Trait DetectorParametersTrait

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pub trait DetectorParametersTrait: DetectorParametersTraitConst {
Show 38 methods    // Required method
    fn as_raw_mut_DetectorParameters(&mut self) -> *mut c_void;

    // Provided methods
    fn set_adaptive_thresh_win_size_min(&mut self, val: i32) { ... }
    fn set_adaptive_thresh_win_size_max(&mut self, val: i32) { ... }
    fn set_adaptive_thresh_win_size_step(&mut self, val: i32) { ... }
    fn set_adaptive_thresh_constant(&mut self, val: f64) { ... }
    fn set_min_marker_perimeter_rate(&mut self, val: f64) { ... }
    fn set_max_marker_perimeter_rate(&mut self, val: f64) { ... }
    fn set_polygonal_approx_accuracy_rate(&mut self, val: f64) { ... }
    fn set_min_corner_distance_rate(&mut self, val: f64) { ... }
    fn set_min_distance_to_border(&mut self, val: i32) { ... }
    fn set_min_marker_distance_rate(&mut self, val: f64) { ... }
    fn set_min_group_distance(&mut self, val: f32) { ... }
    fn set_corner_refinement_method(&mut self, val: i32) { ... }
    fn set_corner_refinement_win_size(&mut self, val: i32) { ... }
    fn set_relative_corner_refinment_win_size(&mut self, val: f32) { ... }
    fn set_corner_refinement_max_iterations(&mut self, val: i32) { ... }
    fn set_corner_refinement_min_accuracy(&mut self, val: f64) { ... }
    fn set_marker_border_bits(&mut self, val: i32) { ... }
    fn set_perspective_remove_pixel_per_cell(&mut self, val: i32) { ... }
    fn set_perspective_remove_ignored_margin_per_cell(&mut self, val: f64) { ... }
    fn set_max_erroneous_bits_in_border_rate(&mut self, val: f64) { ... }
    fn set_min_otsu_std_dev(&mut self, val: f64) { ... }
    fn set_error_correction_rate(&mut self, val: f64) { ... }
    fn set_april_tag_quad_decimate(&mut self, val: f32) { ... }
    fn set_april_tag_quad_sigma(&mut self, val: f32) { ... }
    fn set_april_tag_min_cluster_pixels(&mut self, val: i32) { ... }
    fn set_april_tag_max_nmaxima(&mut self, val: i32) { ... }
    fn set_april_tag_critical_rad(&mut self, val: f32) { ... }
    fn set_april_tag_max_line_fit_mse(&mut self, val: f32) { ... }
    fn set_april_tag_min_white_black_diff(&mut self, val: i32) { ... }
    fn set_april_tag_deglitch(&mut self, val: i32) { ... }
    fn set_detect_inverted_marker(&mut self, val: bool) { ... }
    fn set_use_aruco3_detection(&mut self, val: bool) { ... }
    fn set_min_side_length_canonical_img(&mut self, val: i32) { ... }
    fn set_min_marker_length_ratio_original_img(&mut self, val: f32) { ... }
    fn read_detector_parameters(
        &mut self,
        fn_: &impl FileNodeTraitConst,
    ) -> Result<bool> { ... }
    fn write_detector_parameters(
        &mut self,
        fs: &mut impl FileStorageTrait,
        name: &str,
    ) -> Result<bool> { ... }
    fn write_detector_parameters_def(
        &mut self,
        fs: &mut impl FileStorageTrait,
    ) -> Result<bool> { ... }
}

Expand description

Mutable methods for crate::objdetect::DetectorParameters

Required Methods§

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

Provided Methods§

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fn set_adaptive_thresh_win_size_min(&mut self, val: i32)

minimum window size for adaptive thresholding before finding contours (default 3).

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fn set_adaptive_thresh_win_size_max(&mut self, val: i32)

maximum window size for adaptive thresholding before finding contours (default 23).

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fn set_adaptive_thresh_win_size_step(&mut self, val: i32)

increments from adaptiveThreshWinSizeMin to adaptiveThreshWinSizeMax during the thresholding (default 10).

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fn set_adaptive_thresh_constant(&mut self, val: f64)

constant for adaptive thresholding before finding contours (default 7)

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fn set_min_marker_perimeter_rate(&mut self, val: f64)

determine minimum perimeter for marker contour to be detected.

This is defined as a rate respect to the maximum dimension of the input image (default 0.03).

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fn set_max_marker_perimeter_rate(&mut self, val: f64)

determine maximum perimeter for marker contour to be detected.

This is defined as a rate respect to the maximum dimension of the input image (default 4.0).

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fn set_polygonal_approx_accuracy_rate(&mut self, val: f64)

minimum accuracy during the polygonal approximation process to determine which contours are squares. (default 0.03)

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fn set_min_corner_distance_rate(&mut self, val: f64)

minimum distance between corners for detected markers relative to its perimeter (default 0.05)

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fn set_min_distance_to_border(&mut self, val: i32)

minimum distance of any corner to the image border for detected markers (in pixels) (default 3)

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fn set_min_marker_distance_rate(&mut self, val: f64)

minimum average distance between the corners of the two markers to be grouped (default 0.125).

The rate is relative to the smaller perimeter of the two markers. Two markers are grouped if average distance between the corners of the two markers is less than min(MarkerPerimeter1, MarkerPerimeter2)*minMarkerDistanceRate.

default value is 0.125 because 0.125*MarkerPerimeter = (MarkerPerimeter / 4) * 0.5 = half the side of the marker.

Note: default value was changed from 0.05 after 4.8.1 release, because the filtering algorithm has been changed. Now a few candidates from the same group can be added to the list of candidates if they are far from each other.

§See also

minGroupDistance.

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fn set_min_group_distance(&mut self, val: f32)

minimum average distance between the corners of the two markers in group to add them to the list of candidates

The average distance between the corners of the two markers is calculated relative to its module size (default 0.21).

§C++ default parameters

val: 0.21f

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fn set_corner_refinement_method(&mut self, val: i32)

default value CORNER_REFINE_NONE

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fn set_corner_refinement_win_size(&mut self, val: i32)

maximum window size for the corner refinement process (in pixels) (default 5).

The window size may decrease if the ArUco marker is too small, check relativeCornerRefinmentWinSize. The final window size is calculated as: min(cornerRefinementWinSize, averageArucoModuleSize*relativeCornerRefinmentWinSize), where averageArucoModuleSize is average module size of ArUco marker in pixels. (ArUco marker is composed of black and white modules)

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fn set_relative_corner_refinment_win_size(&mut self, val: f32)

Dynamic window size for corner refinement relative to Aruco module size (default 0.3).

The final window size is calculated as: min(cornerRefinementWinSize, averageArucoModuleSize*relativeCornerRefinmentWinSize), where averageArucoModuleSize is average module size of ArUco marker in pixels. (ArUco marker is composed of black and white modules) In the case of markers located far from each other, it may be useful to increase the value of the parameter to 0.4-0.5. In the case of markers located close to each other, it may be useful to decrease the parameter value to 0.1-0.2.

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fn set_corner_refinement_max_iterations(&mut self, val: i32)

maximum number of iterations for stop criteria of the corner refinement process (default 30).

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fn set_corner_refinement_min_accuracy(&mut self, val: f64)

minimum error for the stop cristeria of the corner refinement process (default: 0.1)

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fn set_marker_border_bits(&mut self, val: i32)

number of bits of the marker border, i.e. marker border width (default 1).

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fn set_perspective_remove_pixel_per_cell(&mut self, val: i32)

number of bits (per dimension) for each cell of the marker when removing the perspective (default 4).

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fn set_perspective_remove_ignored_margin_per_cell(&mut self, val: f64)

width of the margin of pixels on each cell not considered for the determination of the cell bit.

Represents the rate respect to the total size of the cell, i.e. perspectiveRemovePixelPerCell (default 0.13)

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fn set_max_erroneous_bits_in_border_rate(&mut self, val: f64)

maximum number of accepted erroneous bits in the border (i.e. number of allowed white bits in the border).

Represented as a rate respect to the total number of bits per marker (default 0.35).

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fn set_min_otsu_std_dev(&mut self, val: f64)

minimun standard deviation in pixels values during the decodification step to apply Otsu thresholding (otherwise, all the bits are set to 0 or 1 depending on mean higher than 128 or not) (default 5.0)

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fn set_error_correction_rate(&mut self, val: f64)

error correction rate respect to the maximun error correction capability for each dictionary (default 0.6).

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fn set_april_tag_quad_decimate(&mut self, val: f32)

April :: User-configurable parameters.

Detection of quads can be done on a lower-resolution image, improving speed at a cost of pose accuracy and a slight decrease in detection rate. Decoding the binary payload is still

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fn set_april_tag_quad_sigma(&mut self, val: f32)

what Gaussian blur should be applied to the segmented image (used for quad detection?)

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fn set_april_tag_min_cluster_pixels(&mut self, val: i32)

reject quads containing too few pixels (default 5).

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fn set_april_tag_max_nmaxima(&mut self, val: i32)

how many corner candidates to consider when segmenting a group of pixels into a quad (default 10).

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fn set_april_tag_critical_rad(&mut self, val: f32)

reject quads where pairs of edges have angles that are close to straight or close to 180 degrees.

Zero means that no quads are rejected. (In radians) (default 10*PI/180)

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fn set_april_tag_max_line_fit_mse(&mut self, val: f32)

when fitting lines to the contours, what is the maximum mean squared error

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fn set_april_tag_min_white_black_diff(&mut self, val: i32)

add an extra check that the white model must be (overall) brighter than the black model.

When we build our model of black & white pixels, we add an extra check that the white model must be (overall) brighter than the black model. How much brighter? (in pixel values, [0,255]), (default 5)

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