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‎docs/alphamat.rs

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@@ -4,7 +4,7 @@ pub mod alphamat {
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//!
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//! This module is dedicated to computing alpha matte of objects in images from a given input image and a greyscale trimap image that contains information about the foreground, background and unknown pixels. The unknown pixels are assumed to be a combination of foreground and background pixels. The algorithm uses a combination of multiple carefully defined pixels affinities to estimate the opacity of the foreground pixels in the unkown region.
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//!
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//! The implementation is based on [aksoy2017designing](https://docs.opencv.org/4.10.0/d0/de3/citelist.html#CITEREF_aksoy2017designing).
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//! The implementation is based on [aksoy2017designing](https://docs.opencv.org/4.11.0/d0/de3/citelist.html#CITEREF_aksoy2017designing).
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//!
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//! This module was developed by Muskaan Kularia and Sunita Nayak as a project
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//! for Google Summer of Code 2019 (GSoC 19).

‎docs/bgsegm.rs

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@@ -196,16 +196,16 @@ pub mod bgsegm {
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/// Creates an instance of BackgroundSubtractorLSBP algorithm.
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///
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/// Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at [LGuo2016](https://docs.opencv.org/4.10.0/d0/de3/citelist.html#CITEREF_LGuo2016)
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/// Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at [LGuo2016](https://docs.opencv.org/4.11.0/d0/de3/citelist.html#CITEREF_LGuo2016)
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///
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/// ## Parameters
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/// * mc: Whether to use camera motion compensation.
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/// * nSamples: Number of samples to maintain at each point of the frame.
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/// * LSBPRadius: LSBP descriptor radius.
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/// * Tlower: Lower bound for T-values. See [LGuo2016](https://docs.opencv.org/4.10.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
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/// * Tupper: Upper bound for T-values. See [LGuo2016](https://docs.opencv.org/4.10.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
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/// * Tinc: Increase step for T-values. See [LGuo2016](https://docs.opencv.org/4.10.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
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/// * Tdec: Decrease step for T-values. See [LGuo2016](https://docs.opencv.org/4.10.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
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/// * Tlower: Lower bound for T-values. See [LGuo2016](https://docs.opencv.org/4.11.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
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/// * Tupper: Upper bound for T-values. See [LGuo2016](https://docs.opencv.org/4.11.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
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/// * Tinc: Increase step for T-values. See [LGuo2016](https://docs.opencv.org/4.11.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
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/// * Tdec: Decrease step for T-values. See [LGuo2016](https://docs.opencv.org/4.11.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
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/// * Rscale: Scale coefficient for threshold values.
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/// * Rincdec: Increase/Decrease step for threshold values.
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/// * noiseRemovalThresholdFacBG: Strength of the noise removal for background points.
@@ -240,16 +240,16 @@ pub mod bgsegm {
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/// Creates an instance of BackgroundSubtractorLSBP algorithm.
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///
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/// Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at [LGuo2016](https://docs.opencv.org/4.10.0/d0/de3/citelist.html#CITEREF_LGuo2016)
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/// Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at [LGuo2016](https://docs.opencv.org/4.11.0/d0/de3/citelist.html#CITEREF_LGuo2016)
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///
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/// ## Parameters
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/// * mc: Whether to use camera motion compensation.
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/// * nSamples: Number of samples to maintain at each point of the frame.
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/// * LSBPRadius: LSBP descriptor radius.
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/// * Tlower: Lower bound for T-values. See [LGuo2016](https://docs.opencv.org/4.10.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
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/// * Tupper: Upper bound for T-values. See [LGuo2016](https://docs.opencv.org/4.10.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
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/// * Tinc: Increase step for T-values. See [LGuo2016](https://docs.opencv.org/4.10.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
252-
/// * Tdec: Decrease step for T-values. See [LGuo2016](https://docs.opencv.org/4.10.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
249+
/// * Tlower: Lower bound for T-values. See [LGuo2016](https://docs.opencv.org/4.11.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
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/// * Tupper: Upper bound for T-values. See [LGuo2016](https://docs.opencv.org/4.11.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
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/// * Tinc: Increase step for T-values. See [LGuo2016](https://docs.opencv.org/4.11.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
252+
/// * Tdec: Decrease step for T-values. See [LGuo2016](https://docs.opencv.org/4.11.0/d0/de3/citelist.html#CITEREF_LGuo2016) for details.
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/// * Rscale: Scale coefficient for threshold values.
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/// * Rincdec: Increase/Decrease step for threshold values.
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/// * noiseRemovalThresholdFacBG: Strength of the noise removal for background points.
@@ -584,6 +584,16 @@ pub mod bgsegm {
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pub trait BackgroundSubtractorGMGTraitConst: crate::video::BackgroundSubtractorTraitConst {
585585
fn as_raw_BackgroundSubtractorGMG(&self) -> *const c_void;
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587+
#[inline]
588+
fn get_background_image(&self, background_image: &mut impl ToOutputArray) -> Result<()> {
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output_array_arg!(background_image);
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return_send!(via ocvrs_return);
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unsafe { sys::cv_bgsegm_BackgroundSubtractorGMG_getBackgroundImage_const_const__OutputArrayR(self.as_raw_BackgroundSubtractorGMG(), background_image.as_raw__OutputArray(), ocvrs_return.as_mut_ptr()) };
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return_receive!(unsafe ocvrs_return => ret);
593+
let ret = ret.into_result()?;
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Ok(ret)
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}
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/// Returns total number of distinct colors to maintain in histogram.
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#[inline]
589599
fn get_max_features(&self) -> Result<i32> {
@@ -697,6 +707,53 @@ pub mod bgsegm {
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pub trait BackgroundSubtractorGMGTrait: crate::bgsegm::BackgroundSubtractorGMGTraitConst + crate::video::BackgroundSubtractorTrait {
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fn as_raw_mut_BackgroundSubtractorGMG(&mut self) -> *mut c_void;
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/// Computes a foreground mask.
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///
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/// ## Parameters
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/// * image: Next video frame of type CV_8UC(n),CV_8SC(n),CV_16UC(n),CV_16SC(n),CV_32SC(n),CV_32FC(n),CV_64FC(n), where n is 1,2,3,4.
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/// * fgmask: The output foreground mask as an 8-bit binary image.
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/// * learningRate: The value between 0 and 1 that indicates how fast the background model is
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/// learnt. Negative parameter value makes the algorithm to use some automatically chosen learning
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/// rate. 0 means that the background model is not updated at all, 1 means that the background model
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/// is completely reinitialized from the last frame.
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///
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/// ## C++ default parameters
721+
/// * learning_rate: -1
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#[inline]
723+
fn apply(&mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64) -> Result<()> {
724+
input_array_arg!(image);
725+
output_array_arg!(fgmask);
726+
return_send!(via ocvrs_return);
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unsafe { sys::cv_bgsegm_BackgroundSubtractorGMG_apply_const__InputArrayR_const__OutputArrayR_double(self.as_raw_mut_BackgroundSubtractorGMG(), image.as_raw__InputArray(), fgmask.as_raw__OutputArray(), learning_rate, ocvrs_return.as_mut_ptr()) };
728+
return_receive!(unsafe ocvrs_return => ret);
729+
let ret = ret.into_result()?;
730+
Ok(ret)
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}
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733+
/// Computes a foreground mask.
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///
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/// ## Parameters
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/// * image: Next video frame of type CV_8UC(n),CV_8SC(n),CV_16UC(n),CV_16SC(n),CV_32SC(n),CV_32FC(n),CV_64FC(n), where n is 1,2,3,4.
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/// * fgmask: The output foreground mask as an 8-bit binary image.
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/// * learningRate: The value between 0 and 1 that indicates how fast the background model is
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/// learnt. Negative parameter value makes the algorithm to use some automatically chosen learning
740+
/// rate. 0 means that the background model is not updated at all, 1 means that the background model
741+
/// is completely reinitialized from the last frame.
742+
///
743+
/// ## Note
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/// This alternative version of [BackgroundSubtractorGMGTrait::apply] function uses the following default values for its arguments:
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/// * learning_rate: -1
746+
#[inline]
747+
fn apply_def(&mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray) -> Result<()> {
748+
input_array_arg!(image);
749+
output_array_arg!(fgmask);
750+
return_send!(via ocvrs_return);
751+
unsafe { sys::cv_bgsegm_BackgroundSubtractorGMG_apply_const__InputArrayR_const__OutputArrayR(self.as_raw_mut_BackgroundSubtractorGMG(), image.as_raw__InputArray(), fgmask.as_raw__OutputArray(), ocvrs_return.as_mut_ptr()) };
752+
return_receive!(unsafe ocvrs_return => ret);
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let ret = ret.into_result()?;
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Ok(ret)
755+
}
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/// Sets total number of distinct colors to maintain in histogram.
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#[inline]
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fn set_max_features(&mut self, max_features: i32) -> Result<()> {
@@ -799,7 +856,7 @@ pub mod bgsegm {
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800857
}
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802-
/// Background Subtractor module based on the algorithm given in [Gold2012](https://docs.opencv.org/4.10.0/d0/de3/citelist.html#CITEREF_Gold2012) .
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/// Background Subtractor module based on the algorithm given in [Gold2012](https://docs.opencv.org/4.11.0/d0/de3/citelist.html#CITEREF_Gold2012) .
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///
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/// Takes a series of images and returns a sequence of mask (8UC1)
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/// images of the same size, where 255 indicates Foreground and 0 represents Background.
@@ -1027,7 +1084,7 @@ pub mod bgsegm {
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10281085
}
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/// Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at [LGuo2016](https://docs.opencv.org/4.10.0/d0/de3/citelist.html#CITEREF_LGuo2016)
1087+
/// Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at [LGuo2016](https://docs.opencv.org/4.11.0/d0/de3/citelist.html#CITEREF_LGuo2016)
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pub struct BackgroundSubtractorLSBP {
10321089
ptr: *mut c_void,
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}
@@ -1267,7 +1324,7 @@ pub mod bgsegm {
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/// Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
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///
1270-
/// The class implements the algorithm described in [KB2001](https://docs.opencv.org/4.10.0/d0/de3/citelist.html#CITEREF_KB2001) .
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/// The class implements the algorithm described in [KB2001](https://docs.opencv.org/4.11.0/d0/de3/citelist.html#CITEREF_KB2001) .
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pub struct BackgroundSubtractorMOG {
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ptr: *mut c_void,
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}

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