.. role:: hidden :class: hidden-section mmcls.models =================================== The ``models`` package contains several sub-packages for addressing the different components of a model. - :ref:`classifiers`: The top-level module which defines the whole process of a classification model. - :ref:`backbones`: Usually a feature extraction network, e.g., ResNet, MobileNet. - :ref:`necks`: The component between backbones and heads, e.g., GlobalAveragePooling. - :ref:`heads`: The component for specific tasks. In MMClassification, we provides heads for classification. - :ref:`losses`: Loss functions. .. currentmodule:: mmcls.models .. autosummary:: :toctree: generated :nosignatures: build_classifier build_backbone build_neck build_head build_loss .. _classifiers: Classifier ------------------ .. autosummary:: :toctree: generated :nosignatures: :template: classtemplate.rst BaseClassifier ImageClassifier .. _backbones: Backbones ------------------ .. autosummary:: :toctree: generated :nosignatures: :template: classtemplate.rst AlexNet CSPDarkNet CSPNet CSPResNeXt CSPResNet Conformer ConvMixer ConvNeXt DenseNet DistilledVisionTransformer EfficientNet HRNet LeNet5 MlpMixer MobileNetV2 MobileNetV3 PCPVT PoolFormer RegNet RepMLPNet RepVGG Res2Net ResNeSt ResNeXt ResNet ResNetV1c ResNetV1d ResNet_CIFAR SEResNeXt SEResNet SVT ShuffleNetV1 ShuffleNetV2 SwinTransformer T2T_ViT TIMMBackbone TNT VAN VGG VisionTransformer EfficientFormer HorNet .. _necks: Necks ------------------ .. autosummary:: :toctree: generated :nosignatures: :template: classtemplate.rst GlobalAveragePooling GeneralizedMeanPooling HRFuseScales .. _heads: Heads ------------------ .. autosummary:: :toctree: generated :nosignatures: :template: classtemplate.rst ClsHead LinearClsHead StackedLinearClsHead MultiLabelClsHead MultiLabelLinearClsHead VisionTransformerClsHead DeiTClsHead ConformerHead .. _losses: Losses ------------------ .. autosummary:: :toctree: generated :nosignatures: :template: classtemplate.rst Accuracy AsymmetricLoss CrossEntropyLoss LabelSmoothLoss FocalLoss SeesawLoss