Struct NormalizeBBoxLayer 

pub struct NormalizeBBoxLayer { /* private fields */ }

- normalization layer.

Parameters

• p: Normalization factor. The most common p = 1 for - normalization or p = 2 for - normalization or a custom one.
• eps: Parameter 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: @f[ norm = \sqrt[p]{\epsilon + \sum_{x, y, c} |src(x, y, c)|^p } \ dst(x, y, c) = \frac{ src(x, y, c) }{norm} @f]

Channel wise normalization: @f[ norm(c) = \sqrt[p]{\epsilon + \sum_{x, y} |src(x, y, c)|^p } \ dst(x, y, c) = \frac{ src(x, y, c) }{norm(c)} @f]

Where x, y - spatial coordinates, c - channel.

An every sample in the batch is normalized separately. Optionally, output is scaled by the trained parameters.

Implementations

impl NormalizeBBoxLayer

pub fn default() -> NormalizeBBoxLayer

Creates a default instance of the class by calling the default constructor

pub fn create( params: &impl LayerParamsTraitConst, ) -> Result<Ptr<NormalizeBBoxLayer>>

Trait Implementations

impl AlgorithmTrait for NormalizeBBoxLayer

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTraitConst for NormalizeBBoxLayer

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl Boxed for NormalizeBBoxLayer

unsafe fn from_raw( ptr: <NormalizeBBoxLayer as OpenCVFromExtern>::ExternReceive, ) -> Self

Wrap the specified raw pointer

fn into_raw( self, ) -> <NormalizeBBoxLayer as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying raw pointer while consuming this wrapper.

fn as_raw( &self, ) -> <NormalizeBBoxLayer as OpenCVTypeExternContainer>::ExternSend

Return the underlying raw pointer.

fn as_raw_mut( &mut self, ) -> <NormalizeBBoxLayer as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying mutable raw pointer

impl Debug for NormalizeBBoxLayer

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for NormalizeBBoxLayer

fn default() -> Self

Forwards to infallible Self::default()

impl Drop for NormalizeBBoxLayer

fn drop(&mut self)

Executes the destructor for this type.

fn pin_drop(self: Pin<&mut Self>)

🔬This is a nightly-only experimental API. (pin_ergonomics)

Execute the destructor for this type, but different to Drop::drop, it requires self to be pinned.

impl From<NormalizeBBoxLayer> for Algorithm

fn from(s: NormalizeBBoxLayer) -> Self

Converts to this type from the input type.

impl From<NormalizeBBoxLayer> for Layer

fn from(s: NormalizeBBoxLayer) -> Self

Converts to this type from the input type.

impl LayerTrait for NormalizeBBoxLayer

fn as_raw_mut_Layer(&mut self) -> *mut c_void

fn set_blobs(&mut self, val: Vector<Mat>)

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn set_inputs(&mut self, val: Vector<Arg>)

fn set_outputs(&mut self, val: Vector<Arg>)

fn netimpl(&mut self) -> *mut c_void

unsafe fn set_netimpl(&mut self, val: *const c_void)

fn set_name(&mut self, val: &str)

Name of the layer instance, can be used for logging or other internal purposes.

fn set_type(&mut self, val: &str)

Type name which was used for creating layer by layer factory.

fn set_preferable_target(&mut self, val: i32)

prefer target for layer forwarding

fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, ) -> Result<()>

Computes and sets internal parameters according to inputs, outputs and blobs.

fn forward_mat( &mut self, input: &mut Vector<Mat>, output: &mut Vector<Mat>, internals: &mut Vector<Mat>, ) -> Result<()>

👎Deprecated:

Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead

Given the @p input blobs, computes the output @p blobs.

fn forward( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray, ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn forward_fallback( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray, internals: &mut impl ToOutputArray, ) -> Result<()>

Given the @p input blobs, computes the output @p blobs.

fn finalize_mat_to( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, ) -> Result<()>

👎Deprecated:

Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>

👎Deprecated:

Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

Computes and sets internal parameters according to inputs, outputs and blobs.

fn run( &mut self, inputs: &Vector<Mat>, outputs: &mut Vector<Mat>, internals: &mut Vector<Mat>, ) -> Result<()>

👎Deprecated:

This method will be removed in the future release.

Allocates layer and computes output.

fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>

Returns index of input blob into the input array.

fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>

Returns index of output blob in output array.

fn support_backend(&mut self, backend_id: i32) -> Result<bool>

Ask layer if it support specific backend for doing computations.

fn init_ngraph( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>>, ) -> Result<Ptr<BackendNode>>

fn init_vk_com( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &mut Vector<Ptr<BackendWrapper>>, ) -> Result<Ptr<BackendNode>>

fn init_webnn( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>>, ) -> Result<Ptr<BackendNode>>

unsafe fn init_cuda( &mut self, context: *mut c_void, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, ) -> Result<Ptr<BackendNode>>

Returns a CUDA backend node

unsafe fn init_tim_vx( &mut self, tim_vx_info: *mut c_void, inputs_wrapper: &Vector<Ptr<BackendWrapper>>, outputs_wrapper: &Vector<Ptr<BackendWrapper>>, is_last: bool, ) -> Result<Ptr<BackendNode>>

Returns a TimVX backend node

fn init_cann( &mut self, inputs: &Vector<Ptr<BackendWrapper>>, outputs: &Vector<Ptr<BackendWrapper>>, nodes: &Vector<Ptr<BackendNode>>, ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case.

fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>

Try to fuse current layer with a next one

fn unset_attached(&mut self) -> Result<()>

“Detaches” all the layers, attached to particular layer.

fn update_memory_shapes(&mut self, inputs: &Vector<MatShape>) -> Result<bool>

fn set_params_from(&mut self, params: &impl LayerParamsTraitConst) -> Result<()>

impl LayerTraitConst for NormalizeBBoxLayer

fn as_raw_Layer(&self) -> *const c_void

fn blobs(&self) -> Vector<Mat>

List of learned parameters must be stored here to allow read them by using Net::getParam().

fn inputs(&self) -> Vector<Arg>

fn outputs(&self) -> Vector<Arg>

fn name(&self) -> String

Name of the layer instance, can be used for logging or other internal purposes.

fn typ(&self) -> String

Type name which was used for creating layer by layer factory.

fn preferable_target(&self) -> i32

prefer target for layer forwarding

fn subgraphs(&self) -> Result<Vector<Ptr<Graph>>>

fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait, ) -> Result<()>

Returns parameters of layers with channel-wise multiplication and addition.

fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32, ) -> Result<()>

Returns scale and zeropoint of layers

fn get_memory_shapes( &self, inputs: &Vector<MatShape>, required_outputs: i32, outputs: &mut Vector<MatShape>, internals: &mut Vector<MatShape>, ) -> Result<bool>

fn get_types( &self, inputs: &Vector<MatType>, required_outputs: i32, required_internals: i32, outputs: &mut Vector<MatType>, internals: &mut Vector<MatType>, ) -> Result<()>

fn get_layouts( &self, actual_inputs: &Vector<DataLayout>, desired_inputs: &mut Vector<DataLayout>, required_outputs: i32, outputs: &mut Vector<DataLayout>, ) -> Result<i32>

fn get_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape>, ) -> Result<i64>

fn always_support_inplace(&self) -> Result<bool>

fn dynamic_output_shapes(&self) -> Result<bool>

fn is_data_shuffling(&self) -> Result<bool>

impl NormalizeBBoxLayerTrait for NormalizeBBoxLayer

fn as_raw_mut_NormalizeBBoxLayer(&mut self) -> *mut c_void

fn set_pnorm(&mut self, val: f32)

fn set_epsilon(&mut self, val: f32)

fn set_across_spatial(&mut self, val: bool)

impl NormalizeBBoxLayerTraitConst for NormalizeBBoxLayer

fn as_raw_NormalizeBBoxLayer(&self) -> *const c_void

fn pnorm(&self) -> f32

fn epsilon(&self) -> f32

fn across_spatial(&self) -> bool

impl Send for NormalizeBBoxLayer

impl TryFrom<Layer> for NormalizeBBoxLayer

type Error = Error

The type returned in the event of a conversion error.

fn try_from(s: Layer) -> Result<Self>

Performs the conversion.