Merge pull request #25055 from dmatveev:dm/value_initialized_gmat

G-API: A quick value-initialization support GMat #25055

This PR enables `GMat` objects to be value-initialized in the same way as it was done for `GScalar`s (and, possibly, other types).

- Added some helper methods in backends to distinguish if a certain G-type value initialization is supported or not;
- Added tests, including negative.

Where it is needed:

- Further extension of the OVCV backend (#24379 - will be refreshed soon);
- Further experiments with DNN module;
- Further experiments with "G-API behind UMat" sort of aggregation.

In the current form, PR can be reviewed & merged (@TolyaTalamanov please have a look)

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
pull/25171/head
Dmitry Matveev 8 months ago committed by GitHub
parent 0e524ee95a
commit f174363f60
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
  1. 12
      modules/gapi/include/opencv2/gapi/gmat.hpp
  2. 11
      modules/gapi/include/opencv2/gapi/gscalar.hpp
  3. 3
      modules/gapi/src/api/gbackend.cpp
  4. 8
      modules/gapi/src/api/gbackend_priv.hpp
  5. 9
      modules/gapi/src/api/gcomputation.cpp
  6. 4
      modules/gapi/src/api/gmat.cpp
  7. 1
      modules/gapi/src/api/gproto.cpp
  8. 11
      modules/gapi/src/backends/cpu/gcpubackend.cpp
  9. 11
      modules/gapi/src/backends/ocl/goclbackend.cpp
  10. 1
      modules/gapi/src/compiler/gobjref.hpp
  11. 24
      modules/gapi/src/compiler/passes/exec.cpp
  12. 6
      modules/gapi/src/executor/gexecutor.cpp
  13. 6
      modules/gapi/src/executor/gthreadedexecutor.cpp
  14. 114
      modules/gapi/test/gapi_mat_tests.cpp

@ -77,6 +77,18 @@ public:
*/
GAPI_WRAP GMat(); // Empty constructor
/**
* @brief Constructs a value-initialized GMat
*
* GMat may be associated with a buffer at graph construction time.
* It is useful when some operation has a Mat input which doesn't
* change during the program execution, and is set only once.
* In this case, there's no need to declare such GMat as graph input.
*
* @param m a cv::Mat buffer to associate with this GMat object.
*/
GAPI_WRAP explicit GMat(cv::Mat m); // Value-initialization constructor
/// @private
GMat(const GNode &n, std::size_t out); // Operation result constructor
/// @private

@ -54,12 +54,11 @@ public:
/**
* @brief Constructs a value-initialized GScalar
*
* In contrast with GMat (which can be either an explicit graph input
* or a result of some operation), GScalars may have their values
* be associated at graph construction time. It is useful when
* some operation has a GScalar input which doesn't change during
* the program execution, and is set only once. In this case,
* there is no need to declare such GScalar as a graph input.
* GScalars may have their values be associated at graph
* construction time. It is useful when some operation has a
* GScalar input which doesn't change during the program
* execution, and is set only once. In this case, there is no need
* to declare such GScalar as a graph input.
*
* @note The value of GScalar may be overwritten by assigning some
* other GScalar to the object using `operator=` -- on the

@ -80,6 +80,9 @@ bool cv::gapi::GBackend::Priv::allowsMerge(const cv::gimpl::GIslandModel::Graph
return true;
}
bool cv::gapi::GBackend::Priv::supportsConst(cv::GShape) const {
return false;
}
// GBackend public implementation //////////////////////////////////////////////
cv::gapi::GBackend::GBackend()

@ -84,6 +84,14 @@ public:
const ade::NodeHandle &slot_nh,
const ade::NodeHandle &b_nh) const;
// Ask backend if it supports CONST_VAL data of the given shape or not.
// If the backend does support this data type, a Data node with such
// value can be fused into the backend's Island body.
// If the backend doesn't support this data type, a Data node won't
// be fused into the Islands's body -- will be marked as an in-graph
// input connection for this Island.
virtual bool supportsConst(cv::GShape shape) const;
virtual ~Priv() = default;
};

@ -191,8 +191,8 @@ void cv::GComputation::recompile(GMetaArgs&& in_metas, GCompileArgs &&args)
if (m_priv->m_lastMetas != in_metas)
{
if (m_priv->m_lastCompiled &&
m_priv->m_lastCompiled.canReshape() &&
formats_are_same(m_priv->m_lastMetas, in_metas))
m_priv->m_lastCompiled.canReshape() &&
formats_are_same(m_priv->m_lastMetas, in_metas))
{
m_priv->m_lastCompiled.reshape(in_metas, args);
}
@ -203,6 +203,11 @@ void cv::GComputation::recompile(GMetaArgs&& in_metas, GCompileArgs &&args)
}
m_priv->m_lastMetas = in_metas;
}
else if (in_metas.size() == 0) {
// Happens when the graph is head-less (e.g. starts with const-vals only)
// always compile ad-hoc
m_priv->m_lastCompiled = compile(GMetaArgs(in_metas), std::move(args));
}
}
void cv::GComputation::apply(GRunArgs &&ins, GRunArgsP &&outs, GCompileArgs &&args)

@ -26,6 +26,10 @@ cv::GMat::GMat(const GNode &n, std::size_t out)
{
}
cv::GMat::GMat(cv::Mat m)
: m_priv(new GOrigin(GShape::GMAT, cv::gimpl::ConstVal(m))) {
}
cv::GOrigin& cv::GMat::priv()
{
return *m_priv;

@ -80,6 +80,7 @@ cv::GRunArg cv::value_of(const cv::GOrigin &origin)
{
case GShape::GSCALAR: return GRunArg(util::get<cv::Scalar>(origin.value));
case GShape::GARRAY: return GRunArg(util::get<cv::detail::VectorRef>(origin.value));
case GShape::GMAT: return GRunArg(util::get<cv::Mat>(origin.value));
default: util::throw_error(std::logic_error("Unsupported shape for constant"));
}
}

@ -65,6 +65,17 @@ namespace
{
return EPtr{new cv::gimpl::GCPUExecutable(graph, compileArgs, nodes)};
}
virtual bool supportsConst(cv::GShape shape) const override
{
// Supports all types of const values
return shape == cv::GShape::GOPAQUE
|| shape == cv::GShape::GSCALAR
|| shape == cv::GShape::GARRAY;
// yes, value-initialized GMats are not supported currently
// as in-island data -- compiler will lift these values to the
// GIslandModel's SLOT level (will be handled uniformly)
}
};
}

@ -62,6 +62,17 @@ namespace
{
return EPtr{new cv::gimpl::GOCLExecutable(graph, nodes)};
}
virtual bool supportsConst(cv::GShape shape) const override
{
// Supports all types of const values
return shape == cv::GShape::GOPAQUE
|| shape == cv::GShape::GSCALAR
|| shape == cv::GShape::GARRAY;
// yes, value-initialized GMats are not supported currently
// as in-island data -- compiler will lift these values to the
// GIslandModel's SLOT level (will be handled uniformly)
}
};
}

@ -24,6 +24,7 @@ namespace gimpl
< util::monostate
, cv::Scalar
, cv::detail::VectorRef
, cv::Mat
>;
struct RcDesc

@ -9,7 +9,7 @@
#include <string>
#include <list> // list
#include <iomanip> // setw, etc
#include <iomanip> // setw, etc
#include <fstream> // ofstream
#include <memory>
#include <functional>
@ -85,7 +85,7 @@ namespace
const auto& backend = *src_g.metadata().get<ActiveBackends>().backends.cbegin();
const auto& proto = src_g.metadata().get<Protocol>();
GIsland::node_set all, in_ops, out_ops;
GIsland::node_set all, in_ops, out_ops, in_cvals;
all.insert(src_g.nodes().begin(), src_g.nodes().end());
@ -99,7 +99,22 @@ namespace
all.erase(nh);
out_ops.insert(nh->inNodes().begin(), nh->inNodes().end());
}
for (const auto& nh : src_g.nodes())
{
if (src_g.metadata(nh).get<NodeType>().t == NodeType::DATA)
{
const auto &d = src_g.metadata(nh).get<Data>();
if (d.storage == Data::Storage::CONST_VAL
&& !backend.priv().supportsConst(d.shape)) {
// don't put this node into the island's graph - so the island
// executable don't need to handle value-initialized G-type manually.
// Still mark its readers as inputs
all.erase(nh);
in_cvals.insert(nh);
in_ops.insert(nh->outNodes().begin(), nh->outNodes().end());
}
}
}
auto isl = std::make_shared<GIsland>(backend,
std::move(all),
std::move(in_ops),
@ -108,7 +123,8 @@ namespace
auto ih = GIslandModel::mkIslandNode(g, std::move(isl));
for (const auto& nh : proto.in_nhs)
for (const auto& nh : ade::util::chain(ade::util::toRange(proto.in_nhs),
ade::util::toRange(in_cvals)))
{
auto slot = GIslandModel::mkSlotNode(g, nh);
g.link(slot, ih);

@ -208,6 +208,12 @@ void cv::gimpl::GExecutor::initResource(const ade::NodeHandle & nh, const ade::N
switch (d.shape)
{
case GShape::GMAT:
if (d.storage == Data::Storage::CONST_VAL)
{
auto rc = RcDesc{d.rc, d.shape, d.ctor};
magazine::bindInArgExec(m_res, rc, m_gm.metadata(orig_nh).get<ConstValue>().arg);
}
else
{
// Let island allocate it's outputs if it can,
// allocate cv::Mat and wrap it with RMat otherwise

@ -175,7 +175,11 @@ void cv::gimpl::GThreadedExecutor::initResource(const ade::NodeHandle &nh, const
// to as it is bound externally (e.g. already in the m_state.mag)
switch (d.shape) {
case GShape::GMAT: {
case GShape::GMAT:
if (d.storage == Data::Storage::CONST_VAL) {
auto rc = RcDesc{d.rc, d.shape, d.ctor};
magazine::bindInArgExec(m_state.mag, rc, m_gm.metadata(orig_nh).get<ConstValue>().arg);
} else {
// Let island allocate it's outputs if it can,
// allocate cv::Mat and wrap it with RMat otherwise
GAPI_Assert(!nh->inNodes().empty());

@ -0,0 +1,114 @@
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
//
// Copyright (C) 2024 Intel Corporation
#include "test_precomp.hpp"
#include <opencv2/gapi/cpu/core.hpp>
#include <opencv2/gapi/ocl/core.hpp>
#include <opencv2/gapi/fluid/core.hpp>
namespace opencv_test
{
namespace
{
enum class KernelPackage: int
{
OCV,
OCL,
FLUID,
};
std::ostream& operator<< (std::ostream &os, const KernelPackage &e)
{
switch (e)
{
#define _C(X) case KernelPackage::X: os << #X; break
_C(OCV);
_C(OCL);
_C(FLUID);
#undef _C
default: GAPI_Error("Unknown package");
}
return os;
}
} // namespace
struct GMatWithValue : public TestWithParam <KernelPackage> {
cv::GKernelPackage getKernelPackage() {
switch (GetParam()) {
case KernelPackage::OCV: return cv::gapi::core::cpu::kernels();
case KernelPackage::OCL: return cv::gapi::core::ocl::kernels();
case KernelPackage::FLUID: return cv::gapi::core::fluid::kernels();
default: GAPI_Error("Unknown package");
}
}
};
TEST_P(GMatWithValue, SingleIsland)
{
cv::Size sz(2, 2);
cv::Mat in_mat = cv::Mat::eye(sz, CV_8U);
cv::GComputationT<cv::GMat(cv::GMat)> addEye([&](cv::GMat in) {
return in + cv::GMat(cv::Mat::eye(sz, CV_8U));
});
cv::Mat out_mat;
addEye.apply(in_mat, out_mat, cv::compile_args(cv::gapi::use_only{getKernelPackage()}));
cv::Mat out_mat_ref = in_mat*2;
EXPECT_EQ(0, cvtest::norm(out_mat, out_mat_ref, NORM_INF));
}
TEST_P(GMatWithValue, GraphWithNoInput)
{
cv::Mat cval = cv::Mat::eye(cv::Size(2, 2), CV_8U);
cv::GMat gval = cv::GMat(cval);
cv::GMat out = cv::gapi::bitwise_not(gval);
cv::Mat out_mat;
cv::GComputation f(cv::GIn(), cv::GOut(out));
// Compiling this isn't supported for now
EXPECT_ANY_THROW(f.compile(cv::descr_of(cval),
cv::compile_args(cv::gapi::use_only{getKernelPackage()})));
}
INSTANTIATE_TEST_CASE_P(GAPI_GMat, GMatWithValue,
Values(KernelPackage::OCV,
KernelPackage::OCL,
KernelPackage::FLUID));
TEST(GAPI_MatWithValue, MultipleIslands)
{
// This test employs a non-trivial island fusion process
// as there's multiple backends in the graph
cv::Size sz(2, 2);
cv::Mat cval2 = cv::Mat::eye(sz, CV_8U) * 2;
cv::Mat cval1 = cv::Mat::eye(sz, CV_8U);
cv::GMat in;
cv::GMat tmp = in + cv::GMat(cval2); // Will be a Fluid operation
cv::GMat out = tmp - cv::GMat(cval1); // Will be an OCV operation
cv::GKernelPackage fluid_kernels = cv::gapi::core::fluid::kernels();
cv::GKernelPackage opencv_kernels = cv::gapi::core::cpu::kernels();
fluid_kernels.remove<cv::gapi::core::GSub>();
opencv_kernels.remove<cv::gapi::core::GAdd>();
auto kernels = cv::gapi::combine(fluid_kernels, opencv_kernels);
cv::Mat in_mat = cv::Mat::zeros(sz, CV_8U);
cv::Mat out_mat;
auto cc = cv::GComputation(in, out)
.compile(cv::descr_of(in_mat),
cv::compile_args(cv::gapi::use_only{kernels}));
cc(cv::gin(in_mat), cv::gout(out_mat));
EXPECT_EQ(0, cvtest::norm(out_mat, cv::Mat::eye(sz, CV_8U), NORM_INF));
}
} // namespace opencv_test
Loading…
Cancel
Save