Type Definition opencv::types::PtrOfCUDA_OpticalFlowDual_TVL1

type PtrOfCUDA_OpticalFlowDual_TVL1 = Ptr<dyn CUDA_OpticalFlowDual_TVL1>;

Implementations

impl PtrOfCUDA_OpticalFlowDual_TVL1

pub fn as_raw_PtrOfCUDA_OpticalFlowDual_TVL1(&self) -> *const c_void

pub fn as_raw_mut_PtrOfCUDA_OpticalFlowDual_TVL1(&mut self) -> *mut c_void

Trait Implementations

impl AlgorithmTrait for PtrOfCUDA_OpticalFlowDual_TVL1

pub fn as_raw_Algorithm(&self) -> *const c_void

pub fn as_raw_mut_Algorithm(&mut self) -> *mut c_void

pub fn clear(&mut self) -> Result<()>

Clears the algorithm state

pub fn write(&self, fs: &mut FileStorage) -> Result<()>

Stores algorithm parameters in a file storage

pub fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

simplified API for language bindings Stores algorithm parameters in a file storage

pub fn read(&mut self, fn_: &FileNode) -> Result<()>

Reads algorithm parameters from a file storage

pub fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

pub fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

pub fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl CUDA_DenseOpticalFlow for PtrOfCUDA_OpticalFlowDual_TVL1

pub fn as_raw_CUDA_DenseOpticalFlow(&self) -> *const c_void

pub fn as_raw_mut_CUDA_DenseOpticalFlow(&mut self) -> *mut c_void

pub fn calc(
    &mut self,
    i0: &dyn ToInputArray,
    i1: &dyn ToInputArray,
    flow: &mut dyn ToInputOutputArray,
    stream: &mut Stream
) -> Result<()>

Calculates a dense optical flow.

impl CUDA_OpticalFlowDual_TVL1 for PtrOfCUDA_OpticalFlowDual_TVL1

pub fn as_raw_CUDA_OpticalFlowDual_TVL1(&self) -> *const c_void

pub fn as_raw_mut_CUDA_OpticalFlowDual_TVL1(&mut self) -> *mut c_void

pub fn get_tau(&self) -> Result<f64>

Time step of the numerical scheme.

pub fn set_tau(&mut self, tau: f64) -> Result<()>

pub fn get_lambda(&self) -> Result<f64>

Weight parameter for the data term, attachment parameter. This is the most relevant parameter, which determines the smoothness of the output. The smaller this parameter is, the smoother the solutions we obtain. It depends on the range of motions of the images, so its value should be adapted to each image sequence.

pub fn set_lambda(&mut self, lambda: f64) -> Result<()>

pub fn get_gamma(&self) -> Result<f64>

Weight parameter for (u - v)^2, tightness parameter. It serves as a link between the attachment and the regularization terms. In theory, it should have a small value in order to maintain both parts in correspondence. The method is stable for a large range of values of this parameter.

pub fn set_gamma(&mut self, gamma: f64) -> Result<()>

pub fn get_theta(&self) -> Result<f64>

parameter used for motion estimation. It adds a variable allowing for illumination variations Set this parameter to 1. if you have varying illumination. See: Chambolle et al, A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging Journal of Mathematical imaging and vision, may 2011 Vol 40 issue 1, pp 120-145

pub fn set_theta(&mut self, theta: f64) -> Result<()>

pub fn get_num_scales(&self) -> Result<i32>

Number of scales used to create the pyramid of images.

pub fn set_num_scales(&mut self, nscales: i32) -> Result<()>

pub fn get_num_warps(&self) -> Result<i32>

Number of warpings per scale. Represents the number of times that I1(x+u0) and grad( I1(x+u0) ) are computed per scale. This is a parameter that assures the stability of the method. It also affects the running time, so it is a compromise between speed and accuracy.

pub fn set_num_warps(&mut self, warps: i32) -> Result<()>

pub fn get_epsilon(&self) -> Result<f64>

Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time. A small value will yield more accurate solutions at the expense of a slower convergence.

pub fn set_epsilon(&mut self, epsilon: f64) -> Result<()>

pub fn get_num_iterations(&self) -> Result<i32>

Stopping criterion iterations number used in the numerical scheme.

pub fn set_num_iterations(&mut self, iterations: i32) -> Result<()>

pub fn get_scale_step(&self) -> Result<f64>

pub fn set_scale_step(&mut self, scale_step: f64) -> Result<()>

pub fn get_use_initial_flow(&self) -> Result<bool>

pub fn set_use_initial_flow(&mut self, use_initial_flow: bool) -> Result<()>