Struct opencv::xfeatures2d::TBMR
source · pub struct TBMR { /* private fields */ }Expand description
Class implementing the Tree Based Morse Regions (TBMR) as described in Najman2014 extended with scaled extraction ability.
Parameters
- min_area: prune areas smaller than minArea
- max_area_relative: prune areas bigger than maxArea = max_area_relative * input_image_size
- scale_factor: scale factor for scaled extraction.
- n_scales: number of applications of the scale factor (octaves).
Note: This algorithm is based on Component Tree (Min/Max) as well as MSER but uses a Morse-theory approach to extract features.
Features are ellipses (similar to MSER, however a MSER feature can never be a TBMR feature and vice versa).
Implementations§
Trait Implementations§
source§impl AffineFeature2DTrait for TBMR
impl AffineFeature2DTrait for TBMR
fn as_raw_mut_AffineFeature2D(&mut self) -> *mut c_void
source§fn detect(
&mut self,
image: &impl ToInputArray,
keypoints: &mut Vector<Elliptic_KeyPoint>,
mask: &impl ToInputArray
) -> Result<()>
fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<Elliptic_KeyPoint>, mask: &impl ToInputArray ) -> Result<()>
Detects keypoints in the image using the wrapped detector and
performs affine adaptation to augment them with their elliptic regions. Read more
source§fn detect_and_compute(
&mut self,
image: &impl ToInputArray,
mask: &impl ToInputArray,
keypoints: &mut Vector<Elliptic_KeyPoint>,
descriptors: &mut impl ToOutputArray,
use_provided_keypoints: bool
) -> Result<()>
fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<Elliptic_KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>
Detects keypoints and computes descriptors for their surrounding
regions, after warping them into circles. Read more
source§impl AffineFeature2DTraitConst for TBMR
impl AffineFeature2DTraitConst for TBMR
fn as_raw_AffineFeature2D(&self) -> *const c_void
source§impl AlgorithmTrait for TBMR
impl AlgorithmTrait for TBMR
source§impl AlgorithmTraitConst for TBMR
impl AlgorithmTraitConst for TBMR
fn as_raw_Algorithm(&self) -> *const c_void
source§fn write(&self, fs: &mut FileStorage) -> Result<()>
fn write(&self, fs: &mut FileStorage) -> Result<()>
Stores algorithm parameters in a file storage
source§fn write_1(&self, fs: &mut FileStorage, name: &str) -> Result<()>
fn write_1(&self, fs: &mut FileStorage, name: &str) -> Result<()>
Stores algorithm parameters in a file storage Read more
source§fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>
fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>
@deprecated Read more
source§fn empty(&self) -> Result<bool>
fn empty(&self) -> Result<bool>
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read
source§fn save(&self, filename: &str) -> Result<()>
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).
source§fn get_default_name(&self) -> Result<String>
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.
source§impl Boxed for TBMR
impl Boxed for TBMR
source§impl Feature2DTrait for TBMR
impl Feature2DTrait for TBMR
fn as_raw_mut_Feature2D(&mut self) -> *mut c_void
source§fn detect(
&mut self,
image: &impl ToInputArray,
keypoints: &mut Vector<KeyPoint>,
mask: &impl ToInputArray
) -> Result<()>
fn detect( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, mask: &impl ToInputArray ) -> Result<()>
Detects keypoints in an image (first variant) or image set (second variant). Read more
source§fn detect_multiple(
&mut self,
images: &impl ToInputArray,
keypoints: &mut Vector<Vector<KeyPoint>>,
masks: &impl ToInputArray
) -> Result<()>
fn detect_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, masks: &impl ToInputArray ) -> Result<()>
Detects keypoints in an image (first variant) or image set (second variant). Read more
source§fn compute(
&mut self,
image: &impl ToInputArray,
keypoints: &mut Vector<KeyPoint>,
descriptors: &mut impl ToOutputArray
) -> Result<()>
fn compute( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray ) -> Result<()>
Computes the descriptors for a set of keypoints detected in an image (first variant) or image set
(second variant). Read more
source§fn compute_multiple(
&mut self,
images: &impl ToInputArray,
keypoints: &mut Vector<Vector<KeyPoint>>,
descriptors: &mut impl ToOutputArray
) -> Result<()>
fn compute_multiple( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, descriptors: &mut impl ToOutputArray ) -> Result<()>
Computes the descriptors for a set of keypoints detected in an image (first variant) or image set
(second variant). Read more
source§fn detect_and_compute(
&mut self,
image: &impl ToInputArray,
mask: &impl ToInputArray,
keypoints: &mut Vector<KeyPoint>,
descriptors: &mut impl ToOutputArray,
use_provided_keypoints: bool
) -> Result<()>
fn detect_and_compute( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, use_provided_keypoints: bool ) -> Result<()>
Detects keypoints and computes the descriptors Read more
fn read(&mut self, file_name: &str) -> Result<()>
fn read_1(&mut self, unnamed: &FileNode) -> Result<()>
source§impl Feature2DTraitConst for TBMR
impl Feature2DTraitConst for TBMR
fn as_raw_Feature2D(&self) -> *const c_void
fn descriptor_size(&self) -> Result<i32>
fn descriptor_type(&self) -> Result<i32>
fn default_norm(&self) -> Result<i32>
fn write(&self, file_name: &str) -> Result<()>
fn write_1(&self, unnamed: &mut FileStorage) -> Result<()>
fn get_default_name(&self) -> Result<String>
fn write_2(&self, fs: &mut FileStorage, name: &str) -> Result<()>
fn write_3(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>
source§impl From<TBMR> for AffineFeature2D
impl From<TBMR> for AffineFeature2D
source§impl TBMRTrait for TBMR
impl TBMRTrait for TBMR
fn as_raw_mut_TBMR(&mut self) -> *mut c_void
fn set_min_area(&mut self, min_area: i32) -> Result<()>
fn set_max_area_relative(&mut self, max_area: f32) -> Result<()>
fn set_scale_factor(&mut self, scale_factor: f32) -> Result<()>
fn set_n_scales(&mut self, n_scales: i32) -> Result<()>
source§impl TBMRTraitConst for TBMR
impl TBMRTraitConst for TBMR
fn as_raw_TBMR(&self) -> *const c_void
fn get_min_area(&self) -> Result<i32>
fn get_max_area_relative(&self) -> Result<f32>
fn get_scale_factor(&self) -> Result<f32>
fn get_n_scales(&self) -> Result<i32>
source§impl TryFrom<AffineFeature2D> for TBMR
impl TryFrom<AffineFeature2D> for TBMR
impl Send for TBMR
Auto Trait Implementations§
Blanket Implementations§
source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere T: ?Sized,
source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more