Struct opencv::dnn::TextDetectionModel_DB

pub struct TextDetectionModel_DB { /* private fields */ }

This class represents high-level API for text detection DL networks compatible with DB model.

Related publications: liao2020real Paper: https://arxiv.org/abs/1911.08947 For more information about the hyper-parameters setting, please refer to https://github.com/MhLiao/DB

Configurable parameters:

• (float) binaryThreshold - The threshold of the binary map. It is usually set to 0.3.
• (float) polygonThreshold - The threshold of text polygons. It is usually set to 0.5, 0.6, and 0.7. Default is 0.5f
• (double) unclipRatio - The unclip ratio of the detected text region, which determines the output size. It is usually set to 2.0.
• (int) maxCandidates - The max number of the output results.

Implementations

impl TextDetectionModel_DB

pub fn default() -> Result<TextDetectionModel_DB>

pub fn new(network: &Net) -> Result<TextDetectionModel_DB>

Create text detection algorithm from deep learning network.

Parameters

• network: Net object.

pub fn new_1(model: &str, config: &str) -> Result<TextDetectionModel_DB>

Create text detection 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_def(model: &str) -> Result<TextDetectionModel_DB>

Create text detection 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.

Note

This alternative version of [new] function uses the following default values for its arguments:

• config: “”

Trait Implementations

impl Boxed for TextDetectionModel_DB

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 Clone for TextDetectionModel_DB

fn clone(&self) -> Self

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for TextDetectionModel_DB

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

Formats the value using the given formatter.

impl Drop for TextDetectionModel_DB

fn drop(&mut self)

Executes the destructor for this type.

impl From<TextDetectionModel_DB> for Model

fn from(s: TextDetectionModel_DB) -> Self

Converts to this type from the input type.

impl From<TextDetectionModel_DB> for TextDetectionModel

fn from(s: TextDetectionModel_DB) -> Self

Converts to this type from the input type.

impl ModelTrait for TextDetectionModel_DB

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

fn set(&mut self, unnamed: &Model)

fn set_1(&mut self, unnamed: Model)

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: Scalar) -> 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_input_params_def(&mut self) -> 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 TextDetectionModel_DB

fn as_raw_Model(&self) -> *const c_void

fn predict( &self, frame: &impl ToInputArray, outs: &mut impl 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 TextDetectionModelTrait for TextDetectionModel_DB

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

impl TextDetectionModelTraitConst for TextDetectionModel_DB

fn as_raw_TextDetectionModel(&self) -> *const c_void

fn detect_with_confidences( &self, frame: &impl ToInputArray, detections: &mut Vector<Vector<Point>>, confidences: &mut Vector<f32> ) -> Result<()>

Performs detection

fn detect( &self, frame: &impl ToInputArray, detections: &mut Vector<Vector<Point>> ) -> Result<()>

Performs detection

fn detect_text_rectangles( &self, frame: &impl ToInputArray, detections: &mut Vector<RotatedRect>, confidences: &mut Vector<f32> ) -> Result<()>

Performs detection

fn detect_text_rectangles_1( &self, frame: &impl ToInputArray, detections: &mut Vector<RotatedRect> ) -> Result<()>

Performs detection

impl TextDetectionModel_DBTrait for TextDetectionModel_DB

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

fn set_binary_threshold( &mut self, binary_threshold: f32 ) -> Result<TextDetectionModel_DB>

fn set_polygon_threshold( &mut self, polygon_threshold: f32 ) -> Result<TextDetectionModel_DB>

fn set_unclip_ratio( &mut self, unclip_ratio: f64 ) -> Result<TextDetectionModel_DB>

fn set_max_candidates( &mut self, max_candidates: i32 ) -> Result<TextDetectionModel_DB>

impl TextDetectionModel_DBTraitConst for TextDetectionModel_DB

fn as_raw_TextDetectionModel_DB(&self) -> *const c_void

fn get_binary_threshold(&self) -> Result<f32>

fn get_polygon_threshold(&self) -> Result<f32>

fn get_unclip_ratio(&self) -> Result<f64>

fn get_max_candidates(&self) -> Result<i32>

impl Send for TextDetectionModel_DB