Trait opencv::features2d::prelude::BOWTrainerConst [−][src]
pub trait BOWTrainerConst {
fn as_raw_BOWTrainer(&self) -> *const c_void;
fn get_descriptors(&self) -> Result<Vector<Mat>> { ... }
fn descriptors_count(&self) -> Result<i32> { ... }
fn cluster(&self) -> Result<Mat> { ... }
fn cluster_with_descriptors(&self, descriptors: &Mat) -> Result<Mat> { ... }
}Expand description
Abstract base class for training the bag of visual words vocabulary from a set of descriptors.
For details, see, for example, Visual Categorization with Bags of Keypoints by Gabriella Csurka, Christopher R. Dance, Lixin Fan, Jutta Willamowski, Cedric Bray, 2004. :
Required methods
fn as_raw_BOWTrainer(&self) -> *const c_void
Provided methods
fn get_descriptors(&self) -> Result<Vector<Mat>>
fn get_descriptors(&self) -> Result<Vector<Mat>>
Returns a training set of descriptors.
fn descriptors_count(&self) -> Result<i32>
fn descriptors_count(&self) -> Result<i32>
Returns the count of all descriptors stored in the training set.
Clusters train descriptors.
Parameters
- descriptors: Descriptors to cluster. Each row of the descriptors matrix is a descriptor. Descriptors are not added to the inner train descriptor set.
The vocabulary consists of cluster centers. So, this method returns the vocabulary. In the first variant of the method, train descriptors stored in the object are clustered. In the second variant, input descriptors are clustered.
Overloaded parameters
fn cluster_with_descriptors(&self, descriptors: &Mat) -> Result<Mat>
fn cluster_with_descriptors(&self, descriptors: &Mat) -> Result<Mat>
Clusters train descriptors.
Parameters
- descriptors: Descriptors to cluster. Each row of the descriptors matrix is a descriptor. Descriptors are not added to the inner train descriptor set.
The vocabulary consists of cluster centers. So, this method returns the vocabulary. In the first variant of the method, train descriptors stored in the object are clustered. In the second variant, input descriptors are clustered.