BaseTransform(ssd_dim, dataset_mean),
AnnotationTransform(dataset_name=args.dataset_name),
dataset_name=args.dataset_name,
set_file_name=args.set_file_name)
elif args.dataset_name == 'UW':
dataset = VOCDetection(
UWroot, [(args.year, set_type)],
BaseTransform(ssd_dim, dataset_mean),
AnnotationTransform(dataset_name=args.dataset_name),
dataset_name=args.dataset_name,
set_file_name=args.set_file_name)
if args.detection:
if 'RFB' in args.backbone:
from model.rfbnet_vgg import build_net
net = build_net('test', ssd_dim, num_classes, bn=args.bn)
elif 'RefineDet' in args.backbone:
if args.deform:
from model.dualrefinedet_vggbn import build_net
net = build_net('test',
size=ssd_dim,
num_classes=num_classes,
c7_channel=args.c7_channel,
def_groups=args.deform,
multihead=args.multihead,
bn=args.bn)
else:
from model.refinedet_vgg import build_net
net = build_net('test',
size=ssd_dim,
num_classes=num_classes,
if args.dataset_name == 'VOC0712':
dataset = VOCDetection(VOCroot, [('2007', set_type)], BaseTransform(ssd_dim, dataset_mean),
AnnotationTransform(dataset_name=args.dataset_name), dataset_name=args.dataset_name )
elif args.dataset_name == 'VID2017':
dataset = VOCDetection(VIDroot, set_type, BaseTransform(ssd_dim, dataset_mean),
AnnotationTransform(dataset_name=args.dataset_name),
dataset_name=args.dataset_name, set_file_name=args.set_file_name)
elif args.dataset_name == 'UW':
dataset = VOCDetection(UWroot, set_type, BaseTransform(ssd_dim, dataset_mean),
AnnotationTransform(dataset_name=args.dataset_name),
dataset_name=args.dataset_name, set_file_name=args.set_file_name)
if args.detection:
if args.backbone in ['RFB_VGG']:
from model.rfbnet_vgg import build_net
net = build_net('test', ssd_dim, num_classes)
elif args.backbone in ['RefineDet_VGG']:
from model.refinedet_vgg import build_net
net = build_net('test', size=ssd_dim, num_classes=num_classes, use_refine=args.refine)
elif args.backbone[:6] == 'ResNet':
from model.ssd_resnet import build_net
net = build_net('test', backbone=args.backbone, prior=prior,size=ssd_dim, num_classes=num_classes, pm=args.pm)
else:
from model.ssd import build_net
net = build_net('test', ssd_dim, num_classes, tssd=args.tssd,
prior=prior,
top_k=args.top_k,
thresh=args.confidence_threshold,
nms_thresh=args.nms_threshold,
attention=args.attention, #o_ratio=args.oa_ratio[0], a_ratio=args.oa_ratio[1],
bn=args.bn,