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Functions115 in github.com/TencentYoutuResearch/SceneSegmentation-SCRL

⨍ Functions 115◇ Types & classes 17

Functioninference

(args, model, loader, threshhold=0.5)

SceneSeg/main.py:108

Functionpairwise_distance

(data1, data2, device=torch.device('cuda'))

cluster/Group.py:140

Functionprint_pass

pretrain_main.py:54

Functionresnet101

r"""ResNet-101 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_. Args: pretrained

models/backbones/visual/resnet.py:339

Functionresnet152

r"""ResNet-152 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_. Args: pretrained

models/backbones/visual/resnet.py:352

Functionresnet18

r"""ResNet-18 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_. Args: pretrained (

models/backbones/visual/resnet.py:300

Functionresnet34

r"""ResNet-34 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_. Args: pretrained (

models/backbones/visual/resnet.py:313

Functionresnet50

r"""ResNet-50 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_. Args: pretrained (

models/backbones/visual/resnet.py:326

Functionresnext101_32x8d

r"""ResNeXt-101 32x8d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_. Arg

models/backbones/visual/resnet.py:380

Functionresnext50_32x4d

r"""ResNeXt-50 32x4d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_. Args

models/backbones/visual/resnet.py:365

Functiontask_worker

(gpu, ngpus_per_node, cfg)

pretrain_main.py:51

(args, model, train_loader, optimizer, epoch, criterion, log_interval=30)

SceneSeg/main.py:87

Functiontrain_SCRL

(gpu, train_loader, model, criterion, optimizer, epoch, cfg)

pretrain_trainer.py:9

Functionwide_resnet101_2

r"""Wide ResNet-101-2 model from `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_. The model is the same as ResNet except f

models/backbones/visual/resnet.py:414

Functionwide_resnet50_2

r"""Wide ResNet-50-2 model from `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_. The model is the same as ResNet except fo

models/backbones/visual/resnet.py:395

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