| OpenCV 3.4.8 Open Source Computer Vision

Public Types | Public Member Functions | Static Public Member Functions | List of all members
cv::cuda::HOG Class Referenceabstract
CUDA-accelerated Computer Vision » Object Detection

The class implements Histogram of Oriented Gradients ([42]) object detector. More...

`#include <opencv2/cudaobjdetect.hpp>`

Inheritance diagram for cv::cuda::HOG:

## Public Types
enum | { DESCR_FORMAT_ROW_BY_ROW, DESCR_FORMAT_COL_BY_COL }

## Public Member Functions
virtual void | compute (InputArray img, OutputArray descriptors, Stream &stream=Stream::Null())=0
| Returns block descriptors computed for the whole image. More...
virtual void | detect (InputArray img, std::vector< Point > &found_locations, std::vector< double > *confidences=NULL)=0
| Performs object detection without a multi-scale window. More...
virtual void | detectMultiScale (InputArray img, std::vector< Rect > &found_locations, std::vector< double > *confidences=NULL)=0
| Performs object detection with a multi-scale window. More...
virtual size_t | getBlockHistogramSize () const =0
| Returns the block histogram size. More...
virtual Mat | getDefaultPeopleDetector () const =0
| Returns coefficients of the classifier trained for people detection. More...
virtual int | getDescriptorFormat () const =0
virtual size_t | getDescriptorSize () const =0
| Returns the number of coefficients required for the classification. More...
virtual bool | getGammaCorrection () const =0
virtual int | getGroupThreshold () const =0
virtual double | getHitThreshold () const =0
virtual double | getL2HysThreshold () const =0
virtual int | getNumLevels () const =0
virtual double | getScaleFactor () const =0
virtual double | getWinSigma () const =0
virtual Size | getWinStride () const =0
virtual void | setDescriptorFormat (int descr_format)=0
virtual void | setGammaCorrection (bool gamma_correction)=0
| Flag to specify whether the gamma correction preprocessing is required or not. More...
virtual void | setGroupThreshold (int group_threshold)=0
virtual void | setHitThreshold (double hit_threshold)=0
virtual void | setL2HysThreshold (double threshold_L2hys)=0
| L2-Hys normalization method shrinkage. More...
virtual void | setNumLevels (int nlevels)=0
| Maximum number of detection window increases. More...
virtual void | setScaleFactor (double scale0)=0
| Coefficient of the detection window increase. More...
virtual void | setSVMDetector (InputArray detector)=0
| Sets coefficients for the linear SVM classifier. More...
virtual void | setWinSigma (double win_sigma)=0
| Gaussian smoothing window parameter. More...
virtual void | setWinStride (Size win_stride)=0
| Window stride. It must be a multiple of block stride. More...
Public Member Functions inherited from cv::Algorithm
| Algorithm ()
virtual | ~Algorithm ()
virtual void | clear ()
| Clears the algorithm state. More...
virtual bool | empty () const
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...
virtual String | getDefaultName () const
virtual void | read (const FileNode &fn)
| Reads algorithm parameters from a file storage. More...
virtual void | save (const String &filename) const
virtual void | write (FileStorage &fs) const
| Stores algorithm parameters in a file storage. More...
void | write (const Ptr< FileStorage > &fs, const String &name=String()) const
| simplified API for language bindings This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More...

## Static Public Member Functions
static Ptr< HOG > | create (Size win_size=Size(64, 128), Size block_size=Size(16, 16), Size block_stride=Size(8, 8), Size cell_size=Size(8, 8), int nbins=9)
| Creates the HOG descriptor and detector. More...
Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tp > | load (const String &filename, const String &objname=String())
| Loads algorithm from the file. More...
template<typename _Tp >
static Ptr< _Tp > | loadFromString (const String &strModel, const String &objname=String())
| Loads algorithm from a String. More...
template<typename _Tp >
static Ptr< _Tp > | read (const FileNode &fn)
| Reads algorithm from the file node. More...

## Additional Inherited Members
Protected Member Functions inherited from cv::Algorithm
void | writeFormat (FileStorage &fs) const

## Detailed Description

The class implements Histogram of Oriented Gradients ([42]) object detector.

Note
  - An example applying the HOG descriptor for people detection can be found at opencv_source_code/samples/cpp/peopledetect.cpp
  - A CUDA example applying the HOG descriptor for people detection can be found at opencv_source_code/samples/gpu/hog.cpp
  - (Python) An example applying the HOG descriptor for people detection can be found at opencv_source_code/samples/python/peopledetect.py

## Member Enumeration Documentation

## § anonymous enum

anonymous enum

Enumerator
DESCR_FORMAT_ROW_BY_ROW |
DESCR_FORMAT_COL_BY_COL |

## Member Function Documentation

## § compute()

virtual void cv::cuda::HOG::compute | ( | InputArray | img,
|  | OutputArray | descriptors,
|  | Stream & | stream = `Stream::Null()`
| ) |  |
| pure virtual

Returns block descriptors computed for the whole image.

Parameters

  img | Source image. See cuda::HOGDescriptor::detect for type limitations.
  descriptors | 2D array of descriptors.
  stream | CUDA stream.

## § create()

static Ptr<HOG> cv::cuda::HOG::create | ( | Size | win_size = `Size(64, 128)`,
|  | Size | block_size = `Size(16, 16)`,
|  | Size | block_stride = `Size(8, 8)`,
|  | Size | cell_size = `Size(8, 8)`,
|  | int | nbins = `9`
| ) |  |
| static

Creates the HOG descriptor and detector.

Parameters

  win_size | Detection window size. Align to block size and block stride.
  block_size | Block size in pixels. Align to cell size. Only (16,16) is supported for now.
  block_stride | Block stride. It must be a multiple of cell size.
  cell_size | Cell size. Only (8, 8) is supported for now.
  nbins | Number of bins. Only 9 bins per cell are supported for now.

## § detect()

virtual void cv::cuda::HOG::detect | ( | InputArray | img,
|  | std::vector< Point > & | found_locations,
|  | std::vector< double > * | confidences = `NULL`
| ) |  |
| pure virtual

Performs object detection without a multi-scale window.

Parameters

  img | Source image. CV_8UC1 and CV_8UC4 types are supported for now.
  found_locations | Left-top corner points of detected objects boundaries.
  confidences | Optional output array for confidences.

## § detectMultiScale()

virtual void cv::cuda::HOG::detectMultiScale | ( | InputArray | img,
|  | std::vector< Rect > & | found_locations,
|  | std::vector< double > * | confidences = `NULL`
| ) |  |
| pure virtual

Performs object detection with a multi-scale window.

Parameters

  img | Source image. See cuda::HOGDescriptor::detect for type limitations.
  found_locations | Detected objects boundaries.
  confidences | Optional output array for confidences.

## § getBlockHistogramSize()

virtual size_t cv::cuda::HOG::getBlockHistogramSize | ( |  | ) | const
| pure virtual

Returns the block histogram size.

## § getDefaultPeopleDetector()

virtual Mat cv::cuda::HOG::getDefaultPeopleDetector | ( |  | ) | const
| pure virtual

Returns coefficients of the classifier trained for people detection.

## § getDescriptorFormat()

virtual int cv::cuda::HOG::getDescriptorFormat | ( |  | ) | const
| pure virtual

## § getDescriptorSize()

virtual size_t cv::cuda::HOG::getDescriptorSize | ( |  | ) | const
| pure virtual

Returns the number of coefficients required for the classification.

## § getGammaCorrection()

virtual bool cv::cuda::HOG::getGammaCorrection | ( |  | ) | const
| pure virtual

## § getGroupThreshold()

virtual int cv::cuda::HOG::getGroupThreshold | ( |  | ) | const
| pure virtual

## § getHitThreshold()

virtual double cv::cuda::HOG::getHitThreshold | ( |  | ) | const
| pure virtual

## § getL2HysThreshold()

virtual double cv::cuda::HOG::getL2HysThreshold | ( |  | ) | const
| pure virtual

## § getNumLevels()

virtual int cv::cuda::HOG::getNumLevels | ( |  | ) | const
| pure virtual

## § getScaleFactor()

virtual double cv::cuda::HOG::getScaleFactor | ( |  | ) | const
| pure virtual

## § getWinSigma()

virtual double cv::cuda::HOG::getWinSigma | ( |  | ) | const
| pure virtual

## § getWinStride()

virtual Size cv::cuda::HOG::getWinStride | ( |  | ) | const
| pure virtual

## § setDescriptorFormat()

virtual void cv::cuda::HOG::setDescriptorFormat | ( | int | descr_format | ) |
| pure virtual

Descriptor storage format:

- DESCR_FORMAT_ROW_BY_ROW - Row-major order.
- DESCR_FORMAT_COL_BY_COL - Column-major order.

## § setGammaCorrection()

virtual void cv::cuda::HOG::setGammaCorrection | ( | bool | gamma_correction | ) |
| pure virtual

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

## § setGroupThreshold()

virtual void cv::cuda::HOG::setGroupThreshold | ( | int | group_threshold | ) |
| pure virtual

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

## § setHitThreshold()

virtual void cv::cuda::HOG::setHitThreshold | ( | double | hit_threshold | ) |
| pure virtual

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.

## § setL2HysThreshold()

virtual void cv::cuda::HOG::setL2HysThreshold | ( | double | threshold_L2hys | ) |
| pure virtual

L2-Hys normalization method shrinkage.

## § setNumLevels()

virtual void cv::cuda::HOG::setNumLevels | ( | int | nlevels | ) |
| pure virtual

Maximum number of detection window increases.

## § setScaleFactor()

virtual void cv::cuda::HOG::setScaleFactor | ( | double | scale0 | ) |
| pure virtual

Coefficient of the detection window increase.

## § setSVMDetector()

virtual void cv::cuda::HOG::setSVMDetector | ( | InputArray | detector | ) |
| pure virtual

Sets coefficients for the linear SVM classifier.

## § setWinSigma()

virtual void cv::cuda::HOG::setWinSigma | ( | double | win_sigma | ) |
| pure virtual

Gaussian smoothing window parameter.

## § setWinStride()

virtual void cv::cuda::HOG::setWinStride | ( | Size | win_stride | ) |
| pure virtual

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

The documentation for this class was generated from the following file:

- opencv2/cudaobjdetect.hpp