Struct opencv::core::_InputArray
source · pub struct _InputArray { /* private fields */ }
Expand description
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).