pub trait HOGDescriptorTrait: HOGDescriptorTraitConst {
Show 20 methods // Required method fn as_raw_mut_HOGDescriptor(&mut self) -> *mut c_void; // Provided methods fn set_win_size(&mut self, val: Size) { ... } fn set_block_size(&mut self, val: Size) { ... } fn set_block_stride(&mut self, val: Size) { ... } fn set_cell_size(&mut self, val: Size) { ... } fn set_nbins(&mut self, val: i32) { ... } fn set_deriv_aperture(&mut self, val: i32) { ... } fn set_win_sigma(&mut self, val: f64) { ... } fn set_histogram_norm_type(&mut self, val: HOGDescriptor_HistogramNormType) { ... } fn set_l2_hys_threshold(&mut self, val: f64) { ... } fn set_gamma_correction(&mut self, val: bool) { ... } fn set_svm_detector_vec(&mut self, val: Vector<f32>) { ... } fn set_ocl_svm_detector(&mut self, val: UMat) { ... } fn set_free_coef(&mut self, val: f32) { ... } fn set_nlevels(&mut self, val: i32) { ... } fn set_signed_gradient(&mut self, val: bool) { ... } fn set_svm_detector( &mut self, svmdetector: &impl ToInputArray ) -> Result<()> { ... } fn read(&mut self, fn_: &mut FileNode) -> Result<bool> { ... } fn load(&mut self, filename: &str, objname: &str) -> Result<bool> { ... } fn load_def(&mut self, filename: &str) -> Result<bool> { ... }
}
Expand description

Mutable methods for crate::objdetect::HOGDescriptor

Required Methods§

Provided Methods§

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fn set_win_size(&mut self, val: Size)

Detection window size. Align to block size and block stride. Default value is Size(64,128).

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fn set_block_size(&mut self, val: Size)

Block size in pixels. Align to cell size. Default value is Size(16,16).

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fn set_block_stride(&mut self, val: Size)

Block stride. It must be a multiple of cell size. Default value is Size(8,8).

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fn set_cell_size(&mut self, val: Size)

Cell size. Default value is Size(8,8).

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fn set_nbins(&mut self, val: i32)

Number of bins used in the calculation of histogram of gradients. Default value is 9.

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fn set_deriv_aperture(&mut self, val: i32)

not documented

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fn set_win_sigma(&mut self, val: f64)

Gaussian smoothing window parameter.

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fn set_histogram_norm_type(&mut self, val: HOGDescriptor_HistogramNormType)

histogramNormType

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fn set_l2_hys_threshold(&mut self, val: f64)

L2-Hys normalization method shrinkage.

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fn set_gamma_correction(&mut self, val: bool)

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

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fn set_svm_detector_vec(&mut self, val: Vector<f32>)

coefficients for the linear SVM classifier.

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fn set_ocl_svm_detector(&mut self, val: UMat)

coefficients for the linear SVM classifier used when OpenCL is enabled

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fn set_free_coef(&mut self, val: f32)

not documented

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fn set_nlevels(&mut self, val: i32)

Maximum number of detection window increases. Default value is 64

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fn set_signed_gradient(&mut self, val: bool)

Indicates signed gradient will be used or not

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fn set_svm_detector(&mut self, svmdetector: &impl ToInputArray) -> Result<()>

@example samples/cpp/peopledetect.cpp / Sets coefficients for the linear SVM classifier.

Parameters
  • svmdetector: coefficients for the linear SVM classifier.
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fn read(&mut self, fn_: &mut FileNode) -> Result<bool>

Reads HOGDescriptor parameters and coefficients for the linear SVM classifier from a file node.

Parameters
  • fn: File node
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fn load(&mut self, filename: &str, objname: &str) -> Result<bool>

loads HOGDescriptor parameters and coefficients for the linear SVM classifier from a file

Parameters
  • filename: Name of the file to read.
  • objname: The optional name of the node to read (if empty, the first top-level node will be used).
C++ default parameters
  • objname: String()
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fn load_def(&mut self, filename: &str) -> Result<bool>

loads HOGDescriptor parameters and coefficients for the linear SVM classifier from a file

Parameters
  • filename: Name of the file to read.
  • objname: The optional name of the node to read (if empty, the first top-level node will be used).
Note

This alternative version of [load] function uses the following default values for its arguments:

  • objname: String()

Object Safety§

This trait is not object safe.

Implementors§