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101 lines
3.3 KiB
C++
101 lines
3.3 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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//
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// Copyright (C) 2017, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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#ifndef OPENCV_DNN_NMS_INL_HPP
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#define OPENCV_DNN_NMS_INL_HPP
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#include <opencv2/dnn.hpp>
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namespace cv {
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namespace dnn {
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namespace
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{
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template <typename T>
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static inline bool SortScorePairDescend(const std::pair<float, T>& pair1,
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const std::pair<float, T>& pair2)
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{
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return pair1.first > pair2.first;
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}
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} // namespace
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// Get max scores with corresponding indices.
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// scores: a set of scores.
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// threshold: only consider scores higher than the threshold.
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// top_k: if -1, keep all; otherwise, keep at most top_k.
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// score_index_vec: store the sorted (score, index) pair.
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inline void GetMaxScoreIndex(const std::vector<float>& scores, const float threshold, const int top_k,
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std::vector<std::pair<float, int> >& score_index_vec)
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{
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CV_DbgAssert(score_index_vec.empty());
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// Generate index score pairs.
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for (size_t i = 0; i < scores.size(); ++i)
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{
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if (scores[i] > threshold)
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{
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score_index_vec.push_back(std::make_pair(scores[i], i));
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}
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}
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// Sort the score pair according to the scores in descending order
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std::stable_sort(score_index_vec.begin(), score_index_vec.end(),
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SortScorePairDescend<int>);
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// Keep top_k scores if needed.
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if (top_k > 0 && top_k < (int)score_index_vec.size())
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{
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score_index_vec.resize(top_k);
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}
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}
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// Do non maximum suppression given bboxes and scores.
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// Inspired by Piotr Dollar's NMS implementation in EdgeBox.
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// https://goo.gl/jV3JYS
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// bboxes: a set of bounding boxes.
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// scores: a set of corresponding confidences.
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// score_threshold: a threshold used to filter detection results.
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// nms_threshold: a threshold used in non maximum suppression.
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// top_k: if not > 0, keep at most top_k picked indices.
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// indices: the kept indices of bboxes after nms.
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template <typename BoxType>
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inline void NMSFast_(const std::vector<BoxType>& bboxes,
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const std::vector<float>& scores, const float score_threshold,
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const float nms_threshold, const float eta, const int top_k,
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std::vector<int>& indices, float (*computeOverlap)(const BoxType&, const BoxType&))
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{
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CV_Assert(bboxes.size() == scores.size());
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// Get top_k scores (with corresponding indices).
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std::vector<std::pair<float, int> > score_index_vec;
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GetMaxScoreIndex(scores, score_threshold, top_k, score_index_vec);
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// Do nms.
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float adaptive_threshold = nms_threshold;
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indices.clear();
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for (size_t i = 0; i < score_index_vec.size(); ++i) {
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const int idx = score_index_vec[i].second;
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bool keep = true;
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for (int k = 0; k < (int)indices.size() && keep; ++k) {
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const int kept_idx = indices[k];
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float overlap = computeOverlap(bboxes[idx], bboxes[kept_idx]);
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keep = overlap <= adaptive_threshold;
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}
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if (keep)
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indices.push_back(idx);
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if (keep && eta < 1 && adaptive_threshold > 0.5) {
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adaptive_threshold *= eta;
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}
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}
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}
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}// dnn
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}// cv
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#endif
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