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https://github.com/opencv/opencv.git
synced 2026-07-30 15:53:03 +04:00
Fix modules/ typos
Found using `codespell -q 3 -S ./3rdparty -L activ,amin,ang,atleast,childs,dof,endwhile,halfs,hist,iff,nd,od,uint`
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@@ -46,12 +46,12 @@ majority of the work by itself, keeping the algorithm code clean from
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device or optimization details. This approach has its own limitations,
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though, as graph model is a _constrained_ model and not every
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algorithm can be represented as a graph, so the G-API scope is limited
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only to regular image processing -- various filters, arithmentic,
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only to regular image processing -- various filters, arithmetic,
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binary operations, and well-defined geometrical transformations.
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## Porting with Graph API {#gapi_intro_port}
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The essense of G-API is declaring a sequence of operations to run, and
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The essence of G-API is declaring a sequence of operations to run, and
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then executing that sequence. G-API is a constrained API, so it puts a
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number of limitations on which operations can form a pipeline and
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which data these operations may exchange each other.
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@@ -67,7 +67,7 @@ interfaces, not implementations -- thus the same graph can be executed
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on different devices (and, of course, using different optimization
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techniques) with little-to-no changes in the graph itself.
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G-API supports plugins (_Backends_) which aggreate logic and
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G-API supports plugins (_Backends_) which aggregate logic and
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intelligence on what is the best way to execute on a particular
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platform. Once a pipeline is built with G-API, it can be parametrized
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to use either of the backends (or a combination of it) and so a graph
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@@ -701,7 +701,7 @@ GAPI_EXPORTS GMat divRC(const GScalar& divident, const GMat& src, double scale,
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/** @brief Applies a mask to a matrix.
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The function mask set value from given matrix if the corresponding pixel value in mask matrix set to true,
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and set the matrix value to 0 overwise.
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and set the matrix value to 0 otherwise.
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Supported src matrix data types are @ref CV_8UC1, @ref CV_16SC1, @ref CV_16UC1. Supported mask data type is @ref CV_8UC1.
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@@ -1293,7 +1293,7 @@ depths.
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*/
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GAPI_EXPORTS GMat threshold(const GMat& src, const GScalar& thresh, const GScalar& maxval, int depth);
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/** @overload
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This function appicable for all threshold depths except CV_THRESH_OTSU and CV_THRESH_TRIANGLE
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This function applicable for all threshold depths except CV_THRESH_OTSU and CV_THRESH_TRIANGLE
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@note Function textual ID is "org.opencv.core.matrixop.thresholdOT"
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*/
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GAPI_EXPORTS std::tuple<GMat, GScalar> threshold(const GMat& src, const GScalar& maxval, int depth);
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@@ -92,7 +92,7 @@ protected:
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std::vector<GArg> m_args;
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//FIXME: avoid conversion of arguments from internal representaion to OpenCV one on each call
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//FIXME: avoid conversion of arguments from internal representation to OpenCV one on each call
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//to OCV kernel. (This can be achieved by a two single time conversions in GCPUExecutable::run,
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//once on enter for input and output arguments, and once before return for output arguments only
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std::unordered_map<std::size_t, GRunArgP> m_results;
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@@ -229,7 +229,7 @@ struct OCVCallHelper<Impl, std::tuple<Ins...>, std::tuple<Outs...> >
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static void call(Inputs&&... ins, Outputs&&... outs)
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{
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//not using a std::forward on outs is deliberate in order to
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//cause compilation error, by tring to bind rvalue references to lvalue references
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//cause compilation error, by trying to bind rvalue references to lvalue references
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Impl::run(std::forward<Inputs>(ins)..., outs...);
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postprocess(outs...);
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@@ -81,7 +81,7 @@ namespace detail
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protected:
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GArrayU(); // Default constructor
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template<class> friend class cv::GArray; // (avialable to GArray<T> only)
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template<class> friend class cv::GArray; // (available to GArray<T> only)
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void setConstructFcn(ConstructVec &&cv); // Store T-aware constructor
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@@ -23,7 +23,7 @@ namespace wip {
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class GAsyncContext;
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//These functions asynchronously (i.e. probably on a separate thread of execution) call operator() member function of their first argument with copies of rest of arguments (except callback) passed in.
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//The difference between the function is the way to get the completion notification (via callback or a waiting on std::future object)
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//If exception is occurred during execution of apply it is transfered to the callback (via function parameter) or passed to future (and will be thrown on call to std::future::get)
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//If exception is occurred during execution of apply it is transferred to the callback (via function parameter) or passed to future (and will be thrown on call to std::future::get)
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//N.B. :
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//Input arguments are copied on call to async function (actually on call to cv::gin) and thus do not have to outlive the actual completion of asynchronous activity.
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@@ -83,7 +83,7 @@ namespace detail
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* In the above example, sobelEdge expects one Mat on input and
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* produces one Mat; while sobelEdgeSub expects two Mats on input and
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* produces one Mat. GComputation's protocol defines how other
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* computaion methods should be used -- cv::GComputation::compile() and
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* computation methods should be used -- cv::GComputation::compile() and
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* cv::GComputation::apply(). For example, if a graph is defined on
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* two GMat inputs, two cv::Mat objects have to be passed to apply()
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* for execution. GComputation checks protocol correctness in runtime
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@@ -24,7 +24,7 @@ namespace wip {
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class GAsyncContext;
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//These functions asynchronously (i.e. probably on a separate thread of execution) call apply member function of their first argument with copies of rest of arguments (except callback) passed in.
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//The difference between the function is the way to get the completion notification (via callback or a waiting on std::future object)
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//If exception is occurred during execution of apply it is transfered to the callback (via function parameter) or passed to future (and will be thrown on call to std::future::get)
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//If exception is occurred during execution of apply it is transferred to the callback (via function parameter) or passed to future (and will be thrown on call to std::future::get)
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//N.B. :
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//Input arguments are copied on call to async function (actually on call to cv::gin) and thus do not have to outlive the actual completion of asynchronous activity.
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@@ -323,7 +323,7 @@ namespace gapi {
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* implementations in form of type list (variadic template) and
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* generates a kernel package atop of that.
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*
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* Kernel packages can be also generated programatically, starting
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* Kernel packages can be also generated programmatically, starting
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* with an empty package (created with the default constructor)
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* and then by populating it with kernels via call to
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* GKernelPackage::include(). Note this method is also a template
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@@ -164,7 +164,7 @@ typename Net::ResultL infer(cv::GArray<cv::Rect> roi, Args&&... args) {
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* @param args network's input parameters as specified in G_API_NET() macro.
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* @return an object of return type as defined in G_API_NET().
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* If a network has multiple return values (defined with a tuple), a tuple of
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* objects of apprpriate type is returned.
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* objects of appropriate type is returned.
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* @sa G_API_NET()
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*/
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template<typename Net, typename... Args>
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@@ -198,7 +198,7 @@ struct OCLCallHelper<Impl, std::tuple<Ins...>, std::tuple<Outs...> >
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static void call(Inputs&&... ins, Outputs&&... outs)
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{
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//not using a std::forward on outs is deliberate in order to
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//cause compilation error, by tring to bind rvalue references to lvalue references
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//cause compilation error, by trying to bind rvalue references to lvalue references
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Impl::run(std::forward<Inputs>(ins)..., outs...);
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postprocess_ocl(outs...);
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@@ -66,7 +66,7 @@ static inline DST saturate(SRC x, R round)
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GAPI_DbgAssert(std::is_integral<DST>::value &&
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std::is_floating_point<SRC>::value);
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#ifdef _WIN32
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// Suppress warning about convering x to floating-point
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// Suppress warning about converting x to floating-point
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// Note that x is already floating-point at this point
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#pragma warning(disable: 4244)
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#endif
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@@ -239,7 +239,7 @@ void resetInternalData(Mag& mag, const Data &d)
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break;
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case GShape::GMAT:
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// Do nothign here - FIXME unify with initInternalData?
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// Do nothing here - FIXME unify with initInternalData?
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break;
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default:
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@@ -281,7 +281,7 @@ cv::GRunArgP getObjPtr(Mag& mag, const RcDesc &rc, bool is_umat)
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return GRunArgP(&mag.template slot<cv::gapi::own::Mat>()[rc.id]);
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case GShape::GSCALAR: return GRunArgP(&mag.template slot<cv::gapi::own::Scalar>()[rc.id]);
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// Note: .at() is intentional for GArray as object MUST be already there
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// (and constructer by either bindIn/Out or resetInternal)
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// (and constructor by either bindIn/Out or resetInternal)
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case GShape::GARRAY:
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// FIXME(DM): For some absolutely unknown to me reason, move
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// semantics is involved here without const_cast to const (and
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@@ -413,7 +413,7 @@ GAPI_OCV_KERNEL(GCPUSplit3, cv::gapi::core::GSplit3)
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std::vector<cv::Mat> outMats = {m1, m2, m3};
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cv::split(in, outMats);
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// Write back FIXME: Write a helper or avoid this nonsence completely!
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// Write back FIXME: Write a helper or avoid this nonsense completely!
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m1 = outMats[0];
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m2 = outMats[1];
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m3 = outMats[2];
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@@ -427,7 +427,7 @@ GAPI_OCV_KERNEL(GCPUSplit4, cv::gapi::core::GSplit4)
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std::vector<cv::Mat> outMats = {m1, m2, m3, m4};
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cv::split(in, outMats);
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// Write back FIXME: Write a helper or avoid this nonsence completely!
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// Write back FIXME: Write a helper or avoid this nonsense completely!
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m1 = outMats[0];
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m2 = outMats[1];
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m3 = outMats[2];
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@@ -204,7 +204,7 @@ struct IECallContext
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// Input parameters passed to an inference operation.
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std::vector<cv::GArg> args;
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//FIXME: avoid conversion of arguments from internal representaion to OpenCV one on each call
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//FIXME: avoid conversion of arguments from internal representation to OpenCV one on each call
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//to OCV kernel. (This can be achieved by a two single time conversions in GCPUExecutable::run,
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//once on enter for input and output arguments, and once before return for output arguments only
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//FIXME: check if the above applies to this backend (taken from CPU)
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@@ -410,7 +410,7 @@ GAPI_OCL_KERNEL(GOCLSplit3, cv::gapi::core::GSplit3)
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std::vector<cv::UMat> outMats = {m1, m2, m3};
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cv::split(in, outMats);
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// Write back FIXME: Write a helper or avoid this nonsence completely!
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// Write back FIXME: Write a helper or avoid this nonsense completely!
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m1 = outMats[0];
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m2 = outMats[1];
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m3 = outMats[2];
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@@ -424,7 +424,7 @@ GAPI_OCL_KERNEL(GOCLSplit4, cv::gapi::core::GSplit4)
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std::vector<cv::UMat> outMats = {m1, m2, m3, m4};
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cv::split(in, outMats);
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// Write back FIXME: Write a helper or avoid this nonsence completely!
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// Write back FIXME: Write a helper or avoid this nonsense completely!
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m1 = outMats[0];
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m2 = outMats[1];
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m3 = outMats[2];
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@@ -297,7 +297,7 @@ void cv::gimpl::GCompiler::compileIslands(ade::Graph &g)
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cv::GCompiled cv::gimpl::GCompiler::produceCompiled(GPtr &&pg)
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{
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// This is the final compilation step. Here:
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// - An instance of GExecutor is created. Depening on the platform,
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// - An instance of GExecutor is created. Depending on the platform,
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// build configuration, etc, a GExecutor may be:
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// - a naive single-thread graph interpreter;
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// - a std::thread-based thing
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@@ -80,7 +80,7 @@ cv::gimpl::Unrolled cv::gimpl::unrollExpr(const GProtoArgs &ins,
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std::unordered_set<GObjId> in_objs_p;
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for (const auto& in_obj : ins)
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{
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// Objects are guarnateed to remain alive while this method
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// Objects are guaranteed to remain alive while this method
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// is working, so it is safe to keep pointers here and below
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in_objs_p.insert(&proto::origin_of(in_obj));
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}
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@@ -454,7 +454,7 @@ namespace
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m_changes.enqueue<Change::DropLink>(m_g, m_cons, out_edge);
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}
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// D: Process the intermediate slots (betweed Prod n Cons).
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// D: Process the intermediate slots (between Prod n Cons).
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// D/1 - Those which are optimized out are just removed from the model
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for (auto opt_slot_nh : mo.opt_interim_slots)
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{
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@@ -32,7 +32,7 @@ namespace
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cv::GArgs in_args;
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};
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// Generaly the algorithm is following
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// Generally the algorithm is following
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//
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// 1. Get GCompoundKernel implementation
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// 2. Create GCompoundContext
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@@ -113,7 +113,7 @@ void cv::gimpl::passes::inferMeta(ade::passes::PassContext &ctx, bool meta_is_in
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} // for(sorted)
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}
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// After all metadata in graph is infered, store a vector of inferred metas
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// After all metadata in graph is inferred, store a vector of inferred metas
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// for computation output values.
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void cv::gimpl::passes::storeResultingMeta(ade::passes::PassContext &ctx)
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{
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