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Address more comments
Use map to manage unique marker size candidate trees. Avoid code duplication. Add a test to show double detection with overlapping dictionaries. Generalize to marker sizes of not only predefined dictionaries.
This commit is contained in:
Benjamin Knecht
parent
3084f950cf
commit
1aa658fa75
@ -10,7 +10,7 @@
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#include "apriltag/apriltag_quad_thresh.hpp"
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#include "aruco_utils.hpp"
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#include <cmath>
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#include <unordered_set>
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#include <map>
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namespace cv {
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namespace aruco {
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@ -752,44 +752,20 @@ struct ArucoDetector::ArucoDetectorImpl {
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/// STEP 3: Corner refinement :: use corner subpix
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if (detectorParams.cornerRefinementMethod == (int)CORNER_REFINE_SUBPIX) {
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CV_Assert(detectorParams.cornerRefinementWinSize > 0 && detectorParams.cornerRefinementMaxIterations > 0 &&
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detectorParams.cornerRefinementMinAccuracy > 0);
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// Do subpixel estimation. In Aruco3 start on the lowest pyramid level and upscale the corners
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parallel_for_(Range(0, (int)candidates.size()), [&](const Range& range) {
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const int begin = range.start;
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const int end = range.end;
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for (int i = begin; i < end; i++) {
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if (detectorParams.useAruco3Detection) {
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const float scale_init = (float) grey_pyramid[closest_pyr_image_idx].cols / grey.cols;
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findCornerInPyrImage(scale_init, closest_pyr_image_idx, grey_pyramid, Mat(candidates[i]), detectorParams);
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} else {
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int cornerRefinementWinSize = std::max(1, cvRound(detectorParams.relativeCornerRefinmentWinSize*
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getAverageModuleSize(candidates[i], dictionary.markerSize, detectorParams.markerBorderBits)));
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cornerRefinementWinSize = min(cornerRefinementWinSize, detectorParams.cornerRefinementWinSize);
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cornerSubPix(grey, Mat(candidates[i]), Size(cornerRefinementWinSize, cornerRefinementWinSize), Size(-1, -1),
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TermCriteria(TermCriteria::MAX_ITER | TermCriteria::EPS,
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detectorParams.cornerRefinementMaxIterations,
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detectorParams.cornerRefinementMinAccuracy));
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}
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}
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});
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performCornerSubpixRefinement(grey, grey_pyramid, closest_pyr_image_idx, candidates, dictionary);
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}
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} else if (DictionaryMode::Multi == dictMode) {
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unordered_set<int> uniqueMarkerSizes;
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map<size_t, vector<MarkerCandidateTree>> candidatesPerDictionarySize;
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for (const Dictionary& dictionary : dictionaries) {
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uniqueMarkerSizes.insert(dictionary.markerSize);
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candidatesPerDictionarySize.emplace(dictionary.markerSize, vector<MarkerCandidateTree>());
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}
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// create at max 4 marker candidate trees for each dictionary size
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vector<vector<MarkerCandidateTree>> candidatesPerDictionarySize = {{}, {}, {}, {}};
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for (int markerSize : uniqueMarkerSizes) {
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// min marker size is 4, so subtract 4 to get index
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const auto dictionarySizeIndex = markerSize - 4;
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// create candidate trees for each dictionary size
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for (auto& candidatesTreeEntry : candidatesPerDictionarySize) {
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// copy candidates
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vector<vector<Point2f>> candidatesCopy = candidates;
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vector<vector<Point> > contoursCopy = contours;
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candidatesPerDictionarySize[dictionarySizeIndex] = filterTooCloseCandidates(candidatesCopy, contoursCopy, markerSize);
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candidatesTreeEntry.second = filterTooCloseCandidates(candidatesCopy, contoursCopy, candidatesTreeEntry.first);
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}
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candidates.clear();
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contours.clear();
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@ -797,10 +773,9 @@ struct ArucoDetector::ArucoDetectorImpl {
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/// STEP 2: Check candidate codification (identify markers)
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int dictIndex = 0;
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for (const Dictionary& currentDictionary : dictionaries) {
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const auto dictionarySizeIndex = currentDictionary.markerSize - 4;
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// temporary variable to store the current candidates
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vector<vector<Point2f>> currentCandidates;
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identifyCandidates(grey, grey_pyramid, candidatesPerDictionarySize[dictionarySizeIndex], currentCandidates, contours,
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identifyCandidates(grey, grey_pyramid, candidatesPerDictionarySize.at(currentDictionary.markerSize), currentCandidates, contours,
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ids, currentDictionary, rejectedImgPoints);
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if (_dictIndices.needed()) {
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dictIndices.insert(dictIndices.end(), currentCandidates.size(), dictIndex);
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@ -808,29 +783,7 @@ struct ArucoDetector::ArucoDetectorImpl {
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/// STEP 3: Corner refinement :: use corner subpix
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if (detectorParams.cornerRefinementMethod == (int)CORNER_REFINE_SUBPIX) {
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CV_Assert(detectorParams.cornerRefinementWinSize > 0 && detectorParams.cornerRefinementMaxIterations > 0 &&
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detectorParams.cornerRefinementMinAccuracy > 0);
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// Do subpixel estimation. In Aruco3 start on the lowest pyramid level and upscale the corners
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parallel_for_(Range(0, (int)currentCandidates.size()), [&](const Range& range) {
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const int begin = range.start;
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const int end = range.end;
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for (int i = begin; i < end; i++) {
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if (detectorParams.useAruco3Detection) {
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const float scale_init = (float) grey_pyramid[closest_pyr_image_idx].cols / grey.cols;
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findCornerInPyrImage(scale_init, closest_pyr_image_idx, grey_pyramid, Mat(currentCandidates[i]), detectorParams);
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}
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else {
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int cornerRefinementWinSize = std::max(1, cvRound(detectorParams.relativeCornerRefinmentWinSize*
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getAverageModuleSize(currentCandidates[i], currentDictionary.markerSize, detectorParams.markerBorderBits)));
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cornerRefinementWinSize = min(cornerRefinementWinSize, detectorParams.cornerRefinementWinSize);
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cornerSubPix(grey, Mat(currentCandidates[i]), Size(cornerRefinementWinSize, cornerRefinementWinSize), Size(-1, -1),
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TermCriteria(TermCriteria::MAX_ITER | TermCriteria::EPS,
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detectorParams.cornerRefinementMaxIterations,
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detectorParams.cornerRefinementMinAccuracy));
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}
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}
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});
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performCornerSubpixRefinement(grey, grey_pyramid, closest_pyr_image_idx, currentCandidates, currentDictionary);
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}
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candidates.insert(candidates.end(), currentCandidates.begin(), currentCandidates.end());
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dictIndex++;
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@ -1105,6 +1058,30 @@ struct ArucoDetector::ArucoDetectorImpl {
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}
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}
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void performCornerSubpixRefinement(const Mat& grey, const vector<Mat>& grey_pyramid, int closest_pyr_image_idx, const vector<vector<Point2f>>& candidates, const Dictionary& dictionary) const {
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CV_Assert(detectorParams.cornerRefinementWinSize > 0 && detectorParams.cornerRefinementMaxIterations > 0 &&
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detectorParams.cornerRefinementMinAccuracy > 0);
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// Do subpixel estimation. In Aruco3 start on the lowest pyramid level and upscale the corners
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parallel_for_(Range(0, (int)candidates.size()), [&](const Range& range) {
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const int begin = range.start;
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const int end = range.end;
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for (int i = begin; i < end; i++) {
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if (detectorParams.useAruco3Detection) {
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const float scale_init = (float) grey_pyramid[closest_pyr_image_idx].cols / grey.cols;
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findCornerInPyrImage(scale_init, closest_pyr_image_idx, grey_pyramid, Mat(candidates[i]), detectorParams);
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} else {
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int cornerRefinementWinSize = std::max(1, cvRound(detectorParams.relativeCornerRefinmentWinSize*
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getAverageModuleSize(candidates[i], dictionary.markerSize, detectorParams.markerBorderBits)));
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cornerRefinementWinSize = min(cornerRefinementWinSize, detectorParams.cornerRefinementWinSize);
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cornerSubPix(grey, Mat(candidates[i]), Size(cornerRefinementWinSize, cornerRefinementWinSize), Size(-1, -1),
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TermCriteria(TermCriteria::MAX_ITER | TermCriteria::EPS,
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detectorParams.cornerRefinementMaxIterations,
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detectorParams.cornerRefinementMinAccuracy));
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}
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}
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});
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}
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};
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ArucoDetector::ArucoDetector(const Dictionary &_dictionary,
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@ -727,25 +727,55 @@ TEST(CV_ArucoMultiDict, multiMarkerDetection)
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}
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TEST(CV_ArucoMultiDict, multiMarkerDoubleDetection)
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{
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const int markerSidePixels = 100;
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const int imageWidth = 2 * markerSidePixels + 3 * (markerSidePixels / 2);
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const int imageHeight = markerSidePixels + 2 * (markerSidePixels / 2);
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vector<aruco::Dictionary> usedDictionaries = {
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aruco::getPredefinedDictionary(aruco::DICT_5X5_50),
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aruco::getPredefinedDictionary(aruco::DICT_5X5_100)
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};
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// draw synthetic image
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Mat img = Mat(imageHeight, imageWidth, CV_8UC1, Scalar::all(255));
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for(int y = 0; y < 2; y++) {
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Mat marker;
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int id = 49 + y;
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auto dict = aruco::getPredefinedDictionary(aruco::DICT_5X5_100);
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aruco::generateImageMarker(dict, id, markerSidePixels, marker);
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Point2f firstCorner(markerSidePixels / 2.f + y * (1.5f * markerSidePixels),
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markerSidePixels / 2.f);
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Mat aux = img(Rect((int)firstCorner.x, (int)firstCorner.y, markerSidePixels, markerSidePixels));
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marker.copyTo(aux);
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}
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img.convertTo(img, CV_8UC3);
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aruco::ArucoDetector detector(usedDictionaries);
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vector<vector<Point2f> > markerCorners;
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vector<int> markerIds;
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vector<vector<Point2f> > rejectedImgPts;
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vector<int> dictIds;
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detector.detectMarkersMultiDict(img, markerCorners, markerIds, rejectedImgPts, dictIds);
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ASSERT_EQ(markerIds.size(), 3u);
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ASSERT_EQ(dictIds.size(), 3u);
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EXPECT_EQ(dictIds[0], 0); // 5X5_50
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EXPECT_EQ(dictIds[1], 1); // 5X5_100
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EXPECT_EQ(dictIds[2], 1); // 5X5_100
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}
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TEST(CV_ArucoMultiDict, serialization)
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{
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const std::string fileName("test_aruco_serialization.json");
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aruco::ArucoDetector detector;
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{
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FileStorage fs(fileName, FileStorage::Mode::WRITE);
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if (!fs.isOpened()) {
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cout << "[ SKIPPED ] " << "CV_ArucoMultiDict.serialization"
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<< " - Skipping due to 'File system write error.'" << endl;
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return;
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}
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detector.write(fs);
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fs.release();
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FileStorage test_fs(fileName, FileStorage::Mode::READ);
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if (!test_fs.isOpened()) {
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cout << "[ SKIPPED ] " << "CV_ArucoMultiDict.serialization"
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<< " - Skipping due to 'File system read error.'" << endl;
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return;
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}
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FileStorage fs_out(".json", FileStorage::WRITE + FileStorage::MEMORY);
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ASSERT_TRUE(fs_out.isOpened());
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detector.write(fs_out);
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std::string serialized_string = fs_out.releaseAndGetString();
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FileStorage test_fs(serialized_string, FileStorage::Mode::READ + FileStorage::MEMORY);
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ASSERT_TRUE(test_fs.isOpened());
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aruco::ArucoDetector test_detector;
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test_detector.read(test_fs.root());
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// compare default constructor result
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@ -753,20 +783,12 @@ TEST(CV_ArucoMultiDict, serialization)
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}
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detector.setDictionaries({aruco::getPredefinedDictionary(aruco::DICT_4X4_50), aruco::getPredefinedDictionary(aruco::DICT_5X5_100)});
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{
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FileStorage fs(fileName, FileStorage::Mode::WRITE);
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if (!fs.isOpened()) {
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cout << "[ SKIPPED ] " << "CV_ArucoMultiDict.serialization"
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<< " - Skipping due to 'File system write error.'" << endl;
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return;
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}
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detector.write(fs);
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fs.release();
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FileStorage test_fs(fileName, FileStorage::Mode::READ);
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if (!test_fs.isOpened()) {
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cout << "[ SKIPPED ] " << "CV_ArucoMultiDict.serialization"
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<< " - Skipping due to 'File system read error.'" << endl;
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return;
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}
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FileStorage fs_out(".json", FileStorage::WRITE + FileStorage::MEMORY);
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ASSERT_TRUE(fs_out.isOpened());
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detector.write(fs_out);
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std::string serialized_string = fs_out.releaseAndGetString();
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FileStorage test_fs(serialized_string, FileStorage::Mode::READ + FileStorage::MEMORY);
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ASSERT_TRUE(test_fs.isOpened());
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aruco::ArucoDetector test_detector;
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test_detector.read(test_fs.root());
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// check for one additional dictionary
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