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/ types & classes
Types & classes
94 in github.com/TPCD/DCCL
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Functions
480
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Types & classes
94
↓ 24 callers
Class
CustomCIFAR100
data/cifar.py:28
↓ 18 callers
Class
vit_branch
model/attribute_transformer.py:70
↓ 14 callers
Class
vit_backbone
model/attribute_transformer.py:12
↓ 9 callers
Class
FeatureVectorDataset
methods/clustering/feature_vector_dataset.py:10
↓ 8 callers
Class
attribute_subnet
model/attribute_transformer.py:457
↓ 7 callers
Class
AverageMeter
Computes and stores the average and current value
project_utils/cluster_utils.py:118
↓ 7 callers
Class
MergedDataset
Takes two datasets (labelled_dataset, unlabelled_dataset) and merges them Allows you to iterate over them in parallel
data/data_utils.py:13
↓ 6 callers
Class
Timer
project_utils/infomap_cluster_utils.py:21
↓ 4 callers
Class
AverageMeter
Computes and stores the average and current value
project_utils/general_utils.py:12
↓ 4 callers
Class
CarsDataset
Cars Dataset
data/stanford_cars.py:16
↓ 4 callers
Class
ChannelAvgPoolFlat
model/attribute_transformer.py:161
↓ 4 callers
Class
CustomCIFAR10
data/cifar.py:9
↓ 4 callers
Class
CustomCub2011
data/cub.py:14
↓ 4 callers
Class
FGVCAircraft
`FGVC-Aircraft <http://www.robots.ox.ac.uk/~vgg/data/fgvc-aircraft>`_ Dataset. Args: root (string): Root directory path to dataset.
data/fgvc_aircraft.py:43
↓ 4 callers
Class
Flowers102
`Oxford 102 Flower <https://www.robots.ox.ac.uk/~vgg/data/flowers/102/>`_ Dataset. .. warning:: This class needs `scipy <https://docs.sc
data/flower.py:32
↓ 4 callers
Class
OxfordIIITPet
`Oxford-IIIT Pet Dataset <https://www.robots.ox.ac.uk/~vgg/data/pets/>`_. Args: root (string): Root directory of the dataset. s
data/pets.py:30
↓ 3 callers
Class
GraphConvolution
model/meta_graph.py:16
↓ 3 callers
Class
VisionTransformer
Vision Transformer
model/vision_transformer.py:135
↓ 2 callers
Class
AttributeTransformer
model/attribute_transformer.py:87
↓ 2 callers
Class
AttributeTransformer10
model/attribute_transformer.py:575
↓ 2 callers
Class
AttributeTransformer11
model/attribute_transformer.py:620
↓ 2 callers
Class
AttributeTransformer12
model/attribute_transformer.py:664
↓ 2 callers
Class
AttributeTransformer13
model/attribute_transformer.py:705
↓ 2 callers
Class
AttributeTransformer14
model/attribute_transformer.py:734
↓ 2 callers
Class
AttributeTransformer2
model/attribute_transformer.py:200
↓ 2 callers
Class
AttributeTransformer4
model/attribute_transformer.py:268
↓ 2 callers
Class
AttributeTransformer5
model/attribute_transformer.py:310
↓ 2 callers
Class
AttributeTransformer6
model/attribute_transformer.py:356
↓ 2 callers
Class
AttributeTransformer7
model/attribute_transformer.py:407
↓ 2 callers
Class
AttributeTransformer8
model/attribute_transformer.py:480
↓ 2 callers
Class
AttributeTransformer9
model/attribute_transformer.py:528
↓ 2 callers
Class
BNClassifier
bn + fc
model/vision_transformer.py:650
↓ 2 callers
Class
ClusterMemory
project_utils/cluster_memory_utils.py:84
↓ 2 callers
Class
FakeLabelDataset
project_utils/data_utils.py:46
↓ 2 callers
Class
Food101
`The Food-101 Data Set <https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/>`_. The Food-101 is a challenging data set of 101 food catego
data/food.py:31
↓ 2 callers
Class
HerbariumDataset19
data/herbarium_19.py:10
↓ 2 callers
Class
ImageNetBase
data/imagenet.py:11
↓ 2 callers
Class
IterLoader
project_utils/data_utils.py:17
↓ 2 callers
Class
Meta_Attribute_Generator1
model/attribute_transformer.py:844
↓ 2 callers
Class
Meta_Attribute_Generator2
model/attribute_transformer.py:881
↓ 2 callers
Class
RandomMultipleGallerySamplerNoCam
project_utils/sampler.py:109
↓ 1 callers
Class
Attention
model/vision_transformer.py:67
↓ 1 callers
Class
AttributeTransformer3
model/attribute_transformer.py:234
↓ 1 callers
Class
Block
model/vision_transformer.py:94
↓ 1 callers
Class
ChannelMaxPoolFlat
model/attribute_transformer.py:118
↓ 1 callers
Class
ContrastiveLearningViewGenerator
Take two random crops of one image as the query and key.
project_utils/contrastive_utils.py:155
↓ 1 callers
Class
ContrastiveLearningViewGenerator
Take two random crops of one image as the query and key.
methods/representation_learning/representation_learning.py:126
↓ 1 callers
Class
ContrastiveLearningViewGenerator
Take two random crops of one image as the query and key.
methods/partitioning/subset_len.py:31
↓ 1 callers
Class
ContrastiveLearningViewGenerator
Take two random crops of one image as the query and key.
methods/partitioning/kmeans_subset.py:32
↓ 1 callers
Class
CosineAnnealingWarmupRestarts_New
project_utils/schedulers.py:86
↓ 1 callers
Class
DropPath
Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).
model/vision_transformer.py:37
↓ 1 callers
Class
IndicatePlateau
project_utils/general_utils.py:304
↓ 1 callers
Class
K_Means
methods/clustering/faster_mix_k_means_pytorch.py:47
↓ 1 callers
Class
Logger
project_utils/cluster_and_log_utils.py:121
↓ 1 callers
Class
Meta_Graph1
model/attribute_transformer.py:783
↓ 1 callers
Class
Mlp
model/vision_transformer.py:48
↓ 1 callers
Class
PatchEmbed
Image to Patch Embedding
model/vision_transformer.py:117
↓ 1 callers
Class
RandAugment
data/augmentations/randaugment.py:275
↓ 1 callers
Class
SupConLoss
Supervised Contrastive Learning: https://arxiv.org/pdf/2004.11362.pdf. It also supports the unsupervised contrastive loss in SimCLR From: http
project_utils/contrastive_utils.py:166
↓ 1 callers
Class
SupConLoss
Supervised Contrastive Learning: https://arxiv.org/pdf/2004.11362.pdf. It also supports the unsupervised contrastive loss in SimCLR From: http
methods/representation_learning/representation_learning.py:35
↓ 1 callers
Class
WarmRestartPlateau
Reduce learning rate on plateau and reset every T_restart epochs
project_utils/schedulers.py:61
↓ 1 callers
Class
knn_faiss
内积暴力循环 归一化特征的内积等价于余弦相似度
project_utils/infomap_cluster_utils.py:413
Class
Attribute_BN_Classifier
model/vision_transformer.py:547
Class
Attribute_Classifier
model/attribute_classifier.py:8
Class
Attribute_Classifier
model/vision_transformer.py:330
Class
Attribute_Classifier2
model/vision_transformer.py:408
Class
Attribute_Classifier3
model/vision_transformer.py:470
Class
Attribute_Classifier5
model/vision_transformer.py:674
Class
Attribute_Classifier6ind
model/vision_transformer.py:749
Class
Attribute_Classifier7ind
model/vision_transformer.py:780
Class
Attribute_Classifier8ind
model/vision_transformer.py:815
Class
BCE
project_utils/cluster_utils.py:143
Class
BaseVisdomLogger
The base class for logging output to Visdom. ***THIS CLASS IS ABSTRACT AND MUST BE SUBCLASSED*** Note that the Visdom serve
project_utils/visualization_utils.py:843
Class
CM
project_utils/cluster_memory_utils.py:9
Class
CM_Hard
project_utils/cluster_memory_utils.py:42
Class
ClassificationPredSaver
project_utils/general_utils.py:210
Class
CutoutDefault
Reference : https://github.com/quark0/darts/blob/master/cnn/utils.py
data/augmentations/randaugment.py:250
Class
DINOHead
model/attribute_classifier.py:84
Class
DINOHead
model/vision_transformer.py:264
Class
Identity
project_utils/cluster_utils.py:136
Class
Lighting
Lighting noise(AlexNet - style PCA - based noise)
data/augmentations/randaugment.py:229
Class
Logger
project_utils/visualization_utils.py:829
Class
MetaGraph_fd
model/meta_graph.py:55
Class
MetaGraph_fd_bn
model/meta_graph.py:133
Class
Mlp
model/attribute_classifier.py:64
Class
RandomIdentitySampler
project_utils/sampler.py:19
Class
RandomMultipleGallerySampler
project_utils/sampler.py:46
Class
TextColors
project_utils/infomap_cluster_utils.py:10
Class
VisdomFeatureMapsLogger
A generic Visdom class that works with the majority of Visdom plot types.
project_utils/visualization_utils.py:945
Class
VisdomLogger
A generic Visdom class that works with the majority of Visdom plot types.
project_utils/visualization_utils.py:912
Class
VisdomPlotLogger
project_utils/visualization_utils.py:1001
Class
VisdomSaver
Serialize the state of the Visdom server to disk. Unless you have a fancy schedule, where different are saved with different frequencies,
project_utils/visualization_utils.py:897
Class
VisdomTextLogger
Creates a text window in visdom and logs output to it. The output can be formatted with fancy HTML, and it new output can be set to 'append'
project_utils/visualization_utils.py:1056
Class
VisionTransformerWithLinear
model/vision_transformer.py:301