Struct opencv::dnn::SegmentationModel

pub struct SegmentationModel { /* fields omitted */ }

This class represents high-level API for segmentation models

SegmentationModel allows to set params for preprocessing input image. SegmentationModel creates net from file with trained weights and config, sets preprocessing input, runs forward pass and returns the class prediction for each pixel.

Implementations

impl SegmentationModel

pub fn new(model: &str, config: &str) -> Result<SegmentationModel>

Create segmentation model from network represented in one of the supported formats. An order of @p model and @p config arguments does not matter.

Parameters

• model: Binary file contains trained weights.
• config: Text file contains network configuration.

C++ default parameters

• config: “”

pub fn new_1(network: &Net) -> Result<SegmentationModel>

Create model from deep learning network.

Parameters

• network: Net object.

Trait Implementations

impl Boxed for SegmentationModel

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

Wrap the specified raw pointer

fn into_raw(self) -> *mut c_void

Return an the underlying raw pointer while consuming this wrapper.

fn as_raw(&self) -> *const c_void

Return the underlying raw pointer.

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

Return the underlying mutable raw pointer

impl Drop for SegmentationModel

fn drop(&mut self)

Executes the destructor for this type.

impl From<SegmentationModel> for Model

fn from(s: SegmentationModel) -> Self

Performs the conversion.

impl ModelTrait for SegmentationModel

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

fn set_input_size(&mut self, size: Size) -> Result<Model>

Set input size for frame.

fn set_input_size_1(&mut self, width: i32, height: i32) -> Result<Model>

Set input size for frame.

fn set_input_mean(&mut self, mean: Scalar) -> Result<Model>

Set mean value for frame.

fn set_input_scale(&mut self, scale: f64) -> Result<Model>

Set scalefactor value for frame.

fn set_input_crop(&mut self, crop: bool) -> Result<Model>

Set flag crop for frame.

fn set_input_swap_rb(&mut self, swap_rb: bool) -> Result<Model>

Set flag swapRB for frame.

fn set_input_params(
    &mut self,
    scale: f64,
    size: Size,
    mean: Scalar,
    swap_rb: bool,
    crop: bool
) -> Result<()>

Set preprocessing parameters for frame.

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

See also

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

See also

fn get_network__1(&mut self) -> Result<Net>

impl ModelTraitConst for SegmentationModel

fn as_raw_Model(&self) -> *const c_void

fn predict(
    &self,
    frame: &dyn ToInputArray,
    outs: &mut dyn ToOutputArray
) -> Result<()>

Given the @p input frame, create input blob, run net and return the output @p blobs.

fn get_network_(&self) -> Result<Net>

impl SegmentationModelTrait for SegmentationModel

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

fn segment(
    &mut self,
    frame: &dyn ToInputArray,
    mask: &mut dyn ToOutputArray
) -> Result<()>

Given the @p input frame, create input blob, run net

impl SegmentationModelTraitConst for SegmentationModel

fn as_raw_SegmentationModel(&self) -> *const c_void

impl Send for SegmentationModel