[−][src]Trait opencv::prelude::ObjectnessBINGTrait
the Binarized normed gradients algorithm from BING
Required methods
pub fn as_raw_ObjectnessBING(&self) -> *const c_void
[src]
pub fn as_raw_mut_ObjectnessBING(&mut self) -> *mut c_void
[src]
Provided methods
pub fn compute_saliency(
&mut self,
image: &dyn ToInputArray,
saliency_map: &mut dyn ToOutputArray
) -> Result<bool>
[src]
&mut self,
image: &dyn ToInputArray,
saliency_map: &mut dyn ToOutputArray
) -> Result<bool>
pub fn read(&mut self) -> Result<()>
[src]
pub fn write(&self) -> Result<()>
[src]
pub fn getobjectness_values(&mut self) -> Result<Vector<f32>>
[src]
Return the list of the rectangles' objectness value,
in the same order as the vector<Vec4i> objectnessBoundingBox returned by the algorithm (in computeSaliencyImpl function). The bigger value these scores are, it is more likely to be an object window.
pub fn set_training_path(&mut self, training_path: &str) -> Result<()>
[src]
This is a utility function that allows to set the correct path from which the algorithm will load the trained model.
Parameters
- trainingPath: trained model path
pub fn set_bb_res_dir(&mut self, results_dir: &str) -> Result<()>
[src]
This is a utility function that allows to set an arbitrary path in which the algorithm will save the optional results
(ie writing on file the total number and the list of rectangles returned by objectess, one for each row).
Parameters
- resultsDir: results' folder path