mirror of
https://github.com/opencv/opencv.git
synced 2025-07-24 14:06:27 +08:00
Merge remote-tracking branch 'origin/3.4' into merge-3.4
This commit is contained in:
Alexander Smorkalov
commit
004801f1c5
@ -70,7 +70,7 @@ using namespace cv;
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static int icvMkDir( const char* filename )
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{
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char path[PATH_MAX];
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char path[PATH_MAX+1];
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char* p;
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int pos;
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@ -83,7 +83,8 @@ static int icvMkDir( const char* filename )
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mode = 0755;
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#endif /* _WIN32 */
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strcpy( path, filename );
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path[0] = '\0';
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strncat( path, filename, PATH_MAX );
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p = path;
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for( ; ; )
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@ -256,6 +256,7 @@ public:
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//! return codes for cv::solveLP() function
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enum SolveLPResult
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{
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SOLVELP_LOST = -3, //!< problem is feasible, but solver lost solution due to floating-point arithmetic errors
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SOLVELP_UNBOUNDED = -2, //!< problem is unbounded (target function can achieve arbitrary high values)
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SOLVELP_UNFEASIBLE = -1, //!< problem is unfeasible (there are no points that satisfy all the constraints imposed)
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SOLVELP_SINGLE = 0, //!< there is only one maximum for target function
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@ -291,8 +292,12 @@ in the latter case it is understood to correspond to \f$c^T\f$.
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and the remaining to \f$A\f$. It should contain 32- or 64-bit floating point numbers.
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@param z The solution will be returned here as a column-vector - it corresponds to \f$c\f$ in the
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formulation above. It will contain 64-bit floating point numbers.
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@param constr_eps allowed numeric disparity for constraints
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@return One of cv::SolveLPResult
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*/
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CV_EXPORTS_W int solveLP(InputArray Func, InputArray Constr, OutputArray z, double constr_eps);
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/** @overload */
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CV_EXPORTS_W int solveLP(InputArray Func, InputArray Constr, OutputArray z);
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//! @}
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@ -90,7 +90,7 @@ static void swap_columns(Mat_<double>& A,int col1,int col2);
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#define SWAP(type,a,b) {type tmp=(a);(a)=(b);(b)=tmp;}
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//return codes:-2 (no_sol - unbdd),-1(no_sol - unfsbl), 0(single_sol), 1(multiple_sol=>least_l2_norm)
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int solveLP(InputArray Func_, InputArray Constr_, OutputArray z_)
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int solveLP(InputArray Func_, InputArray Constr_, OutputArray z_, double constr_eps)
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{
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dprintf(("call to solveLP\n"));
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@ -143,9 +143,25 @@ int solveLP(InputArray Func_, InputArray Constr_, OutputArray z_)
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}
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z.copyTo(z_);
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//check constraints feasibility
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Mat prod = Constr(Rect(0, 0, Constr.cols - 1, Constr.rows)) * z;
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Mat constr_check = Constr.col(Constr.cols - 1) - prod;
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double min_value = 0.0;
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minMaxIdx(constr_check, &min_value);
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if (min_value < -constr_eps)
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{
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return SOLVELP_LOST;
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}
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return res;
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}
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int solveLP(InputArray Func, InputArray Constr, OutputArray z)
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{
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return solveLP(Func, Constr, z, 1e-12);
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}
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static int initialize_simplex(Mat_<double>& c, Mat_<double>& b,double& v,vector<int>& N,vector<int>& B,vector<unsigned int>& indexToRow){
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N.resize(c.cols);
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N[0]=0;
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@ -255,7 +271,7 @@ static int initialize_simplex(Mat_<double>& c, Mat_<double>& b,double& v,vector<
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static int inner_simplex(Mat_<double>& c, Mat_<double>& b,double& v,vector<int>& N,vector<int>& B,vector<unsigned int>& indexToRow){
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for(;;){
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static MatIterator_<double> pos_ptr;
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MatIterator_<double> pos_ptr;
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int e=-1,pos_ctr=0,min_var=INT_MAX;
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bool all_nonzero=true;
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for(pos_ptr=c.begin();pos_ptr!=c.end();pos_ptr++,pos_ctr++){
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@ -151,4 +151,18 @@ TEST(Core_LPSolver, issue_12337)
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EXPECT_ANY_THROW(Mat1b z_8u; cv::solveLP(A, B, z_8u));
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}
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// NOTE: Test parameters found experimentally to get numerically inaccurate result.
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// The test behaviour may change after algorithm tuning and may removed.
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TEST(Core_LPSolver, issue_12343)
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{
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Mat A = (cv::Mat_<double>(4, 1) << 3., 3., 3., 4.);
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Mat B = (cv::Mat_<double>(4, 5) << 0., 1., 4., 4., 3.,
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3., 1., 2., 2., 3.,
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4., 4., 0., 1., 4.,
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4., 0., 4., 1., 4.);
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Mat z;
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int result = cv::solveLP(A, B, z);
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EXPECT_EQ(SOLVELP_LOST, result);
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}
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}} // namespace
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@ -448,7 +448,7 @@ static void getDistanceTransformMask( int maskType, float *metrics )
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struct DTColumnInvoker : ParallelLoopBody
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{
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DTColumnInvoker( const Mat* _src, Mat* _dst, const int* _sat_tab, const float* _sqr_tab)
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DTColumnInvoker( const Mat* _src, Mat* _dst, const int* _sat_tab, const int* _sqr_tab)
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{
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src = _src;
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dst = _dst;
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@ -481,7 +481,7 @@ struct DTColumnInvoker : ParallelLoopBody
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{
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dist = dist + 1 - sat_tab[dist - d[j]];
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d[j] = dist;
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dptr[0] = sqr_tab[dist];
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dptr[0] = (float)sqr_tab[dist];
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}
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}
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}
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@ -489,12 +489,12 @@ struct DTColumnInvoker : ParallelLoopBody
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const Mat* src;
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Mat* dst;
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const int* sat_tab;
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const float* sqr_tab;
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const int* sqr_tab;
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};
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struct DTRowInvoker : ParallelLoopBody
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{
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DTRowInvoker( Mat* _dst, const float* _sqr_tab, const float* _inv_tab )
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DTRowInvoker( Mat* _dst, const int* _sqr_tab, const float* _inv_tab )
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{
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dst = _dst;
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sqr_tab = _sqr_tab;
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@ -529,7 +529,7 @@ struct DTRowInvoker : ParallelLoopBody
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for(;;k--)
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{
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p = v[k];
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float s = (fq + sqr_tab[q] - d[p] - sqr_tab[p])*inv_tab[q - p];
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float s = (fq - d[p] + (sqr_tab[q]-sqr_tab[p]))*inv_tab[q - p];
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if( s > z[k] )
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{
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k++;
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@ -552,28 +552,28 @@ struct DTRowInvoker : ParallelLoopBody
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}
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Mat* dst;
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const float* sqr_tab;
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const int* sqr_tab;
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const float* inv_tab;
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};
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static void
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trueDistTrans( const Mat& src, Mat& dst )
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{
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const float inf = 1e15f;
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const int inf = INT_MAX;
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CV_Assert( src.size() == dst.size() );
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CV_Assert( src.type() == CV_8UC1 && dst.type() == CV_32FC1 );
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int i, m = src.rows, n = src.cols;
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cv::AutoBuffer<uchar> _buf(std::max(m*2*sizeof(float) + (m*3+1)*sizeof(int), n*2*sizeof(float)));
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cv::AutoBuffer<uchar> _buf(std::max(m*2*sizeof(int) + (m*3+1)*sizeof(int), n*2*sizeof(float)));
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// stage 1: compute 1d distance transform of each column
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float* sqr_tab = (float*)_buf.data();
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int* sqr_tab = (int*)_buf.data();
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int* sat_tab = cv::alignPtr((int*)(sqr_tab + m*2), sizeof(int));
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int shift = m*2;
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for( i = 0; i < m; i++ )
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sqr_tab[i] = (float)(i*i);
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sqr_tab[i] = i*i;
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for( i = m; i < m*2; i++ )
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sqr_tab[i] = inf;
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for( i = 0; i < shift; i++ )
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@ -584,13 +584,14 @@ trueDistTrans( const Mat& src, Mat& dst )
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cv::parallel_for_(cv::Range(0, n), cv::DTColumnInvoker(&src, &dst, sat_tab, sqr_tab), src.total()/(double)(1<<16));
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// stage 2: compute modified distance transform for each row
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float* inv_tab = sqr_tab + n;
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float* inv_tab = (float*)sqr_tab + n;
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inv_tab[0] = sqr_tab[0] = 0.f;
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inv_tab[0] = 0.f;
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sqr_tab[0] = 0;
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for( i = 1; i < n; i++ )
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{
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inv_tab[i] = (float)(0.5/i);
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sqr_tab[i] = (float)(i*i);
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sqr_tab[i] = i*i;
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}
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cv::parallel_for_(cv::Range(0, m), cv::DTRowInvoker(&dst, sqr_tab, inv_tab));
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@ -750,7 +751,9 @@ void cv::distanceTransform( InputArray _src, OutputArray _dst, OutputArray _labe
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CV_IPP_CHECK()
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{
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#if IPP_DISABLE_PERF_TRUE_DIST_MT
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if(cv::getNumThreads()<=1 || (src.total()<(int)(1<<14)))
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// IPP uses floats, but 4097 cannot be squared into a float
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if((cv::getNumThreads()<=1 || (src.total()<(int)(1<<14))) &&
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src.rows < 4097 && src.cols < 4097)
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#endif
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{
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IppStatus status;
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@ -302,4 +302,46 @@ BIGDATA_TEST(Imgproc_DistanceTransform, large_image_12218)
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EXPECT_EQ(nz, (size.height*size.width / 2));
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}
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TEST(Imgproc_DistanceTransform, wide_image_22732)
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{
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Mat src = Mat::zeros(1, 4099, CV_8U); // 4099 or larger used to be bad
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Mat dist(src.rows, src.cols, CV_32F);
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distanceTransform(src, dist, DIST_L2, DIST_MASK_PRECISE, CV_32F);
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int nz = countNonZero(dist);
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EXPECT_EQ(nz, 0);
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}
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TEST(Imgproc_DistanceTransform, large_square_22732)
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{
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Mat src = Mat::zeros(8000, 8005, CV_8U), dist;
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distanceTransform(src, dist, DIST_L2, DIST_MASK_PRECISE, CV_32F);
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int nz = countNonZero(dist);
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EXPECT_EQ(dist.size(), src.size());
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EXPECT_EQ(dist.type(), CV_32F);
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EXPECT_EQ(nz, 0);
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Point p0(src.cols-1, src.rows-1);
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src.setTo(1);
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src.at<uchar>(p0) = 0;
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distanceTransform(src, dist, DIST_L2, DIST_MASK_PRECISE, CV_32F);
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EXPECT_EQ(dist.size(), src.size());
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EXPECT_EQ(dist.type(), CV_32F);
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bool first = true;
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int nerrs = 0;
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for (int y = 0; y < dist.rows; y++)
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for (int x = 0; x < dist.cols; x++) {
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float d = dist.at<float>(y, x);
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double dx = (double)(x - p0.x), dy = (double)(y - p0.y);
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float d0 = (float)sqrt(dx*dx + dy*dy);
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if (std::abs(d0 - d) > 1) {
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if (first) {
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printf("y=%d, x=%d. dist_ref=%.2f, dist=%.2f\n", y, x, d0, d);
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first = false;
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}
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nerrs++;
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}
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}
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EXPECT_EQ(0, nerrs) << "reference distance map is different from computed one at " << nerrs << " pixels\n";
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}
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}} // namespace
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@ -1847,7 +1847,7 @@ int64_t CvCapture_FFMPEG::get_bitrate() const
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double CvCapture_FFMPEG::get_fps() const
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{
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#if 0 && LIBAVFORMAT_BUILD >= CALC_FFMPEG_VERSION(55, 1, 100) && LIBAVFORMAT_VERSION_MICRO >= 100
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#if LIBAVFORMAT_BUILD >= CALC_FFMPEG_VERSION(55, 1, 100) && LIBAVFORMAT_VERSION_MICRO >= 100
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double fps = r2d(av_guess_frame_rate(ic, ic->streams[video_stream], NULL));
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#else
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double fps = r2d(ic->streams[video_stream]->avg_frame_rate);
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@ -101,8 +101,17 @@ if(NOT DEFINED IPHONEOS_DEPLOYMENT_TARGET AND NOT MAC_CATALYST)
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endif()
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if(NOT __IN_TRY_COMPILE)
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set(_xcodebuild_wrapper "${CMAKE_BINARY_DIR}/xcodebuild_wrapper")
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if(NOT EXISTS "${_xcodebuild_wrapper}")
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set(_xcodebuild_wrapper "")
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if(NOT (CMAKE_VERSION VERSION_LESS "3.25.1")) # >= 3.25.1
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# no workaround is required (#23156)
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elseif(NOT (CMAKE_VERSION VERSION_LESS "3.25.0")) # >= 3.25.0 < 3.25.1
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if(NOT OPENCV_SKIP_MESSAGE_ISSUE_23156)
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message(FATAL_ERROR "OpenCV: Please upgrade CMake to 3.25.1+. Current CMake version is ${CMAKE_VERSION}. Details: https://github.com/opencv/opencv/issues/23156")
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endif()
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else() # < 3.25.0, apply workaround from #13912
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set(_xcodebuild_wrapper "${CMAKE_BINARY_DIR}/xcodebuild_wrapper")
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endif()
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if(_xcodebuild_wrapper AND NOT EXISTS "${_xcodebuild_wrapper}")
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set(_xcodebuild_wrapper_tmp "${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/xcodebuild_wrapper")
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if(NOT DEFINED CMAKE_MAKE_PROGRAM) # empty since CMake 3.10
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find_program(XCODEBUILD_PATH "xcodebuild")
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@ -122,7 +131,9 @@ if(NOT __IN_TRY_COMPILE)
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configure_file("${CMAKE_CURRENT_LIST_DIR}/xcodebuild_wrapper.in" "${_xcodebuild_wrapper_tmp}" @ONLY)
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file(COPY "${_xcodebuild_wrapper_tmp}" DESTINATION ${CMAKE_BINARY_DIR} FILE_PERMISSIONS OWNER_READ OWNER_WRITE OWNER_EXECUTE GROUP_READ GROUP_EXECUTE WORLD_READ WORLD_EXECUTE)
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endif()
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set(CMAKE_MAKE_PROGRAM "${_xcodebuild_wrapper}" CACHE INTERNAL "" FORCE)
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if(_xcodebuild_wrapper)
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set(CMAKE_MAKE_PROGRAM "${_xcodebuild_wrapper}" CACHE INTERNAL "" FORCE)
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endif()
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endif()
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# Standard settings
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