def build_resnet_fpn_backbone(cfg):
body = resnet.ResNet(cfg)
in_channels_stage2 = cfg.MODEL.RESNETS.RES2_OUT_CHANNELS
out_channels = cfg.MODEL.RESNETS.BACKBONE_OUT_CHANNELS
fpn = fpn_module.FPN(
in_channels_list=[
in_channels_stage2,
in_channels_stage2 * 2,
in_channels_stage2 * 4,
in_channels_stage2 * 8,
],
out_channels=out_channels,
conv_block=conv_with_kaiming_uniform(cfg.MODEL.FPN.USE_GN,
cfg.MODEL.FPN.USE_RELU),
top_blocks=fpn_module.LastLevelMaxPool(),
)
model = nn.Sequential(OrderedDict([("body", body), ("fpn", fpn)]))
model.out_channels = out_channels
return model
def build_mnv2_fpn_backbone(cfg):
body = mobilenet.MobileNetV2(cfg)
in_channels_stage2 = body.return_features_num_channels
out_channels = cfg.MODEL.RESNETS.BACKBONE_OUT_CHANNELS
fpn = fpn_module.FPN(
in_channels_list=[
0,
in_channels_stage2[1],
in_channels_stage2[2],
in_channels_stage2[3],
],
out_channels=out_channels,
conv_block=conv_with_kaiming_uniform(cfg.MODEL.FPN.USE_GN,
cfg.MODEL.FPN.USE_RELU),
top_blocks=fpn_module.LastLevelP6P7(out_channels, out_channels),
)
model = nn.Sequential(OrderedDict([("body", body), ("fpn", fpn)]))
model.out_channels = out_channels
return model
def build_vovnet_fpn_backbone(cfg):
body = vovnet.VoVNet(cfg)
in_channels_stage = cfg.MODEL.VOVNET.OUT_CHANNELS
out_channels = cfg.MODEL.VOVNET.BACKBONE_OUT_CHANNELS
in_channels_p6p7 = in_channels_stage * 4 if cfg.MODEL.RETINANET.USE_C5 \
else out_channels
fpn = fpn_module.FPN(
in_channels_list=[
0,
in_channels_stage * 2,
in_channels_stage * 3,
in_channels_stage * 4,
],
out_channels=out_channels,
conv_block=conv_with_kaiming_uniform(cfg.MODEL.FPN.USE_GN,
cfg.MODEL.FPN.USE_RELU),
top_blocks=fpn_module.LastLevelP6P7(in_channels_p6p7, out_channels),
)
model = nn.Sequential(OrderedDict([("body", body), ("fpn", fpn)]))
model.out_channels = out_channels
return model
