| Class | Description |
|---|---|
| _Range | |
| AbsLayer | |
| ActivationLayer | |
| BackendNode |
\brief Derivatives of this class encapsulates functions of certain backends.
|
| BackendWrapper |
\brief Derivatives of this class wraps cv::Mat for different backends and targets.
|
| BaseConvolutionLayer | |
| BatchNormLayer | |
| BlankLayer |
\addtogroup dnn
\{
|
| BNLLLayer | |
| ChannelsPReLULayer | |
| ClassificationModel |
\brief This class represents high-level API for classification models.
|
| ConcatLayer | |
| ConstLayer |
Constant layer produces the same data blob at an every forward pass.
|
| ConvolutionLayer | |
| CropAndResizeLayer | |
| CropLayer | |
| DeconvolutionLayer | |
| DetectionModel |
\brief This class represents high-level API for object detection networks.
|
| DetectionOutputLayer | |
| Dict |
\brief This class implements name-value dictionary, values are instances of DictValue.
|
| DictValue |
\addtogroup dnn
\{
|
| EltwiseLayer |
\brief Element wise operation on inputs
|
| ELULayer | |
| FlattenLayer | |
| InnerProductLayer | |
| InterpLayer |
\brief Bilinear resize layer from https://github.com/cdmh/deeplab-public-ver2
It differs from \ref ResizeLayer in output shape and resize scales computations.
|
| IntFloatPair | |
| KeypointsModel |
\brief This class represents high-level API for keypoints models
KeypointsModel allows to set params for preprocessing input image.
|
| Layer |
\brief This interface class allows to build new Layers - are building blocks of networks.
|
| LayerFactory |
\addtogroup dnn
\{
\defgroup dnnLayerFactory Utilities for New Layers Registration
\{
|
| LayerFactory.Constructor |
Each Layer class must provide this function to the factory
|
| LayerParams |
\brief This class provides all data needed to initialize layer.
|
| LRNLayer | |
| LSTMLayer |
LSTM recurrent layer
|
| MatPointerVector | |
| MatPointerVector.Iterator | |
| MatShapeVector | |
| MatShapeVector.Iterator | |
| MatShapeVectorVector | |
| MatShapeVectorVector.Iterator | |
| MaxUnpoolLayer | |
| MishLayer | |
| Model |
\brief This class is presented high-level API for neural networks.
|
| MVNLayer | |
| Net |
\brief This class allows to create and manipulate comprehensive artificial neural networks.
|
| NormalizeBBoxLayer |
\brief
L_p - normalization layer. |
| PaddingLayer |
\brief Adds extra values for specific axes.
|
| PermuteLayer | |
| PoolingLayer | |
| PowerLayer | |
| PriorBoxLayer | |
| ProposalLayer | |
| RangeVectorVector | |
| RegionLayer | |
| ReLU6Layer | |
| ReLULayer | |
| ReorgLayer | |
| ReshapeLayer | |
| ResizeLayer |
\brief Resize input 4-dimensional blob by nearest neighbor or bilinear strategy.
|
| RNNLayer |
\brief Classical recurrent layer
|
| ScaleLayer | |
| SegmentationModel |
\brief This class represents high-level API for segmentation models
SegmentationModel allows to set params for preprocessing input image.
|
| ShiftLayer | |
| ShuffleChannelLayer |
Permute channels of 4-dimensional input blob.
|
| SigmoidLayer | |
| SliceLayer |
Slice layer has several modes:
1.
|
| SoftmaxLayer | |
| SplitLayer | |
| SwishLayer | |
| TanHLayer |
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