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Merge pull request #16415 from arnaudbrejeon:bug_fix_16410
* Fix bug 16410 and add test
* imgproc(connectedcomponents): avoid manual uninitialized allocations
* imgproc(connectedcomponents): force 'odd' chunk range size
* imgproc(connectedcomponents): reuse stripeFirstLabel{4/8}Connectivity
* imgproc(connectedcomponents): extend fix from PR14964
This commit is contained in:
Arnaud Brejeon
GitHub
parent
48c8c95381
commit
ecbba852cf
@ -265,6 +265,21 @@ namespace cv{
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}
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}
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template <typename LT> static inline
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LT stripeFirstLabel4Connectivity(int y, int w)
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{
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CV_DbgAssert((y & 1) == 0);
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return (LT(y) * LT(w) /*+ 1*/) / 2 + 1;
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}
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template <typename LT> static inline
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LT stripeFirstLabel8Connectivity(int y, int w)
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{
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CV_DbgAssert((y & 1) == 0);
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return LT((y /*+ 1*/) / 2) * LT((w + 1) / 2) + 1;
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}
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//Based on "Two Strategies to Speed up Connected Components Algorithms", the SAUF (Scan array union find) variant
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//using decision trees
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//Kesheng Wu, et al
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@ -283,12 +298,14 @@ namespace cv{
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FirstScan8Connectivity& operator=(const FirstScan8Connectivity& ) { return *this; }
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void operator()(const cv::Range& range) const CV_OVERRIDE
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void operator()(const cv::Range& range2) const CV_OVERRIDE
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{
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const Range range(range2.start * 2, std::min(range2.end * 2, img_.rows));
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int r = range.start;
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chunksSizeAndLabels_[r] = range.end;
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LabelT label = LabelT((r + 1) / 2) * LabelT((imgLabels_.cols + 1) / 2) + 1;
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LabelT label = stripeFirstLabel8Connectivity<LabelT>(r, imgLabels_.cols);
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const LabelT firstLabel = label;
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const int w = img_.cols;
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@ -385,12 +402,14 @@ namespace cv{
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FirstScan4Connectivity& operator=(const FirstScan4Connectivity& ) { return *this; }
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void operator()(const cv::Range& range) const CV_OVERRIDE
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void operator()(const cv::Range& range2) const CV_OVERRIDE
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{
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const Range range(range2.start * 2, std::min(range2.end * 2, img_.rows));
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int r = range.start;
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chunksSizeAndLabels_[r] = range.end;
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LabelT label = LabelT((r * imgLabels_.cols + 1) / 2 + 1);
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LabelT label = stripeFirstLabel4Connectivity<LabelT>(r, imgLabels_.cols);
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const LabelT firstLabel = label;
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const int w = img_.cols;
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@ -462,8 +481,9 @@ namespace cv{
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SecondScan& operator=(const SecondScan& ) { return *this; }
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void operator()(const cv::Range& range) const CV_OVERRIDE
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void operator()(const cv::Range& range2) const CV_OVERRIDE
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{
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const Range range(range2.start * 2, std::min(range2.end * 2, imgLabels_.rows));
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int r = range.start;
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const int rowBegin = r;
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const int rowEnd = range.end;
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@ -595,53 +615,51 @@ namespace cv{
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//Array used to store info and labeled pixel by each thread.
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//Different threads affect different memory location of chunksSizeAndLabels
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int *chunksSizeAndLabels = (int *)cv::fastMalloc(h * sizeof(int));
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std::vector<int> chunksSizeAndLabels(roundUp(h, 2));
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//Tree of labels
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LabelT *P = (LabelT *)cv::fastMalloc(Plength * sizeof(LabelT));
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std::vector<LabelT> P_(Plength, 0);
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LabelT *P = P_.data();
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//First label is for background
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P[0] = 0;
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//P[0] = 0;
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cv::Range range(0, h);
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cv::Range range2(0, divUp(h, 2));
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const double nParallelStripes = std::max(1, std::min(h / 2, getNumThreads()*4));
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LabelT nLabels = 1;
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if (connectivity == 8){
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//First scan
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cv::parallel_for_(range, FirstScan8Connectivity(img, imgLabels, P, chunksSizeAndLabels), nParallelStripes);
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cv::parallel_for_(range2, FirstScan8Connectivity(img, imgLabels, P, chunksSizeAndLabels.data()), nParallelStripes);
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//merge labels of different chunks
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mergeLabels8Connectivity(imgLabels, P, chunksSizeAndLabels);
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mergeLabels8Connectivity(imgLabels, P, chunksSizeAndLabels.data());
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for (int i = 0; i < h; i = chunksSizeAndLabels[i]){
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flattenL(P, int((i + 1) / 2) * int((w + 1) / 2) + 1, chunksSizeAndLabels[i + 1], nLabels);
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flattenL(P, stripeFirstLabel8Connectivity<int>(i, w), chunksSizeAndLabels[i + 1], nLabels);
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}
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}
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else{
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//First scan
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cv::parallel_for_(range, FirstScan4Connectivity(img, imgLabels, P, chunksSizeAndLabels), nParallelStripes);
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cv::parallel_for_(range2, FirstScan4Connectivity(img, imgLabels, P, chunksSizeAndLabels.data()), nParallelStripes);
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//merge labels of different chunks
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mergeLabels4Connectivity(imgLabels, P, chunksSizeAndLabels);
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mergeLabels4Connectivity(imgLabels, P, chunksSizeAndLabels.data());
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for (int i = 0; i < h; i = chunksSizeAndLabels[i]){
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flattenL(P, int(i * w + 1) / 2 + 1, chunksSizeAndLabels[i + 1], nLabels);
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flattenL(P, stripeFirstLabel4Connectivity<int>(i, w), chunksSizeAndLabels[i + 1], nLabels);
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}
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}
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//Array for statistics dataof threads
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StatsOp *sopArray = new StatsOp[h];
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std::vector<StatsOp> sopArray(h);
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sop.init(nLabels);
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//Second scan
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cv::parallel_for_(range, SecondScan(imgLabels, P, sop, sopArray, nLabels), nParallelStripes);
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StatsOp::mergeStats(imgLabels, sopArray, sop, nLabels);
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cv::parallel_for_(range2, SecondScan(imgLabels, P, sop, sopArray.data(), nLabels), nParallelStripes);
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StatsOp::mergeStats(imgLabels, sopArray.data(), sop, nLabels);
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sop.finish();
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delete[] sopArray;
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cv::fastFree(chunksSizeAndLabels);
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cv::fastFree(P);
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return nLabels;
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}
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};//End struct LabelingWuParallel
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@ -671,9 +689,10 @@ namespace cv{
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//Obviously, 4-way connectivity upper bound is also good for 8-way connectivity labeling
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const size_t Plength = (size_t(h) * size_t(w) + 1) / 2 + 1;
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//array P for equivalences resolution
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LabelT *P = (LabelT *)fastMalloc(sizeof(LabelT) *Plength);
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std::vector<LabelT> P_(Plength, 0);
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LabelT *P = P_.data();
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//first label is for background pixels
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P[0] = 0;
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//P[0] = 0;
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LabelT lunique = 1;
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if (connectivity == 8){
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@ -811,7 +830,6 @@ namespace cv{
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}
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sop.finish();
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fastFree(P);
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return nLabels;
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}//End function LabelingWu operator()
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@ -836,14 +854,14 @@ namespace cv{
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FirstScan& operator=(const FirstScan&) { return *this; }
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void operator()(const cv::Range& range) const CV_OVERRIDE
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void operator()(const cv::Range& range2) const CV_OVERRIDE
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{
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const Range range(range2.start * 2, std::min(range2.end * 2, img_.rows));
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int r = range.start;
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r += (r % 2);
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chunksSizeAndLabels_[r] = range.end + (range.end % 2);
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chunksSizeAndLabels_[r] = range.end;
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LabelT label = LabelT((r + 1) / 2) * LabelT((imgLabels_.cols + 1) / 2) + 1;
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LabelT label = stripeFirstLabel8Connectivity<LabelT>(r, imgLabels_.cols);
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const LabelT firstLabel = label;
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const int h = img_.rows, w = img_.cols;
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@ -1902,14 +1920,13 @@ namespace cv{
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SecondScan(const cv::Mat& img, cv::Mat& imgLabels, LabelT *P, StatsOp& sop, StatsOp *sopArray, LabelT& nLabels)
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: img_(img), imgLabels_(imgLabels), P_(P), sop_(sop), sopArray_(sopArray), nLabels_(nLabels){}
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SecondScan& operator=(const SecondScan& ) { return *this; }
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void operator()(const cv::Range& range) const CV_OVERRIDE
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void operator()(const cv::Range& range2) const CV_OVERRIDE
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{
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const Range range(range2.start * 2, std::min(range2.end * 2, img_.rows));
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int r = range.start;
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r += (r % 2);
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const int rowBegin = r;
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const int rowEnd = range.end + range.end % 2;
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const int rowEnd = range.end;
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if (rowBegin > 0){
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sopArray_[rowBegin].initElement(nLabels_);
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@ -2542,36 +2559,35 @@ namespace cv{
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//Array used to store info and labeled pixel by each thread.
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//Different threads affect different memory location of chunksSizeAndLabels
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const int chunksSizeAndLabelsSize = h + 1;
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cv::AutoBuffer<int, 0> chunksSizeAndLabels(chunksSizeAndLabelsSize);
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const int chunksSizeAndLabelsSize = roundUp(h, 2);
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std::vector<int> chunksSizeAndLabels(chunksSizeAndLabelsSize);
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//Tree of labels
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cv::AutoBuffer<LabelT, 0> P(Plength);
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std::vector<LabelT> P(Plength, 0);
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//First label is for background
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P[0] = 0;
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//P[0] = 0;
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cv::Range range(0, h);
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cv::Range range2(0, divUp(h, 2));
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const double nParallelStripes = std::max(1, std::min(h / 2, getNumThreads()*4));
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//First scan, each thread works with chunk of img.rows/nThreads rows
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//e.g. 300 rows, 4 threads -> each chunks is composed of 75 rows
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cv::parallel_for_(range, FirstScan(img, imgLabels, P.data(), chunksSizeAndLabels.data()), nParallelStripes);
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//First scan
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cv::parallel_for_(range2, FirstScan(img, imgLabels, P.data(), chunksSizeAndLabels.data()), nParallelStripes);
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//merge labels of different chunks
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mergeLabels(img, imgLabels, P.data(), chunksSizeAndLabels.data());
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LabelT nLabels = 1;
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for (int i = 0; i < h; i = chunksSizeAndLabels[i]){
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CV_Assert(i + 1 < chunksSizeAndLabelsSize);
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flattenL(P.data(), LabelT((i + 1) / 2) * LabelT((w + 1) / 2) + 1, chunksSizeAndLabels[i + 1], nLabels);
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CV_DbgAssert(i + 1 < chunksSizeAndLabelsSize);
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flattenL(P.data(), stripeFirstLabel8Connectivity<LabelT>(i, w), chunksSizeAndLabels[i + 1], nLabels);
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}
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//Array for statistics data
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cv::AutoBuffer<StatsOp, 0> sopArray(h);
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std::vector<StatsOp> sopArray(h);
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sop.init(nLabels);
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//Second scan
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cv::parallel_for_(range, SecondScan(img, imgLabels, P.data(), sop, sopArray.data(), nLabels), nParallelStripes);
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cv::parallel_for_(range2, SecondScan(img, imgLabels, P.data(), sop, sopArray.data(), nLabels), nParallelStripes);
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StatsOp::mergeStats(imgLabels, sopArray.data(), sop, nLabels);
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sop.finish();
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@ -2602,8 +2618,9 @@ namespace cv{
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//............
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const size_t Plength = size_t(((h + 1) / 2) * size_t((w + 1) / 2)) + 1;
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LabelT *P = (LabelT *)fastMalloc(sizeof(LabelT) *Plength);
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P[0] = 0;
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std::vector<LabelT> P_(Plength, 0);
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LabelT *P = P_.data();
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//P[0] = 0;
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LabelT lunique = 1;
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// First scan
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@ -3911,7 +3928,6 @@ namespace cv{
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}
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sop.finish();
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fastFree(P);
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return nLabels;
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@ -150,4 +150,80 @@ TEST(Imgproc_ConnectedComponents, grana_buffer_overflow)
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EXPECT_EQ(1, nbComponents);
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}
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static cv::Mat createCrashMat(int numThreads) {
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const int h = numThreads * 4 * 2 + 8;
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const double nParallelStripes = std::max(1, std::min(h / 2, numThreads * 4));
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const int w = 4;
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const int nstripes = cvRound(nParallelStripes <= 0 ? h : MIN(MAX(nParallelStripes, 1.), h));
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const cv::Range stripeRange(0, nstripes);
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const cv::Range wholeRange(0, h);
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cv::Mat m(h, w, CV_8U);
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m = 0;
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// Look for a range that starts with odd value and ends with even value
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cv::Range bugRange;
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for (int s = stripeRange.start; s < stripeRange.end; s++) {
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cv::Range sr(s, s + 1);
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cv::Range r;
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r.start = (int) (wholeRange.start +
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((uint64) sr.start * (wholeRange.end - wholeRange.start) + nstripes / 2) / nstripes);
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r.end = sr.end >= nstripes ?
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wholeRange.end :
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(int) (wholeRange.start +
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((uint64) sr.end * (wholeRange.end - wholeRange.start) + nstripes / 2) / nstripes);
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if (r.start > 0 && r.start % 2 == 1 && r.end % 2 == 0 && r.end >= r.start + 2) {
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bugRange = r;
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break;
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}
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}
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if (bugRange.empty()) { // Could not create a buggy range
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return m;
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}
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// Fill in bug Range
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for (int x = 1; x < w; x++) {
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m.at<char>(bugRange.start - 1, x) = 1;
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}
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m.at<char>(bugRange.start + 0, 0) = 1;
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m.at<char>(bugRange.start + 0, 1) = 1;
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m.at<char>(bugRange.start + 0, 3) = 1;
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m.at<char>(bugRange.start + 1, 1) = 1;
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m.at<char>(bugRange.start + 2, 1) = 1;
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m.at<char>(bugRange.start + 2, 3) = 1;
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m.at<char>(bugRange.start + 3, 0) = 1;
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m.at<char>(bugRange.start + 3, 1) = 1;
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return m;
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}
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TEST(Imgproc_ConnectedComponents, parallel_wu_labels)
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{
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cv::Mat mat = createCrashMat(cv::getNumThreads());
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if(mat.empty()) {
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return;
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}
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const int nbPixels = cv::countNonZero(mat);
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cv::Mat labels;
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cv::Mat stats;
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cv::Mat centroids;
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int nb = 0;
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EXPECT_NO_THROW( nb = cv::connectedComponentsWithStats(mat, labels, stats, centroids, 8, CV_32S, cv::CCL_WU) );
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int area = 0;
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for(int i=1; i<nb; ++i) {
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area += stats.at<int32_t>(i, cv::CC_STAT_AREA);
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}
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EXPECT_EQ(nbPixels, area);
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}
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}} // namespace
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