Struct opencv::dnn::PaddingLayer
source · pub struct PaddingLayer { /* private fields */ }
Expand description
Adds extra values for specific axes.
§Parameters
-
paddings: Vector of paddings in format
C++ [ pad_before, pad_after, // [0]th dimension pad_before, pad_after, // [1]st dimension ... pad_before, pad_after ] // [n]th dimension
that represents number of padded values at every dimension starting from the first one. The rest of dimensions won't be padded.
-
value: Value to be padded. Defaults to zero.
-
type: Padding type: ‘constant’, ‘reflect’
-
input_dims: Torch’s parameter. If @p input_dims is not equal to the actual input dimensionality then the
[0]th
dimension is considered as a batch dimension and @p paddings are shifted to a one dimension. Defaults to-1
that means padding corresponding to @p paddings.
Implementations§
source§impl PaddingLayer
impl PaddingLayer
pub fn create(params: &impl LayerParamsTraitConst) -> Result<Ptr<PaddingLayer>>
Trait Implementations§
source§impl AlgorithmTrait for PaddingLayer
impl AlgorithmTrait for PaddingLayer
source§impl AlgorithmTraitConst for PaddingLayer
impl AlgorithmTraitConst for PaddingLayer
fn as_raw_Algorithm(&self) -> *const c_void
source§fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>
fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>
Stores algorithm parameters in a file storage
source§fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>
fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>
Stores algorithm parameters in a file storage Read more
source§fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>
fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>
@deprecated Read more
source§fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>
fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>
👎Deprecated:
§Note
Deprecated: ## Note
This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments: Read more
source§fn empty(&self) -> Result<bool>
fn empty(&self) -> Result<bool>
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read
source§fn save(&self, filename: &str) -> Result<()>
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).
source§fn get_default_name(&self) -> Result<String>
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.
source§impl Boxed for PaddingLayer
impl Boxed for PaddingLayer
source§unsafe fn from_raw(
ptr: <PaddingLayer as OpenCVFromExtern>::ExternReceive
) -> Self
unsafe fn from_raw( ptr: <PaddingLayer as OpenCVFromExtern>::ExternReceive ) -> Self
Wrap the specified raw pointer Read more
source§fn into_raw(self) -> <PaddingLayer as OpenCVTypeExternContainer>::ExternSendMut
fn into_raw(self) -> <PaddingLayer as OpenCVTypeExternContainer>::ExternSendMut
Return the underlying raw pointer while consuming this wrapper. Read more
source§fn as_raw(&self) -> <PaddingLayer as OpenCVTypeExternContainer>::ExternSend
fn as_raw(&self) -> <PaddingLayer as OpenCVTypeExternContainer>::ExternSend
Return the underlying raw pointer. Read more
source§fn as_raw_mut(
&mut self
) -> <PaddingLayer as OpenCVTypeExternContainer>::ExternSendMut
fn as_raw_mut( &mut self ) -> <PaddingLayer as OpenCVTypeExternContainer>::ExternSendMut
Return the underlying mutable raw pointer Read more
source§impl Debug for PaddingLayer
impl Debug for PaddingLayer
source§impl Default for PaddingLayer
impl Default for PaddingLayer
source§impl Drop for PaddingLayer
impl Drop for PaddingLayer
source§impl From<PaddingLayer> for Algorithm
impl From<PaddingLayer> for Algorithm
source§fn from(s: PaddingLayer) -> Self
fn from(s: PaddingLayer) -> Self
Converts to this type from the input type.
source§impl From<PaddingLayer> for Layer
impl From<PaddingLayer> for Layer
source§fn from(s: PaddingLayer) -> Self
fn from(s: PaddingLayer) -> Self
Converts to this type from the input type.
source§impl LayerTrait for PaddingLayer
impl LayerTrait for PaddingLayer
fn as_raw_mut_Layer(&mut self) -> *mut c_void
source§fn set_blobs(&mut self, val: Vector<Mat>)
fn set_blobs(&mut self, val: Vector<Mat>)
List of learned parameters must be stored here to allow read them by using Net::getParam().
source§fn set_name(&mut self, val: &str)
fn set_name(&mut self, val: &str)
Name of the layer instance, can be used for logging or other internal purposes.
source§fn set_type(&mut self, val: &str)
fn set_type(&mut self, val: &str)
Type name which was used for creating layer by layer factory.
source§fn set_preferable_target(&mut self, val: i32)
fn set_preferable_target(&mut self, val: i32)
prefer target for layer forwarding
source§fn finalize(
&mut self,
inputs: &impl ToInputArray,
outputs: &mut impl ToOutputArray
) -> Result<()>
fn finalize( &mut self, inputs: &impl ToInputArray, outputs: &mut impl ToOutputArray ) -> Result<()>
Computes and sets internal parameters according to inputs, outputs and blobs. Read more
source§fn forward_mat(
&mut self,
input: &mut Vector<Mat>,
output: &mut Vector<Mat>,
internals: &mut Vector<Mat>
) -> Result<()>
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. Read more
source§fn forward(
&mut self,
inputs: &impl ToInputArray,
outputs: &mut impl ToOutputArray,
internals: &mut impl ToOutputArray
) -> Result<()>
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. Read more
source§fn try_quantize(
&mut self,
scales: &Vector<Vector<f32>>,
zeropoints: &Vector<Vector<i32>>,
params: &mut impl LayerParamsTrait
) -> Result<bool>
fn try_quantize( &mut self, scales: &Vector<Vector<f32>>, zeropoints: &Vector<Vector<i32>>, params: &mut impl LayerParamsTrait ) -> Result<bool>
Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation. Read more
source§fn forward_fallback(
&mut self,
inputs: &impl ToInputArray,
outputs: &mut impl ToOutputArray,
internals: &mut impl ToOutputArray
) -> Result<()>
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. Read more
source§fn finalize_mat_to(
&mut self,
inputs: &Vector<Mat>,
outputs: &mut Vector<Mat>
) -> Result<()>
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. Read more
source§fn finalize_mat(&mut self, inputs: &Vector<Mat>) -> Result<Vector<Mat>>
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. Read more
source§fn run(
&mut self,
inputs: &Vector<Mat>,
outputs: &mut Vector<Mat>,
internals: &mut Vector<Mat>
) -> Result<()>
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. Read more
source§fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>
fn input_name_to_index(&mut self, input_name: &str) -> Result<i32>
Returns index of input blob into the input array. Read more
source§fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>
fn output_name_to_index(&mut self, output_name: &str) -> Result<i32>
Returns index of output blob in output array. Read more
source§fn support_backend(&mut self, backend_id: i32) -> Result<bool>
fn support_backend(&mut self, backend_id: i32) -> Result<bool>
Ask layer if it support specific backend for doing computations. Read more
source§fn init_halide(
&mut self,
inputs: &Vector<Ptr<BackendWrapper>>
) -> Result<Ptr<BackendNode>>
fn init_halide( &mut self, inputs: &Vector<Ptr<BackendWrapper>> ) -> Result<Ptr<BackendNode>>
Returns Halide backend node. Read more
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>>
source§unsafe fn init_cuda(
&mut self,
context: *mut c_void,
inputs: &Vector<Ptr<BackendWrapper>>,
outputs: &Vector<Ptr<BackendWrapper>>
) -> 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 Read more
source§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>>
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 Read more
source§fn init_cann(
&mut self,
inputs: &Vector<Ptr<BackendWrapper>>,
outputs: &Vector<Ptr<BackendWrapper>>,
nodes: &Vector<Ptr<BackendNode>>
) -> Result<Ptr<BackendNode>>
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 Read more
source§fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>
fn try_attach(&mut self, node: &Ptr<BackendNode>) -> Result<Ptr<BackendNode>>
Implement layers fusing. Read more
source§fn set_activation(&mut self, layer: &Ptr<ActivationLayer>) -> Result<bool>
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. Read more
source§fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>
fn try_fuse(&mut self, top: &mut Ptr<Layer>) -> Result<bool>
Try to fuse current layer with a next one Read more
source§fn unset_attached(&mut self) -> Result<()>
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<()>
source§impl LayerTraitConst for PaddingLayer
impl LayerTraitConst for PaddingLayer
fn as_raw_Layer(&self) -> *const c_void
source§fn blobs(&self) -> Vector<Mat>
fn blobs(&self) -> Vector<Mat>
List of learned parameters must be stored here to allow read them by using Net::getParam().
source§fn name(&self) -> String
fn name(&self) -> String
Name of the layer instance, can be used for logging or other internal purposes.
source§fn preferable_target(&self) -> i32
fn preferable_target(&self) -> i32
prefer target for layer forwarding
source§fn apply_halide_scheduler(
&self,
node: &mut Ptr<BackendNode>,
inputs: &Vector<Mat>,
outputs: &Vector<Mat>,
target_id: i32
) -> Result<()>
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. Read more
source§fn get_scale_shift(
&self,
scale: &mut impl MatTrait,
shift: &mut impl MatTrait
) -> Result<()>
fn get_scale_shift( &self, scale: &mut impl MatTrait, shift: &mut impl MatTrait ) -> Result<()>
Returns parameters of layers with channel-wise multiplication and addition. Read more
source§fn get_scale_zeropoint(
&self,
scale: &mut f32,
zeropoint: &mut i32
) -> Result<()>
fn get_scale_zeropoint( &self, scale: &mut f32, zeropoint: &mut i32 ) -> Result<()>
Returns scale and zeropoint of layers Read more
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>
source§impl PaddingLayerTrait for PaddingLayer
impl PaddingLayerTrait for PaddingLayer
fn as_raw_mut_PaddingLayer(&mut self) -> *mut c_void
source§impl PaddingLayerTraitConst for PaddingLayer
impl PaddingLayerTraitConst for PaddingLayer
fn as_raw_PaddingLayer(&self) -> *const c_void
source§impl TryFrom<Layer> for PaddingLayer
impl TryFrom<Layer> for PaddingLayer
impl Send for PaddingLayer
Auto Trait Implementations§
impl Freeze for PaddingLayer
impl RefUnwindSafe for PaddingLayer
impl !Sync for PaddingLayer
impl Unpin for PaddingLayer
impl UnwindSafe for PaddingLayer
Blanket Implementations§
source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
source§impl<Mat> ModifyInplace for Matwhere
Mat: Boxed,
impl<Mat> ModifyInplace for Matwhere
Mat: Boxed,
source§unsafe fn modify_inplace<Res>(
&mut self,
f: impl FnOnce(&Mat, &mut Mat) -> Res
) -> Res
unsafe fn modify_inplace<Res>( &mut self, f: impl FnOnce(&Mat, &mut Mat) -> Res ) -> Res
Helper function to call OpenCV functions that allow in-place modification of a
Mat
or another similar object. By passing
a mutable reference to the Mat
to this function your closure will get called with the read reference and a write references
to the same Mat
. This is of course unsafe as it breaks the Rust aliasing rules, but it might be useful for some performance
sensitive operations. One example of an OpenCV function that allows such in-place modification is imgproc::threshold
. Read more