(
self,
backbone_cfg,
last_in_channels=(1024, 512),
out_channels=128,
ffm_cfg=dict(in_channels=512, out_channels=256, scale_factor=4),
upsample_mode="nearest",
align_corners=None,
norm_cfg=dict(type="BN"),
init_cfg=None,
)
| 354 | """ |
| 355 | |
| 356 | def __init__( |
| 357 | self, |
| 358 | backbone_cfg, |
| 359 | last_in_channels=(1024, 512), |
| 360 | out_channels=128, |
| 361 | ffm_cfg=dict(in_channels=512, out_channels=256, scale_factor=4), |
| 362 | upsample_mode="nearest", |
| 363 | align_corners=None, |
| 364 | norm_cfg=dict(type="BN"), |
| 365 | init_cfg=None, |
| 366 | ): |
| 367 | super(STDCContextPathNet, self).__init__(init_cfg=init_cfg) |
| 368 | self.backbone = build_backbone(backbone_cfg) |
| 369 | self.arms = ModuleList() |
| 370 | self.convs = ModuleList() |
| 371 | for channels in last_in_channels: |
| 372 | self.arms.append(AttentionRefinementModule(channels, out_channels)) |
| 373 | self.convs.append(ConvModule(out_channels, out_channels, 3, padding=1, norm_cfg=norm_cfg)) |
| 374 | self.conv_avg = ConvModule(last_in_channels[0], out_channels, 1, norm_cfg=norm_cfg) |
| 375 | |
| 376 | self.ffm = FeatureFusionModule(**ffm_cfg) |
| 377 | |
| 378 | self.upsample_mode = upsample_mode |
| 379 | self.align_corners = align_corners |
| 380 | |
| 381 | def forward(self, x): |
| 382 | outs = list(self.backbone(x)) |
nothing calls this directly
no test coverage detected