Refinement of BlobShape API explicit BlobShape(int,int) constructor was removed

BlobShape::all(int, int) substitutes explicit BlobShape(int,int)
added new intuitive constructors: BlobShape(s0); BlobShape(s0, s1)...
added corresponding tests

modules/dnn/include/opencv2/dnn/blob.hpp

@@ -55,13 +55,21 @@ namespace dnn
     /** @brief Lightweight class for storing and processing a shape of blob (or anything else). */
     struct BlobShape
     {
-        explicit BlobShape(int ndims = 4, int fill = 1);    //!< Creates n-dim shape and fill its by @p fill
+        BlobShape();                                        //!< Returns @ref all(4, 1)
+        BlobShape(int s0);                                  //!< Creates 1-dim shape [@p s0]
+        BlobShape(int s0, int s1);                          //!< @overload
+        BlobShape(int s0, int s1, int s2);                  //!< @overload
         BlobShape(int num, int cn, int rows, int cols);     //!< Creates 4-dim shape [@p num, @p cn, @p rows, @p cols]
-        BlobShape(int ndims, const int *sizes);             //!< Creates n-dim shape from the @p sizes array
+
+        //! Creates n-dim shape from the @p sizes array; if @p sizes is NULL then shape will contain unspecified data
+        BlobShape(int ndims, const int *sizes);
         BlobShape(const std::vector<int> &sizes);           //!< Creates n-dim shape from the @p sizes vector
         template<int n>
         BlobShape(const Vec<int, n> &shape);                //!< Creates n-dim shape from @ref cv::Vec
 
+        //! Creates n-dim shape and fill its by @p fill
+        static BlobShape all(int ndims, int fill = 1);
+
         /** @brief Returns number of dimensions. */
         int dims() const;
 

modules/dnn/include/opencv2/dnn/blob.inl.hpp

@@ -48,20 +48,50 @@ namespace cv
 namespace dnn
 {
 
-inline BlobShape::BlobShape(int ndims, int fill) : sz( (size_t)std::max(ndims, 0) )
+inline BlobShape::BlobShape()
+{
+    sz.allocate(4);
+    for (size_t i = 0; i < sz.size(); i++)
+        sz[i] = 1;
+}
+
+inline BlobShape BlobShape::all(int ndims, int fill)
 {
     CV_Assert(ndims >= 0);
+    BlobShape res;
+    res.sz.allocate(ndims);
     for (int i = 0; i < ndims; i++)
-        sz[i] = fill;
+        res.sz[i] = fill;
+    return res;
 }
 
 inline BlobShape::BlobShape(int ndims, const int *sizes) : sz( (size_t)std::max(ndims, 0) )
 {
     CV_Assert(ndims >= 0);
+    if (!sizes)
+        return;
     for (int i = 0; i < ndims; i++)
         sz[i] = sizes[i];
 }
 
+inline BlobShape::BlobShape(int s0) : sz(1)
+{
+    sz[0] = s0;
+}
+
+inline BlobShape::BlobShape(int s0, int s1) : sz(2)
+{
+    sz[0] = s0;
+    sz[1] = s1;
+}
+
+inline BlobShape::BlobShape(int s0, int s1, int s2) : sz(3)
+{
+    sz[0] = s0;
+    sz[1] = s1;
+    sz[2] = s2;
+}
+
 inline BlobShape::BlobShape(int num, int cn, int rows, int cols) : sz(4)
 {
     sz[0] = num;

modules/dnn/src/blob.cpp

@@ -59,7 +59,7 @@ namespace dnn
 
     static BlobShape getBlobShape(std::vector<Mat> &vmat, int requestedCn = -1)
     {
-        BlobShape shape(4);
+        BlobShape shape(BlobShape::all(4));
         int cnSum = 0, matCn;
 
         CV_Assert(vmat.size() > 0);

modules/dnn/src/caffe/caffe_importer.cpp

@@ -191,7 +191,7 @@ namespace
             else if (pbBlob.has_shape())
             {
                 const caffe::BlobShape &_shape = pbBlob.shape();
-                BlobShape shape(_shape.dim_size());
+                BlobShape shape = BlobShape::all(_shape.dim_size());
 
                 for (int i = 0; i < _shape.dim_size(); i++)
                     shape[i] = (int)_shape.dim(i);
@@ -201,7 +201,7 @@ namespace
             else
             {
                 CV_Error(Error::StsError, "Unknown shape of input blob");
-                return BlobShape(-1);
+                return BlobShape();
             }
         }
 

modules/dnn/src/layers/op_blas.cpp

@@ -76,9 +76,10 @@ void setBlasThreads(int numThreads)
     openblas_set_num_threads(numThreads);
     goto_set_num_threads(numThreads);
     #else
-    numThreads = 0; //suppress compiler's warning
+    (void)numThreads;   //suppress compilers' warning
+    numThreads = 0;
     #endif
 }
 
 }
-}
\ No newline at end of file
+}

modules/dnn/src/layers/reshape_layer.cpp

@@ -58,12 +58,12 @@ ReshapeLayer::ReshapeLayer(LayerParams &params) : Layer(params)
 
     if (!params.has("dim"))
     {
-        shapeDesc = BlobShape(0);
+        shapeDesc = BlobShape::all(0);
         return;
     }
 
     DictValue paramShape = params.get("dim");
-    shapeDesc = BlobShape(paramShape.size());
+    shapeDesc = BlobShape::all(paramShape.size());
 
     for (int i = 0; i < paramShape.size(); i++)
     {
@@ -97,7 +97,7 @@ void ReshapeLayer::allocate(const std::vector<Blob*> &inputs, std::vector<Blob>
         CV_Assert(0 <= endAxis && endAxis <= inpShape.dims());
 
         int newDims = inpShape.dims() - (endAxis - startAxis) + shapeDesc.dims();
-        BlobShape outShape(newDims);
+        BlobShape outShape = BlobShape::all(newDims);
 
         computeOutputShape(startAxis, endAxis, inpShape, outShape);
 

modules/dnn/test/test_layers.cpp

@@ -190,9 +190,9 @@ public:
         Nx = _Nx;
         Nc = _Nc;
 
-        Wh = Blob(BlobShape(Vec2i(4 * Nc, Nc)));
-        Wx = Blob(BlobShape(Vec2i(4 * Nc, Nx)));
-        b  = Blob(BlobShape(Vec2i(4 * Nc, 1)));
+        Wh = Blob(BlobShape(4 * Nc, Nc));
+        Wx = Blob(BlobShape(4 * Nc, Nx));
+        b  = Blob(BlobShape(4 * Nc, 1));
 
         layer = LSTMLayer::create();
         layer->setWeights(Wh, Wx, b);
@@ -248,11 +248,11 @@ public:
         Nh = _Nh;
         No = _No;
 
-        Whh = Blob(BlobShape(Vec2i(Nh, Nh)));
-        Wxh = Blob(BlobShape(Vec2i(Nh, Nx)));
-        bh  = Blob(BlobShape(Vec2i(Nh, 1)));
-        Who = Blob(BlobShape(Vec2i(No, Nh)));
-        bo  = Blob(BlobShape(Vec2i(No, 1)));
+        Whh = Blob(BlobShape(Nh, Nh));
+        Wxh = Blob(BlobShape(Nh, Nx));
+        bh  = Blob(BlobShape(Nh, 1));
+        Who = Blob(BlobShape(No, Nh));
+        bo  = Blob(BlobShape(No, 1));
 
         layer = RNNLayer::create();
         layer->setWeights(Whh, Wxh, bh, Who, bo);

modules/dnn/test/test_main.cpp

 #include "test_precomp.hpp"
 
 CV_TEST_MAIN("")
+
+namespace cvtest
+{
+
+using namespace cv;
+using namespace cv::dnn;
+
+TEST(BlobShape_SimpleConstr, Regression)
+{
+    BlobShape sd;
+
+    BlobShape s1(0);
+    EXPECT_EQ(s1.dims(), 1);
+    EXPECT_EQ(s1[0], 0);
+
+    BlobShape s2(0, 0);
+    EXPECT_EQ(s2.dims(), 2);
+    EXPECT_EQ(s2[0], 0);
+    EXPECT_EQ(s2[1], 0);
+}
+
+TEST(BlobShape_EmptyFill, Regression)
+{
+    BlobShape s(10, (int*)NULL);
+    EXPECT_EQ(s.dims(), 10);
+}
+
+}