Trait opencv::face::prelude::LBPHFaceRecognizer[−][src]

pub trait LBPHFaceRecognizer: FaceRecognizer + LBPHFaceRecognizerConst {
    fn as_raw_mut_LBPHFaceRecognizer(&mut self) -> *mut c_void;

    fn set_grid_x(&mut self, val: i32) -> Result<()> { ... }

    fn set_grid_y(&mut self, val: i32) -> Result<()> { ... }

    fn set_radius(&mut self, val: i32) -> Result<()> { ... }

    fn set_neighbors(&mut self, val: i32) -> Result<()> { ... }

    fn set_threshold(&mut self, val: f64) -> Result<()> { ... }
}

Required methods

Provided methods

See also

setGridX getGridX

See also

setGridY getGridY

See also

setRadius getRadius

See also

setNeighbors getNeighbors

See also

setThreshold getThreshold

Implementations

Parameters
  • radius: The radius used for building the Circular Local Binary Pattern. The greater the radius, the smoother the image but more spatial information you can get.
  • neighbors: The number of sample points to build a Circular Local Binary Pattern from. An appropriate value is to use 8 sample points. Keep in mind: the more sample points you include, the higher the computational cost.
  • grid_x: The number of cells in the horizontal direction, 8 is a common value used in publications. The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.
  • grid_y: The number of cells in the vertical direction, 8 is a common value used in publications. The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.
  • threshold: The threshold applied in the prediction. If the distance to the nearest neighbor is larger than the threshold, this method returns -1.
Notes:
  • The Circular Local Binary Patterns (used in training and prediction) expect the data given as grayscale images, use cvtColor to convert between the color spaces.
  • This model supports updating.
Model internal data:
  • radius see LBPHFaceRecognizer::create.
  • neighbors see LBPHFaceRecognizer::create.
  • grid_x see LLBPHFaceRecognizer::create.
  • grid_y see LBPHFaceRecognizer::create.
  • threshold see LBPHFaceRecognizer::create.
  • histograms Local Binary Patterns Histograms calculated from the given training data (empty if none was given).
  • labels Labels corresponding to the calculated Local Binary Patterns Histograms.
C++ default parameters
  • radius: 1
  • neighbors: 8
  • grid_x: 8
  • grid_y: 8
  • threshold: DBL_MAX

Implementors