need_backprop = Variable(need_backprop)
tgt_im_data = Variable(tgt_im_data)
tgt_im_info = Variable(tgt_im_info)
tgt_num_boxes = Variable(tgt_num_boxes)
tgt_gt_boxes = Variable(tgt_gt_boxes)
tgt_need_backprop = Variable(tgt_need_backprop)
if args.cuda:
cfg.CUDA = True
# initilize the network here.
if args.net == 'vgg16':
fasterRCNN = vgg16(s_imdb.classes, pretrained=True, class_agnostic=args.class_agnostic)
elif args.net == 'res101':
fasterRCNN = resnet(s_imdb.classes, 101, pretrained=True, class_agnostic=args.class_agnostic)
elif args.net == 'res50':
fasterRCNN = resnet(s_imdb.classes, 50, pretrained=True, class_agnostic=args.class_agnostic)
elif args.net == 'res152':
fasterRCNN = resnet(s_imdb.classes, 152, pretrained=True, class_agnostic=args.class_agnostic)
else:
print("network is not defined")
pdb.set_trace()
fasterRCNN.create_architecture()
lr = cfg.TRAIN.LEARNING_RATE
lr = args.lr
#tr_momentum = cfg.TRAIN.MOMENTUM
#tr_momentum = args.momentum
# initilize the network here.
if args.net == "vgg16":
fasterRCNN = vgg16(
imdb.classes,
pretrained=False,
pretrained_path=None,
class_agnostic=args.class_agnostic,
lc=args.lc,
gc=args.gc,
)
elif args.net == "res101":
fasterRCNN = resnet(
imdb.classes,
101,
pretrained_path=None,
pretrained=False,
class_agnostic=args.class_agnostic,
lc=args.lc,
gc=args.gc,
)
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, class_agnostic=args.class_agnostic
)
else:
print("network is not defined")
pdb.set_trace()