Merge pull request #28907 from chacha21:more_autobuffer

More use of AutoBuffer #28907

When possible, AutoBuffer should be faster than std::vector<>, and should not be worse if it requires a heap allocation rather than a stack allocation.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [X] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [X] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake

modules/core/src/matrix_transform.cpp

@@ -558,7 +558,7 @@ void transposeND(InputArray src_, const std::vector<int>& order, OutputArray dst
         CV_CheckEQ(static_cast<size_t>(order_[i]), i, "New order should be a valid permutation of the old one");
     }
 
-    std::vector<int> newShape(order.size());
+    AutoBuffer<int> newShape(order.size());
     for (size_t i = 0; i < order.size(); ++i)
     {
         newShape[i] = inp.size[order[i]];
@@ -582,7 +582,7 @@ void transposeND(InputArray src_, const std::vector<int>& order, OutputArray dst
     size_t continuous_size = continuous_idx == 0 ? out.total() : out.step1(continuous_idx - 1);
     size_t outer_size = out.total() / continuous_size;
 
-    std::vector<size_t> steps(order.size());
+    AutoBuffer<size_t> steps(order.size());
     for (int i = 0; i < static_cast<int>(steps.size()); ++i)
     {
         steps[i] = inp.step1(order[i]);
@@ -1229,7 +1229,7 @@ void broadcast(InputArray _src, InputArray _shape, OutputArray _dst) {
     // impl
     _dst.create(dims_shape, shape.ptr<int>(), src.type());
     Mat dst = _dst.getMat();
-    std::vector<int> is_same_shape(dims_shape, 0);
+    AutoBuffer<int> is_same_shape(dims_shape, 0);
     for (int i = 0; i < static_cast<int>(shape_src.size()); ++i) {
         if (shape_src[i] == ptr_shape[i]) {
             is_same_shape[i] = 1;
@@ -1328,7 +1328,7 @@ void broadcast(InputArray _src, InputArray _shape, OutputArray _dst) {
             std::memcpy(p_dst + dst_offset, p_src + src_offset, dst.elemSize());
         }
         // broadcast copy (dst inplace)
-        std::vector<int> cumulative_shape(dims_shape, 1);
+        AutoBuffer<int> cumulative_shape(dims_shape, 1);
         int total = static_cast<int>(dst.total());
         for (int i = dims_shape - 1; i >= 0; --i) {
             cumulative_shape[i] = static_cast<int>(total / ptr_shape[i]);

modules/core/src/minmax.cpp

@@ -1330,7 +1330,7 @@ static void reduceMinMax(cv::InputArray src, cv::OutputArray dst, ReduceMode mod
     axis = (axis + srcMat.dims) % srcMat.dims;
     CV_Assert(srcMat.channels() == 1 && axis >= 0 && axis < srcMat.dims);
 
-    std::vector<int> sizes(srcMat.dims);
+    cv::AutoBuffer<int> sizes(srcMat.dims);
     std::copy(srcMat.size.p, srcMat.size.p + srcMat.dims, sizes.begin());
     sizes[axis] = 1;
 

modules/core/src/persistence_base64_encoding.cpp

@@ -65,15 +65,15 @@ public:
     /*
      * a convertor must provide :
      * - `operator >> (uchar * & dst)` for writing current binary data to `dst` and moving to next data.
-     * - `operator bool` for checking if current loaction is valid and not the end.
+     * - `operator bool` for checking if current location is valid and not the end.
      */
     template<typename _to_binary_convertor_t> inline
     Base64ContextEmitter & write(_to_binary_convertor_t & convertor)
     {
-        static const size_t BUFFER_MAX_LEN = 1024U;
+        constexpr size_t BUFFER_MAX_LEN = 1024U;
 
-        std::vector<uchar> buffer(BUFFER_MAX_LEN);
-        uchar * beg = buffer.data();
+        uchar buffer[BUFFER_MAX_LEN];
+        uchar * beg = buffer;
         uchar * end = beg;
 
         while (convertor) {

modules/core/src/persistence_types.cpp

@@ -75,7 +75,7 @@ void write( FileStorage& fs, const String& name, const SparseMat& m )
     fs << "data" << "[:";
 
     size_t i = 0, n = m.nzcount();
-    std::vector<const SparseMat::Node*> elems(n);
+    AutoBuffer<const SparseMat::Node*> elems(n);
     SparseMatConstIterator it = m.begin(), it_end = m.end();
 
     for( ; it != it_end; ++it )