Trait opencv::prelude::OCRHMMDecoderTrait
source · pub trait OCRHMMDecoderTrait: BaseOCR + OCRHMMDecoderTraitConst {
fn as_raw_mut_OCRHMMDecoder(&mut self) -> *mut c_void;
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<()> { ... }
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<()> { ... }
fn run(
&mut self,
image: &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> { ... }
}
Required Methods§
fn as_raw_mut_OCRHMMDecoder(&mut self) -> *mut c_void
Provided Methods§
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.
Takes binary image on input and returns recognized text in the output_text parameter. Optionally provides also the Rects for individual text elements found (e.g. words), and the list of those text elements with their confidence values.
Parameters
-
image: Input binary image CV_8UC1 with a single text line (or word).
-
output_text: Output text. Most likely character sequence found by the HMM decoder.
-
component_rects: If provided the method will output a list of Rects for the individual text elements found (e.g. words).
-
component_texts: If provided the method will output a list of text strings for the recognition of individual text elements found (e.g. words).
-
component_confidences: If provided the method will output a list of confidence values for the recognition of individual text elements found (e.g. words).
-
component_level: Only OCR_LEVEL_WORD is supported.
C++ default parameters
- component_rects: NULL
- component_texts: NULL
- component_confidences: NULL
- component_level: 0
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.
Takes an image and a mask (where each connected component corresponds to a segmented character) on input and returns recognized text in the output_text parameter. Optionally provides also the Rects for individual text elements found (e.g. words), and the list of those text elements with their confidence values.
Parameters
-
image: Input image CV_8UC1 or CV_8UC3 with a single text line (or word).
-
mask: Input binary image CV_8UC1 same size as input image. Each connected component in mask corresponds to a segmented character in the input image.
-
output_text: Output text. Most likely character sequence found by the HMM decoder.
-
component_rects: If provided the method will output a list of Rects for the individual text elements found (e.g. words).
-
component_texts: If provided the method will output a list of text strings for the recognition of individual text elements found (e.g. words).
-
component_confidences: If provided the method will output a list of confidence values for the recognition of individual text elements found (e.g. words).
-
component_level: Only OCR_LEVEL_WORD is supported.
C++ default parameters
- component_rects: NULL
- component_texts: NULL
- component_confidences: NULL
- component_level: 0
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
- component_level: 0
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
- component_level: 0