Struct opencv::face::LBPHFaceRecognizer

pub struct LBPHFaceRecognizer { /* private fields */ }

Implementations

impl LBPHFaceRecognizer

pub fn create( radius: i32, neighbors: i32, grid_x: i32, grid_y: i32, threshold: f64 ) -> Result<Ptr<LBPHFaceRecognizer>>

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

pub fn create_def() -> Result<Ptr<LBPHFaceRecognizer>>

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.

Note

This alternative version of [create] function uses the following default values for its arguments:

• radius: 1
• neighbors: 8
• grid_x: 8
• grid_y: 8
• threshold: DBL_MAX

Trait Implementations

impl AlgorithmTrait for LBPHFaceRecognizer

fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &FileNode) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTraitConst for LBPHFaceRecognizer

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut FileStorage) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut FileStorage, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of [write_with_name] function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl Boxed for LBPHFaceRecognizer

unsafe fn from_raw(ptr: *mut c_void) -> Self

Wrap the specified raw pointer

fn into_raw(self) -> *mut c_void

Return an the underlying raw pointer while consuming this wrapper.

fn as_raw(&self) -> *const c_void

Return the underlying raw pointer.

fn as_raw_mut(&mut self) -> *mut c_void

Return the underlying mutable raw pointer

impl Debug for LBPHFaceRecognizer

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Drop for LBPHFaceRecognizer

fn drop(&mut self)

Executes the destructor for this type.

impl FaceRecognizerTrait for LBPHFaceRecognizer

fn as_raw_mut_FaceRecognizer(&mut self) -> *mut c_void

fn train( &mut self, src: &impl ToInputArray, labels: &impl ToInputArray ) -> Result<()>

Trains a FaceRecognizer with given data and associated labels.

fn update( &mut self, src: &impl ToInputArray, labels: &impl ToInputArray ) -> Result<()>

Updates a FaceRecognizer with given data and associated labels.

fn read(&mut self, filename: &str) -> Result<()>

Loads a FaceRecognizer and its model state.

fn read_1(&mut self, fn_: &FileNode) -> Result<()>

Loads a FaceRecognizer and its model state.

fn set_label_info(&mut self, label: i32, str_info: &str) -> Result<()>

Sets string info for the specified model’s label.

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

Sets threshold of model

impl FaceRecognizerTraitConst for LBPHFaceRecognizer

fn as_raw_FaceRecognizer(&self) -> *const c_void

fn predict_label(&self, src: &impl ToInputArray) -> Result<i32>

Predicts a label and associated confidence (e.g. distance) for a given input image.

fn predict( &self, src: &impl ToInputArray, label: &mut i32, confidence: &mut f64 ) -> Result<()>

Predicts a label and associated confidence (e.g. distance) for a given input image.

fn predict_collect( &self, src: &impl ToInputArray, collector: Ptr<PredictCollector> ) -> Result<()>

if implemented - send all result of prediction to collector that can be used for somehow custom result handling

fn write(&self, filename: &str) -> Result<()>

Saves a FaceRecognizer and its model state.

fn write_1(&self, fs: &mut FileStorage) -> Result<()>

Saves a FaceRecognizer and its model state.

fn empty(&self) -> Result<bool>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

fn get_label_info(&self, label: i32) -> Result<String>

Gets string information by label.

fn get_labels_by_string(&self, str: &str) -> Result<Vector<i32>>

Gets vector of labels by string.

fn get_threshold(&self) -> Result<f64>

threshold parameter accessor - required for default BestMinDist collector

impl From<LBPHFaceRecognizer> for Algorithm

fn from(s: LBPHFaceRecognizer) -> Self

Converts to this type from the input type.

impl From<LBPHFaceRecognizer> for FaceRecognizer

fn from(s: LBPHFaceRecognizer) -> Self

Converts to this type from the input type.

impl LBPHFaceRecognizerTrait for LBPHFaceRecognizer

fn as_raw_mut_LBPHFaceRecognizer(&mut self) -> *mut c_void

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

See also

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

See also

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

See also

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

See also

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

See also

impl LBPHFaceRecognizerTraitConst for LBPHFaceRecognizer

fn as_raw_LBPHFaceRecognizer(&self) -> *const c_void

fn get_grid_x(&self) -> Result<i32>

See also

fn get_grid_y(&self) -> Result<i32>

See also

fn get_radius(&self) -> Result<i32>

See also

fn get_neighbors(&self) -> Result<i32>

See also

fn get_threshold(&self) -> Result<f64>

See also

fn get_histograms(&self) -> Result<Vector<Mat>>

fn get_labels(&self) -> Result<Mat>

impl TryFrom<FaceRecognizer> for LBPHFaceRecognizer

type Error = Error

The type returned in the event of a conversion error.

fn try_from(s: FaceRecognizer) -> Result<Self>

Performs the conversion.

impl Send for LBPHFaceRecognizer