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OpenCV
3.4.20-dev
Open Source Computer Vision
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OpenCV
3.4.20-dev
Open Source Computer Vision
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\( L_p \) - normalization layer. More...
#include <opencv2/dnn/all_layers.hpp>
Static Public Member Functions | |
| static Ptr< NormalizeBBoxLayer > | create (const LayerParams ¶ms) |
 Static Public Member Functions inherited from cv::Algorithm | |
| template<typename _Tp > | |
| static Ptr< _Tp > | load (const String &filename, const String &objname=String()) |
| Loads algorithm from the file. More... | |
| template<typename _Tp > | |
| static Ptr< _Tp > | loadFromString (const String &strModel, const String &objname=String()) |
| Loads algorithm from a String. More... | |
| template<typename _Tp > | |
| static Ptr< _Tp > | read (const FileNode &fn) |
| Reads algorithm from the file node. More... | |
Public Attributes | |
| bool | acrossSpatial |
| float | epsilon |
| float | pnorm |
| Public Attributes inherited from cv::dnn::Layer | |
| std::vector< Mat > | blobs |
| List of learned parameters must be stored here to allow read them by using Net::getParam(). More... | |
| String | name |
| Name of the layer instance, can be used for logging or other internal purposes. More... | |
| int | preferableTarget |
| prefer target for layer forwarding More... | |
| String | type |
| Type name which was used for creating layer by layer factory. More... | |
Additional Inherited Members | |
| Public Member Functions inherited from cv::dnn::Layer | |
| Layer () | |
| Layer (const LayerParams ¶ms) | |
| Initializes only name, type and blobs fields. More... | |
| virtual | ~Layer () |
| virtual void | applyHalideScheduler (Ptr< BackendNode > &node, const std::vector< Mat *> &inputs, const std::vector< Mat > &outputs, int targetId) const |
| Automatic Halide scheduling based on layer hyper-parameters. More... | |
| virtual void | finalize (const std::vector< Mat *> &input, std::vector< Mat > &output) |
| Computes and sets internal parameters according to inputs, outputs and blobs. More... | |
| virtual void | finalize (InputArrayOfArrays inputs, OutputArrayOfArrays outputs) |
| Computes and sets internal parameters according to inputs, outputs and blobs. More... | |
| void | finalize (const std::vector< Mat > &inputs, std::vector< Mat > &outputs) |
| This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More... | |
| std::vector< Mat > | finalize (const std::vector< Mat > &inputs) |
| This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More... | |
| virtual void | forward (std::vector< Mat *> &input, std::vector< Mat > &output, std::vector< Mat > &internals) |
Given the input blobs, computes the output blobs. More... | |
| virtual void | forward (InputArrayOfArrays inputs, OutputArrayOfArrays outputs, OutputArrayOfArrays internals) |
Given the input blobs, computes the output blobs. More... | |
| void | forward_fallback (InputArrayOfArrays inputs, OutputArrayOfArrays outputs, OutputArrayOfArrays internals) |
Given the input blobs, computes the output blobs. More... | |
| virtual int64 | getFLOPS (const std::vector< MatShape > &inputs, const std::vector< MatShape > &outputs) const |
| virtual bool | getMemoryShapes (const std::vector< MatShape > &inputs, const int requiredOutputs, std::vector< MatShape > &outputs, std::vector< MatShape > &internals) const |
| virtual void | getScaleShift (Mat &scale, Mat &shift) const |
| Returns parameters of layers with channel-wise multiplication and addition. More... | |
| virtual Ptr< BackendNode > | initHalide (const std::vector< Ptr< BackendWrapper > > &inputs) |
| Returns Halide backend node. More... | |
| virtual Ptr< BackendNode > | initNgraph (const std::vector< Ptr< BackendWrapper > > &inputs, const std::vector< Ptr< BackendNode > > &nodes) |
| virtual int | inputNameToIndex (String inputName) |
| Returns index of input blob into the input array. More... | |
| virtual int | outputNameToIndex (const String &outputName) |
| Returns index of output blob in output array. More... | |
| void | run (const std::vector< Mat > &inputs, std::vector< Mat > &outputs, std::vector< Mat > &internals) |
| Allocates layer and computes output. More... | |
| virtual bool | setActivation (const Ptr< ActivationLayer > &layer) |
| Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case. More... | |
| void | setParamsFrom (const LayerParams ¶ms) |
| Initializes only name, type and blobs fields. More... | |
| virtual bool | supportBackend (int backendId) |
| Ask layer if it support specific backend for doing computations. More... | |
| virtual Ptr< BackendNode > | tryAttach (const Ptr< BackendNode > &node) |
| Implement layers fusing. More... | |
| virtual bool | tryFuse (Ptr< Layer > &top) |
| Try to fuse current layer with a next one. More... | |
| virtual void | unsetAttached () |
| "Deattaches" all the layers, attached to particular layer. More... | |
| virtual bool | updateMemoryShapes (const std::vector< MatShape > &inputs) |
| Public Member Functions inherited from cv::Algorithm | |
| Algorithm () | |
| virtual | ~Algorithm () |
| virtual void | clear () |
| Clears the algorithm state. More... | |
| virtual bool | empty () const |
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More... | |
| virtual String | getDefaultName () const |
| virtual void | read (const FileNode &fn) |
| Reads algorithm parameters from a file storage. More... | |
| virtual void | save (const String &filename) const |
| virtual void | write (FileStorage &fs) const |
| Stores algorithm parameters in a file storage. More... | |
| void | write (FileStorage &fs, const String &name) const |
| void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
| Protected Member Functions inherited from cv::Algorithm | |
| void | writeFormat (FileStorage &fs) const |
\( L_p \) - normalization layer.
| p | Normalization factor. The most common p = 1 for \( L_1 \) - normalization or p = 2 for \( L_2 \) - normalization or a custom one. |
| eps | Parameter \( \epsilon \) to prevent a division by zero. |
| across_spatial | If true, normalize an input across all non-batch dimensions. Otherwise normalize an every channel separately. |
Across spatial:
\[ norm = \sqrt[p]{\epsilon + \sum_{x, y, c} |src(x, y, c)|^p } \\ dst(x, y, c) = \frac{ src(x, y, c) }{norm} \]
Channel wise normalization:
\[ norm(c) = \sqrt[p]{\epsilon + \sum_{x, y} |src(x, y, c)|^p } \\ dst(x, y, c) = \frac{ src(x, y, c) }{norm(c)} \]
Where x, y - spatial coordinates, c - channel.
An every sample in the batch is normalized separately. Optionally, output is scaled by the trained parameters.
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static |
| bool cv::dnn::NormalizeBBoxLayer::acrossSpatial |
| float cv::dnn::NormalizeBBoxLayer::epsilon |
| float cv::dnn::NormalizeBBoxLayer::pnorm |
1.8.13