Struct opencv::surface_matching::PPF3DDetector

pub struct PPF3DDetector { /* private fields */ }

Class, allowing the load and matching 3D models. Typical Use:

// Train a model
ppf_match_3d::PPF3DDetector detector(0.05, 0.05);
detector.trainModel(pc);
// Search the model in a given scene
vector<Pose3DPtr> results;
detector.match(pcTest, results, 1.0/5.0,0.05);

Implementations

impl PPF3DDetector

pub fn default() -> Result<PPF3DDetector>

\brief Empty constructor. Sets default arguments

pub fn new( relative_sampling_step: f64, relative_distance_step: f64, num_angles: f64 ) -> Result<PPF3DDetector>

Constructor with arguments

Parameters

• relativeSamplingStep: Sampling distance relative to the object’s diameter. Models are first sampled uniformly in order to improve efficiency. Decreasing this value leads to a denser model, and a more accurate pose estimation but the larger the model, the slower the training. Increasing the value leads to a less accurate pose computation but a smaller model and faster model generation and matching. Beware of the memory consumption when using small values.
• relativeDistanceStep: The discretization distance of the point pair distance relative to the model’s diameter. This value has a direct impact on the hashtable. Using small values would lead to too fine discretization, and thus ambiguity in the bins of hashtable. Too large values would lead to no discrimination over the feature vectors and different point pair features would be assigned to the same bin. This argument defaults to the value of RelativeSamplingStep. For noisy scenes, the value can be increased to improve the robustness of the matching against noisy points.
• numAngles: Set the discretization of the point pair orientation as the number of subdivisions of the angle. This value is the equivalent of RelativeDistanceStep for the orientations. Increasing the value increases the precision of the matching but decreases the robustness against incorrect normal directions. Decreasing the value decreases the precision of the matching but increases the robustness against incorrect normal directions. For very noisy scenes where the normal directions can not be computed accurately, the value can be set to 25 or 20.

C++ default parameters

• relative_distance_step: 0.05
• num_angles: 30

pub fn new_def(relative_sampling_step: f64) -> Result<PPF3DDetector>

Constructor with arguments

Parameters

• relativeSamplingStep: Sampling distance relative to the object’s diameter. Models are first sampled uniformly in order to improve efficiency. Decreasing this value leads to a denser model, and a more accurate pose estimation but the larger the model, the slower the training. Increasing the value leads to a less accurate pose computation but a smaller model and faster model generation and matching. Beware of the memory consumption when using small values.
• relativeDistanceStep: The discretization distance of the point pair distance relative to the model’s diameter. This value has a direct impact on the hashtable. Using small values would lead to too fine discretization, and thus ambiguity in the bins of hashtable. Too large values would lead to no discrimination over the feature vectors and different point pair features would be assigned to the same bin. This argument defaults to the value of RelativeSamplingStep. For noisy scenes, the value can be increased to improve the robustness of the matching against noisy points.
• numAngles: Set the discretization of the point pair orientation as the number of subdivisions of the angle. This value is the equivalent of RelativeDistanceStep for the orientations. Increasing the value increases the precision of the matching but decreases the robustness against incorrect normal directions. Decreasing the value decreases the precision of the matching but increases the robustness against incorrect normal directions. For very noisy scenes where the normal directions can not be computed accurately, the value can be set to 25 or 20.

Note

This alternative version of [new] function uses the following default values for its arguments:

• relative_distance_step: 0.05
• num_angles: 30

Trait Implementations

impl Boxed for PPF3DDetector

unsafe fn from_raw( ptr: <PPF3DDetector as OpenCVFromExtern>::ExternReceive ) -> Self

Wrap the specified raw pointer

fn into_raw(self) -> <PPF3DDetector as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying raw pointer while consuming this wrapper.

fn as_raw(&self) -> <PPF3DDetector as OpenCVTypeExternContainer>::ExternSend

Return the underlying raw pointer.

fn as_raw_mut( &mut self ) -> <PPF3DDetector as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying mutable raw pointer

impl Debug for PPF3DDetector

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

Formats the value using the given formatter.

impl Drop for PPF3DDetector

fn drop(&mut self)

Executes the destructor for this type.

impl PPF3DDetectorTrait for PPF3DDetector

fn as_raw_mut_PPF3DDetector(&mut self) -> *mut c_void

fn set_search_params( &mut self, position_threshold: f64, rotation_threshold: f64, use_weighted_clustering: bool ) -> Result<()>

Set the parameters for the search

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

Set the parameters for the search

fn train_model(&mut self, model: &impl MatTraitConst) -> Result<()>

\brief Trains a new model.

fn match_( &mut self, scene: &impl MatTraitConst, results: &mut Vector<Pose3DPtr>, relative_scene_sample_step: f64, relative_scene_distance: f64 ) -> Result<()>

\brief Matches a trained model across a provided scene.

fn match__def( &mut self, scene: &impl MatTraitConst, results: &mut Vector<Pose3DPtr> ) -> Result<()>

\brief Matches a trained model across a provided scene.

impl PPF3DDetectorTraitConst for PPF3DDetector

fn as_raw_PPF3DDetector(&self) -> *const c_void

impl Send for PPF3DDetector