mirror of
https://github.com/opencv/opencv_contrib.git
synced 2025-10-18 08:44:11 +08:00
added dpm module
This commit is contained in:
jiaolong_x220
148
modules/dpm/include/opencv2/dpm.hpp
Normal file
148
modules/dpm/include/opencv2/dpm.hpp
Normal file
@@ -0,0 +1,148 @@
|
||||
/*M///////////////////////////////////////////////////////////////////////////////////////
|
||||
//
|
||||
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
||||
//
|
||||
// By downloading, copying, installing or using the software you agree to this license.
|
||||
// If you do not agree to this license, do not download, install,
|
||||
// copy or use the software.
|
||||
//
|
||||
//
|
||||
// License Agreement
|
||||
// For Open Source Computer Vision Library
|
||||
//
|
||||
// Copyright (C) 2015, Itseez Inc, all rights reserved.
|
||||
// Third party copyrights are property of their respective owners.
|
||||
//
|
||||
// Redistribution and use in source and binary forms, with or without modification,
|
||||
// are permitted provided that the following conditions are met:
|
||||
//
|
||||
// * Redistribution's of source code must retain the above copyright notice,
|
||||
// this list of conditions and the following disclaimer.
|
||||
//
|
||||
// * Redistribution's in binary form must reproduce the above copyright notice,
|
||||
// this list of conditions and the following disclaimer in the documentation
|
||||
// and/or other materials provided with the distribution.
|
||||
//
|
||||
// * The name of the copyright holders may not be used to endorse or promote products
|
||||
// derived from this software without specific prior written permission.
|
||||
//
|
||||
// This software is provided by the copyright holders and contributors "as is" and
|
||||
// any express or implied warranties, including, but not limited to, the implied
|
||||
// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
||||
// In no event shall the Itseez Inc or contributors be liable for any direct,
|
||||
// indirect, incidental, special, exemplary, or consequential damages
|
||||
// (including, but not limited to, procurement of substitute goods or services;
|
||||
// loss of use, data, or profits; or business interruption) however caused
|
||||
// and on any theory of liability, whether in contract, strict liability,
|
||||
// or tort (including negligence or otherwise) arising in any way out of
|
||||
// the use of this software, even if advised of the possibility of such damage.
|
||||
//
|
||||
// Implementation authors:
|
||||
// Jiaolong Xu - jiaolongxu@gmail.com
|
||||
// Evgeniy Kozinov - evgeniy.kozinov@gmail.com
|
||||
// Valentina Kustikova - valentina.kustikova@gmail.com
|
||||
// Nikolai Zolotykh - Nikolai.Zolotykh@gmail.com
|
||||
// Iosif Meyerov - meerov@vmk.unn.ru
|
||||
// Alexey Polovinkin - polovinkin.alexey@gmail.com
|
||||
//
|
||||
//M*/
|
||||
|
||||
#ifndef __OPENCV_LATENTSVM_HPP__
|
||||
#define __OPENCV_LATENTSVM_HPP__
|
||||
|
||||
#include "opencv2/core.hpp"
|
||||
|
||||
#include <map>
|
||||
#include <vector>
|
||||
#include <string>
|
||||
|
||||
/** @defgroup dpm Deformable Part-based Models
|
||||
|
||||
Discriminatively Trained Part Based Models for Object Detection
|
||||
---------------------------------------------------------------
|
||||
|
||||
The object detector described below has been initially proposed by P.F. Felzenszwalb in
|
||||
@cite Felzenszwalb2010a . It is based on a Dalal-Triggs detector that uses a single filter on histogram
|
||||
of oriented gradients (HOG) features to represent an object category. This detector uses a sliding
|
||||
window approach, where a filter is applied at all positions and scales of an image. The first
|
||||
innovation is enriching the Dalal-Triggs model using a star-structured part-based model defined by a
|
||||
"root" filter (analogous to the Dalal-Triggs filter) plus a set of parts filters and associated
|
||||
deformation models. The score of one of star models at a particular position and scale within an
|
||||
image is the score of the root filter at the given location plus the sum over parts of the maximum,
|
||||
over placements of that part, of the part filter score on its location minus a deformation cost
|
||||
easuring the deviation of the part from its ideal location relative to the root. Both root and part
|
||||
filter scores are defined by the dot product between a filter (a set of weights) and a subwindow of
|
||||
a feature pyramid computed from the input image. Another improvement is a representation of the
|
||||
class of models by a mixture of star models. The score of a mixture model at a particular position
|
||||
and scale is the maximum over components, of the score of that component model at the given
|
||||
location.
|
||||
|
||||
The detector was dramatically speeded-up with cascade algorithm proposed by P.F. Felzenszwalb in
|
||||
@cite Felzenszwalb2010b . The algorithm prunes partial hypotheses using thresholds on their scores.The
|
||||
basic idea of the algorithm is to use a hierarchy of models defined by an ordering of the original
|
||||
model's parts. For a model with (n+1) parts, including the root, a sequence of (n+1) models is
|
||||
obtained. The i-th model in this sequence is defined by the first i parts from the original model.
|
||||
Using this hierarchy, low scoring hypotheses can be pruned after looking at the best configuration
|
||||
of a subset of the parts. Hypotheses that score high under a weak model are evaluated further using
|
||||
a richer model.
|
||||
|
||||
In OpenCV there is an C++ implementation of DPM cascade detector.
|
||||
|
||||
*/
|
||||
|
||||
namespace cv
|
||||
{
|
||||
|
||||
namespace dpm
|
||||
{
|
||||
|
||||
/** @brief This is a C++ abstract class, it provides external user API to work with DPM.
|
||||
*/
|
||||
class CV_EXPORTS_W DPMDetector
|
||||
{
|
||||
public:
|
||||
|
||||
struct CV_EXPORTS_W ObjectDetection
|
||||
{
|
||||
ObjectDetection();
|
||||
ObjectDetection( const Rect& rect, float score, int classID=-1 );
|
||||
Rect rect;
|
||||
float score;
|
||||
int classID;
|
||||
};
|
||||
|
||||
virtual bool isEmpty() const = 0;
|
||||
|
||||
/** @brief Find rectangular regions in the given image that are likely to contain objects of loaded classes
|
||||
(models) and corresponding confidence levels.
|
||||
@param image An image.
|
||||
@param objects The detections: rectangulars, scores and class IDs.
|
||||
*/
|
||||
virtual void detect(cv::Mat &image, CV_OUT std::vector<ObjectDetection> &objects) = 0;
|
||||
|
||||
/** @brief Return the class (model) names that were passed in constructor or method load or extracted from
|
||||
models filenames in those methods.
|
||||
*/
|
||||
virtual std::vector<std::string> const& getClassNames() const = 0;
|
||||
|
||||
/** @brief Return a count of loaded models (classes).
|
||||
*/
|
||||
virtual size_t getClassCount() const = 0;
|
||||
|
||||
/** @brief Load the trained models from given .xml files and return cv::Ptr\<DPMDetector\>.
|
||||
@param filenames A set of filenames storing the trained detectors (models). Each file contains one
|
||||
model. See examples of such files here `/opencv_extra/testdata/cv/dpm/VOC2007_Cascade/`.
|
||||
@param classNames A set of trained models names. If it's empty then the name of each model will be
|
||||
constructed from the name of file containing the model. E.g. the model stored in
|
||||
"/home/user/cat.xml" will get the name "cat".
|
||||
*/
|
||||
static cv::Ptr<DPMDetector> create(std::vector<std::string> const &filenames,
|
||||
std::vector<std::string> const &classNames = std::vector<std::string>());
|
||||
|
||||
virtual ~DPMDetector(){}
|
||||
};
|
||||
|
||||
} // namespace dpm
|
||||
} // namespace cv
|
||||
|
||||
#endif
|
||||
Reference in New Issue
Block a user