['comparison_dataset']:
comparison_options = options.copy()
comparison_options['dataset'] = options['comparison_dataset']
comparison_dataloader = CustomDataloader(last_batch=True,
shuffle=False,
**comparison_options)
comparison_name = options['comparison_dataset'].split('/')[-1].split(
'.')[0]