def transt_resnet50(settings):
num_classes = 1
backbone_net = build_backbone(settings, backbone_pretrained=True)
featurefusion_network = build_featurefusion_network(settings)
model = TransT(backbone_net,
featurefusion_network,
num_classes=num_classes)
device = torch.device(settings.device)
model.to(device)
return model
def transt_resnet50(settings):
num_classes = 1
backbone_net = build_backbone(settings, backbone_pretrained=True)
featurefusion_network = build_featurefusion_network(settings)
model = TransT(backbone_net,
featurefusion_network,
num_classes=num_classes)
device = torch.device(settings.device)
model.to(device)
# if hasattr(settings, "init_ckpt") and settings.init_ckpt:
# print("Initializing from settings.init_ckpt")
# model = load_weights(model, settings.init_ckpt, strict=True)
return model
def transt_resnet50(settings):
num_classes = 1
backbone_net = build_backbone(settings, backbone_pretrained=True)
featurefusion_network = build_featurefusion_network(settings)
model = TransT(backbone_net,
featurefusion_network,
num_classes=num_classes)
device = torch.device(settings.device)
model.to(device)
if settings.init_ckpt:
print("Initializing from settings.init_ckpt")
model = load_weights(
model, settings.init_ckpt,
strict=False) # Not strict so we can add to the model
return model
