def darknet53(pretrained=False, **kwargs):
model = Darknet53(**kwargs)
# only load state_dict()
if pretrained:
load_state_dict(
torch.load(model_urls['darknet53'],
map_location=torch.device('cpu')), model)
return model
def cspdarknettiny(pretrained=False, **kwargs):
model = CSPDarknetTiny(**kwargs)
# only load state_dict()
if pretrained:
load_state_dict(
torch.load(model_urls['yolov4_cspdarknettiny'],
map_location=torch.device('cpu')), model)
return model
def _repvgg(arch, pretrained, deploy, **kwargs):
model = RepVGG(arch, deploy, **kwargs)
# only load state_dict()
if pretrained:
load_state_dict(
torch.load(model_urls[arch], map_location=torch.device('cpu')),
model)
return model
def _vovnet(arch, pretrained, **kwargs):
model = VoVNet(arch, **kwargs)
# only load state_dict()
if pretrained:
load_state_dict(
torch.load(model_urls[arch], map_location=torch.device('cpu')),
model)
return model
def _resnet(arch, block, layers, pretrained, **kwargs):
model = ResNet(block, layers, **kwargs)
# only load state_dict()
if pretrained:
load_state_dict(
torch.load(model_urls[arch], map_location=torch.device('cpu')),
model)
return model
def _efficientnet(arch, origin_globalparams, origin_blocks_args, pretrained,
**kwargs):
model = EfficientNet(arch,
origin_globalparams=origin_globalparams,
origin_blocks_args=origin_blocks_args,
**kwargs)
# only load state_dict()
if pretrained:
load_state_dict(
torch.load(model_urls[arch], map_location=torch.device('cpu')),
model)
return model