[−][src]Struct opencv::core::_InputArray

pub struct _InputArray { /* fields omitted */ }

This is the proxy class for passing read-only input arrays into OpenCV functions.

It is defined as:

   typedef const _InputArray& InputArray;

where _InputArray is a class that can be constructed from Mat, Mat_<T>, Matx<T, m, n>, std::vector<T>, std::vector<std::vector<T> >, std::vector<Mat>, std::vector<Mat_<T> >, UMat, std::vector<UMat> or double. It can also be constructed from a matrix expression.

Since this is mostly implementation-level class, and its interface may change in future versions, we do not describe it in details. There are a few key things, though, that should be kept in mind:

When you see in the reference manual or in OpenCV source code a function that takes InputArray, it means that you can actually pass Mat, Matx, vector<T> etc. (see above the complete list).
Optional input arguments: If some of the input arrays may be empty, pass cv::noArray() (or simply cv::Mat() as you probably did before).
The class is designed solely for passing parameters. That is, normally you should not declare class members, local and global variables of this type.
If you want to design your own function or a class method that can operate of arrays of multiple types, you can use InputArray (or OutputArray) for the respective parameters. Inside a function you should use _InputArray::getMat() method to construct a matrix header for the array (without copying data). _InputArray::kind() can be used to distinguish Mat from vector<> etc., but normally it is not needed.

Here is how you can use a function that takes InputArray :

   std::vector<Point2f> vec;
   // points or a circle
   for( int i = 0; i < 30; i++ )
       vec.push_back(Point2f((float)(100 + 30*cos(i*CV_PI*2/5)),
                              (float)(100 - 30*sin(i*CV_PI*2/5))));
   cv::transform(vec, vec, cv::Matx23f(0.707, -0.707, 10, 0.707, 0.707, 20));

That is, we form an STL vector containing points, and apply in-place affine transformation to the vector using the 2x3 matrix created inline as Matx<float, 2, 3> instance.

Here is how such a function can be implemented (for simplicity, we implement a very specific case of it, according to the assertion statement inside) :

   void myAffineTransform(InputArray _src, OutputArray _dst, InputArray _m)
   {
       // get Mat headers for input arrays. This is O(1) operation,
       // unless _src and/or _m are matrix expressions.
       Mat src = _src.getMat(), m = _m.getMat();
       CV_Assert( src.type() == CV_32FC2 && m.type() == CV_32F && m.size() == Size(3, 2) );
 
       // [re]create the output array so that it has the proper size and type.
       // In case of Mat it calls Mat::create, in case of STL vector it calls vector::resize.
       _dst.create(src.size(), src.type());
       Mat dst = _dst.getMat();
 
       for( int i = 0; i < src.rows; i++ )
           for( int j = 0; j < src.cols; j++ )
           {
               Point2f pt = src.at<Point2f>(i, j);
               dst.at<Point2f>(i, j) = Point2f(m.at<float>(0, 0)*pt.x +
                                                m.at<float>(0, 1)*pt.y +
                                                m.at<float>(0, 2),
                                                m.at<float>(1, 0)*pt.x +
                                                m.at<float>(1, 1)*pt.y +
                                                m.at<float>(1, 2));
           }
   }

There is another related type, InputArrayOfArrays, which is currently defined as a synonym for InputArray:

   typedef InputArray InputArrayOfArrays;

It denotes function arguments that are either vectors of vectors or vectors of matrices. A separate synonym is needed to generate Python/Java etc. wrappers properly. At the function implementation level their use is similar, but _InputArray::getMat(idx) should be used to get header for the idx-th component of the outer vector and _InputArray::size().area() should be used to find the number of components (vectors/matrices) of the outer vector.

In general, type support is limited to cv::Mat types. Other types are forbidden. But in some cases we need to support passing of custom non-general Mat types, like arrays of cv::KeyPoint, cv::DMatch, etc. This data is not intended to be interpreted as an image data, or processed somehow like regular cv::Mat. To pass such custom type use rawIn() / rawOut() / rawInOut() wrappers. Custom type is wrapped as Mat-compatible CV_8UC<N> values (N = sizeof(T), N <= CV_CN_MAX).