Note

You are reading the documentation for MMClassification 0.x, which will soon be deprecated at the end of 2022. We recommend you upgrade to MMClassification 1.0 to enjoy fruitful new features and better performance brought by OpenMMLab 2.0. Check the installation tutorial, migration tutorial and changelog for more details.

Index

A

Accuracy (class in mmcls.models) adjust_width_group() (mmcls.models.RegNet method) after_train_epoch() (mmcls.core.PreciseBNHook method) AlexNet (class in mmcls.models)

AsymmetricLoss (class in mmcls.models) AutoAugment (class in mmcls.datasets.pipelines) AutoContrast (class in mmcls.datasets.pipelines) average_performance() (in module mmcls.core) average_precision() (in module mmcls.core)

B

BaseClassifier (class in mmcls.models) BaseDataset (class in mmcls.datasets) BatchCutMixLayer (class in mmcls.models.utils.augment) BatchMixupLayer (class in mmcls.models.utils.augment) BatchResizeMixLayer (class in mmcls.models.utils.augment) before_train_epoch() (mmcls.core.ClassNumCheckHook method) before_train_iter() (mmcls.core.ClassNumCheckHook method)

before_val_epoch() (mmcls.core.ClassNumCheckHook method) before_val_iter() (mmcls.core.ClassNumCheckHook method) Brightness (class in mmcls.datasets.pipelines) build_backbone() (in module mmcls.models) build_classifier() (in module mmcls.models) build_head() (in module mmcls.models) build_loss() (in module mmcls.models) build_neck() (in module mmcls.models)

C

calculate_confusion_matrix() (in module mmcls.core) CenterCrop (class in mmcls.datasets.pipelines) channel_shuffle() (in module mmcls.models.utils) CIFAR10 (class in mmcls.datasets) CIFAR100 (class in mmcls.datasets) ClassBalancedDataset (class in mmcls.datasets) ClassNumCheckHook (class in mmcls.core) ClsHead (class in mmcls.models) Collect (class in mmcls.datasets.pipelines) collect_env() (in module mmcls.utils) ColorJitter (class in mmcls.datasets.pipelines) ColorTransform (class in mmcls.datasets.pipelines) ConcatDataset (class in mmcls.datasets)

ConditionalPositionEncoding (class in mmcls.models.utils) Conformer (class in mmcls.models) ConformerHead (class in mmcls.models) Contrast (class in mmcls.datasets.pipelines) ConvMixer (class in mmcls.models) ConvNeXt (class in mmcls.models) CosineAnnealingCooldownLrUpdaterHook (class in mmcls.core) CrossEntropyLoss (class in mmcls.models) CSPDarkNet (class in mmcls.models) CSPNet (class in mmcls.models) CSPResNet (class in mmcls.models) CSPResNeXt (class in mmcls.models) CustomDataset (class in mmcls.datasets) Cutout (class in mmcls.datasets.pipelines)

D

DeiTClsHead (class in mmcls.models)

DenseNet (class in mmcls.models) DistilledVisionTransformer (class in mmcls.models)

E

EfficientFormer (class in mmcls.models) EfficientNet (class in mmcls.models)

Equalize (class in mmcls.datasets.pipelines) extract_feat() (mmcls.models.ImageClassifier method)

F

f1_score() (in module mmcls.core) FashionMNIST (class in mmcls.datasets) FocalLoss (class in mmcls.models) forward() (mmcls.models.Accuracy method) (mmcls.models.AlexNet method) (mmcls.models.AsymmetricLoss method) (mmcls.models.BaseClassifier method) (mmcls.models.Conformer method) (mmcls.models.ConvMixer method) (mmcls.models.ConvNeXt method) (mmcls.models.CrossEntropyLoss method) (mmcls.models.CSPNet method) (mmcls.models.DenseNet method) (mmcls.models.DistilledVisionTransformer method) (mmcls.models.EfficientFormer method) (mmcls.models.EfficientNet method) (mmcls.models.FocalLoss method) (mmcls.models.GeneralizedMeanPooling method) (mmcls.models.GlobalAveragePooling method) (mmcls.models.HorNet method) (mmcls.models.HRFuseScales method) (mmcls.models.HRNet method) (mmcls.models.LabelSmoothLoss method) (mmcls.models.LeNet5 method) (mmcls.models.MlpMixer method) (mmcls.models.MobileNetV2 method) (mmcls.models.MobileNetV3 method) (mmcls.models.PCPVT method) (mmcls.models.PoolFormer method) (mmcls.models.RegNet method) (mmcls.models.RepMLPNet method) (mmcls.models.RepVGG method) (mmcls.models.ResNet method) (mmcls.models.ResNet_CIFAR method) (mmcls.models.SeesawLoss method) (mmcls.models.ShuffleNetV1 method) (mmcls.models.ShuffleNetV2 method) (mmcls.models.SwinTransformer method) (mmcls.models.T2T_ViT method) (mmcls.models.TIMMBackbone method) (mmcls.models.TNT method) (mmcls.models.utils.ConditionalPositionEncoding method) (mmcls.models.utils.InvertedResidual method) (mmcls.models.utils.MultiheadAttention method) (mmcls.models.utils.SELayer method) (mmcls.models.utils.ShiftWindowMSA method) (mmcls.models.VAN method) (mmcls.models.VGG method) (mmcls.models.VisionTransformer method)

forward_dummy() (mmcls.models.ImageClassifier method) forward_test() (mmcls.models.BaseClassifier method) forward_train() (mmcls.models.BaseClassifier method) (mmcls.models.ImageClassifier method)

G

GeneralizedMeanPooling (class in mmcls.models) generate_one_hot_like_label() (mmcls.models.LabelSmoothLoss method) generate_regnet() (mmcls.models.RegNet method)

get_root_logger() (in module mmcls.utils) get_stages_from_blocks() (mmcls.models.RegNet method) GlobalAveragePooling (class in mmcls.models)

H

HorNet (class in mmcls.models)

HRFuseScales (class in mmcls.models) HRNet (class in mmcls.models)

I

ImageClassifier (class in mmcls.models) ImageNet (class in mmcls.datasets) ImageNet21k (class in mmcls.datasets) ImageToTensor (class in mmcls.datasets.pipelines) inference_model() (in module mmcls.apis) init_model() (in module mmcls.apis) init_random_seed() (in module mmcls.apis) init_weights() (mmcls.models.Conformer method) (mmcls.models.ConformerHead method) (mmcls.models.DistilledVisionTransformer method) (mmcls.models.PCPVT method) (mmcls.models.ResNet method) (mmcls.models.ShuffleNetV1 method) (mmcls.models.ShuffleNetV2 method) (mmcls.models.StackedLinearClsHead method) (mmcls.models.SwinTransformer method) (mmcls.models.T2T_ViT method) (mmcls.models.VisionTransformer method) (mmcls.models.VisionTransformerClsHead method)

Invert (class in mmcls.datasets.pipelines) InvertedResidual (class in mmcls.models.utils) is_tracing() (in module mmcls.models.utils)

L

LabelSmoothLoss (class in mmcls.models) Lamb (class in mmcls.core) LeNet5 (class in mmcls.models)

Lighting (class in mmcls.datasets.pipelines) LinearClsHead (class in mmcls.models) load_json_log() (in module mmcls.utils) LoadImageFromFile (class in mmcls.datasets.pipelines)

M

make_divisible() (in module mmcls.models.utils) make_layer() (mmcls.models.MobileNetV2 method) (mmcls.models.ShuffleNetV1 method) mAP() (in module mmcls.core) MlpMixer (class in mmcls.models) MMClsWandbHook (class in mmcls.core) MNIST (class in mmcls.datasets)

MobileNetV2 (class in mmcls.models) MobileNetV3 (class in mmcls.models) multi_gpu_test() (in module mmcls.apis) MultiheadAttention (class in mmcls.models.utils) MultiLabelClsHead (class in mmcls.models) MultiLabelDataset (class in mmcls.datasets) MultiLabelLinearClsHead (class in mmcls.models)

N

norm1 (mmcls.models.HRNet property)

norm2 (mmcls.models.HRNet property) Normalize (class in mmcls.datasets.pipelines)

P

Pad (class in mmcls.datasets.pipelines) PCPVT (class in mmcls.models) PoolFormer (class in mmcls.models)

Posterize (class in mmcls.datasets.pipelines) PreciseBNHook (class in mmcls.core) precision() (in module mmcls.core) precision_recall_f1() (in module mmcls.core)

Q

quantize_float() (mmcls.models.RegNet static method)

R

RandAugment (class in mmcls.datasets.pipelines) RandomCrop (class in mmcls.datasets.pipelines) RandomErasing (class in mmcls.datasets.pipelines) RandomFlip (class in mmcls.datasets.pipelines) RandomGrayscale (class in mmcls.datasets.pipelines) RandomResizedCrop (class in mmcls.datasets.pipelines) recall() (in module mmcls.core) RegNet (class in mmcls.models) RepeatDataset (class in mmcls.datasets) RepMLPNet (class in mmcls.models)

RepVGG (class in mmcls.models) Res2Net (class in mmcls.models) Resize (class in mmcls.datasets.pipelines) resize_pos_embed() (mmcls.models.VisionTransformer static method) ResNeSt (class in mmcls.models) ResNet (class in mmcls.models) ResNet_CIFAR (class in mmcls.models) ResNetV1c (class in mmcls.models) ResNetV1d (class in mmcls.models) ResNeXt (class in mmcls.models) Rotate (class in mmcls.datasets.pipelines)

S

SeesawLoss (class in mmcls.models) SELayer (class in mmcls.models.utils) SEResNet (class in mmcls.models) SEResNeXt (class in mmcls.models) set_random_seed() (in module mmcls.apis) setup_multi_processes() (in module mmcls.utils) Sharpness (class in mmcls.datasets.pipelines) Shear (class in mmcls.datasets.pipelines) ShiftWindowMSA (class in mmcls.models.utils) show_result() (mmcls.models.BaseClassifier method) show_result_pyplot() (in module mmcls.apis) ShuffleNetV1 (class in mmcls.models) ShuffleNetV2 (class in mmcls.models) simple_test() (mmcls.models.ClsHead method) (mmcls.models.ConformerHead method) (mmcls.models.DeiTClsHead method) (mmcls.models.ImageClassifier method) (mmcls.models.LinearClsHead method) (mmcls.models.MultiLabelClsHead method) (mmcls.models.MultiLabelLinearClsHead method) (mmcls.models.StackedLinearClsHead method) (mmcls.models.VisionTransformerClsHead method)

single_gpu_test() (in module mmcls.apis) Solarize (class in mmcls.datasets.pipelines) SolarizeAdd (class in mmcls.datasets.pipelines) StackedLinearClsHead (class in mmcls.models) StanfordCars (class in mmcls.datasets) step() (mmcls.core.Lamb method) support() (in module mmcls.core) SVT (class in mmcls.models) SwinTransformer (class in mmcls.models)

T

T2T_ViT (class in mmcls.models) TIMMBackbone (class in mmcls.models) TNT (class in mmcls.models) to_2tuple() (in module mmcls.models.utils) to_3tuple() (in module mmcls.models.utils) to_4tuple() (in module mmcls.models.utils) to_ntuple() (in module mmcls.models.utils) ToNumpy (class in mmcls.datasets.pipelines) ToPIL (class in mmcls.datasets.pipelines) ToTensor (class in mmcls.datasets.pipelines) train() (mmcls.models.ConvMixer method) (mmcls.models.ConvNeXt method) (mmcls.models.CSPNet method) (mmcls.models.DenseNet method) (mmcls.models.EfficientFormer method) (mmcls.models.EfficientNet method) (mmcls.models.HorNet method) (mmcls.models.HRNet method) (mmcls.models.MobileNetV2 method) (mmcls.models.MobileNetV3 method) (mmcls.models.PoolFormer method) (mmcls.models.RepVGG method) (mmcls.models.ResNet method) (mmcls.models.ShuffleNetV1 method) (mmcls.models.ShuffleNetV2 method) (mmcls.models.SwinTransformer method) (mmcls.models.VAN method) (mmcls.models.VGG method)

train_model() (in module mmcls.apis) train_step() (mmcls.models.BaseClassifier method) Translate (class in mmcls.datasets.pipelines) Transpose (class in mmcls.datasets.pipelines)

V

val_step() (mmcls.models.BaseClassifier method) VAN (class in mmcls.models) VGG (class in mmcls.models)

VisionTransformer (class in mmcls.models) VisionTransformerClsHead (class in mmcls.models) VOC (class in mmcls.datasets)