Struct opencv::features2d::SIFT

pub struct SIFT { /* fields omitted */ }

Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) algorithm by D. Lowe Lowe04 .

Implementations

impl SIFT

pub fn as_raw_SIFT(&self) -> *const c_void

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

impl SIFT

pub fn create(
    nfeatures: i32,
    n_octave_layers: i32,
    contrast_threshold: f64,
    edge_threshold: f64,
    sigma: f64
) -> Result<Ptr<SIFT>>

Parameters

• nfeatures: The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)

• nOctaveLayers: The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.

• contrastThreshold: The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.

Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.

• edgeThreshold: The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).

• sigma: The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.

C++ default parameters

• nfeatures: 0
• n_octave_layers: 3
• contrast_threshold: 0.04
• edge_threshold: 10
• sigma: 1.6

pub fn create_1(
    nfeatures: i32,
    n_octave_layers: i32,
    contrast_threshold: f64,
    edge_threshold: f64,
    sigma: f64,
    descriptor_type: i32
) -> Result<Ptr<SIFT>>

Create SIFT with specified descriptorType.

Parameters

• nfeatures: The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)

• nOctaveLayers: The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.

• contrastThreshold: The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.

Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.

• edgeThreshold: The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).

• sigma: The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.

• descriptorType: The type of descriptors. Only CV_32F and CV_8U are supported.

Trait Implementations

impl AlgorithmTrait for SIFT

pub fn as_raw_Algorithm(&self) -> *const c_void

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

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

Clears the algorithm state

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

Stores algorithm parameters in a file storage

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

simplified API for language bindings Stores algorithm parameters in a file storage

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

Reads algorithm parameters from a file storage

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

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

pub 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).

pub 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 SIFT

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

Wrap the specified raw pointer

pub fn into_raw(self) -> *mut c_void

Return an the underlying raw pointer while consuming this wrapper.

pub fn as_raw(&self) -> *const c_void

Return the underlying raw pointer.

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

Return the underlying mutable raw pointer

impl Drop for SIFT

pub fn drop(&mut self)

Executes the destructor for this type.

impl Feature2DTrait for SIFT

pub fn as_raw_Feature2D(&self) -> *const c_void

pub fn as_raw_mut_Feature2D(&mut self) -> *mut c_void

pub fn detect(
    &mut self,
    image: &dyn ToInputArray,
    keypoints: &mut Vector<KeyPoint>,
    mask: &dyn ToInputArray
) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

pub fn detect_multiple(
    &mut self,
    images: &dyn ToInputArray,
    keypoints: &mut Vector<Vector<KeyPoint>>,
    masks: &dyn ToInputArray
) -> Result<()>

Detects keypoints in an image (first variant) or image set (second variant).

pub fn compute(
    &mut self,
    image: &dyn ToInputArray,
    keypoints: &mut Vector<KeyPoint>,
    descriptors: &mut dyn ToOutputArray
) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

pub fn compute_multiple(
    &mut self,
    images: &dyn ToInputArray,
    keypoints: &mut Vector<Vector<KeyPoint>>,
    descriptors: &mut dyn ToOutputArray
) -> Result<()>

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

pub fn detect_and_compute(
    &mut self,
    image: &dyn ToInputArray,
    mask: &dyn ToInputArray,
    keypoints: &mut Vector<KeyPoint>,
    descriptors: &mut dyn ToOutputArray,
    use_provided_keypoints: bool
) -> Result<()>

Detects keypoints and computes the descriptors

pub fn descriptor_size(&self) -> Result<i32>

pub fn descriptor_type(&self) -> Result<i32>

pub fn default_norm(&self) -> Result<i32>

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

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

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

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

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

Return true if detector object is empty

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

pub fn write_2(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

C++ default parameters

impl SIFTTrait for SIFT

pub fn as_raw_SIFT(&self) -> *const c_void

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

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

impl Send for SIFT