Struct opencv::dnn::ReduceLayerInt8

pub struct ReduceLayerInt8 { /* private fields */ }

Implementations

impl ReduceLayerInt8

pub fn create(params: &LayerParams) -> Result<Ptr<ReduceLayerInt8>>

Trait Implementations

impl AlgorithmTrait for ReduceLayerInt8

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

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

Clears the algorithm state

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

Reads algorithm parameters from a file storage

impl AlgorithmTraitConst for ReduceLayerInt8

fn as_raw_Algorithm(&self) -> *const c_void

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

Stores algorithm parameters in a file storage

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

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

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 ReduceLayerInt8

unsafe fn from_raw(ptr: *mut c_void) -> Self

Wrap the specified raw pointer

fn into_raw(self) -> *mut c_void

Return an the underlying raw pointer while consuming this wrapper.

fn as_raw(&self) -> *const c_void

Return the underlying raw pointer.

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

Return the underlying mutable raw pointer

impl Drop for ReduceLayerInt8

fn drop(&mut self)

Executes the destructor for this type.

impl From<ReduceLayerInt8> for Algorithm

fn from(s: ReduceLayerInt8) -> Self

Converts to this type from the input type.

impl From<ReduceLayerInt8> for Layer

fn from(s: ReduceLayerInt8) -> Self

Converts to this type from the input type.

impl From<ReduceLayerInt8> for ReduceLayer

fn from(s: ReduceLayerInt8) -> Self

Converts to this type from the input type.

impl LayerTrait for ReduceLayerInt8

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_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: &dyn ToInputArray, outputs: &mut dyn 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: &dyn ToInputArray, outputs: &mut dyn ToOutputArray, internals: &mut dyn ToOutputArray ) -> Result<()>

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

fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut LayerParams ) -> Result<bool>

Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.

fn forward_fallback( &mut self, inputs: &dyn ToInputArray, outputs: &mut dyn ToOutputArray, internals: &mut dyn 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_halide( &mut self, inputs: &Vector<Ptr<dyn BackendWrapper>> ) -> Result<Ptr<BackendNode>>

Returns Halide backend node.

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

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

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

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

Returns a TimVX backend node

fn init_cann( &mut self, inputs_wrapper: &Vector<Ptr<dyn BackendWrapper>>, index: i32, nodes: &Vector<Ptr<BackendNode>> ) -> Result<Ptr<BackendNode>>

Returns a CANN backend node

fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>

Implement layers fusing.

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: &LayerParams) -> Result<()>

impl LayerTraitConst for ReduceLayerInt8

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 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 apply_halide_scheduler( &self, node: &mut Ptr<BackendNode>, inputs: &Vector<Mat>, outputs: &Vector<Mat>, target_id: i32 ) -> Result<()>

Automatic Halide scheduling based on layer hyper-parameters.

fn get_scale_shift(&self, scale: &mut Mat, shift: &mut Mat) -> 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_flops( &self, inputs: &Vector<MatShape>, outputs: &Vector<MatShape> ) -> Result<i64>

impl ReduceLayerInt8Trait for ReduceLayerInt8

fn as_raw_mut_ReduceLayerInt8(&mut self) -> *mut c_void

impl ReduceLayerInt8TraitConst for ReduceLayerInt8

fn as_raw_ReduceLayerInt8(&self) -> *const c_void

impl ReduceLayerTrait for ReduceLayerInt8

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

fn set_reduce_type(&mut self, val: i32)

fn set_reduce_dims(&mut self, val: Vector<size_t>)

fn set_target_dims(&mut self, val: Vector<size_t>)

impl ReduceLayerTraitConst for ReduceLayerInt8

fn as_raw_ReduceLayer(&self) -> *const c_void

fn reduce_type(&self) -> i32

fn reduce_dims(&self) -> Vector<size_t>

fn target_dims(&self) -> Vector<size_t>

impl Send for ReduceLayerInt8