This is the proxy class for passing read-only input arrays into OpenCV functions.
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| _InputArray () |
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| _InputArray (int _flags, void *_obj) |
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| _InputArray (const Mat &m) |
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| _InputArray (const MatExpr &expr) |
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| _InputArray (const std::vector< Mat > &vec) |
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template<typename _Tp > |
| _InputArray (const Mat_< _Tp > &m) |
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template<typename _Tp > |
| _InputArray (const std::vector< _Tp > &vec) |
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| _InputArray (const std::vector< bool > &vec) |
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template<typename _Tp > |
| _InputArray (const std::vector< std::vector< _Tp > > &vec) |
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| _InputArray (const std::vector< std::vector< bool > > &)=delete |
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template<typename _Tp > |
| _InputArray (const std::vector< Mat_< _Tp > > &vec) |
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template<typename _Tp > |
| _InputArray (const _Tp *vec, int n) |
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template<typename _Tp , int m, int n> |
| _InputArray (const Matx< _Tp, m, n > &matx) |
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| _InputArray (const double &val) |
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| _InputArray (const cuda::GpuMat &d_mat) |
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| _InputArray (const std::vector< cuda::GpuMat > &d_mat_array) |
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| _InputArray (const ogl::Buffer &buf) |
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| _InputArray (const cuda::HostMem &cuda_mem) |
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template<typename _Tp > |
| _InputArray (const cudev::GpuMat_< _Tp > &m) |
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| _InputArray (const UMat &um) |
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| _InputArray (const std::vector< UMat > &umv) |
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template<typename _Tp , std::size_t _Nm> |
| _InputArray (const std::array< _Tp, _Nm > &arr) |
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template<std::size_t _Nm> |
| _InputArray (const std::array< Mat, _Nm > &arr) |
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| ~_InputArray () |
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int | channels (int i=-1) const |
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int | cols (int i=-1) const |
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void | copyTo (const _OutputArray &arr) const |
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void | copyTo (const _OutputArray &arr, const _InputArray &mask) const |
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int | depth (int i=-1) const |
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int | dims (int i=-1) const |
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bool | empty () const |
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int | getFlags () const |
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cuda::GpuMat | getGpuMat () const |
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void | getGpuMatVector (std::vector< cuda::GpuMat > &gpumv) const |
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Mat | getMat (int idx=-1) const |
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Mat | getMat_ (int idx=-1) const |
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void | getMatVector (std::vector< Mat > &mv) const |
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void * | getObj () const |
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ogl::Buffer | getOGlBuffer () const |
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Size | getSz () const |
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UMat | getUMat (int idx=-1) const |
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void | getUMatVector (std::vector< UMat > &umv) const |
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bool | isContinuous (int i=-1) const |
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bool | isGpuMat () const |
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bool | isGpuMatVector () const |
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bool | isMat () const |
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bool | isMatVector () const |
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bool | isMatx () const |
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bool | isSubmatrix (int i=-1) const |
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bool | isUMat () const |
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bool | isUMatVector () const |
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bool | isVector () const |
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_InputArray::KindFlag | kind () const |
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size_t | offset (int i=-1) const |
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int | rows (int i=-1) const |
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bool | sameSize (const _InputArray &arr) const |
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Size | size (int i=-1) const |
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int | sizend (int *sz, int i=-1) const |
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size_t | step (int i=-1) const |
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size_t | total (int i=-1) const |
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int | type (int i=-1) const |
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This is the proxy class for passing read-only input arrays into OpenCV functions.
It is defined as:
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;
for( int i = 0; i < 30; i++ )
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)
{
Mat src = _src.getMat(), m = _m.getMat();
_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++ )
{
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:
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 intented 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).
- Examples:
- samples/cpp/pca.cpp, and samples/cpp/peopledetect.cpp.