Trait opencv::dnn::prelude::TextDetectionModelTraitConst[−][src]

pub trait TextDetectionModelTraitConst: ModelTraitConst {
    fn as_raw_TextDetectionModel(&self) -> *const c_void;

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

    fn detect(
        &self, 
        frame: &dyn ToInputArray, 
        detections: &mut Vector<Vector<Point>>
    ) -> Result<()> { ... }

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

    fn detect_text_rectangles_1(
        &self, 
        frame: &dyn ToInputArray, 
        detections: &mut Vector<RotatedRect>
    ) -> Result<()> { ... }
}
Expand description

Base class for text detection networks

Required methods

Provided methods

Performs detection

Given the input @p frame, prepare network input, run network inference, post-process network output and return result detections.

Each result is quadrangle’s 4 points in this order:

  • bottom-left
  • top-left
  • top-right
  • bottom-right

Use cv::getPerspectiveTransform function to retrive image region without perspective transformations.

Note: If DL model doesn’t support that kind of output then result may be derived from detectTextRectangles() output.

Parameters
  • frame: The input image
  • detections:[out] array with detections’ quadrangles (4 points per result)
  • confidences:[out] array with detection confidences

Performs detection

Given the input @p frame, prepare network input, run network inference, post-process network output and return result detections.

Each result is quadrangle’s 4 points in this order:

  • bottom-left
  • top-left
  • top-right
  • bottom-right

Use cv::getPerspectiveTransform function to retrive image region without perspective transformations.

Note: If DL model doesn’t support that kind of output then result may be derived from detectTextRectangles() output.

Parameters
  • frame: The input image
  • detections:[out] array with detections’ quadrangles (4 points per result)
  • confidences:[out] array with detection confidences
Overloaded parameters
[src]

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

Performs detection

Given the input @p frame, prepare network input, run network inference, post-process network output and return result detections.

Each result is rotated rectangle.

Note: Result may be inaccurate in case of strong perspective transformations.

Parameters
  • frame: the input image
  • detections:[out] array with detections’ RotationRect results
  • confidences:[out] array with detection confidences
[src]

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

Performs detection

Given the input @p frame, prepare network input, run network inference, post-process network output and return result detections.

Each result is rotated rectangle.

Note: Result may be inaccurate in case of strong perspective transformations.

Parameters
  • frame: the input image
  • detections:[out] array with detections’ RotationRect results
  • confidences:[out] array with detection confidences
Overloaded parameters

Implementors