def debug():
data = torch.load('input.pt')['input']
data = [d.cuda() for d in data]
fasterRCNN = gcn(torch.load('voc_classes.pt')['classes'],
pretrained=True,
class_agnostic=False)
fasterRCNN.create_architecture()
fasterRCNN.cuda()
fasterRCNN.train()
fasterRCNN(*data)
raise Exception(
'There is no input directory for loading network from ' +
input_dir)
load_name = os.path.join(
input_dir,
'faster_rcnn_{}_{}_{}.pth'.format(args.checksession, args.checkepoch,
args.checkpoint))
# initilize the network here.
if args.net == 'vgg16':
fasterRCNN = vgg16(imdb.classes,
pretrained=False,
class_agnostic=args.class_agnostic)
elif args.net == 'gcn':
fasterRCNN = gcn(imdb.classes,
pretrained=True,
class_agnostic=args.class_agnostic)
elif args.net == 'res101':
fasterRCNN = resnet(imdb.classes,
101,
pretrained=False,
class_agnostic=args.class_agnostic)
elif args.net == 'res50':
fasterRCNN = resnet(imdb.classes,
50,
pretrained=False,
class_agnostic=args.class_agnostic)
elif args.net == 'res152':
fasterRCNN = resnet(imdb.classes,
152,
pretrained=False,