Trait BackgroundSubtractorGMGTrait

Source

pub trait BackgroundSubtractorGMGTrait: BackgroundSubtractorGMGTraitConst + BackgroundSubtractorTrait {
Show 13 methods    // Required method
    fn as_raw_mut_BackgroundSubtractorGMG(&mut self) -> *mut c_void;

    // Provided methods
    fn apply(
        &mut self,
        image: &impl ToInputArray,
        fgmask: &mut impl ToOutputArray,
        learning_rate: f64,
    ) -> Result<()> { ... }
    fn apply_def(
        &mut self,
        image: &impl ToInputArray,
        fgmask: &mut impl ToOutputArray,
    ) -> Result<()> { ... }
    fn set_max_features(&mut self, max_features: i32) -> Result<()> { ... }
    fn set_default_learning_rate(&mut self, lr: f64) -> Result<()> { ... }
    fn set_num_frames(&mut self, nframes: i32) -> Result<()> { ... }
    fn set_quantization_levels(&mut self, nlevels: i32) -> Result<()> { ... }
    fn set_background_prior(&mut self, bgprior: f64) -> Result<()> { ... }
    fn set_smoothing_radius(&mut self, radius: i32) -> Result<()> { ... }
    fn set_decision_threshold(&mut self, thresh: f64) -> Result<()> { ... }
    fn set_update_background_model(&mut self, update: bool) -> Result<()> { ... }
    fn set_min_val(&mut self, val: f64) -> Result<()> { ... }
    fn set_max_val(&mut self, val: f64) -> Result<()> { ... }
}

Expand description

Mutable methods for crate::bgsegm::BackgroundSubtractorGMG

Required Methods§

Source

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

Provided Methods§

Source

fn apply( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, learning_rate: f64, ) -> Result<()>

Computes a foreground mask.

§Parameters

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.
fgmask: The output foreground mask as an 8-bit binary image.
learningRate: The value between 0 and 1 that indicates how fast the background model is learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate. 0 means that the background model is not updated at all, 1 means that the background model is completely reinitialized from the last frame.

§C++ default parameters

learning_rate: -1

Source

fn apply_def( &mut self, image: &impl ToInputArray, fgmask: &mut impl ToOutputArray, ) -> Result<()>

Computes a foreground mask.

§Parameters

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.
fgmask: The output foreground mask as an 8-bit binary image.
learningRate: The value between 0 and 1 that indicates how fast the background model is learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate. 0 means that the background model is not updated at all, 1 means that the background model is completely reinitialized from the last frame.