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First model version
4ea50ff
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
from collections import OrderedDict
from torch import nn
from maskrcnn_benchmark.modeling import registry
from maskrcnn_benchmark.modeling.make_layers import conv_with_kaiming_uniform
from . import fpn as fpn_module
from .pan import PAN
from .msr import MSR
from . import resnet
@registry.BACKBONES.register("R-50-C4")
@registry.BACKBONES.register("R-50-C5")
@registry.BACKBONES.register("R-101-C4")
@registry.BACKBONES.register("R-101-C5")
def build_resnet_backbone(cfg):
body = resnet.ResNet(cfg)
model = nn.Sequential(OrderedDict([("body", body)]))
model.out_channels = cfg.MODEL.RESNETS.BACKBONE_OUT_CHANNELS
return model
@registry.BACKBONES.register("R-50-FPN")
@registry.BACKBONES.register("R-101-FPN")
@registry.BACKBONES.register("R-152-FPN")
def build_resnet_fpn_backbone(cfg):
in_channels_stage2 = cfg.MODEL.RESNETS.RES2_OUT_CHANNELS # 256
in_channels_list = [
in_channels_stage2, # 256
in_channels_stage2 * 2, # 512
in_channels_stage2 * 4, # 1024
in_channels_stage2 * 8, # 2048
]
body = resnet.ResNet(cfg)
out_channels = cfg.MODEL.RESNETS.BACKBONE_OUT_CHANNELS # 256
fpn = fpn_module.FPN(
in_channels_list=in_channels_list,
out_channels=out_channels,
conv_block=conv_with_kaiming_uniform(
cfg.MODEL.FPN.USE_GN, cfg.MODEL.FPN.USE_RELU,
cfg.MODEL.FPN.USE_DEFORMABLE
),
top_blocks=fpn_module.LastLevelMaxPool(),
)
if cfg.MODEL.MSR_ON:
model = MSR(body, in_channels_list, fpn=fpn)
else:
model = nn.Sequential(OrderedDict([("body", body), ("fpn", fpn)]))
model.out_channels = out_channels
return model
@registry.BACKBONES.register("R-50-PAN")
@registry.BACKBONES.register("R-101-PAN")
@registry.BACKBONES.register("R-152-PAN")
def build_resnet_fpn_backbone(cfg):
in_channels_stage2 = cfg.MODEL.RESNETS.RES2_OUT_CHANNELS
in_channels_list = [
in_channels_stage2,
in_channels_stage2 * 2,
in_channels_stage2 * 4,
in_channels_stage2 * 8,
]
body = resnet.ResNet(cfg)
out_channels = cfg.MODEL.RESNETS.BACKBONE_OUT_CHANNELS
fpn = fpn_module.FPN(
in_channels_list=in_channels_list,
out_channels=out_channels,
conv_block=conv_with_kaiming_uniform(
cfg.MODEL.FPN.USE_GN, cfg.MODEL.FPN.USE_RELU,
cfg.MODEL.FPN.USE_DEFORMABLE
),
top_blocks=fpn_module.LastLevelMaxPool(),
)
pan = PAN()
if cfg.MODEL.MSR_ON:
model = MSR(body, in_channels_list, fpn=fpn, pan=pan)
else:
model = nn.Sequential(OrderedDict([("body", body),
("pan", pan),
("fpn", fpn)]))
model.out_channels = out_channels
return model
@registry.BACKBONES.register("R-50-FPN-RETINANET")
@registry.BACKBONES.register("R-101-FPN-RETINANET")
def build_resnet_fpn_p3p7_backbone(cfg):
body = resnet.ResNet(cfg)
in_channels_stage2 = cfg.MODEL.RESNETS.RES2_OUT_CHANNELS
out_channels = cfg.MODEL.RESNETS.BACKBONE_OUT_CHANNELS
in_channels_p6p7 = in_channels_stage2 * 8 if cfg.MODEL.RETINANET.USE_C5 \
else out_channels
fpn = fpn_module.FPN(
in_channels_list=[
0,
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.LastLevelP6P7(in_channels_p6p7, out_channels),
)
model = nn.Sequential(OrderedDict([("body", body), ("fpn", fpn)]))
model.out_channels = out_channels
return model
def build_backbone(cfg):
assert cfg.MODEL.BACKBONE.CONV_BODY in registry.BACKBONES, \
"cfg.MODEL.BACKBONE.CONV_BODY: {} are not registered in registry".format(
cfg.MODEL.BACKBONE.CONV_BODY
)
return registry.BACKBONES[cfg.MODEL.BACKBONE.CONV_BODY](cfg)