Struct KNearest 

pub struct KNearest { /* private fields */ }

The class implements K-Nearest Neighbors model

See also

[ml_intro_knn]

Implementations

impl KNearest

pub fn create() -> Result<Ptr<KNearest>>

Creates the empty model

The static method creates empty %KNearest classifier. It should be then trained using StatModel::train method.

pub fn load(filepath: &str) -> Result<Ptr<KNearest>>

Loads and creates a serialized knearest from a file

Use KNearest::save to serialize and store an KNearest to disk. Load the KNearest from this file again, by calling this function with the path to the file.

Parameters

• filepath: path to serialized KNearest

Trait Implementations

impl AlgorithmTrait for KNearest

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

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

Clears the algorithm state

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

Reads algorithm parameters from a file storage

impl AlgorithmTraitConst for KNearest

fn as_raw_Algorithm(&self) -> *const c_void

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

Stores algorithm parameters in a file storage

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

Stores algorithm parameters in a file storage

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 KNearest

unsafe fn from_raw(ptr: <KNearest as OpenCVFromExtern>::ExternReceive) -> Self

Wrap the specified raw pointer

fn into_raw(self) -> <KNearest as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying raw pointer while consuming this wrapper.

fn as_raw(&self) -> <KNearest as OpenCVTypeExternContainer>::ExternSend

Return the underlying raw pointer.

fn as_raw_mut( &mut self, ) -> <KNearest as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying mutable raw pointer

impl Debug for KNearest

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

Formats the value using the given formatter.

impl Drop for KNearest

fn drop(&mut self)

Executes the destructor for this type.

fn pin_drop(self: Pin<&mut Self>)

🔬This is a nightly-only experimental API. (pin_ergonomics)

Execute the destructor for this type, but different to Drop::drop, it requires self to be pinned.

impl From<KNearest> for Algorithm

fn from(s: KNearest) -> Self

Converts to this type from the input type.

impl From<KNearest> for StatModel

fn from(s: KNearest) -> Self

Converts to this type from the input type.

impl KNearestTrait for KNearest

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

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

Default number of neighbors to use in predict method.

fn set_is_classifier(&mut self, val: bool) -> Result<()>

Whether classification or regression model should be trained.

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

Parameter for KDTree implementation.

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

%Algorithm type, one of KNearest::Types.

impl KNearestTraitConst for KNearest

fn as_raw_KNearest(&self) -> *const c_void

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

Default number of neighbors to use in predict method.

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

Whether classification or regression model should be trained.

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

Parameter for KDTree implementation.

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

%Algorithm type, one of KNearest::Types.

fn find_nearest( &self, samples: &impl ToInputArray, k: i32, results: &mut impl ToOutputArray, neighbor_responses: &mut impl ToOutputArray, dist: &mut impl ToOutputArray, ) -> Result<f32>

Finds the neighbors and predicts responses for input vectors.

fn find_nearest_def( &self, samples: &impl ToInputArray, k: i32, results: &mut impl ToOutputArray, ) -> Result<f32>

Finds the neighbors and predicts responses for input vectors.

impl Send for KNearest

impl StatModelTrait for KNearest

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

fn train_with_data( &mut self, train_data: &Ptr<TrainData>, flags: i32, ) -> Result<bool>

Trains the statistical model

fn train_with_data_def(&mut self, train_data: &Ptr<TrainData>) -> Result<bool>

Trains the statistical model

fn train( &mut self, samples: &impl ToInputArray, layout: i32, responses: &impl ToInputArray, ) -> Result<bool>

Trains the statistical model

impl StatModelTraitConst for KNearest

fn as_raw_StatModel(&self) -> *const c_void

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

Returns the number of variables in training samples

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

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

Returns true if the model is trained

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

Returns true if the model is classifier

fn calc_error( &self, data: &Ptr<TrainData>, test: bool, resp: &mut impl ToOutputArray, ) -> Result<f32>

Computes error on the training or test dataset

fn predict( &self, samples: &impl ToInputArray, results: &mut impl ToOutputArray, flags: i32, ) -> Result<f32>

Predicts response(s) for the provided sample(s)

fn predict_def(&self, samples: &impl ToInputArray) -> Result<f32>

Predicts response(s) for the provided sample(s)

impl TryFrom<StatModel> for KNearest

type Error = Error

The type returned in the event of a conversion error.

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

Performs the conversion.