Struct LearningBasedWB

pub struct LearningBasedWB { /* private fields */ }

More sophisticated learning-based automatic white balance algorithm.

As GrayworldWB, this algorithm works by applying different gains to the input image channels, but their computation is a bit more involved compared to the simple gray-world assumption. More details about the algorithm can be found in Cheng2015 .

To mask out saturated pixels this function uses only pixels that satisfy the following condition:

Currently supports images of type [CV_8UC3] and [CV_16UC3].

Trait Implementations

impl AlgorithmTrait for LearningBasedWB

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 LearningBasedWB

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 LearningBasedWB

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

Wrap the specified raw pointer

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

Return the underlying raw pointer while consuming this wrapper.

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

Return the underlying raw pointer.

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

Return the underlying mutable raw pointer

impl Debug for LearningBasedWB

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

Formats the value using the given formatter.

impl Drop for LearningBasedWB

fn drop(&mut self)

Executes the destructor for this type.

impl From<LearningBasedWB> for Algorithm

fn from(s: LearningBasedWB) -> Self

Converts to this type from the input type.

impl From<LearningBasedWB> for WhiteBalancer

fn from(s: LearningBasedWB) -> Self

Converts to this type from the input type.

impl LearningBasedWBTrait for LearningBasedWB

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

fn extract_simple_features( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, ) -> Result<()>

Implements the feature extraction part of the algorithm.

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

Maximum possible value of the input image (e.g. 255 for 8 bit images, 4095 for 12 bit images)

fn set_saturation_threshold(&mut self, val: f32) -> Result<()>

Threshold that is used to determine saturated pixels, i.e. pixels where at least one of the channels exceeds inline formula are ignored.

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

Defines the size of one dimension of a three-dimensional RGB histogram that is used internally by the algorithm. It often makes sense to increase the number of bins for images with higher bit depth (e.g. 256 bins for a 12 bit image).

impl LearningBasedWBTraitConst for LearningBasedWB

fn as_raw_LearningBasedWB(&self) -> *const c_void

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

Maximum possible value of the input image (e.g. 255 for 8 bit images, 4095 for 12 bit images)

fn get_saturation_threshold(&self) -> Result<f32>

Threshold that is used to determine saturated pixels, i.e. pixels where at least one of the channels exceeds inline formula are ignored.

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

Defines the size of one dimension of a three-dimensional RGB histogram that is used internally by the algorithm. It often makes sense to increase the number of bins for images with higher bit depth (e.g. 256 bins for a 12 bit image).

impl TryFrom<WhiteBalancer> for LearningBasedWB

type Error = Error

The type returned in the event of a conversion error.

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

Performs the conversion.

impl WhiteBalancerTrait for LearningBasedWB

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

fn balance_white( &mut self, src: &impl ToInputArray, dst: &mut impl ToOutputArray, ) -> Result<()>

Applies white balancing to the input image

impl WhiteBalancerTraitConst for LearningBasedWB

fn as_raw_WhiteBalancer(&self) -> *const c_void

impl Send for LearningBasedWB