Struct opencv::features2d::BFMatcher

pub struct BFMatcher { /* fields omitted */ }

Brute-force descriptor matcher.

For each descriptor in the first set, this matcher finds the closest descriptor in the second set by trying each one. This descriptor matcher supports masking permissible matches of descriptor sets.

Methods

impl BFMatcher

pub fn as_raw_BFMatcher(&self) -> *mut c_void

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

impl BFMatcher

pub fn new(norm_type: i32, cross_check: bool) -> Result<BFMatcher>

Brute-force matcher constructor (obsolete). Please use BFMatcher.create()

C++ default parameters

• norm_type: NORM_L2
• cross_check: false

pub fn is_mask_supported(&self) -> Result<bool>

pub fn create(norm_type: i32, cross_check: bool) -> Result<PtrOfBFMatcher>

Brute-force matcher create method.

Parameters

• normType: One of NORM_L1, NORM_L2, NORM_HAMMING, NORM_HAMMING2. L1 and L2 norms are preferable choices for SIFT and SURF descriptors, NORM_HAMMING should be used with ORB, BRISK and BRIEF, NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 (see ORB::ORB constructor description).
• crossCheck: If it is false, this is will be default BFMatcher behaviour when it finds the k nearest neighbors for each query descriptor. If crossCheck==true, then the knnMatch() method with k=1 will only return pairs (i,j) such that for i-th query descriptor the j-th descriptor in the matcher's collection is the nearest and vice versa, i.e. the BFMatcher will only return consistent pairs. Such technique usually produces best results with minimal number of outliers when there are enough matches. This is alternative to the ratio test, used by D. Lowe in SIFT paper.

C++ default parameters

• norm_type: NORM_L2
• cross_check: false

pub fn clone(&self, empty_train_data: bool) -> Result<PtrOfDescriptorMatcher>

C++ default parameters

• empty_train_data: false

Trait Implementations

impl AlgorithmTrait for BFMatcher

fn as_raw_Algorithm(&self) -> *mut c_void

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

Clears the algorithm state

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

Stores algorithm parameters in a file storage

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

simplified API for language bindings

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

Reads algorithm parameters from 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 DescriptorMatcher for BFMatcher

fn as_raw_DescriptorMatcher(&self) -> *mut c_void

fn add(&mut self, descriptors: &dyn ToInputArray) -> Result<()>

Adds descriptors to train a CPU(trainDescCollectionis) or GPU(utrainDescCollectionis) descriptor collection.

fn get_train_descriptors(&self) -> Result<VectorOfMat>

Returns a constant link to the train descriptor collection trainDescCollection .

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

Clears the train descriptor collections.

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

Returns true if there are no train descriptors in the both collections.

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

Returns true if the descriptor matcher supports masking permissible matches.

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

Trains a descriptor matcher

fn train_matches(
    &self,
    query_descriptors: &dyn ToInputArray,
    train_descriptors: &dyn ToInputArray,
    matches: &mut VectorOfDMatch,
    mask: &dyn ToInputArray
) -> Result<()>

Finds the best match for each descriptor from a query set.

fn knn_train_matches(
    &self,
    query_descriptors: &dyn ToInputArray,
    train_descriptors: &dyn ToInputArray,
    matches: &mut VectorOfVectorOfDMatch,
    k: i32,
    mask: &dyn ToInputArray,
    compact_result: bool
) -> Result<()>

Finds the k best matches for each descriptor from a query set.

fn train_radius_matches(
    &self,
    query_descriptors: &dyn ToInputArray,
    train_descriptors: &dyn ToInputArray,
    matches: &mut VectorOfVectorOfDMatch,
    max_distance: f32,
    mask: &dyn ToInputArray,
    compact_result: bool
) -> Result<()>

For each query descriptor, finds the training descriptors not farther than the specified distance.

fn matches(
    &mut self,
    query_descriptors: &dyn ToInputArray,
    matches: &mut VectorOfDMatch,
    masks: &dyn ToInputArray
) -> Result<()>

Parameters * queryDescriptors: Query set of descriptors. * matches: Matches. If a query descriptor is masked out in mask , no match is added for this descriptor. So, matches size may be smaller than the query descriptors count. * masks: Set of masks. Each masks[i] specifies permissible matches between the input query descriptors and stored train descriptors from the i-th image trainDescCollection[i].

fn knn_matches(
    &mut self,
    query_descriptors: &dyn ToInputArray,
    matches: &mut VectorOfVectorOfDMatch,
    k: i32,
    masks: &dyn ToInputArray,
    compact_result: bool
) -> Result<()>

Parameters * queryDescriptors: Query set of descriptors. * matches: Matches. Each matches[i] is k or less matches for the same query descriptor. * k: Count of best matches found per each query descriptor or less if a query descriptor has less than k possible matches in total. * masks: Set of masks. Each masks[i] specifies permissible matches between the input query descriptors and stored train descriptors from the i-th image trainDescCollection[i]. * compactResult: Parameter used when the mask (or masks) is not empty. If compactResult is false, the matches vector has the same size as queryDescriptors rows. If compactResult is true, the matches vector does not contain matches for fully masked-out query descriptors.

fn radius_matches(
    &mut self,
    query_descriptors: &dyn ToInputArray,
    matches: &mut VectorOfVectorOfDMatch,
    max_distance: f32,
    masks: &dyn ToInputArray,
    compact_result: bool
) -> Result<()>

Parameters * queryDescriptors: Query set of descriptors. * matches: Found matches. * maxDistance: Threshold for the distance between matched descriptors. Distance means here metric distance (e.g. Hamming distance), not the distance between coordinates (which is measured in Pixels)! * masks: Set of masks. Each masks[i] specifies permissible matches between the input query descriptors and stored train descriptors from the i-th image trainDescCollection[i]. * compactResult: Parameter used when the mask (or masks) is not empty. If compactResult is false, the matches vector has the same size as queryDescriptors rows. If compactResult is true, the matches vector does not contain matches for fully masked-out query descriptors.

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

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

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

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

fn clone(&self, empty_train_data: bool) -> Result<PtrOfDescriptorMatcher>

Clones the matcher.

fn write_2(&self, fs: &PtrOfFileStorage, name: &str) -> Result<()>

C++ default parameters * name: String()

impl Drop for BFMatcher

fn drop(&mut self)

Executes the destructor for this type.

impl Send for BFMatcher