Functions — github.com/Andy-zhujunwen/UNET-ZOO

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Functions143 in github.com/Andy-zhujunwen/UNET-ZOO

⨍ Functions 143◇ Types & classes 50

↓ 17 callersMethod__init__

(self, in_ch, out_ch, bilinear=True)

↓ 8 callersFunction_vgg

(arch, cfg, batch_norm, pretrained, progress, **kwargs)

↓ 5 callersMethod__init__

(self, features, num_classes=1000, init_weights=True)

↓ 3 callersMethod__init__

(self, in_ch, out_ch)

↓ 3 callersMethod__init__

(self,ch_in,ch_out)

↓ 3 callersMethod__init__

(self,ch_in,ch_out)

attention_unet.py:22

↓ 2 callersMethod__init__

(self, channels_high, channels_low, upsample=True)

channel_unet.py:6

↓ 2 callersFunctionget_dice

(mask_name,predict)

↓ 2 callersFunctionget_hd

(mask_name,predict)

↓ 2 callersFunctionget_iou

(mask_name,predict)

↓ 2 callersFunctionmake_layers

(cfg, batch_norm=False)

↓ 2 callersFunctionmetrics_plot

(arg,name,*args)

↓ 1 callersMethod__init__

(self, in_ch, out_ch)

↓ 1 callersMethod_fast_hist

(self, label_pred, label_true)

↓ 1 callersMethod_initialize_weights

↓ 1 callersMethod_make_stage

(self, features, size)

↓ 1 callersFunctiongetArgs

↓ 1 callersMethodgetDataPath

↓ 1 callersMethodgetDataPath

↓ 1 callersMethodgetDataPath

↓ 1 callersMethodgetDataPath

↓ 1 callersMethodgetDataPath

↓ 1 callersMethodgetDataPath

↓ 1 callersMethodgetDataPath

↓ 1 callersFunctiongetDataset

↓ 1 callersFunctiongetLog

↓ 1 callersFunctiongetModel

↓ 1 callersFunctionget_fcn8s

↓ 1 callersFunctionloss_plot

↓ 1 callersFunctiontest

(val_dataloaders,save_predict=False)

↓ 1 callersFunctiontrain

(model, criterion, optimizer, train_dataloader,val_dataloader, args)

↓ 1 callersFunctionval

(model,best_iou,val_dataloaders)

Method__getitem__

Method__getitem__

Method__getitem__

Method__getitem__

Method__getitem__

Method__getitem__

Method__getitem__

(self,input_nbr,label_nbr)

(self, args,in_channel,out_channel)

(self, in_ch, out_ch)

channel_unet.py:47

(self, in_ch, out_ch)

channel_unet.py:63

(self, pretrained_net, n_class)

(self, pretrained_net, n_class)

(self, pretrained_net, n_class)

(self, pretrained_net, n_class)

(self, pretrained=True, model='vgg16', requires_grad=True, remove_fc=True, show_params=False)

(self, state, transform=None, target_transform=None)

(self, state, transform=None, target_transform=None)

(self, state, transform=None, target_transform=None)

(self, state, transform=None, target_transform=None)

(self, state, transform=None, target_transform=None)

(self, state, transform=None, target_transform=None)

(self, state, transform=None, target_transform=None)

(self, num_classes)

(self, channel)

(self, channel)

(self, channel)

(self, channel)

(self, features, out_features=1024, sizes=(2, 3, 6, 14))

(self, in_channels)

(self, in_channels, n_filters)

(self, num_classes=1, num_channels=3)

(self, num_classes=1, num_channels=3)

(self, num_classes=1, num_channels=3)

(self, num_classes=1, num_channels=3)

(self, num_classes=12, num_channels=3)

(self, in_ch, out_ch)

(self, in_ch, out_ch)

(self, in_ch, out_ch)

(self, in_ch, out_ch)

(self, n_channels=3, n_classes=1)

(self, in_ch, out_ch)

(self, in_channels, n_filters)

(self, num_classes=1, num_channels=3,pretrained=True)

(self, ch_out, t=2)

(self,ch_in,ch_out,t=2)

(self, img_ch=3, output_ch=1, t=2)

(self,ch_in,ch_out)

attention_unet.py:7

(self, F_g, F_l, F_int)

attention_unet.py:36

(self, img_ch=3, output_ch=1)

attention_unet.py:70

Methodadd_batch

(self, predictions, gts)

(self, fms_high, fms_low, fm_mask=None)

channel_unet.py:24

channel_unet.py:58

channel_unet.py:89

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