Type Definition opencv::types::PtrOfReshapeLayer

type PtrOfReshapeLayer = Ptr<ReshapeLayer>;

Implementations

impl PtrOfReshapeLayer

pub fn as_raw_PtrOfReshapeLayer(&self) -> *const c_void

pub fn as_raw_mut_PtrOfReshapeLayer(&mut self) -> *mut c_void

Trait Implementations

impl AlgorithmTrait for PtrOfReshapeLayer

fn as_raw_Algorithm(&self) -> *const c_void

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

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

Clears the algorithm state

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

Stores algorithm parameters in a file storage

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

simplified API for language bindings Stores algorithm parameters in a file storage

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

Reads algorithm parameters from 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 LayerTrait for PtrOfReshapeLayer

fn as_raw_Layer(&self) -> *const c_void

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

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

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

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 name(&self) -> String

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

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

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 set_type(&mut self, val: &str)

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

fn preferable_target(&self) -> i32

prefer target for layer forwarding

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. ## Parameters * inputs: vector of already allocated input blobs * outputs:[out] vector of already allocated output 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. ## Parameters * inputs: the input blobs. * outputs:[out] allocated output blobs, which will store results of the computation. * internals:[out] allocated internal blobs

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. ## Parameters * inputs: the input blobs. * outputs:[out] allocated output blobs, which will store results of the computation. * internals:[out] allocated internal blobs

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

👎 Deprecated:

Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

@brief Computes and sets internal parameters according to inputs, outputs and blobs. ## Parameters * inputs: vector of already allocated input blobs * outputs:[out] vector of already allocated output blobs

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

👎 Deprecated:

Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead

@brief Computes and sets internal parameters according to inputs, outputs and blobs. ## Parameters * inputs: vector of already allocated input blobs * outputs:[out] vector of already allocated output 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. ## Parameters * inputName: label of input blob

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

Returns index of output blob in output array. ## See also inputNameToIndex()

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

Ask layer if it support specific backend for doing computations. ## Parameters * backendId: computation backend identifier. ## See also Backend

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

Returns Halide backend node. ## Parameters * inputs: Input Halide buffers. ## See also BackendNode, BackendWrapper

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

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_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

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. ## Parameters * node: Backend node with Halide functions. * inputs: Blobs that will be used in forward invocations. * outputs: Blobs that will be used in forward invocations. * targetId: Target identifier ## See also BackendNode, Target

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

Implement layers fusing. ## Parameters * node: Backend node of bottom layer. ## See also BackendNode

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

Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case. ## Parameters * layer: The subsequent activation layer.

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

Try to fuse current layer with a next one ## Parameters * top: Next layer to be fused. ## Returns True if fusion was performed.

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

Returns parameters of layers with channel-wise multiplication and addition. ## Parameters * scale:[out] Channel-wise multipliers. Total number of values should be equal to number of channels. * shift:[out] Channel-wise offsets. Total number of values should be equal to number of channels.

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

"Deattaches" all the layers, attached to particular layer.

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>

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

impl ReshapeLayerTrait for PtrOfReshapeLayer

fn as_raw_ReshapeLayer(&self) -> *const c_void

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

fn new_shape_desc(&mut self) -> Vector<i32>

fn set_new_shape_desc(&mut self, val: MatShape)

fn new_shape_range(&mut self) -> Range

fn set_new_shape_range(&mut self, val: Range)