Struct opencv::text::OCRHMMDecoder
source · [−]pub struct OCRHMMDecoder { /* private fields */ }
Expand description
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
sourceimpl OCRHMMDecoder
impl OCRHMMDecoder
sourcepub fn create(
classifier: Ptr<OCRHMMDecoder_ClassifierCallback>,
vocabulary: &str,
transition_probabilities_table: &dyn ToInputArray,
emission_probabilities_table: &dyn ToInputArray,
mode: i32
) -> Result<Ptr<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
sourcepub fn create_from_file(
filename: &str,
vocabulary: &str,
transition_probabilities_table: &dyn ToInputArray,
emission_probabilities_table: &dyn ToInputArray,
mode: i32,
classifier: i32
) -> Result<Ptr<OCRHMMDecoder>>
pub fn create_from_file(
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
sourceimpl BaseOCR for OCRHMMDecoder
impl BaseOCR for OCRHMMDecoder
fn as_raw_mut_BaseOCR(&mut self) -> *mut c_void
sourceimpl BaseOCRConst for OCRHMMDecoder
impl BaseOCRConst for OCRHMMDecoder
fn as_raw_BaseOCR(&self) -> *const c_void
sourceimpl Boxed for OCRHMMDecoder
impl Boxed for OCRHMMDecoder
sourceimpl Drop for OCRHMMDecoder
impl Drop for OCRHMMDecoder
sourceimpl OCRHMMDecoderTrait for OCRHMMDecoder
impl OCRHMMDecoderTrait for OCRHMMDecoder
fn as_raw_mut_OCRHMMDecoder(&mut self) -> *mut c_void
sourcefn 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<()>
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. Read more
sourcefn 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<()>
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. Read more
sourcefn run(
&mut self,
image: &dyn ToInputArray,
min_confidence: i32,
component_level: i32
) -> Result<String>
fn run(
&mut self,
image: &dyn ToInputArray,
min_confidence: i32,
component_level: i32
) -> Result<String>
C++ default parameters Read more
sourcefn run_mask(
&mut self,
image: &dyn ToInputArray,
mask: &dyn ToInputArray,
min_confidence: i32,
component_level: i32
) -> Result<String>
fn run_mask(
&mut self,
image: &dyn ToInputArray,
mask: &dyn ToInputArray,
min_confidence: i32,
component_level: i32
) -> Result<String>
C++ default parameters Read more
sourceimpl OCRHMMDecoderTraitConst for OCRHMMDecoder
impl OCRHMMDecoderTraitConst for OCRHMMDecoder
fn as_raw_OCRHMMDecoder(&self) -> *const c_void
impl Send for OCRHMMDecoder
Auto Trait Implementations
impl RefUnwindSafe for OCRHMMDecoder
impl !Sync for OCRHMMDecoder
impl Unpin for OCRHMMDecoder
impl UnwindSafe for OCRHMMDecoder
Blanket Implementations
sourceimpl<T> BorrowMut<T> for T where
T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
const: unstable · sourcefn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more