Struct opencv::cudaoptflow::CUDA_OpticalFlowDual_TVL1

pub struct CUDA_OpticalFlowDual_TVL1 { /* private fields */ }

Implementation of the Zach, Pock and Bischof Dual TV-L1 Optical Flow method.

Note: C. Zach, T. Pock and H. Bischof, “A Duality Based Approach for Realtime TV-L1 Optical Flow”.

Note: Javier Sanchez, Enric Meinhardt-Llopis and Gabriele Facciolo. “TV-L1 Optical Flow Estimation”.

Implementations

impl CUDA_OpticalFlowDual_TVL1

pub fn create( tau: f64, lambda: f64, theta: f64, nscales: i32, warps: i32, epsilon: f64, iterations: i32, scale_step: f64, gamma: f64, use_initial_flow: bool ) -> Result<Ptr<CUDA_OpticalFlowDual_TVL1>>

C++ default parameters

• tau: 0.25
• lambda: 0.15
• theta: 0.3
• nscales: 5
• warps: 5
• epsilon: 0.01
• iterations: 300
• scale_step: 0.8
• gamma: 0.0
• use_initial_flow: false

pub fn create_def() -> Result<Ptr<CUDA_OpticalFlowDual_TVL1>>

Note

This alternative version of CUDA_OpticalFlowDual_TVL1::create function uses the following default values for its arguments:

• tau: 0.25
• lambda: 0.15
• theta: 0.3
• nscales: 5
• warps: 5
• epsilon: 0.01
• iterations: 300
• scale_step: 0.8
• gamma: 0.0
• use_initial_flow: false

Trait Implementations

impl AlgorithmTrait for CUDA_OpticalFlowDual_TVL1

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

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

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTraitConst for CUDA_OpticalFlowDual_TVL1

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

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

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

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

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

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).

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 Boxed for CUDA_OpticalFlowDual_TVL1

unsafe fn from_raw( ptr: <CUDA_OpticalFlowDual_TVL1 as OpenCVFromExtern>::ExternReceive ) -> Self

Wrap the specified raw pointer

fn into_raw( self ) -> <CUDA_OpticalFlowDual_TVL1 as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying raw pointer while consuming this wrapper.

fn as_raw( &self ) -> <CUDA_OpticalFlowDual_TVL1 as OpenCVTypeExternContainer>::ExternSend

Return the underlying raw pointer.

fn as_raw_mut( &mut self ) -> <CUDA_OpticalFlowDual_TVL1 as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying mutable raw pointer

impl CUDA_DenseOpticalFlowTrait for CUDA_OpticalFlowDual_TVL1

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

fn calc( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray, stream: &mut impl StreamTrait ) -> Result<()>

Calculates a dense optical flow.

fn calc_def( &mut self, i0: &impl ToInputArray, i1: &impl ToInputArray, flow: &mut impl ToInputOutputArray ) -> Result<()>

Calculates a dense optical flow.

impl CUDA_DenseOpticalFlowTraitConst for CUDA_OpticalFlowDual_TVL1

fn as_raw_CUDA_DenseOpticalFlow(&self) -> *const c_void

impl CUDA_OpticalFlowDual_TVL1Trait for CUDA_OpticalFlowDual_TVL1

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

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

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

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

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

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

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

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

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

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

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

impl CUDA_OpticalFlowDual_TVL1TraitConst for CUDA_OpticalFlowDual_TVL1

fn as_raw_CUDA_OpticalFlowDual_TVL1(&self) -> *const c_void

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

Time step of the numerical scheme.

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.

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.

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

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

Number of scales used to create the pyramid of images.

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.

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.

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

Stopping criterion iterations number used in the numerical scheme.

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

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

impl Debug for CUDA_OpticalFlowDual_TVL1

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Drop for CUDA_OpticalFlowDual_TVL1

fn drop(&mut self)

Executes the destructor for this type.

impl From<CUDA_OpticalFlowDual_TVL1> for Algorithm

fn from(s: CUDA_OpticalFlowDual_TVL1) -> Self

Converts to this type from the input type.

impl From<CUDA_OpticalFlowDual_TVL1> for CUDA_DenseOpticalFlow

fn from(s: CUDA_OpticalFlowDual_TVL1) -> Self

Converts to this type from the input type.

impl TryFrom<CUDA_DenseOpticalFlow> for CUDA_OpticalFlowDual_TVL1

type Error = Error

The type returned in the event of a conversion error.

fn try_from(s: CUDA_DenseOpticalFlow) -> Result<Self>

Performs the conversion.

impl Send for CUDA_OpticalFlowDual_TVL1