Struct opencv::optflow::DualTVL1OpticalFlow

pub struct DualTVL1OpticalFlow { /* private fields */ }

“Dual TV L1” Optical Flow Algorithm.

The class implements the “Dual TV L1” optical flow algorithm described in Zach2007 and Javier2012 . Here are important members of the class that control the algorithm, which you can set after constructing the class instance:

• member double tau Time step of the numerical scheme.

• member double lambda 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.

• member double theta 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.

• member int nscales Number of scales used to create the pyramid of images.

• member int warps 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.

• member double epsilon 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.

• member int iterations Stopping criterion iterations number used in the numerical scheme.

C. Zach, T. Pock and H. Bischof, “A Duality Based Approach for Realtime TV-L1 Optical Flow”. Javier Sanchez, Enric Meinhardt-Llopis and Gabriele Facciolo. “TV-L1 Optical Flow Estimation”.

Implementations

impl DualTVL1OpticalFlow

pub fn create( tau: f64, lambda: f64, theta: f64, nscales: i32, warps: i32, epsilon: f64, innner_iterations: i32, outer_iterations: i32, scale_step: f64, gamma: f64, median_filtering: i32, use_initial_flow: bool ) -> Result<Ptr<DualTVL1OpticalFlow>>

Creates instance of cv::DualTVL1OpticalFlow

C++ default parameters

• tau: 0.25
• lambda: 0.15
• theta: 0.3
• nscales: 5
• warps: 5
• epsilon: 0.01
• innner_iterations: 30
• outer_iterations: 10
• scale_step: 0.8
• gamma: 0.0
• median_filtering: 5
• use_initial_flow: false

pub fn create_def() -> Result<Ptr<DualTVL1OpticalFlow>>

Creates instance of cv::DualTVL1OpticalFlow

Note

This alternative version of DualTVL1OpticalFlow::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
• innner_iterations: 30
• outer_iterations: 10
• scale_step: 0.8
• gamma: 0.0
• median_filtering: 5
• use_initial_flow: false

Trait Implementations

impl AlgorithmTrait for DualTVL1OpticalFlow

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 DualTVL1OpticalFlow

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 DualTVL1OpticalFlow

unsafe fn from_raw( ptr: <DualTVL1OpticalFlow as OpenCVFromExtern>::ExternReceive ) -> Self

Wrap the specified raw pointer

fn into_raw( self ) -> <DualTVL1OpticalFlow as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying raw pointer while consuming this wrapper.

fn as_raw( &self ) -> <DualTVL1OpticalFlow as OpenCVTypeExternContainer>::ExternSend

Return the underlying raw pointer.

fn as_raw_mut( &mut self ) -> <DualTVL1OpticalFlow as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying mutable raw pointer

impl Debug for DualTVL1OpticalFlow

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

Formats the value using the given formatter.

impl DenseOpticalFlowTrait for DualTVL1OpticalFlow

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

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

Calculates an optical flow.

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

Releases all inner buffers.

impl DenseOpticalFlowTraitConst for DualTVL1OpticalFlow

fn as_raw_DenseOpticalFlow(&self) -> *const c_void

impl Drop for DualTVL1OpticalFlow

fn drop(&mut self)

Executes the destructor for this type.

impl DualTVL1OpticalFlowTrait for DualTVL1OpticalFlow

fn as_raw_mut_DualTVL1OpticalFlow(&mut self) -> *mut c_void

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

Time step of the numerical scheme

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

Weight parameter for the data term, attachment parameter

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

Weight parameter for (u - v)^2, tightness parameter

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

coefficient for additional illumination variation term

fn set_scales_number(&mut self, val: i32) -> Result<()>

Number of scales used to create the pyramid of images

fn set_warpings_number(&mut self, val: i32) -> Result<()>

Number of warpings per scale

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

Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time

fn set_inner_iterations(&mut self, val: i32) -> Result<()>

Inner iterations (between outlier filtering) used in the numerical scheme

fn set_outer_iterations(&mut self, val: i32) -> Result<()>

Outer iterations (number of inner loops) used in the numerical scheme

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

Use initial flow

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

Step between scales (<1)

fn set_median_filtering(&mut self, val: i32) -> Result<()>

Median filter kernel size (1 = no filter) (3 or 5)

impl DualTVL1OpticalFlowTraitConst for DualTVL1OpticalFlow

fn as_raw_DualTVL1OpticalFlow(&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

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

Weight parameter for (u - v)^2, tightness parameter

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

coefficient for additional illumination variation term

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

Number of scales used to create the pyramid of images

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

Number of warpings per scale

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

Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time

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

Inner iterations (between outlier filtering) used in the numerical scheme

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

Outer iterations (number of inner loops) used in the numerical scheme

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

Use initial flow

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

Step between scales (<1)

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

Median filter kernel size (1 = no filter) (3 or 5)

impl From<DualTVL1OpticalFlow> for Algorithm

fn from(s: DualTVL1OpticalFlow) -> Self

Converts to this type from the input type.

impl From<DualTVL1OpticalFlow> for DenseOpticalFlow

fn from(s: DualTVL1OpticalFlow) -> Self

Converts to this type from the input type.

impl Send for DualTVL1OpticalFlow