mirror of https://github.com/opencv/opencv.git
Merge pull request #9862 from sovrasov:dnn_nms
Vadim Pisarevsky
7 years ago
commit
bc93775385
5 changed files with 199 additions and 70 deletions
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// 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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#include "precomp.hpp" |
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#include <nms.inl.hpp> |
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namespace cv |
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{ |
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namespace dnn |
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{ |
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CV__DNN_EXPERIMENTAL_NS_BEGIN |
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static inline float rectOverlap(const Rect& a, const Rect& b) |
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{ |
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return 1.f - static_cast<float>(jaccardDistance(a, b)); |
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} |
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void NMSBoxes(const std::vector<Rect>& bboxes, const std::vector<float>& scores, |
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const float score_threshold, const float nms_threshold, |
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std::vector<int>& indices, const float eta, const int top_k) |
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{ |
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CV_Assert(bboxes.size() == scores.size(), score_threshold >= 0, |
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nms_threshold >= 0, eta > 0); |
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NMSFast_(bboxes, scores, score_threshold, nms_threshold, eta, top_k, indices, rectOverlap); |
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} |
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CV__DNN_EXPERIMENTAL_NS_END |
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}// dnn
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}// cv
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// 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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// 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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#include "test_precomp.hpp" |
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namespace cvtest |
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{ |
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TEST(NMS, Accuracy) |
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{ |
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//reference results obtained using tf.image.non_max_suppression with iou_threshold=0.5
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std::string dataPath = findDataFile("dnn/nms_reference.yml"); |
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FileStorage fs(dataPath, FileStorage::READ); |
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std::vector<Rect> bboxes; |
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std::vector<float> scores; |
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std::vector<int> ref_indices; |
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fs["boxes"] >> bboxes; |
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fs["probs"] >> scores; |
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fs["output"] >> ref_indices; |
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const float nms_thresh = .5f; |
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const float score_thresh = .01f; |
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std::vector<int> indices; |
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cv::dnn::NMSBoxes(bboxes, scores, score_thresh, nms_thresh, indices); |
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ASSERT_EQ(ref_indices.size(), indices.size()); |
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std::sort(indices.begin(), indices.end()); |
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std::sort(ref_indices.begin(), ref_indices.end()); |
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for(size_t i = 0; i < indices.size(); i++) |
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ASSERT_EQ(indices[i], ref_indices[i]); |
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} |
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}//cvtest
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