def build_backbone(self, input_img_batch):
if self.base_network_name.startswith('resnet_v1'):
feature_dict = resnet.ResNetBackbone(self.cfgs).resnet_base(
input_img_batch,
scope_name=self.base_network_name,
is_training=self.is_training)
return self.fpn_func.fpn_retinanet(feature_dict, self.is_training)
elif self.base_network_name in [
'resnet152_v1d', 'resnet101_v1d', 'resnet50_v1d',
'resnet152_v1b', 'resnet101_v1b', 'resnet50_v1b',
'resnet34_v1b', 'resnet18_v1b'
]:
feature_dict = resnet_gluoncv.ResNetGluonCVBackbone(
self.cfgs).resnet_base(input_img_batch,
scope_name=self.base_network_name,
is_training=self.is_training)
return self.fpn_func.fpn_retinanet(feature_dict, self.is_training)
elif self.base_network_name.startswith('MobilenetV2'):
feature_dict = mobilenet_v2.MobileNetV2Backbone(
self.cfgs).mobilenetv2_base(input_img_batch,
is_training=self.is_training)
return self.fpn_func.fpn_retinanet(feature_dict, self.is_training)
elif 'efficientnet-lite' in self.base_network_name:
feature_dict = efficientnet_lite_builder.EfficientNetLiteBackbone(
self.cfgs).build_model_fpn_base(
input_img_batch,
model_name=self.base_network_name,
training=True)
return self.fpn_func.fpn_retinanet(feature_dict, self.is_training)
elif 'efficientnet' in self.base_network_name:
feature_dict = efficientnet_builder.EfficientNetBackbone(
self.cfgs).build_model_fpn_base(
input_img_batch,
model_name=self.base_network_name,
training=True)
return self.fpn_func.fpn_retinanet(feature_dict, self.is_training)
elif 'darknet' in self.base_network_name:
feature_dict = darknet.DarkNetBackbone(self.cfgs).darknet53_body(
input_img_batch, is_training=self.is_training)
return self.fpn_func.fpn_retinanet(feature_dict, self.is_training)
else:
raise ValueError(
'Sorry, we only support resnet, mobilenet_v2 and efficient.')
def build_backbone(self, input_img_batch):
if self.base_network_name.startswith('resnet_v1'):
feature_dict = resnet.ResNetBackbone(self.cfgs).resnet_base(
input_img_batch,
scope_name=self.base_network_name,
is_training=self.is_training)
elif self.base_network_name in self.pretrain_zoo.mxnet_zoo:
feature_dict = resnet_gluoncv.ResNetGluonCVBackbone(
self.cfgs).resnet_base(input_img_batch,
scope_name=self.base_network_name,
is_training=self.is_training)
elif self.base_network_name in self.pretrain_zoo.pth_zoo:
feature_dict = resnet_pytorch.ResNetPytorchBackbone(
self.cfgs).resnet_base(input_img_batch,
scope_name=self.base_network_name,
is_training=self.is_training)
elif self.base_network_name.startswith('MobilenetV2'):
feature_dict = mobilenet_v2.MobileNetV2Backbone(
self.cfgs).mobilenetv2_base(input_img_batch,
is_training=self.is_training)
elif 'efficientnet-lite' in self.base_network_name:
feature_dict = efficientnet_lite_builder.EfficientNetLiteBackbone(
self.cfgs).build_model_fpn_base(
input_img_batch,
model_name=self.base_network_name,
training=True)
elif 'efficientnet' in self.base_network_name:
feature_dict = efficientnet_builder.EfficientNetBackbone(
self.cfgs).build_model_fpn_base(
input_img_batch,
model_name=self.base_network_name,
training=True)
elif 'darknet' in self.base_network_name:
feature_dict = darknet.DarkNetBackbone(self.cfgs).darknet53_body(
input_img_batch, is_training=self.is_training)
else:
raise ValueError('Sorry, we only support {}'.format(
self.pretrain_zoo.all_pretrain))
return self.fpn_func.fpn_retinanet(feature_dict, self.is_training)