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Types & classes23 in github.com/ShihaoShao-GH/SuperGlobal

⨍ Functions 103◇ Types & classes 23

↓ 9 callersClassrelup

Reranking with maximum descriptors aggregation

modules/coarse_retrieval/relup.py:10

↓ 4 callersClassResStage

Stage of ResNet.

model/resnet.py:170

↓ 2 callersClassCVNet_Rerank

model/CVNet_Rerank_model.py:18

↓ 2 callersClassResBlock

Residual block: x + F(x).

model/resnet.py:139

↓ 1 callersClassCVLearner

model/CVlearner.py:11

↓ 1 callersClassDataSet

Common dataset.

test/dataset.py:23

↓ 1 callersClassDataSet

Common dataset.

test/dataset_1m.py:27

↓ 1 callersClassGeneralizedMeanPoolingP

Same, but norm is trainable

model/resnet.py:68

↓ 1 callersClassGlobalHead

model/resnet.py:77

↓ 1 callersClassMDescAug

Top-M Descriptor Augmentation

modules/reranking/MDescAug.py:10

↓ 1 callersClassRerankwMDA

Reranking with maximum descriptors aggregation

modules/reranking/RerankwMDA.py:10

↓ 1 callersClassResNet

model/resnet.py:219

↓ 1 callersClassResStemIN

ResNet stem for ImageNet: 7x7, BN, ReLU, MaxPool.

model/resnet.py:204

↓ 1 callersClassgemp

Reranking with maximum descriptors aggregation

modules/coarse_retrieval/gemp.py:10

↓ 1 callersClassrgem

Reranking with maximum descriptors aggregation

modules/coarse_retrieval/rgem.py:10

↓ 1 callersClasssgem

Reranking with maximum descriptors aggregation

modules/coarse_retrieval/sgem.py:10

ClassBasicTransform

Basic transformation: 3x3, BN, ReLU, 3x3, BN.

model/resnet.py:89

ClassBottleneckTransform

Bottleneck transformation: 1x1, BN, ReLU, 3x3, BN, ReLU, 1x1, BN.

model/resnet.py:111

ClassCenterPivotConv4d

r""" CenterPivot 4D conv

model/base/conv4d.py:7

ClassCorrelation

model/base/correlation.py:11

ClassGeneralizedMeanPooling

r"""Applies a 2D power-average adaptive pooling over an input signal composed of several input planes. The function computed is: :math:`f(X) = pow

model/resnet.py:37

model/base/geometry.py:9

ClassResStage_basetransform

Stage of ResNet.

model/resnet.py:187