Struct opencv::dnn_superres::DnnSuperResImpl

pub struct DnnSuperResImpl { /* fields omitted */ }

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

• edsr
• espcn
• fsrcnn
• lapsrn

Implementations

impl DnnSuperResImpl

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

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

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

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

Wrap the specified raw pointer

pub fn into_raw(self) -> *mut c_void

Return an the underlying raw pointer while consuming this wrapper.

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

Return the underlying raw pointer.

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

Return the underlying mutable raw pointer

impl DnnSuperResImplTrait for DnnSuperResImpl

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

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

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

Read the model from the given path

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

Read the model from the given path

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

Set desired model

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

Set computation backend

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

Set computation target

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

Upsample via neural network

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

Upsample via neural network of multiple outputs

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

Returns the scale factor of the model:

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

Returns the scale factor of the model:

impl Drop for DnnSuperResImpl

pub fn drop(&mut self)

Executes the destructor for this type.

impl Send for DnnSuperResImpl