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Merge pull request #26405 from kaingwade:rename_features2d
Rename features2d #26405 This PR renames the module _features2d_ to _features_ as one of the Big OpenCV Cleanup #25007. Related PR: opencv/opencv_contrib: [#3820](https://github.com/opencv/opencv_contrib/pull/3820) opencv/ci-gha-workflow: [#192](https://github.com/opencv/ci-gha-workflow/pull/192)
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WU Jia
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Redistribution and use in source and binary forms, with or without modification,
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "precomp.hpp"
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namespace cv
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{
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using std::vector;
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Feature2D::~Feature2D() {}
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/*
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* Detect keypoints in an image.
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* image The image.
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* keypoints The detected keypoints.
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* mask Mask specifying where to look for keypoints (optional). Must be a char
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* matrix with non-zero values in the region of interest.
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*/
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void Feature2D::detect( InputArray image,
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std::vector<KeyPoint>& keypoints,
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InputArray mask )
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{
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CV_INSTRUMENT_REGION();
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if( image.empty() )
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{
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keypoints.clear();
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return;
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}
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detectAndCompute(image, mask, keypoints, noArray(), false);
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}
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void Feature2D::detect( InputArrayOfArrays images,
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std::vector<std::vector<KeyPoint> >& keypoints,
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InputArrayOfArrays masks )
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{
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CV_INSTRUMENT_REGION();
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int nimages = (int)images.total();
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if (!masks.empty())
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{
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CV_Assert(masks.total() == (size_t)nimages);
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}
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keypoints.resize(nimages);
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if (images.isMatVector())
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{
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for (int i = 0; i < nimages; i++)
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{
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detect(images.getMat(i), keypoints[i], masks.empty() ? noArray() : masks.getMat(i));
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}
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}
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else
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{
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// assume UMats
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for (int i = 0; i < nimages; i++)
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{
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detect(images.getUMat(i), keypoints[i], masks.empty() ? noArray() : masks.getUMat(i));
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}
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}
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}
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/*
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* Compute the descriptors for a set of keypoints in an image.
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* image The image.
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* keypoints The input keypoints. Keypoints for which a descriptor cannot be computed are removed.
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* descriptors Copmputed descriptors. Row i is the descriptor for keypoint i.
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*/
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void Feature2D::compute( InputArray image,
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std::vector<KeyPoint>& keypoints,
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OutputArray descriptors )
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{
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CV_INSTRUMENT_REGION();
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if( image.empty() )
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{
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descriptors.release();
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return;
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}
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detectAndCompute(image, noArray(), keypoints, descriptors, true);
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}
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void Feature2D::compute( InputArrayOfArrays images,
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std::vector<std::vector<KeyPoint> >& keypoints,
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OutputArrayOfArrays descriptors )
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{
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CV_INSTRUMENT_REGION();
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if( !descriptors.needed() )
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return;
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int nimages = (int)images.total();
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CV_Assert( keypoints.size() == (size_t)nimages );
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// resize descriptors to appropriate size and compute
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if (descriptors.isMatVector())
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{
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vector<Mat>& vec = *(vector<Mat>*)descriptors.getObj();
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vec.resize(nimages);
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for (int i = 0; i < nimages; i++)
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{
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compute(images.getMat(i), keypoints[i], vec[i]);
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}
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}
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else if (descriptors.isUMatVector())
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{
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vector<UMat>& vec = *(vector<UMat>*)descriptors.getObj();
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vec.resize(nimages);
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for (int i = 0; i < nimages; i++)
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{
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compute(images.getUMat(i), keypoints[i], vec[i]);
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}
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}
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else
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{
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CV_Error(Error::StsBadArg, "descriptors must be vector<Mat> or vector<UMat>");
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}
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}
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/* Detects keypoints and computes the descriptors */
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void Feature2D::detectAndCompute( InputArray, InputArray,
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std::vector<KeyPoint>&,
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OutputArray,
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bool )
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{
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CV_INSTRUMENT_REGION();
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CV_Error(Error::StsNotImplemented, "");
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}
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void Feature2D::write( const String& fileName ) const
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{
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FileStorage fs(fileName, FileStorage::WRITE);
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write(fs);
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}
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void Feature2D::read( const String& fileName )
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{
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FileStorage fs(fileName, FileStorage::READ);
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read(fs.root());
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}
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void Feature2D::write( FileStorage&) const
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{
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}
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void Feature2D::read( const FileNode&)
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{
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}
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int Feature2D::descriptorSize() const
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{
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return 0;
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}
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int Feature2D::descriptorType() const
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{
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return CV_32F;
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}
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int Feature2D::defaultNorm() const
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{
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int tp = descriptorType();
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return tp == CV_8U ? NORM_HAMMING : NORM_L2;
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}
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// Return true if detector object is empty
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bool Feature2D::empty() const
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{
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return true;
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}
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String Feature2D::getDefaultName() const
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{
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return "Feature2D";
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}
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}
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