Struct TEBLID

pub struct TEBLID { /* private fields */ }

Class implementing TEBLID (Triplet-based Efficient Binary Local Image Descriptor), described in Suarez2021TEBLID.

TEBLID stands for Triplet-based Efficient Binary Local Image Descriptor, although originally it was called BAD \cite Suarez2021TEBLID. It is an improvement over BEBLID \cite Suarez2020BEBLID, that uses triplet loss, hard negative mining, and anchor swap to improve the image matching results. It is able to describe keypoints from any detector just by changing the scale_factor parameter. TEBLID is as efficient as ORB, BEBLID or BRISK, but the triplet-based training objective selected more discriminative features that explain the accuracy gain. It is also more compact than BEBLID, when running the AKAZE example with 10000 keypoints detected by ORB, BEBLID obtains 561 inliers (75%) with 512 bits, whereas TEBLID obtains 621 (75.2%) with 256 bits. ORB obtains only 493 inliers (63%).

If you find this code useful, please add a reference to the following paper:

Iago Suárez, José M. Buenaposada, and Luis Baumela. Revisiting Binary Local Image Description for Resource Limited Devices. IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 8317-8324, Oct. 2021.

The descriptor was trained in Liberty split of the UBC datasets \cite winder2007learning .

Implementations

impl TEBLID

pub fn create(scale_factor: f32, n_bits: i32) -> Result<Ptr<TEBLID>>

Creates the TEBLID descriptor.

Parameters

• scale_factor: Adjust the sampling window around detected keypoints:

• 1.00f should be the scale for ORB keypoints
• 6.75f should be the scale for SIFT detected keypoints
• 6.25f is default and fits for KAZE, SURF detected keypoints
• 5.00f should be the scale for AKAZE, MSD, AGAST, FAST, BRISK keypoints

• n_bits: Determine the number of bits in the descriptor. Should be either TEBLID::SIZE_256_BITS or TEBLID::SIZE_512_BITS.

C++ default parameters

• n_bits: TEBLID::SIZE_256_BITS

pub fn create_def(scale_factor: f32) -> Result<Ptr<TEBLID>>

Creates the TEBLID descriptor.

Parameters

• scale_factor: Adjust the sampling window around detected keypoints:

• 1.00f should be the scale for ORB keypoints
• 6.75f should be the scale for SIFT detected keypoints
• 6.25f is default and fits for KAZE, SURF detected keypoints
• 5.00f should be the scale for AKAZE, MSD, AGAST, FAST, BRISK keypoints

• n_bits: Determine the number of bits in the descriptor. Should be either TEBLID::SIZE_256_BITS or TEBLID::SIZE_512_BITS.

Note

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

• n_bits: TEBLID::SIZE_256_BITS

Trait Implementations

impl AlgorithmTrait for TEBLID

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 TEBLID

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 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 AlgorithmTraitConst::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 TEBLID

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

Wrap the specified raw pointer

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

Return the underlying raw pointer while consuming this wrapper.

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

Return the underlying raw pointer.

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

Return the underlying mutable raw pointer

impl Debug for TEBLID

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

Formats the value using the given formatter.

impl Default for TEBLID

fn default() -> Self

Forwards to infallible Self::default()

impl Drop for TEBLID

fn drop(&mut self)

Executes the destructor for this type.

impl Feature2DTrait for TEBLID

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

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).

fn detect_def( &mut self, image: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, ) -> Result<()>

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

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).

fn detect_multiple_def( &mut self, images: &impl ToInputArray, keypoints: &mut Vector<Vector<KeyPoint>>, ) -> Result<()>

@overload

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).

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).

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

fn detect_and_compute_def( &mut self, image: &impl ToInputArray, mask: &impl ToInputArray, keypoints: &mut Vector<KeyPoint>, descriptors: &mut impl ToOutputArray, ) -> Result<()>

Detects keypoints and computes the descriptors

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

fn read_from_node(&mut self, unnamed: &impl FileNodeTraitConst) -> Result<()>

impl Feature2DTraitConst for TEBLID

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_to_storage(&self, unnamed: &mut impl FileStorageTrait) -> Result<()>

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

Return true if detector object is empty

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

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

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

impl From<TEBLID> for Algorithm

fn from(s: TEBLID) -> Self

Converts to this type from the input type.

impl From<TEBLID> for Feature2D

fn from(s: TEBLID) -> Self

Converts to this type from the input type.

impl TEBLIDTrait for TEBLID

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

impl TEBLIDTraitConst for TEBLID

fn as_raw_TEBLID(&self) -> *const c_void

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

impl Send for TEBLID