def SEm_resnet34(backbone_pretrained=True,
used_layers=('layer3', ),
pool_size=None,
unfreeze_layer3=False):
# backbone
backbone_net = backbones.resnet34(pretrained=backbone_pretrained)
# neck
neck_net = Corr(pool_size=pool_size)
# multiple heads
mask_head = mask.Mask_Predictor_fine()
# net
net = SEcmnet(feature_extractor=backbone_net,
neck_module=neck_net,
head_module=(None, mask_head),
used_layers=used_layers,
extractor_grad=True,
unfreeze_layer3=unfreeze_layer3)
return net
def SEc_resnet34(backbone_pretrained=True,
used_layers=('layer3', ),
pool_size=None,
unfreeze_layer3=False):
# backbone
backbone_net = backbones.resnet34(pretrained=backbone_pretrained)
# neck
neck_net = Corr(pool_size=pool_size)
# multiple heads
corner_head = corner_coarse.Corner_Predictor(inplanes=pool_size *
pool_size) # 64
# net
net = SEcmnet(feature_extractor=backbone_net,
neck_module=neck_net,
head_module=(corner_head, None),
used_layers=used_layers,
extractor_grad=True,
unfreeze_layer3=unfreeze_layer3)
return net