OpenCV
4.10.0
Open Source Computer Vision
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Deprecated List
File
block.hpp
Use
Device layer
instead.
File
border_interpolate.hpp
Use
Device layer
instead.
File
color.hpp
Use
Device layer
instead.
File
common.hpp
Use
Device layer
instead.
File
core.hpp
Use <
opencv2/gapi/ocl/core.hpp
> instead.
File
cuda_types.hpp
Use
Device layer
instead.
Member
cv::Algorithm::write
(const Ptr< FileStorage > &fs, const String &name=
String()
) const
Member
cv::aruco::calibrateCameraAruco
(InputArrayOfArrays corners, InputArray ids, InputArray counter, const Ptr< Board > &board, Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, OutputArray stdDeviationsIntrinsics, OutputArray stdDeviationsExtrinsics, OutputArray perViewErrors, int flags=0, const
TermCriteria
&criteria=
TermCriteria
(
TermCriteria::COUNT
+
TermCriteria::EPS
, 30, DBL_EPSILON))
Use
Board::matchImagePoints
and
cv::solvePnP
Member
cv::aruco::calibrateCameraAruco
(InputArrayOfArrays corners, InputArray ids, InputArray counter, const Ptr< Board > &board, Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, OutputArrayOfArrays rvecs=
noArray()
, OutputArrayOfArrays tvecs=
noArray()
, int flags=0, const
TermCriteria
&criteria=
TermCriteria
(
TermCriteria::COUNT
+
TermCriteria::EPS
, 30, DBL_EPSILON))
Use
Board::matchImagePoints
and
cv::solvePnP
Member
cv::aruco::calibrateCameraCharuco
(InputArrayOfArrays charucoCorners, InputArrayOfArrays charucoIds, const Ptr< CharucoBoard > &board, Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, OutputArrayOfArrays rvecs=
noArray()
, OutputArrayOfArrays tvecs=
noArray()
, int flags=0, const
TermCriteria
&criteria=
TermCriteria
(
TermCriteria::COUNT
+
TermCriteria::EPS
, 30, DBL_EPSILON))
Use
CharucoBoard::matchImagePoints
and
cv::solvePnP
Member
cv::aruco::calibrateCameraCharuco
(InputArrayOfArrays charucoCorners, InputArrayOfArrays charucoIds, const Ptr< CharucoBoard > &board, Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, OutputArray stdDeviationsIntrinsics, OutputArray stdDeviationsExtrinsics, OutputArray perViewErrors, int flags=0, const
TermCriteria
&criteria=
TermCriteria
(
TermCriteria::COUNT
+
TermCriteria::EPS
, 30, DBL_EPSILON))
Use
CharucoBoard::matchImagePoints
and
cv::solvePnP
Member
cv::aruco::detectCharucoDiamond
(InputArray image, InputArrayOfArrays markerCorners, InputArray markerIds, float squareMarkerLengthRate, OutputArrayOfArrays diamondCorners, OutputArray diamondIds, InputArray cameraMatrix=
noArray()
, InputArray distCoeffs=
noArray()
, Ptr< Dictionary > dictionary=makePtr< Dictionary >(getPredefinedDictionary(PredefinedDictionaryType::DICT_4X4_50)))
Use
CharucoDetector::detectDiamonds
Member
cv::aruco::detectMarkers
(InputArray image, const Ptr< Dictionary > &dictionary, OutputArrayOfArrays corners, OutputArray ids, const Ptr< DetectorParameters > ¶meters=
makePtr< DetectorParameters >()
, OutputArrayOfArrays rejectedImgPoints=
noArray()
)
Use class
ArucoDetector::detectMarkers
Member
cv::aruco::drawCharucoDiamond
(const Ptr< Dictionary > &dictionary, Vec4i ids, int squareLength, int markerLength, OutputArray img, int marginSize=0, int borderBits=1)
Use
CharucoBoard::generateImage()
Member
cv::aruco::drawPlanarBoard
(const Ptr< Board > &board, Size outSize, OutputArray img, int marginSize, int borderBits)
Use
Board::generateImage
Struct
cv::aruco::EstimateParameters
Use
Board::matchImagePoints
and
cv::solvePnP
Member
cv::aruco::estimatePoseBoard
(InputArrayOfArrays corners, InputArray ids, const Ptr< Board > &board, InputArray cameraMatrix, InputArray distCoeffs, InputOutputArray rvec, InputOutputArray tvec, bool useExtrinsicGuess=false)
Use
Board::matchImagePoints
and
cv::solvePnP
Member
cv::aruco::estimatePoseCharucoBoard
(InputArray charucoCorners, InputArray charucoIds, const Ptr< CharucoBoard > &board, InputArray cameraMatrix, InputArray distCoeffs, InputOutputArray rvec, InputOutputArray tvec, bool useExtrinsicGuess=false)
Use
CharucoBoard::matchImagePoints
and
cv::solvePnP
Member
cv::aruco::estimatePoseSingleMarkers
(InputArrayOfArrays corners, float markerLength, InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvecs, OutputArray tvecs, OutputArray objPoints=
noArray()
, const Ptr< EstimateParameters > &estimateParameters=
makePtr< EstimateParameters >()
)
Use
cv::solvePnP
Member
cv::aruco::getBoardObjectAndImagePoints
(const Ptr< Board > &board, InputArrayOfArrays detectedCorners, InputArray detectedIds, OutputArray objPoints, OutputArray imgPoints)
Use
Board::matchImagePoints
Member
cv::aruco::interpolateCornersCharuco
(InputArrayOfArrays markerCorners, InputArray markerIds, InputArray image, const Ptr< CharucoBoard > &board, OutputArray charucoCorners, OutputArray charucoIds, InputArray cameraMatrix=
noArray()
, InputArray distCoeffs=
noArray()
, int minMarkers=2)
Use
CharucoDetector::detectBoard
Member
cv::aruco::PatternPositionType
Use
Board::matchImagePoints
and
cv::solvePnP
Member
cv::aruco::refineDetectedMarkers
(InputArray image, const Ptr< Board > &board, InputOutputArrayOfArrays detectedCorners, InputOutputArray detectedIds, InputOutputArrayOfArrays rejectedCorners, InputArray cameraMatrix=
noArray()
, InputArray distCoeffs=
noArray()
, float minRepDistance=10.f, float errorCorrectionRate=3.f, bool checkAllOrders=true, OutputArray recoveredIdxs=
noArray()
, const Ptr< DetectorParameters > ¶meters=
makePtr< DetectorParameters >()
)
Use class
ArucoDetector::refineDetectedMarkers
Member
cv::aruco::testCharucoCornersCollinear
(const Ptr< CharucoBoard > &board, InputArray charucoIds)
Use
CharucoBoard::checkCharucoCornersCollinear
Member
cv::convertFp16
(InputArray src, OutputArray dst)
Use
Mat::convertTo
with CV_16F instead.
Member
cv::createStitcher
(bool try_use_gpu=false)
use
Stitcher::create
Member
cv::createStitcherScans
(bool try_use_gpu=false)
use
Stitcher::create
Member
cv::dnn::getInferenceEngineBackendType
()
Member
cv::dnn::Layer::finalize
(const std::vector< Mat > &inputs)
Use
Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays)
instead
Member
cv::dnn::Layer::finalize
(const std::vector< Mat > &inputs, std::vector< Mat > &outputs)
Use
Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays)
instead
Member
cv::dnn::Layer::finalize
(const std::vector< Mat * > &input, std::vector< Mat > &output)
Use
Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays)
instead
Member
cv::dnn::Layer::forward
(std::vector< Mat * > &input, std::vector< Mat > &output, std::vector< Mat > &internals)
Use
Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays)
instead
Member
cv::dnn::Layer::run
(const std::vector< Mat > &inputs, std::vector< Mat > &outputs, std::vector< Mat > &internals)
This method will be removed in the future release.
Member
cv::dnn::LSTMLayer::setProduceCellOutput
(bool produce=false)=0
Use flag
use_timestamp_dim
in
LayerParams
.
Member
cv::dnn::LSTMLayer::setUseTimstampsDim
(bool use=true)=0
Use flag
produce_cell_output
in
LayerParams
.
Member
cv::dnn::LSTMLayer::setWeights
(const
Mat
&Wh, const
Mat
&Wx, const
Mat
&b)=0
Use
LayerParams::blobs
instead.
Member
cv::dnn::Net::getLayer
(const LayerId &layerId) const
to be removed
Member
cv::dnn::Net::getLayer
(const String &layerName) const
Use int getLayerId(const String &layer)
Member
cv::dnn::Net::LayerId
Use
getLayerId()
with int result.
Member
cv::dnn::setInferenceEngineBackendType
(const
cv::String
&newBackendType)
Member
cv::error
(const
Exception
&exc)
drop this version
Member
cv::estimateRigidTransform
(InputArray src, InputArray dst, bool fullAffine)
Use
cv::estimateAffine2D
,
cv::estimateAffinePartial2D
instead. If you are using this function with images, extract points using
cv::calcOpticalFlowPyrLK
and then use the estimation functions.
Member
cv::FileNode::FileNode
(const
FileStorage
*fs, size_t blockIdx, size_t ofs)
Member
cv::getThreadNum
()
Current implementation doesn't corresponding to this documentation.
Member
cv::linearPolar
(InputArray src, OutputArray dst, Point2f center, double maxRadius, int flags)
This function produces same result as
cv::warpPolar
(src, dst, src.size(), center, maxRadius, flags)
Member
cv::logPolar
(InputArray src, OutputArray dst, Point2f center, double M, int flags)
This function produces same result as
cv::warpPolar
(src, dst, src.size(), center, maxRadius, flags+WARP_POLAR_LOG);
Member
cv::ocl::Context::Context
(int dtype)
Member
cv::ocl::Context::create
()
Member
cv::ocl::Context::create
(int dtype)
Member
cv::ocl::initializeContextFromHandle
(
Context
&ctx, void *platform, void *context, void *device)
Class
cv::ocl::Platform
Member
cv::ocl::Platform::getDefault
()
Member
cv::ovis::updateTexture
(const String &name, InputArray image)
use setMaterialProperty
Member
cv::text::loadOCRHMMClassifierCNN
(const String &filename)
use loadOCRHMMClassifier instead
Member
cv::text::loadOCRHMMClassifierNM
(const String &filename)
loadOCRHMMClassifier instead
Member
cv::TLSDataAccumulator< T >::gather
(std::vector< T * > &data) const
replaced by
detachData()
Member
cv::TLSDataContainer::gatherData
(std::vector< void * > &data) const
use
detachData()
instead
Member
cv::v_signmask
(const v_reg< _Tp, n > &a)
v_signmask depends on a lane count heavily and therefore isn't universal enough
Member
CV_DNN_BACKEND_INFERENCE_ENGINE_NGRAPH
Member
CV_DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_API
File
datamov_utils.hpp
Use
Device layer
instead.
File
dynamic_smem.hpp
Use
Device layer
instead.
File
emulation.hpp
Use
Device layer
instead.
File
filters.hpp
Use
Device layer
instead.
File
funcattrib.hpp
Use
Device layer
instead.
File
functional.hpp
Use
Device layer
instead.
Member
G_TYPED_KERNEL_M
This macro is deprecated in favor of
G_TYPED_KERNEL
that is used for declaring any G-API Operation.
File
ggpukernel.hpp
Use <
opencv2/gapi/ocl/goclkernel.hpp
> instead.
File
imgproc.hpp
Use <
opencv2/gapi/ocl/imgproc.hpp
> instead.
File
limits.hpp
Use
Device layer
instead.
File
reduce.hpp
Use
Device layer
instead.
File
saturate_cast.hpp
Use
Device layer
instead.
File
scan.hpp
Use
Device layer
instead.
File
simd_functions.hpp
Use
Device layer
instead.
File
transform.hpp
Use
Device layer
instead.
File
type_traits.hpp
Use
Device layer
instead.
File
utility.hpp
Use
Device layer
instead.
File
vec_distance.hpp
Use
Device layer
instead.
File
vec_math.hpp
Use
Device layer
instead.
File
vec_traits.hpp
Use
Device layer
instead.
File
warp.hpp
Use
Device layer
instead.
File
warp_reduce.hpp
Use
Device layer
instead.
File
warp_shuffle.hpp
Use
Device layer
instead.
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