Type Definition opencv::types::PtrOfHOG

type PtrOfHOG = Ptr<dyn HOG>;

Implementations

impl PtrOfHOG

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

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

Trait Implementations

impl AlgorithmTrait for PtrOfHOG

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 HOG for PtrOfHOG

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

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

pub fn set_win_sigma(&mut self, win_sigma: f64) -> Result<()>

Gaussian smoothing window parameter.

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

pub fn set_l2_hys_threshold(&mut self, threshold_l2hys: f64) -> Result<()>

L2-Hys normalization method shrinkage.

pub fn get_l2_hys_threshold(&self) -> Result<f64>

pub fn set_gamma_correction(&mut self, gamma_correction: bool) -> Result<()>

Flag to specify whether the gamma correction preprocessing is required or not.

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

pub fn set_num_levels(&mut self, nlevels: i32) -> Result<()>

Maximum number of detection window increases.

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

pub fn set_hit_threshold(&mut self, hit_threshold: f64) -> Result<()>

Threshold for the distance between features and SVM classifying plane. Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient). But if the free coefficient is omitted (which is allowed), you can specify it manually here.

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

pub fn set_win_stride(&mut self, win_stride: Size) -> Result<()>

Window stride. It must be a multiple of block stride.

pub fn get_win_stride(&self) -> Result<Size>

pub fn set_scale_factor(&mut self, scale0: f64) -> Result<()>

Coefficient of the detection window increase.

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

pub fn set_group_threshold(&mut self, group_threshold: i32) -> Result<()>

Coefficient to regulate the similarity threshold. When detected, some objects can be covered by many rectangles. 0 means not to perform grouping. See groupRectangles.

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

pub fn set_descriptor_format(
    &mut self,
    descr_format: HOGDescriptor_DescriptorStorageFormat
) -> Result<()>

Descriptor storage format:

pub fn get_descriptor_format(
    &self
) -> Result<HOGDescriptor_DescriptorStorageFormat>

pub fn get_descriptor_size(&self) -> Result<size_t>

Returns the number of coefficients required for the classification.

pub fn get_block_histogram_size(&self) -> Result<size_t>

Returns the block histogram size.

pub fn set_svm_detector(&mut self, detector: &dyn ToInputArray) -> Result<()>

Sets coefficients for the linear SVM classifier.

pub fn get_default_people_detector(&self) -> Result<Mat>

Returns coefficients of the classifier trained for people detection.

pub fn detect(
    &mut self,
    img: &dyn ToInputArray,
    found_locations: &mut Vector<Point>,
    confidences: &mut Vector<f64>
) -> Result<()>

Performs object detection without a multi-scale window.

pub fn detect_1(
    &mut self,
    img: &dyn ToInputArray,
    found_locations: &mut Vector<Point>,
    confidences: &mut Vector<f64>
) -> Result<()>

pub fn detect_without_conf(
    &mut self,
    img: &dyn ToInputArray,
    found_locations: &mut Vector<Point>
) -> Result<()>

Performs object detection without a multi-scale window.

pub fn detect_multi_scale(
    &mut self,
    img: &dyn ToInputArray,
    found_locations: &mut Vector<Rect>,
    confidences: &mut Vector<f64>
) -> Result<()>

Performs object detection with a multi-scale window.

pub fn detect_multi_scale_1(
    &mut self,
    img: &dyn ToInputArray,
    found_locations: &mut Vector<Rect>,
    confidences: &mut Vector<f64>
) -> Result<()>

pub fn detect_multi_scale_without_conf(
    &mut self,
    img: &dyn ToInputArray,
    found_locations: &mut Vector<Rect>
) -> Result<()>

Performs object detection with a multi-scale window.

pub fn compute(
    &mut self,
    img: &dyn ToInputArray,
    descriptors: &mut dyn ToOutputArray,
    stream: &mut Stream
) -> Result<()>

Returns block descriptors computed for the whole image.