opencv::prelude

Trait SelectiveSearchSegmentationTrait

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pub trait SelectiveSearchSegmentationTrait: AlgorithmTrait + SelectiveSearchSegmentationTraitConst {

Show 15 methods    // Required method
    fn as_raw_mut_SelectiveSearchSegmentation(&mut self) -> *mut c_void;

    // Provided methods
    fn set_base_image(&mut self, img: &impl ToInputArray) -> Result<()> { ... }
    fn switch_to_single_strategy(&mut self, k: i32, sigma: f32) -> Result<()> { ... }
    fn switch_to_single_strategy_def(&mut self) -> Result<()> { ... }
    fn switch_to_selective_search_fast(
        &mut self,
        base_k: i32,
        inc_k: i32,
        sigma: f32,
    ) -> Result<()> { ... }
    fn switch_to_selective_search_fast_def(&mut self) -> Result<()> { ... }
    fn switch_to_selective_search_quality(
        &mut self,
        base_k: i32,
        inc_k: i32,
        sigma: f32,
    ) -> Result<()> { ... }
    fn switch_to_selective_search_quality_def(&mut self) -> Result<()> { ... }
    fn add_image(&mut self, img: &impl ToInputArray) -> Result<()> { ... }
    fn clear_images(&mut self) -> Result<()> { ... }
    fn add_graph_segmentation(
        &mut self,
        g: Ptr<GraphSegmentation>,
    ) -> Result<()> { ... }
    fn clear_graph_segmentations(&mut self) -> Result<()> { ... }
    fn add_strategy(
        &mut self,
        s: Ptr<SelectiveSearchSegmentationStrategy>,
    ) -> Result<()> { ... }
    fn clear_strategies(&mut self) -> Result<()> { ... }
    fn process(&mut self, rects: &mut Vector<Rect>) -> Result<()> { ... }

}
Expand description

Mutable methods for crate::ximgproc::SelectiveSearchSegmentation

Required Methods§

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

Provided Methods§

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fn set_base_image(&mut self, img: &impl ToInputArray) -> Result<()>

Set a image used by switch* functions to initialize the class

§Parameters
  • img: The image
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fn switch_to_single_strategy(&mut self, k: i32, sigma: f32) -> Result<()>

Initialize the class with the ‘Single stragegy’ parameters describled in uijlings2013selective.

§Parameters
  • k: The k parameter for the graph segmentation
  • sigma: The sigma parameter for the graph segmentation
§C++ default parameters
  • k: 200
  • sigma: 0.8f
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fn switch_to_single_strategy_def(&mut self) -> Result<()>

Initialize the class with the ‘Single stragegy’ parameters describled in uijlings2013selective.

§Parameters
  • k: The k parameter for the graph segmentation
  • sigma: The sigma parameter for the graph segmentation
§Note

This alternative version of SelectiveSearchSegmentationTrait::switch_to_single_strategy function uses the following default values for its arguments:

  • k: 200
  • sigma: 0.8f
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fn switch_to_selective_search_fast( &mut self, base_k: i32, inc_k: i32, sigma: f32, ) -> Result<()>

Initialize the class with the ‘Selective search fast’ parameters describled in uijlings2013selective.

§Parameters
  • base_k: The k parameter for the first graph segmentation
  • inc_k: The increment of the k parameter for all graph segmentations
  • sigma: The sigma parameter for the graph segmentation
§C++ default parameters
  • base_k: 150
  • inc_k: 150
  • sigma: 0.8f
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fn switch_to_selective_search_fast_def(&mut self) -> Result<()>

Initialize the class with the ‘Selective search fast’ parameters describled in uijlings2013selective.

§Parameters
  • base_k: The k parameter for the first graph segmentation
  • inc_k: The increment of the k parameter for all graph segmentations
  • sigma: The sigma parameter for the graph segmentation
§Note

This alternative version of SelectiveSearchSegmentationTrait::switch_to_selective_search_fast function uses the following default values for its arguments:

  • base_k: 150
  • inc_k: 150
  • sigma: 0.8f
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fn switch_to_selective_search_quality( &mut self, base_k: i32, inc_k: i32, sigma: f32, ) -> Result<()>

Initialize the class with the ‘Selective search fast’ parameters describled in uijlings2013selective.

§Parameters
  • base_k: The k parameter for the first graph segmentation
  • inc_k: The increment of the k parameter for all graph segmentations
  • sigma: The sigma parameter for the graph segmentation
§C++ default parameters
  • base_k: 150
  • inc_k: 150
  • sigma: 0.8f
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fn switch_to_selective_search_quality_def(&mut self) -> Result<()>

Initialize the class with the ‘Selective search fast’ parameters describled in uijlings2013selective.

§Parameters
  • base_k: The k parameter for the first graph segmentation
  • inc_k: The increment of the k parameter for all graph segmentations
  • sigma: The sigma parameter for the graph segmentation
§Note

This alternative version of SelectiveSearchSegmentationTrait::switch_to_selective_search_quality function uses the following default values for its arguments:

  • base_k: 150
  • inc_k: 150
  • sigma: 0.8f
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fn add_image(&mut self, img: &impl ToInputArray) -> Result<()>

Add a new image in the list of images to process.

§Parameters
  • img: The image
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fn clear_images(&mut self) -> Result<()>

Clear the list of images to process

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fn add_graph_segmentation(&mut self, g: Ptr<GraphSegmentation>) -> Result<()>

Add a new graph segmentation in the list of graph segementations to process.

§Parameters
  • g: The graph segmentation
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fn clear_graph_segmentations(&mut self) -> Result<()>

Clear the list of graph segmentations to process;

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fn add_strategy( &mut self, s: Ptr<SelectiveSearchSegmentationStrategy>, ) -> Result<()>

Add a new strategy in the list of strategy to process.

§Parameters
  • s: The strategy
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fn clear_strategies(&mut self) -> Result<()>

Clear the list of strategy to process;

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fn process(&mut self, rects: &mut Vector<Rect>) -> Result<()>

Based on all images, graph segmentations and stragies, computes all possible rects and return them

§Parameters
  • rects: The list of rects. The first ones are more relevents than the lasts ones.

Object Safety§

This trait is not object safe.

Implementors§