Trait opencv::hub_prelude::TransientAreasSegmentationModule

source · 
pub trait TransientAreasSegmentationModule: AlgorithmTrait + TransientAreasSegmentationModuleConst {
    fn as_raw_mut_TransientAreasSegmentationModule(&mut self) -> *mut c_void;

    fn get_size(&mut self) -> Result<Size> { ... }
    fn setup_from_file(
        &mut self,
        segmentation_parameter_file: &str,
        apply_default_setup_on_failure: bool
    ) -> Result<()> { ... }
    fn setup_from_storage(
        &mut self,
        fs: &mut FileStorage,
        apply_default_setup_on_failure: bool
    ) -> Result<()> { ... }
    fn setup(&mut self, new_parameters: SegmentationParameters) -> Result<()> { ... }
    fn get_parameters(&mut self) -> Result<SegmentationParameters> { ... }
    fn print_setup(&mut self) -> Result<String> { ... }
    fn run(
        &mut self,
        input_to_segment: &dyn ToInputArray,
        channel_index: i32
    ) -> Result<()> { ... }
    fn get_segmentation_picture(
        &mut self,
        transient_areas: &mut dyn ToOutputArray
    ) -> Result<()> { ... }
    fn clear_all_buffers(&mut self) -> Result<()> { ... }
}
Expand description

class which provides a transient/moving areas segmentation module

perform a locally adapted segmentation by using the retina magno input data Based on Alexandre BENOIT thesis: “Le système visuel humain au secours de la vision par ordinateur”

3 spatio temporal filters are used:

  • a first one which filters the noise and local variations of the input motion energy
  • a second (more powerfull low pass spatial filter) which gives the neighborhood motion energy the segmentation consists in the comparison of these both outputs, if the local motion energy is higher to the neighborhood otion energy, then the area is considered as moving and is segmented
  • a stronger third low pass filter helps decision by providing a smooth information about the “motion context” in a wider area

Required Methods§

Provided Methods§

return the sze of the manage input and output images

try to open an XML segmentation parameters file to adjust current segmentation instance setup

  • if the xml file does not exist, then default setup is applied
  • warning, Exceptions are thrown if read XML file is not valid
Parameters
  • segmentationParameterFile: : the parameters filename
  • applyDefaultSetupOnFailure: : set to true if an error must be thrown on error
C++ default parameters
  • segmentation_parameter_file: “”
  • apply_default_setup_on_failure: true

try to open an XML segmentation parameters file to adjust current segmentation instance setup

  • if the xml file does not exist, then default setup is applied
  • warning, Exceptions are thrown if read XML file is not valid
Parameters
  • fs: : the open Filestorage which contains segmentation parameters
  • applyDefaultSetupOnFailure: : set to true if an error must be thrown on error
C++ default parameters
  • apply_default_setup_on_failure: true

try to open an XML segmentation parameters file to adjust current segmentation instance setup

  • if the xml file does not exist, then default setup is applied
  • warning, Exceptions are thrown if read XML file is not valid
Parameters
  • newParameters: : a parameters structures updated with the new target configuration

return the current parameters setup

parameters setup display method

Returns

a string which contains formatted parameters information

main processing method, get result using methods getSegmentationPicture()

Parameters
  • inputToSegment: : the image to process, it must match the instance buffer size !
  • channelIndex: : the channel to process in case of multichannel images
C++ default parameters
  • channel_index: 0

access function return the last segmentation result: a boolean picture which is resampled between 0 and 255 for a display purpose

cleans all the buffers of the instance

Implementations§

source§

impl dyn TransientAreasSegmentationModule + '_

allocator

Parameters
  • inputSize: : size of the images input to segment (output will be the same size)

Implementors§