Struct opencv::text::OCRHMMDecoder

pub struct OCRHMMDecoder { /* fields omitted */ }

OCRHMMDecoder class provides an interface for OCR using Hidden Markov Models.

Note:

• (C++) An example on using OCRHMMDecoder recognition combined with scene text detection can be found at the webcam_demo sample: https://github.com/opencv/opencv_contrib/blob/master/modules/text/samples/webcam_demo.cpp

Implementations

impl OCRHMMDecoder

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

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

impl OCRHMMDecoder

pub fn create(
    classifier: Ptr<OCRHMMDecoder_ClassifierCallback>,
    vocabulary: &str,
    transition_probabilities_table: &dyn ToInputArray,
    emission_probabilities_table: &dyn ToInputArray,
    mode: i32
) -> Result<Ptr<OCRHMMDecoder>>

Creates an instance of the OCRHMMDecoder class. Initializes HMMDecoder.

Parameters

• classifier: The character classifier with built in feature extractor.

• vocabulary: The language vocabulary (chars when ascii english text). vocabulary.size() must be equal to the number of classes of the classifier.

• transition_probabilities_table: Table with transition probabilities between character pairs. cols == rows == vocabulary.size().

• emission_probabilities_table: Table with observation emission probabilities. cols == rows == vocabulary.size().

• mode: HMM Decoding algorithm. Only OCR_DECODER_VITERBI is available for the moment (http://en.wikipedia.org/wiki/Viterbi_algorithm).

C++ default parameters

• mode: OCR_DECODER_VITERBI

pub fn create_1(
    filename: &str,
    vocabulary: &str,
    transition_probabilities_table: &dyn ToInputArray,
    emission_probabilities_table: &dyn ToInputArray,
    mode: i32,
    classifier: i32
) -> Result<Ptr<OCRHMMDecoder>>

Creates an instance of the OCRHMMDecoder class. Loads and initializes HMMDecoder from the specified path

 Creates an instance of the OCRHMMDecoder class. Initializes HMMDecoder.

Parameters

• classifier: The character classifier with built in feature extractor.

• vocabulary: The language vocabulary (chars when ascii english text). vocabulary.size() must be equal to the number of classes of the classifier.

• transition_probabilities_table: Table with transition probabilities between character pairs. cols == rows == vocabulary.size().

• emission_probabilities_table: Table with observation emission probabilities. cols == rows == vocabulary.size().

• mode: HMM Decoding algorithm. Only OCR_DECODER_VITERBI is available for the moment (http://en.wikipedia.org/wiki/Viterbi_algorithm).

Overloaded parameters

C++ default parameters

• mode: OCR_DECODER_VITERBI
• classifier: OCR_KNN_CLASSIFIER

Trait Implementations

impl BaseOCR for OCRHMMDecoder

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

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

pub fn run(
    &mut self,
    image: &mut Mat,
    output_text: &mut String,
    component_rects: &mut Vector<Rect>,
    component_texts: &mut Vector<String>,
    component_confidences: &mut Vector<f32>,
    component_level: i32
) -> Result<()>

C++ default parameters

pub fn run_mask(
    &mut self,
    image: &mut Mat,
    mask: &mut Mat,
    output_text: &mut String,
    component_rects: &mut Vector<Rect>,
    component_texts: &mut Vector<String>,
    component_confidences: &mut Vector<f32>,
    component_level: i32
) -> Result<()>

C++ default parameters

impl Boxed for OCRHMMDecoder

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 Drop for OCRHMMDecoder

pub fn drop(&mut self)

Executes the destructor for this type.

impl OCRHMMDecoderTrait for OCRHMMDecoder

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

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

pub fn run_multiple(
    &mut self,
    image: &mut Mat,
    output_text: &mut String,
    component_rects: &mut Vector<Rect>,
    component_texts: &mut Vector<String>,
    component_confidences: &mut Vector<f32>,
    component_level: i32
) -> Result<()>

Recognize text using HMM.

pub fn run_multiple_mask(
    &mut self,
    image: &mut Mat,
    mask: &mut Mat,
    output_text: &mut String,
    component_rects: &mut Vector<Rect>,
    component_texts: &mut Vector<String>,
    component_confidences: &mut Vector<f32>,
    component_level: i32
) -> Result<()>

Recognize text using HMM.

pub fn run(
    &mut self,
    image: &dyn ToInputArray,
    min_confidence: i32,
    component_level: i32
) -> Result<String>

C++ default parameters

pub fn run_mask(
    &mut self,
    image: &dyn ToInputArray,
    mask: &dyn ToInputArray,
    min_confidence: i32,
    component_level: i32
) -> Result<String>

C++ default parameters

impl Send for OCRHMMDecoder