Trait opencv::dnn::prelude::BlankLayerTrait

pub trait BlankLayerTrait: LayerTrait {
    pub fn as_raw_BlankLayer(&self) -> *const c_void;
    pub fn as_raw_mut_BlankLayer(&mut self) -> *mut c_void;
}

Partial List of Implemented Layers

This subsection of dnn module contains information about built-in layers and their descriptions.

Classes listed here, in fact, provides C++ API for creating instances of built-in layers. In addition to this way of layers instantiation, there is a more common factory API (see @ref dnnLayerFactory), it allows to create layers dynamically (by name) and register new ones. You can use both API, but factory API is less convenient for native C++ programming and basically designed for use inside importers (see @ref readNetFromCaffe(), @ref readNetFromTorch(), @ref readNetFromTensorflow()).

Built-in layers partially reproduce functionality of corresponding Caffe and Torch7 layers. In particular, the following layers and Caffe importer were tested to reproduce Caffe functionality:

• Convolution
• Deconvolution
• Pooling
• InnerProduct
• TanH, ReLU, Sigmoid, BNLL, Power, AbsVal
• Softmax
• Reshape, Flatten, Slice, Split
• LRN
• MVN
• Dropout (since it does nothing on forward pass -))

Required methods

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

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

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Implementors

impl BlankLayerTrait for BlankLayer

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

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

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