Struct DnnSuperResImpl

pub struct DnnSuperResImpl { /* private fields */ }

A class to upscale images via convolutional neural networks. The following four models are implemented:

• edsr
• espcn
• fsrcnn
• lapsrn

Implementations

impl DnnSuperResImpl

pub fn create() -> Result<Ptr<DnnSuperResImpl>>

Empty constructor for python

pub fn default() -> Result<DnnSuperResImpl>

pub fn new(algo: &str, scale: i32) -> Result<DnnSuperResImpl>

Constructor which immediately sets the desired model

Parameters

• algo: String containing one of the desired models:
  • edsr
  • espcn
  • fsrcnn
  • lapsrn
• scale: Integer specifying the upscale factor

Trait Implementations

impl Boxed for DnnSuperResImpl

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

Wrap the specified raw pointer

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

Return the underlying raw pointer while consuming this wrapper.

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

Return the underlying raw pointer.

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

Return the underlying mutable raw pointer

impl Debug for DnnSuperResImpl

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

Formats the value using the given formatter.

impl DnnSuperResImplTrait for DnnSuperResImpl

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

fn read_model(&mut self, path: &str) -> Result<()>

Read the model from the given path

fn read_model_1(&mut self, weights: &str, definition: &str) -> Result<()>

Read the model from the given path

fn set_model(&mut self, algo: &str, scale: i32) -> Result<()>

Set desired model

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

Set computation backend

fn set_preferable_target(&mut self, target_id: i32) -> Result<()>

Set computation target

fn upsample( &mut self, img: &impl ToInputArray, result: &mut impl ToOutputArray, ) -> Result<()>

Upsample via neural network

fn upsample_multioutput( &mut self, img: &impl ToInputArray, imgs_new: &mut Vector<Mat>, scale_factors: &Vector<i32>, node_names: &Vector<String>, ) -> Result<()>

Upsample via neural network of multiple outputs

fn get_scale(&mut self) -> Result<i32>

Returns the scale factor of the model:

fn get_algorithm(&mut self) -> Result<String>

Returns the scale factor of the model:

impl DnnSuperResImplTraitConst for DnnSuperResImpl

fn as_raw_DnnSuperResImpl(&self) -> *const c_void

impl Drop for DnnSuperResImpl

fn drop(&mut self)

Executes the destructor for this type.

impl Send for DnnSuperResImpl