def __init__(self,
backbone='resnet',
output_stride=16,
num_classes=21,
sync_bn=False,
freeze_bn=False,
mc_dropout=False):
super(DeepLab, self).__init__()
if backbone == 'drn':
output_stride = 8
if sync_bn == True:
BatchNorm = SynchronizedBatchNorm2d
else:
BatchNorm = nn.BatchNorm2d
self.backbone = build_backbone(backbone,
output_stride,
BatchNorm,
mc_dropout=mc_dropout)
self.aspp = build_aspp(backbone, output_stride, BatchNorm)
self.decoder = build_decoder(num_classes, backbone, BatchNorm)
self.return_features = False
if freeze_bn:
self.freeze_bn()
def __init__(self,
args,
cfg=None,
net='resnet',
output_stride=32,
num_classes=21,
img_size=512,
pretrained=True,
freeze_bn=False):
super(DSSD, self).__init__()
self.args = args
self.cfg = cfg
self.net = net
self.num_classes = num_classes
self.image_size = img_size
self.priorbox = PriorBox(cfg, net, output_stride)
self.priors = self.priorbox().to(args.device)
self.backbone = build_backbone(net, output_stride, pretrained)
self.aspp = build_aspp(net, output_stride)
self.decoder = build_decoder(net)
self.head = build_head(inplances=self.decoder.plances,
num_classes=num_classes,
num_anchor=cfg.anchor_number)
if freeze_bn:
self.freeze_bn
# For detect
self.softmax = nn.Softmax(dim=-1)
self.detect = Detect(self.args, self.cfg, self.num_classes)
def __init__(self, output_stride=16, num_classes=21):
super(DeepLab, self).__init__()
BatchNorm = nn.BatchNorm2d
self.backbone = build_resnet(output_stride, pretrained=True)
self.aspp = build_aspp(output_stride)
self.decoder = build_decoder(num_classes)
def __init__(self, output_stride=16, num_classes=21, freeze_bn=False):
super(DeepLab, self).__init__()
BatchNorm = nn.BatchNorm2d
self.backbone = build_backbone(output_stride, BatchNorm)
self.aspp = build_aspp(output_stride, BatchNorm)
self.decoder = build_decoder(num_classes, BatchNorm)
if freeze_bn:
self.freeze_bn()
def __init__(self, args):
super(DeepLab, self).__init__()
if args.backbone == 'drn':
output_stride = 8
else:
output_stride = args.output_stride
if args.sync_bn == True:
BatchNorm = SynchronizedBatchNorm2d
else:
BatchNorm = nn.BatchNorm2d
self.backbone = build_backbone(args.backbone, output_stride, BatchNorm)
self.aspp = build_aspp(args.backbone, output_stride, BatchNorm)
self.decoder = build_decoder(args.num_classes, args.backbone,
BatchNorm)
self.freeze_bn = args.freeze_bn